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Ultimate Bunny needed that pre-mission injection. Model - keyd10iori 🔞 [Commisions Open] VA - OpaluVA 🎰💙🔞 Map - Scamarai DL and alts in comments.

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Character : Kitsune's custom prints 🔞 🇲🇽 Ui controlled addons. (System is a work in progress but will be improved and brought onto 4.0+ model library patch progressively) Thanks to SudaBanan🔞 for helping me found the script needed for making that possible 🥴👍
0:43

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Character : Kitsune's custom prints 🔞 🇲🇽 Ui controlled addons. (System is a work in progress but will be improved and brought onto 4.0+ model library patch progressively) Thanks to SudaBanan🔞 for helping me found the script needed for making that possible 🥴👍

DogZeela🔞(Commissions : CLOSED)

98,842 görüntüleme • 2 yıl önce

This week we’re getting GPT 5.5 and I couldn’t be more excited to see the first new pre train base in a while Before Spud releases, here’s the last video you need to watch - Greg Brockman perfectly indicated to us 3 important things that perfectly encapsulate the lineage of OpenAI and the mission. 1.This is the culmination of 2 years of research and is a fresh base pre-train that we haven’t gotten for a long time. 2.This is an “exciting release” and it will bring new capabilities (sort of a given but still very grateful nonetheless) & that it is AN EARLY VERSION of what we have coming - meaning they have a lot of RL to do to make this model even better since it’s a fresh pre-train. 3.THIS IS THE BEGINNING OF THE FLYWHEEL. As he said toward the end, “we have this engine of progress that just moves faster and faster and Spud is just one step along the way.” Depending on the capabilities we see this week from Spud, we may be able to map out if AGI will be sooner rather than later, judging by how much recursive work can exist within this model and the harness. In other words, the flywheel.
0:42

This week we’re getting GPT 5.5 and I couldn’t be more excited to see the first new pre train base in a while Before Spud releases, here’s the last video you need to watch - Greg Brockman perfectly indicated to us 3 important things that perfectly encapsulate the lineage of OpenAI and the mission. 1.This is the culmination of 2 years of research and is a fresh base pre-train that we haven’t gotten for a long time. 2.This is an “exciting release” and it will bring new capabilities (sort of a given but still very grateful nonetheless) & that it is AN EARLY VERSION of what we have coming - meaning they have a lot of RL to do to make this model even better since it’s a fresh pre-train. 3.THIS IS THE BEGINNING OF THE FLYWHEEL. As he said toward the end, “we have this engine of progress that just moves faster and faster and Spud is just one step along the way.” Depending on the capabilities we see this week from Spud, we may be able to map out if AGI will be sooner rather than later, judging by how much recursive work can exist within this model and the harness. In other words, the flywheel.

Chris

103,198 görüntüleme • 2 ay önce

I’m thrilled to present something Marián Marčiš and I have been working on for the past few weeks. To my knowledge, this is something that has never been done before, and this is our first model that includes underground parts. Behold a photogrammetric 3D model of Zona X! Zona X (also known as Lanlakuyoc or Lancacuyo) is a mysterious site about a mile North-East of Sacsayhuaman. It’s a big limestone outcrop intersected by a network of tunnels and narrow passageways, some open to the sky, and others going deep underground. It also features several right-angled cuts in the bedrock ("hanan pacha" style) whose function remains unknown to this day, as well as a section of a megalithic wall. It is also said that this site once had a chincana entrance, possibly connecting to Sacsayhuaman, that has now been sealed off. I have an idea of which passage could lead to an entrance, but it remains to be confirmed. It's a true stone labyrinth in which it's easy to get lost, which is why I wanted to create a 3D map of it. I wanted to get a better idea of how these passages are oriented in relation to each other and where they could lead. It took several visits to the site to map all the passages I could crawl through. Some of these passageways become too narrow to squeeze through for an adult of average build, but seem to extend much deeper. It took Marián a LOT of work (and a lot of processing power) to combine and align the thousands of photos from a drone and extracted from a 360° ground video needed to create the 55 millions triangles that make up this model. I’m not sure how he did it but he pulled it off. He really deserves his title of photogrammetry wizard. Please make sure to give him the follow he deserves Marián Marčiš. The video doesn't show all the passages I filmed for the creation of the model. We decided to only show the main ones, and some of the most prominent stone carvings in order to keep the video relatively short. The site has many more nooks and crannies not shown in the video that are just begging to be explored. I hope we can complete this model in the future. Until then, enjoy this one!
4:26

I’m thrilled to present something Marián Marčiš and I have been working on for the past few weeks. To my knowledge, this is something that has never been done before, and this is our first model that includes underground parts. Behold a photogrammetric 3D model of Zona X! Zona X (also known as Lanlakuyoc or Lancacuyo) is a mysterious site about a mile North-East of Sacsayhuaman. It’s a big limestone outcrop intersected by a network of tunnels and narrow passageways, some open to the sky, and others going deep underground. It also features several right-angled cuts in the bedrock ("hanan pacha" style) whose function remains unknown to this day, as well as a section of a megalithic wall. It is also said that this site once had a chincana entrance, possibly connecting to Sacsayhuaman, that has now been sealed off. I have an idea of which passage could lead to an entrance, but it remains to be confirmed. It's a true stone labyrinth in which it's easy to get lost, which is why I wanted to create a 3D map of it. I wanted to get a better idea of how these passages are oriented in relation to each other and where they could lead. It took several visits to the site to map all the passages I could crawl through. Some of these passageways become too narrow to squeeze through for an adult of average build, but seem to extend much deeper. It took Marián a LOT of work (and a lot of processing power) to combine and align the thousands of photos from a drone and extracted from a 360° ground video needed to create the 55 millions triangles that make up this model. I’m not sure how he did it but he pulled it off. He really deserves his title of photogrammetry wizard. Please make sure to give him the follow he deserves Marián Marčiš. The video doesn't show all the passages I filmed for the creation of the model. We decided to only show the main ones, and some of the most prominent stone carvings in order to keep the video relatively short. The site has many more nooks and crannies not shown in the video that are just begging to be explored. I hope we can complete this model in the future. Until then, enjoy this one!

Weird Old World

11,766 görüntüleme • 1 yıl önce

A GUY AT GOOGLE DEEPMIND MADE AN ISOMETRIC PIXEL-ART MAP OF NEW YORK CITY AND PUT IT ON THE OPEN WEB FOR FREE it's called you open the tab and the city is just sitting there in classic SimCity 2000 isometric pixel art. you scroll. and it keeps going. and going. i zoomed in on midtown and i could read the H&M signage in times square. in red. as actual pixel-art letters on the side of a building. i could see the crystalline spire of the Bank of America Tower poking out of a clump of skyscrapers. individual rooftop HVAC units. tiny green roof gardens. the little driveway loops in front of the hotels. he estimates the map needs roughly 40,000 tiles. nothing is a placeholder. the guy who made it is Andy Coenen, a senior staff engineer at Google DeepMind. he is not a pixel artist. by his own admission he is "a former electronic musician." what he actually did is kind of insane: > pulled NYC's geometry from the Google Maps 3D tiles API > fine-tuned an open-source image model (Qwen-Image-Edit) on ~40 hand-paired examples of "satellite tile → pixel art tile" > spun up 50 parallel instances on rented GPUs and generated tens of thousands of tiles in a few hours > the fine-tune cost him 12 bucks his own stated mission for the project, verbatim, is one sentence: "what's possible now that was impossible before?" apparently the answer is "one engineer can pixel-art most of a metropolis for the price of a sandwich." and the wildest part to me is he didn't sell it. no signup. no paywall. no NFT. you open the URL and the city is yours to wander. the post landed at 1,325 points on Hacker News and topped bestofshowhn's 2026 list. we live in a timeline where a senior engineer at one of the largest AI labs on earth spent his nights pixel-arting Manhattan for fun and then gave it away. the internet is healing.
0:33

A GUY AT GOOGLE DEEPMIND MADE AN ISOMETRIC PIXEL-ART MAP OF NEW YORK CITY AND PUT IT ON THE OPEN WEB FOR FREE it's called you open the tab and the city is just sitting there in classic SimCity 2000 isometric pixel art. you scroll. and it keeps going. and going. i zoomed in on midtown and i could read the H&M signage in times square. in red. as actual pixel-art letters on the side of a building. i could see the crystalline spire of the Bank of America Tower poking out of a clump of skyscrapers. individual rooftop HVAC units. tiny green roof gardens. the little driveway loops in front of the hotels. he estimates the map needs roughly 40,000 tiles. nothing is a placeholder. the guy who made it is Andy Coenen, a senior staff engineer at Google DeepMind. he is not a pixel artist. by his own admission he is "a former electronic musician." what he actually did is kind of insane: > pulled NYC's geometry from the Google Maps 3D tiles API > fine-tuned an open-source image model (Qwen-Image-Edit) on ~40 hand-paired examples of "satellite tile → pixel art tile" > spun up 50 parallel instances on rented GPUs and generated tens of thousands of tiles in a few hours > the fine-tune cost him 12 bucks his own stated mission for the project, verbatim, is one sentence: "what's possible now that was impossible before?" apparently the answer is "one engineer can pixel-art most of a metropolis for the price of a sandwich." and the wildest part to me is he didn't sell it. no signup. no paywall. no NFT. you open the URL and the city is yours to wander. the post landed at 1,325 points on Hacker News and topped bestofshowhn's 2026 list. we live in a timeline where a senior engineer at one of the largest AI labs on earth spent his nights pixel-arting Manhattan for fun and then gave it away. the internet is healing.

Nav Toor

438,267 görüntüleme • 1 ay önce

‘pip install elysia’ and ‘elysia start’ That’s literally all it takes to get the most advanced open source agentic RAG app running on your data. We just released 𝗘𝗹𝘆𝘀𝗶𝗮, our open source, agentic RAG framework and an app so cool needed a cool video to go with it. Watch the full video: In the video, we go through these components of Elysia: 1️⃣ 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗧𝗿𝗲𝗲 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: Instead of giving agents access to all tools at once, Elysia uses a pre-defined web of nodes with corresponding actions. Each decision agent has global context awareness. 2️⃣ 𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗗𝗮𝘁𝗮 𝗗𝗶𝘀𝗽𝗹𝗮𝘆𝘀: Seven different data display formats including tables, e-commerce product cards, GitHub tickets, and charts. The system automatically choses the best display format. 3️⃣ 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗰 𝗗𝗮𝘁𝗮 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲: Unlike naive RAG systems that perform blind vector searches, Elysia analyzes your collections to understand data structure and meaning before performing queries. 𝗢𝘁𝗵𝗲𝗿 𝗖𝗼𝗼𝗹 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀: • 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 𝗦𝘆𝘀𝘁𝗲𝗺: Uses positive examples as few-shot demonstrations for smaller, faster models • 𝗖𝗵𝘂𝗻𝗸-𝗢𝗻-𝗗𝗲𝗺𝗮𝗻𝗱: Dynamically chunks documents at query time instead of pre-chunking • 𝗠𝘂𝗹𝘁𝗶-𝗠𝗼𝗱𝗲𝗹 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆: Routes different tasks to appropriate model sizes based on complexity …And also how to get started with your own data! The entire project is open source and designed with customization in mind. You can use it as-is for effective data searching, or install the Python package to create custom tools for whatever agentic AI purposes you need. Big kudos to Edward for the vision, filming, and editing this masterpiece
1:16

‘pip install elysia’ and ‘elysia start’ That’s literally all it takes to get the most advanced open source agentic RAG app running on your data. We just released 𝗘𝗹𝘆𝘀𝗶𝗮, our open source, agentic RAG framework and an app so cool needed a cool video to go with it. Watch the full video: In the video, we go through these components of Elysia: 1️⃣ 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗧𝗿𝗲𝗲 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: Instead of giving agents access to all tools at once, Elysia uses a pre-defined web of nodes with corresponding actions. Each decision agent has global context awareness. 2️⃣ 𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗗𝗮𝘁𝗮 𝗗𝗶𝘀𝗽𝗹𝗮𝘆𝘀: Seven different data display formats including tables, e-commerce product cards, GitHub tickets, and charts. The system automatically choses the best display format. 3️⃣ 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗰 𝗗𝗮𝘁𝗮 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲: Unlike naive RAG systems that perform blind vector searches, Elysia analyzes your collections to understand data structure and meaning before performing queries. 𝗢𝘁𝗵𝗲𝗿 𝗖𝗼𝗼𝗹 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀: • 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 𝗦𝘆𝘀𝘁𝗲𝗺: Uses positive examples as few-shot demonstrations for smaller, faster models • 𝗖𝗵𝘂𝗻𝗸-𝗢𝗻-𝗗𝗲𝗺𝗮𝗻𝗱: Dynamically chunks documents at query time instead of pre-chunking • 𝗠𝘂𝗹𝘁𝗶-𝗠𝗼𝗱𝗲𝗹 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆: Routes different tasks to appropriate model sizes based on complexity …And also how to get started with your own data! The entire project is open source and designed with customization in mind. You can use it as-is for effective data searching, or install the Python package to create custom tools for whatever agentic AI purposes you need. Big kudos to Edward for the vision, filming, and editing this masterpiece

Victoria Slocum

45,497 görüntüleme • 10 ay önce

The Pipeline Deal That Could Remake Iraq’s Oil Map As the Turkey-Iraq pipeline agreement is set to expire in July, the two countries have started negotiations on a new agreement. The treaty lapses during the sharpest contraction in Gulf energy shipping in recent memory, and that has turned a technical renewal into a contest over the shape of Iraq’s export map. The legal background shapes every Iraqi position in the talks. The pipeline went dark in 2023 after Iraq won arbitration against Turkey over unauthorized Kurdish exports between 2014 and 2018, with Turkey ordered to pay about $1.5 billion. Baghdad will not sign a successor agreement that leaves ownership of the crude, the marketing channel, or the payment route open to a parallel Erbil-Ankara reading. Ankara, for its part, is not negotiating a simple renewal. Turkish Energy Minister Alparslan Bayraktar has argued repeatedly that the line carries a nominal capacity of nearly 1.5 million bpd and has never been used at scale. Any new agreement, he says, must include a mechanism to guarantee fuller use. Reaching that volume requires extending the line south toward Basra, since northern production cannot fill it. Turkey folds this into the wider Development Road from Faw to Turkey, reframed as an energy corridor carrying oil, gas, petrochemicals, refining, and electricity alongside road and rail. Baghdad’s instrument is the Basra-Haditha pipeline, which the Oil Ministry calls the backbone of the northern export system. Baghdad has chosen a turnkey, state-financed model with full Oil Ministry ownership after rejecting an investment structure that would have handed an outside party long-term transit rights. If Turkey is seeking ownership leverage under the heading of investment, that is the Iraqi red line. The decisive feature of the Iraqi design is that Basra-Haditha is multidirectional. From Haditha, crude could move north to Ceyhan. In theory, it could also support future western exits toward Baniyas and Tartus on the Syrian coast, or southwest toward Aqaba in Jordan. These branches should not be read as equally imminent projects. Their immediate value is strategic optionality. They give Baghdad a map of alternatives, even before all of them become physical export routes. For the Kurdistan Region, the trajectory is unfavourable. Its 2014-built line, with a design capacity of nearly 900,000 bpd, remains physically useful in the short term while the ministry-controlled Kirkuk-Fishkhabur line, rated at nearly 1.5 million bpd, is rehabilitated as a federal bypass. Once that bypass and Basra-Haditha are in place, the KRG pipeline becomes a feeder rather than a strategic bottleneck. Baghdad’s aim is not necessarily to shut it. The aim is to strip it of independent commercial authority. Turkey signs with Baghdad alone, SOMO markets the crude, and revenue runs through the federal treasury. The KRG line may remain part of the infrastructure, but not as the basis for a parallel political economy. Whatever the structure, a deal struck before the deadline will not restore the pre-2023 model. The likeliest endpoint is Ceyhan returning as a federal corridor under SOMO and the treasury, the KRG line being tolerated as infrastructure without political-commercial autonomy, and Turkey gaining volume guarantees and investment access but not a chokehold over Iraqi oil. Baghdad’s wager is that holding the Syrian and Jordanian options open is what keeps Ceyhan a corridor rather than a second Hormuz. More details:
0:41

The Pipeline Deal That Could Remake Iraq’s Oil Map As the Turkey-Iraq pipeline agreement is set to expire in July, the two countries have started negotiations on a new agreement. The treaty lapses during the sharpest contraction in Gulf energy shipping in recent memory, and that has turned a technical renewal into a contest over the shape of Iraq’s export map. The legal background shapes every Iraqi position in the talks. The pipeline went dark in 2023 after Iraq won arbitration against Turkey over unauthorized Kurdish exports between 2014 and 2018, with Turkey ordered to pay about $1.5 billion. Baghdad will not sign a successor agreement that leaves ownership of the crude, the marketing channel, or the payment route open to a parallel Erbil-Ankara reading. Ankara, for its part, is not negotiating a simple renewal. Turkish Energy Minister Alparslan Bayraktar has argued repeatedly that the line carries a nominal capacity of nearly 1.5 million bpd and has never been used at scale. Any new agreement, he says, must include a mechanism to guarantee fuller use. Reaching that volume requires extending the line south toward Basra, since northern production cannot fill it. Turkey folds this into the wider Development Road from Faw to Turkey, reframed as an energy corridor carrying oil, gas, petrochemicals, refining, and electricity alongside road and rail. Baghdad’s instrument is the Basra-Haditha pipeline, which the Oil Ministry calls the backbone of the northern export system. Baghdad has chosen a turnkey, state-financed model with full Oil Ministry ownership after rejecting an investment structure that would have handed an outside party long-term transit rights. If Turkey is seeking ownership leverage under the heading of investment, that is the Iraqi red line. The decisive feature of the Iraqi design is that Basra-Haditha is multidirectional. From Haditha, crude could move north to Ceyhan. In theory, it could also support future western exits toward Baniyas and Tartus on the Syrian coast, or southwest toward Aqaba in Jordan. These branches should not be read as equally imminent projects. Their immediate value is strategic optionality. They give Baghdad a map of alternatives, even before all of them become physical export routes. For the Kurdistan Region, the trajectory is unfavourable. Its 2014-built line, with a design capacity of nearly 900,000 bpd, remains physically useful in the short term while the ministry-controlled Kirkuk-Fishkhabur line, rated at nearly 1.5 million bpd, is rehabilitated as a federal bypass. Once that bypass and Basra-Haditha are in place, the KRG pipeline becomes a feeder rather than a strategic bottleneck. Baghdad’s aim is not necessarily to shut it. The aim is to strip it of independent commercial authority. Turkey signs with Baghdad alone, SOMO markets the crude, and revenue runs through the federal treasury. The KRG line may remain part of the infrastructure, but not as the basis for a parallel political economy. Whatever the structure, a deal struck before the deadline will not restore the pre-2023 model. The likeliest endpoint is Ceyhan returning as a federal corridor under SOMO and the treasury, the KRG line being tolerated as infrastructure without political-commercial autonomy, and Turkey gaining volume guarantees and investment access but not a chokehold over Iraqi oil. Baghdad’s wager is that holding the Syrian and Jordanian options open is what keeps Ceyhan a corridor rather than a second Hormuz. More details:

The National Context

13,412 görüntüleme • 1 ay önce

Introducing LobeHub: Agent teammates that grow with you. LobeHub is the ultimate space for work and life: to find, build, and collaborate with agent teammates that grow with you. We’re building the world’s first and largest human–agent co-evolving network. Two years ago, we built LobeChat, an open-source interface for using different AI models. Today, LobeChat has 70k+ GitHub stars and serves 6M+ users worldwide. How to fully unlock the power of models has always been a shared mission between us and the community. We started with interaction — a fundamentally new, agent-first experience. Agents are no longer passive tools invoked in a single conversation. They should be proactive, always-on units of work. Treating agents as the minimal atomic unit is also the core of our agent harness infra. Today’s agents are mostly one-off executors. Even with memory, it’s often global — and hallucinates. We build long-term agent teammates that evolve with users. Each agent has its own dedicated memory space, editable by users, allowing humans and agents to co-evolve over time. This, in turn, allows us to design clearer rewards for reinforcement learning and create cleaner environments for continual learning. Agent teammates can work in groups. Through a multi-agent system, agent groups operate faster, more cost-effective, and go beyond what single-agent systems can achieve. For example, a single agent often requires heavy user involvement to proceed step by step, whereas LobeHub can execute the same work from a single instruction, with a supervisor orchestrating agents that run in parallel or debate to produce better results. We are building the collaboration network among agent teammates — and between humans and agent teammates as well. Ease of use matters. AI intelligence and shared human intelligence are equally important. With simple instructions and tool selection, you can effortlessly build and team up with agent coworkers to deliver complex, systematic work — even assembling a quant team to execute trades. Through the LobeHub community, anyone can discover, reuse, and remix agents and agent groups, customizing them to fit their own workflows, preferences, and needs. Last but not least, our vision started with LobeChat: multi-model support is the most efficient approach for users. We believe different models excel in different scenarios. By routing across multiple models, LobeHub improves cost efficiency and unlocks capabilities that a single-model setup cannot easily support.
2:41

Introducing LobeHub: Agent teammates that grow with you. LobeHub is the ultimate space for work and life: to find, build, and collaborate with agent teammates that grow with you. We’re building the world’s first and largest human–agent co-evolving network. Two years ago, we built LobeChat, an open-source interface for using different AI models. Today, LobeChat has 70k+ GitHub stars and serves 6M+ users worldwide. How to fully unlock the power of models has always been a shared mission between us and the community. We started with interaction — a fundamentally new, agent-first experience. Agents are no longer passive tools invoked in a single conversation. They should be proactive, always-on units of work. Treating agents as the minimal atomic unit is also the core of our agent harness infra. Today’s agents are mostly one-off executors. Even with memory, it’s often global — and hallucinates. We build long-term agent teammates that evolve with users. Each agent has its own dedicated memory space, editable by users, allowing humans and agents to co-evolve over time. This, in turn, allows us to design clearer rewards for reinforcement learning and create cleaner environments for continual learning. Agent teammates can work in groups. Through a multi-agent system, agent groups operate faster, more cost-effective, and go beyond what single-agent systems can achieve. For example, a single agent often requires heavy user involvement to proceed step by step, whereas LobeHub can execute the same work from a single instruction, with a supervisor orchestrating agents that run in parallel or debate to produce better results. We are building the collaboration network among agent teammates — and between humans and agent teammates as well. Ease of use matters. AI intelligence and shared human intelligence are equally important. With simple instructions and tool selection, you can effortlessly build and team up with agent coworkers to deliver complex, systematic work — even assembling a quant team to execute trades. Through the LobeHub community, anyone can discover, reuse, and remix agents and agent groups, customizing them to fit their own workflows, preferences, and needs. Last but not least, our vision started with LobeChat: multi-model support is the most efficient approach for users. We believe different models excel in different scenarios. By routing across multiple models, LobeHub improves cost efficiency and unlocks capabilities that a single-model setup cannot easily support.

LobeHub

185,032 görüntüleme • 5 ay önce

🚨Science nerds are going to lose their minds. Kai Rowan just open sourced a framework that predicts how your brain responds to any text, audio, or video by simulating cortical fMRI activity with 30% more accuracy than Meta's own model. No fMRI scanner. No neuroscience PhD. No million-dollar lab. It's called NForge. Here's what this thing actually does: → Feed it any combination of text, audio, or video and it predicts cortical surface activity across ~20,484 brain vertices → Extracts deep features via LLaMA 3.2, V-JEPA2, and Wav2Vec-BERT simultaneously → Generates ROI attention maps showing exactly which brain regions fire hardest at which moments → Runs real-time streaming predictions from live feature streams -- no pre-loading the full clip → Breaks down exactly how much text vs audio vs video drove each prediction with per-vertex modality attribution scores → Adapts to entirely new subjects with just a few calibration scans -- no full retraining required Here's the wildest part: Built on Meta's TRIBE v2 foundation but adds 6 major capabilities Meta never shipped. Cross-subject generalization. Streaming inference. Modality attribution. torch.compile support. Full test coverage. Professional src/ package layout. You literally point this at a movie clip and it tells you which parts of the human cortex light up -- broken down by what your eyes, ears, and language centers each contributed. That sentence shouldn't be real in 2026. But here we are. 100% Open Source. pip install nforge. (Link in the comments)
0:23

🚨Science nerds are going to lose their minds. Kai Rowan just open sourced a framework that predicts how your brain responds to any text, audio, or video by simulating cortical fMRI activity with 30% more accuracy than Meta's own model. No fMRI scanner. No neuroscience PhD. No million-dollar lab. It's called NForge. Here's what this thing actually does: → Feed it any combination of text, audio, or video and it predicts cortical surface activity across ~20,484 brain vertices → Extracts deep features via LLaMA 3.2, V-JEPA2, and Wav2Vec-BERT simultaneously → Generates ROI attention maps showing exactly which brain regions fire hardest at which moments → Runs real-time streaming predictions from live feature streams -- no pre-loading the full clip → Breaks down exactly how much text vs audio vs video drove each prediction with per-vertex modality attribution scores → Adapts to entirely new subjects with just a few calibration scans -- no full retraining required Here's the wildest part: Built on Meta's TRIBE v2 foundation but adds 6 major capabilities Meta never shipped. Cross-subject generalization. Streaming inference. Modality attribution. torch.compile support. Full test coverage. Professional src/ package layout. You literally point this at a movie clip and it tells you which parts of the human cortex light up -- broken down by what your eyes, ears, and language centers each contributed. That sentence shouldn't be real in 2026. But here we are. 100% Open Source. pip install nforge. (Link in the comments)

Guri Singh

244,515 görüntüleme • 3 ay önce

The July 4th weekend All-In The All-In Podcast turned into a long argument about who owns the intelligence layer. The besties think enterprises just woke up to a trap they had been walking into, here's how the conversation went (save this): ◽️ The Palantir-Nvidia deal is a bet against the model-layer duopoly. Palantir will use Nvidia's Nemotron open models to build a custom frontier-quality model for US government agencies, and the agencies own the hardware, the data, and the weights. Sacks framed it as structural: an application company and a chip company both want a competitive model layer, so they are natural partners against a two-provider middle. ◽️ Alex Karp's CNBC "crashout" was actually the thesis. Karp argued enterprises have lost trust in the frontier labs and want to own their compute, models, data, and alpha. Sacks translated it as a new definition of enterprise AI safety: safety means the model provider cannot hoover up your proprietary knowledge and turn it into its next product. ◽️ Figma is the cautionary tale that made it real. Anthropic launched Claude Design into Figma's category, its chief product officer sat on Figma's board and resigned only 3 days before launch, and Figma's stock is down about 50% this year while Anthropic's valuation surged. Sacks listed Claude Science, Security, Legal, Financial, and Code as the same move: dominate the model layer, then take the lucrative verticals. ◽️ The playbook has a name, and it is Microsoft and Google. Sacks argued Anthropic is running the operating-system strategy: own the layer everyone builds on, then walk up the stack. His Google receipt is that fewer than half of searches now send you off-site, versus an early Google that prided itself on how fast it kicked you away. ◽️ The BCG number is what raises the stakes. Chamath cited a BCG return-on-capital-employed study: the cost of capital is back to its long-run 8 to 11%, and half of large US companies cannot earn returns above it. If you are already teetering on your cost of capital, handing your alpha to a provider that may compete with you is not a luxury risk, it is fatal. ◽️ The 16.4x number is the whole argument in one data point. Chamath ran a code-migration task through 8090's harness. Wrapping Claude was 1.4x cheaper and 1.5x faster than Claude Opus alone. Wrapping the best open-source model was 16.4x cheaper, at about 3x slower. For a background task, three extra hours to cut cost by 16x is not a close call. ◽️ Even at 100x cheaper, enterprises were saying no for the wrong reason. Chamath relayed an ex-Meta PM's point that companies reject open models over China and safety fears, when they could host those same open weights on their own GPUs in US data centers with nothing flowing back. The safety objection, she argued, is backwards: the leak is the data you hand the frontier labs. ◽️ Friedberg says the frontier labs are trying to commoditize their own customers. Anthropic has been signing up life-sciences companies to feed a new life-focused model in exchange for early access, and nearly everyone he has talked to now refuses, recognizing that data they spent billions generating becomes worthless once it is pooled with everyone else's. ◽️ The deployment topology is shifting from big hubs to distributed spokes. Friedberg's map: the old assumption was a few capital-advantaged mega-clusters plus inference clouds. The new one is large hubs, medium hubs (enterprise training clusters), and distributed spokes, including on-prem inference in your own building. Owning your weights is the point. ◽️ Chamath's endgame is running GLM himself. An industry contact told him that with harness post-training and telemetry, an open Chinese model like GLM could get as good as Anthropic's Mythos. His conclusion: take GLM, control it soup-to-nuts on US hardware with only US citizens touching it, and pay a fraction. ◽️ The Apple analogy sharpens why renting intelligence is different from renting distribution. Chamath argued Apple is the only platform that respected developers, deliberately keeping its stock apps basic to protect the ecosystem and collect its 30% tax. There is no 30% tax on open models, and worse, you cannot rent intelligence from the same place that rents it to your competitor without ending up identical to them. ◽️ Nvidia's open model is now good enough to matter. Calacanis claimed you cannot tell Jensen Huang's Nemotron from Claude on 95% of searches, and that Nvidia downplayed the model until now to avoid alarming its top customers. The gloves came off once OpenAI, Anthropic, and Elon all signaled their own silicon ambitions. ◽️ Sacks sized the duopoly: roughly $60B and $40B in ARR. Anthropic is around ~$60 billion of ARR, OpenAI at ~$40 billion, and no one else generates meaningful model-layer revenue. Sacks's policy line: the US does not ban monopolies, only anti-competitive tactics, but the government should do nothing to make the duopoly more likely. ◽️ The token deflation call: 90% a year for three years. Calacanis predicted token costs fall 90% annually for three years, putting the price of intelligence near free and making it rational to waste tokens on hardware you already own. Friedberg's version is a 70/20/10 split between big cloud, local, and other clouds. ◽️ A wave of platform lock-in spending is already landing. Calacanis flagged Microsoft standing up a roughly $2.5 billion forward-deployed-engineer effort and Amazon spending about $1 billion on the same, plus OpenAI's version. His read: enterprises will slam the door, because letting a provider's engineers study your business is how it ends up in their model. ◽️ The server-per-employee prediction. Calacanis expects every employee to get $10,000 to $20,000 of local compute, a Mac Studio or a high-RAM Dell, running a personal local model that syncs to a thin laptop. A server per person, so nothing leaks. ◽️ On jobs, the data does not show present-tense loss. Sacks cited a RAMP and Revelio Labs study of over 21,000 US firms: the heaviest AI spenders grew headcount about 10% over two years, and entry-level headcount grew even faster at 12%. Friedberg's harder claim: there is no AI job loss yet, only clunky, gradual value creation, and the media will not reverse its narrative because that destroys its credibility. ◽️ The displacement case is real but forward-dated. The counterpoint on the show was that customer support, entry-level data entry and BPO, and driving are the near-term displacements, with Waymo cited as present-tense evidence: in markets where it hits critical mass, Uber and Lyft stop recruiting drivers. Sacks noted most US entry-level support was already offshored, so the acute risk sits in those countries first. ◽️ The human-premium counternarrative. Friedberg argued that as automation spreads, human interaction gets a premium: the skilled bartender, the real driver, the human-in-the-loop tier. He cited the company (referenced as Klarna) that hyped replacing its whole support team with AI, then reversed a year later on brand grounds. ◽️ The export-control episode needed three conditions, and Sacks says do not over-read it. Commerce lifted controls on Anthropic's Fable 5 after two weeks, with Mythos 5 restored to US customers around June 26 once co-founder Tom Brown replaced Dario as lead negotiator. Sacks's three conditions: Dario boasting for months about a cyber weapon, Amazon reporting failed guardrails in testing, and Dario refusing to roll Fable back. His message to allies: this was a particular set of circumstances rather than the debut of a standing lever. ◽️ The import question nobody answered cleanly. Calacanis pressed on why the US blocks Chinese cars and drones but not Chinese open models like DeepSeek and Kimi. Sacks's answer: a forked open model run on US hardware stops being Chinese, and banning open source would isolate the US and impose a token tax on American enterprises, so let the market decide if American open models win. ◽️ The California fiscal story is a business-climate story. Friedberg walked through the numbers behind Newsom's "balanced" $351B budget: expenses exceed revenue and $20-40B is borrowed to close the gap, the budget grew 65% in six years ($215B to $355B), personal income tax is $142B of ~$211B revenue with the top 1% (150,000 people) paying $70B of it, and the corporate rate of 8.9% sits far above Texas at zero. ◽️ The tax base is leaving, and the state is now taxing everyone else. Friedberg cited 1 to 1.5% of adjusted gross income leaving each year (about 15% over a decade), at least 15 Fortune 500 HQs and ~2,100 firms gone since 2019, and a new 8% software sales tax hitting Word, Gmail, and ChatGPT subscriptions plus a health-insurance tax, on top of a now-permanent 14.4% top bracket. The liabilities behind it run $1.4T in debt, up to $1.5T in unfunded pensions senior to state bonds, and ~$40B/year in out-year deficits. Lastly, the line that framed the whole show: "You can't rent intelligence from the same place that rents it to your competitor." That is the sovereignty thesis in one sentence, and every number in this episode is an argument for it. ____ Follow Fireside Alpha for more summaries on key business and technology conversations.
1:33

The July 4th weekend All-In The All-In Podcast turned into a long argument about who owns the intelligence layer. The besties think enterprises just woke up to a trap they had been walking into, here's how the conversation went (save this): ◽️ The Palantir-Nvidia deal is a bet against the model-layer duopoly. Palantir will use Nvidia's Nemotron open models to build a custom frontier-quality model for US government agencies, and the agencies own the hardware, the data, and the weights. Sacks framed it as structural: an application company and a chip company both want a competitive model layer, so they are natural partners against a two-provider middle. ◽️ Alex Karp's CNBC "crashout" was actually the thesis. Karp argued enterprises have lost trust in the frontier labs and want to own their compute, models, data, and alpha. Sacks translated it as a new definition of enterprise AI safety: safety means the model provider cannot hoover up your proprietary knowledge and turn it into its next product. ◽️ Figma is the cautionary tale that made it real. Anthropic launched Claude Design into Figma's category, its chief product officer sat on Figma's board and resigned only 3 days before launch, and Figma's stock is down about 50% this year while Anthropic's valuation surged. Sacks listed Claude Science, Security, Legal, Financial, and Code as the same move: dominate the model layer, then take the lucrative verticals. ◽️ The playbook has a name, and it is Microsoft and Google. Sacks argued Anthropic is running the operating-system strategy: own the layer everyone builds on, then walk up the stack. His Google receipt is that fewer than half of searches now send you off-site, versus an early Google that prided itself on how fast it kicked you away. ◽️ The BCG number is what raises the stakes. Chamath cited a BCG return-on-capital-employed study: the cost of capital is back to its long-run 8 to 11%, and half of large US companies cannot earn returns above it. If you are already teetering on your cost of capital, handing your alpha to a provider that may compete with you is not a luxury risk, it is fatal. ◽️ The 16.4x number is the whole argument in one data point. Chamath ran a code-migration task through 8090's harness. Wrapping Claude was 1.4x cheaper and 1.5x faster than Claude Opus alone. Wrapping the best open-source model was 16.4x cheaper, at about 3x slower. For a background task, three extra hours to cut cost by 16x is not a close call. ◽️ Even at 100x cheaper, enterprises were saying no for the wrong reason. Chamath relayed an ex-Meta PM's point that companies reject open models over China and safety fears, when they could host those same open weights on their own GPUs in US data centers with nothing flowing back. The safety objection, she argued, is backwards: the leak is the data you hand the frontier labs. ◽️ Friedberg says the frontier labs are trying to commoditize their own customers. Anthropic has been signing up life-sciences companies to feed a new life-focused model in exchange for early access, and nearly everyone he has talked to now refuses, recognizing that data they spent billions generating becomes worthless once it is pooled with everyone else's. ◽️ The deployment topology is shifting from big hubs to distributed spokes. Friedberg's map: the old assumption was a few capital-advantaged mega-clusters plus inference clouds. The new one is large hubs, medium hubs (enterprise training clusters), and distributed spokes, including on-prem inference in your own building. Owning your weights is the point. ◽️ Chamath's endgame is running GLM himself. An industry contact told him that with harness post-training and telemetry, an open Chinese model like GLM could get as good as Anthropic's Mythos. His conclusion: take GLM, control it soup-to-nuts on US hardware with only US citizens touching it, and pay a fraction. ◽️ The Apple analogy sharpens why renting intelligence is different from renting distribution. Chamath argued Apple is the only platform that respected developers, deliberately keeping its stock apps basic to protect the ecosystem and collect its 30% tax. There is no 30% tax on open models, and worse, you cannot rent intelligence from the same place that rents it to your competitor without ending up identical to them. ◽️ Nvidia's open model is now good enough to matter. Calacanis claimed you cannot tell Jensen Huang's Nemotron from Claude on 95% of searches, and that Nvidia downplayed the model until now to avoid alarming its top customers. The gloves came off once OpenAI, Anthropic, and Elon all signaled their own silicon ambitions. ◽️ Sacks sized the duopoly: roughly $60B and $40B in ARR. Anthropic is around ~$60 billion of ARR, OpenAI at ~$40 billion, and no one else generates meaningful model-layer revenue. Sacks's policy line: the US does not ban monopolies, only anti-competitive tactics, but the government should do nothing to make the duopoly more likely. ◽️ The token deflation call: 90% a year for three years. Calacanis predicted token costs fall 90% annually for three years, putting the price of intelligence near free and making it rational to waste tokens on hardware you already own. Friedberg's version is a 70/20/10 split between big cloud, local, and other clouds. ◽️ A wave of platform lock-in spending is already landing. Calacanis flagged Microsoft standing up a roughly $2.5 billion forward-deployed-engineer effort and Amazon spending about $1 billion on the same, plus OpenAI's version. His read: enterprises will slam the door, because letting a provider's engineers study your business is how it ends up in their model. ◽️ The server-per-employee prediction. Calacanis expects every employee to get $10,000 to $20,000 of local compute, a Mac Studio or a high-RAM Dell, running a personal local model that syncs to a thin laptop. A server per person, so nothing leaks. ◽️ On jobs, the data does not show present-tense loss. Sacks cited a RAMP and Revelio Labs study of over 21,000 US firms: the heaviest AI spenders grew headcount about 10% over two years, and entry-level headcount grew even faster at 12%. Friedberg's harder claim: there is no AI job loss yet, only clunky, gradual value creation, and the media will not reverse its narrative because that destroys its credibility. ◽️ The displacement case is real but forward-dated. The counterpoint on the show was that customer support, entry-level data entry and BPO, and driving are the near-term displacements, with Waymo cited as present-tense evidence: in markets where it hits critical mass, Uber and Lyft stop recruiting drivers. Sacks noted most US entry-level support was already offshored, so the acute risk sits in those countries first. ◽️ The human-premium counternarrative. Friedberg argued that as automation spreads, human interaction gets a premium: the skilled bartender, the real driver, the human-in-the-loop tier. He cited the company (referenced as Klarna) that hyped replacing its whole support team with AI, then reversed a year later on brand grounds. ◽️ The export-control episode needed three conditions, and Sacks says do not over-read it. Commerce lifted controls on Anthropic's Fable 5 after two weeks, with Mythos 5 restored to US customers around June 26 once co-founder Tom Brown replaced Dario as lead negotiator. Sacks's three conditions: Dario boasting for months about a cyber weapon, Amazon reporting failed guardrails in testing, and Dario refusing to roll Fable back. His message to allies: this was a particular set of circumstances rather than the debut of a standing lever. ◽️ The import question nobody answered cleanly. Calacanis pressed on why the US blocks Chinese cars and drones but not Chinese open models like DeepSeek and Kimi. Sacks's answer: a forked open model run on US hardware stops being Chinese, and banning open source would isolate the US and impose a token tax on American enterprises, so let the market decide if American open models win. ◽️ The California fiscal story is a business-climate story. Friedberg walked through the numbers behind Newsom's "balanced" $351B budget: expenses exceed revenue and $20-40B is borrowed to close the gap, the budget grew 65% in six years ($215B to $355B), personal income tax is $142B of ~$211B revenue with the top 1% (150,000 people) paying $70B of it, and the corporate rate of 8.9% sits far above Texas at zero. ◽️ The tax base is leaving, and the state is now taxing everyone else. Friedberg cited 1 to 1.5% of adjusted gross income leaving each year (about 15% over a decade), at least 15 Fortune 500 HQs and ~2,100 firms gone since 2019, and a new 8% software sales tax hitting Word, Gmail, and ChatGPT subscriptions plus a health-insurance tax, on top of a now-permanent 14.4% top bracket. The liabilities behind it run $1.4T in debt, up to $1.5T in unfunded pensions senior to state bonds, and ~$40B/year in out-year deficits. Lastly, the line that framed the whole show: "You can't rent intelligence from the same place that rents it to your competitor." That is the sovereignty thesis in one sentence, and every number in this episode is an argument for it. ____ Follow Fireside Alpha for more summaries on key business and technology conversations.

Fireside Alpha

54,225 görüntüleme • 11 gün önce

OpenLedger X Morpheus The partnership of openledger with Morpheus enables Use Morpheus to build "The Autonomous Smart Contract Engineer" on top of OpenLedger. What is Morpheus? Morpheus is a Web3-native AI coding agent that turns natural language into executable smart contracts and full-stack dApps. It is powered by a specialized Solidity model built on top of OpenLedger, tailored for the unique demands of secure and efficient onchain development. It goes beyond code generation. Using fine-tuned models, agent-based architecture, and modular plugin support, Morpheus automates the entire development pipeline-from writing and simulating contracts to deploying and maintaining them. Its mission is to reduce the barrier to dApp creation while enabling autonomous agents and individuals to participate in decentralized economies. Why OpenLedger? The rise of AI agents in Web3 raises urgent questions around transparency, attribution, explainability, and contributor incentives. OpenLedger provides the infrastructure to ensure that contributor data used in model outputs is recorded with verifiable attribution. Through Proof of Attribution, contributors-whether they provide prompts, datasets, or logic refinements-can receive credit and rewards when their work influences model behavior. But attribution alone isn’t enough. In critical domains like smart contract deployment, DeFi automation, and DAO governance, understanding why a model made a decision is just as important as the output itself. OpenLedger supports explainability by linking outputs back to their original data sources-allowing developers and auditors to trace logic, validate decisions, and build trust in AI-powered systems. OpenLedger supports Morpheus by: Recording which data was used in generating model outputs Enabling verifiable attribution of contributed datasets Powering reward mechanisms for contributors Offering scalable and efficient model execution via OpenLoRA Supporting transparency and traceability in model decision-making This creates an open, rewardable foundation for AI-driven coding-without relying on opaque systems. How is the system built? The Morpheus architecture has three layers: Datanet Layer OpenLedger powers Morpheus with a specialized Datanet - a decentralized data layer where developers, auditors, and contributors can share smart contract patterns, audit logs, exploit reports, and logic modules. Each submission is recorded onchain with attribution using OpenLedger’s Proof of Attribution. As the model learns and evolves from this data, contributors receive rewards proportional to their impact on future outputs. The Morpheus architecture has two layers: Intent Layer Users describe what they want to build. Example: "Create a token with tax logic that routes to a DAO." Morpheus parses the instruction, retrieves relevant contract types, and plans a modular execution flow. Agent Layer The agent generates, tests, and assembles the contract. It handles versioning, logic validation, and deployment readiness. Security checks-reentrancy protection, overflow control, gas modeling-are embedded into the generation phase. Generated outputs are mapped to their source data using OpenLedger’s Proof of Attribution, providing traceability across the pipeline. How does the AI model work? Morpheus is being powered by a specialized Solidity model built on top of OpenLedger. This model is purpose-built to handle the nuances of smart contract logic, security, and upgradeability. Unlike generalized coding agents, it is designed specifically for EVM environments and Web3 use cases, drawing from real protocol data and security best practices. Morpheus is fine-tuned on a vertical stack of smart contract data: Audited protocol code (e.g., Uniswap V4, Compound) OpenZeppelin libraries and EIP reference implementations Smart contract vulnerability reports and exploit reconstructions Edge cases from fuzz testing and adversarial examples It uses models like CodeLlama and DeepSeek-Coder, enhanced through RAG pipelines referencing standardized security patterns and emerging protocol designs. This training stack is integrated into a continuous feedback loop, enabling real-time specialization for EVM and beyond. Why a specialized model is needed? Smart contract development is uniquely high-stakes. A generalized AI model is not enough. As 'vibe coding' and natural language programming become more common, we're seeing an influx of AI-generated code in Web3 as well. But smart contracts are not frontends or prototypes-they govern real value, enforce trustless execution, and often become immutable after deployment. Billions have been lost in Web3 due to bugs and inefficiencies: In 2022 alone, over $3.8 billion was stolen due to smart contract exploits, many of which stemmed from avoidable issues like reentrancy, integer overflows, or access control failures. Inefficient contract structures lead to unnecessary gas consumption. Optimizing for gas can reduce costs by up to 40%, saving projects millions over time. Upgradeable contract patterns, like UUPS or Transparent Proxies, require strict adherence to storage layout and initialization rules. Mistakes here often go undetected by generic models and can render a contract unupgradeable or vulnerable. A specialized Solidity model is trained on real-world exploits, EIP standards, and libraries like OpenZeppelin to: Generate secure, gas-efficient code by default Recognize and correctly implement complex proxy patterns Map user intent to modular, auditable contract architectures Incorporate battle-tested logic from audited protocols and fuzz-tested edge cases Morpheus goes beyond syntax-it understands the nuances of decentralized infrastructure and deploys code that meets production-grade standards. What applications will this enable Token creation with built-in logic (tax, liquidity, governance) DeFi automations triggered by market conditions Payment contracts between agents and contributors DAO tooling with dynamic NFT-based voting Cross-chain bridging logic tied to real-world oracles Asset issuance flows through chat-based interfaces Natural language contract templates with reusable logic Each of these flows is backed by OpenLedger’s Proof of Attribution-ensuring traceability, explainability, and fair rewards across the ecosystem. This is the future of AI-native development. Open. Attributed. Explainable. Community-powered. Morpheus and OpenLedger are building the first system for autonomous coding agents where: Contributor work is recorded onchain Reuse is incentivized through attribution Model outputs are traceable and explainable Contracts evolve through human-agent collaboration Anyone can contribute prompts, logic, or flows-and get rewarded The smart contract engineer is no longer a human-only role. It is an agentic, decentralized, and transparent process-powered by OpenLedger.
0:28

OpenLedger X Morpheus The partnership of openledger with Morpheus enables Use Morpheus to build "The Autonomous Smart Contract Engineer" on top of OpenLedger. What is Morpheus? Morpheus is a Web3-native AI coding agent that turns natural language into executable smart contracts and full-stack dApps. It is powered by a specialized Solidity model built on top of OpenLedger, tailored for the unique demands of secure and efficient onchain development. It goes beyond code generation. Using fine-tuned models, agent-based architecture, and modular plugin support, Morpheus automates the entire development pipeline-from writing and simulating contracts to deploying and maintaining them. Its mission is to reduce the barrier to dApp creation while enabling autonomous agents and individuals to participate in decentralized economies. Why OpenLedger? The rise of AI agents in Web3 raises urgent questions around transparency, attribution, explainability, and contributor incentives. OpenLedger provides the infrastructure to ensure that contributor data used in model outputs is recorded with verifiable attribution. Through Proof of Attribution, contributors-whether they provide prompts, datasets, or logic refinements-can receive credit and rewards when their work influences model behavior. But attribution alone isn’t enough. In critical domains like smart contract deployment, DeFi automation, and DAO governance, understanding why a model made a decision is just as important as the output itself. OpenLedger supports explainability by linking outputs back to their original data sources-allowing developers and auditors to trace logic, validate decisions, and build trust in AI-powered systems. OpenLedger supports Morpheus by: Recording which data was used in generating model outputs Enabling verifiable attribution of contributed datasets Powering reward mechanisms for contributors Offering scalable and efficient model execution via OpenLoRA Supporting transparency and traceability in model decision-making This creates an open, rewardable foundation for AI-driven coding-without relying on opaque systems. How is the system built? The Morpheus architecture has three layers: Datanet Layer OpenLedger powers Morpheus with a specialized Datanet - a decentralized data layer where developers, auditors, and contributors can share smart contract patterns, audit logs, exploit reports, and logic modules. Each submission is recorded onchain with attribution using OpenLedger’s Proof of Attribution. As the model learns and evolves from this data, contributors receive rewards proportional to their impact on future outputs. The Morpheus architecture has two layers: Intent Layer Users describe what they want to build. Example: "Create a token with tax logic that routes to a DAO." Morpheus parses the instruction, retrieves relevant contract types, and plans a modular execution flow. Agent Layer The agent generates, tests, and assembles the contract. It handles versioning, logic validation, and deployment readiness. Security checks-reentrancy protection, overflow control, gas modeling-are embedded into the generation phase. Generated outputs are mapped to their source data using OpenLedger’s Proof of Attribution, providing traceability across the pipeline. How does the AI model work? Morpheus is being powered by a specialized Solidity model built on top of OpenLedger. This model is purpose-built to handle the nuances of smart contract logic, security, and upgradeability. Unlike generalized coding agents, it is designed specifically for EVM environments and Web3 use cases, drawing from real protocol data and security best practices. Morpheus is fine-tuned on a vertical stack of smart contract data: Audited protocol code (e.g., Uniswap V4, Compound) OpenZeppelin libraries and EIP reference implementations Smart contract vulnerability reports and exploit reconstructions Edge cases from fuzz testing and adversarial examples It uses models like CodeLlama and DeepSeek-Coder, enhanced through RAG pipelines referencing standardized security patterns and emerging protocol designs. This training stack is integrated into a continuous feedback loop, enabling real-time specialization for EVM and beyond. Why a specialized model is needed? Smart contract development is uniquely high-stakes. A generalized AI model is not enough. As 'vibe coding' and natural language programming become more common, we're seeing an influx of AI-generated code in Web3 as well. But smart contracts are not frontends or prototypes-they govern real value, enforce trustless execution, and often become immutable after deployment. Billions have been lost in Web3 due to bugs and inefficiencies: In 2022 alone, over $3.8 billion was stolen due to smart contract exploits, many of which stemmed from avoidable issues like reentrancy, integer overflows, or access control failures. Inefficient contract structures lead to unnecessary gas consumption. Optimizing for gas can reduce costs by up to 40%, saving projects millions over time. Upgradeable contract patterns, like UUPS or Transparent Proxies, require strict adherence to storage layout and initialization rules. Mistakes here often go undetected by generic models and can render a contract unupgradeable or vulnerable. A specialized Solidity model is trained on real-world exploits, EIP standards, and libraries like OpenZeppelin to: Generate secure, gas-efficient code by default Recognize and correctly implement complex proxy patterns Map user intent to modular, auditable contract architectures Incorporate battle-tested logic from audited protocols and fuzz-tested edge cases Morpheus goes beyond syntax-it understands the nuances of decentralized infrastructure and deploys code that meets production-grade standards. What applications will this enable Token creation with built-in logic (tax, liquidity, governance) DeFi automations triggered by market conditions Payment contracts between agents and contributors DAO tooling with dynamic NFT-based voting Cross-chain bridging logic tied to real-world oracles Asset issuance flows through chat-based interfaces Natural language contract templates with reusable logic Each of these flows is backed by OpenLedger’s Proof of Attribution-ensuring traceability, explainability, and fair rewards across the ecosystem. This is the future of AI-native development. Open. Attributed. Explainable. Community-powered. Morpheus and OpenLedger are building the first system for autonomous coding agents where: Contributor work is recorded onchain Reuse is incentivized through attribution Model outputs are traceable and explainable Contracts evolve through human-agent collaboration Anyone can contribute prompts, logic, or flows-and get rewarded The smart contract engineer is no longer a human-only role. It is an agentic, decentralized, and transparent process-powered by OpenLedger.

OpenLedger

46,735 görüntüleme • 1 yıl önce

VoxCPM 2 just dropped by OpenBMB Only 2B-param open-source TTS (Text-to-Speech) model built for production-grade multilingual voice work. Apache-2.0 license, Can run on only 8GB VRAM. • Eliminates the "robotic" feel of traditional TTS, delivering prosody and emotional depth suitable for high-stakes professional environments like filmmaking, gaming, animation, and audiobooks. • 30-language multilingual: no language tag needed, just type in a supported language and generate directly. • Voice design: create a brand-new voice from a text description alone, like age, tone, pace, or emotion. No reference audio required. Describe the desired voice characteristics (gender, age, tone, emotion, pace …) in Control Instruction, and VoxCPM2 will craft a unique voice from your description alone. • Controllable cloning: clone from a short clip, then steer delivery style without losing the speaker’s core voice. • Ultimate cloning: use reference audio + transcript for continuation-style cloning that keeps the tiny vocal details. • 48kHz output: takes 16kHz reference audio and produces studio-quality speech without an external upsampler. • Real-time ready: around 0.3 RTF on RTX 4090, even lower with Nano-VLLM. • Commercial use: Apache-2.0 licensed. Developer-Friendly Infrastructure: - Native Torch Inference: Direct support for PyTorch-based workflows. - Training Flexibility: Supports both full-parameter and LoRA fine-tuning for specific domain adaptation. - Production Readiness: Compatible with voxcpm-nanovllm for large-scale, high-concurrency deployment.
1:58

VoxCPM 2 just dropped by OpenBMB Only 2B-param open-source TTS (Text-to-Speech) model built for production-grade multilingual voice work. Apache-2.0 license, Can run on only 8GB VRAM. • Eliminates the "robotic" feel of traditional TTS, delivering prosody and emotional depth suitable for high-stakes professional environments like filmmaking, gaming, animation, and audiobooks. • 30-language multilingual: no language tag needed, just type in a supported language and generate directly. • Voice design: create a brand-new voice from a text description alone, like age, tone, pace, or emotion. No reference audio required. Describe the desired voice characteristics (gender, age, tone, emotion, pace …) in Control Instruction, and VoxCPM2 will craft a unique voice from your description alone. • Controllable cloning: clone from a short clip, then steer delivery style without losing the speaker’s core voice. • Ultimate cloning: use reference audio + transcript for continuation-style cloning that keeps the tiny vocal details. • 48kHz output: takes 16kHz reference audio and produces studio-quality speech without an external upsampler. • Real-time ready: around 0.3 RTF on RTX 4090, even lower with Nano-VLLM. • Commercial use: Apache-2.0 licensed. Developer-Friendly Infrastructure: - Native Torch Inference: Direct support for PyTorch-based workflows. - Training Flexibility: Supports both full-parameter and LoRA fine-tuning for specific domain adaptation. - Production Readiness: Compatible with voxcpm-nanovllm for large-scale, high-concurrency deployment.

Rohan Paul

13,541 görüntüleme • 3 ay önce

I know there are many people out there who credit dogs for keeping them going, getting through tough times and even saving their lives. I’ve heard the personal stories from 100s of people. Dogs are so pure and unconditional with their support and love. I can’t explain how much pressure and stress I’ve been under the last year and in particular the last 3-4 months. Tina may no longer be with us but it is because of her that I keep going on this mission. In the dark times I think about her face and her warm cosy fur. I’m not sure but were it not for Tina there are times when I might have broken or had to stop such was the suffering and pain we see. So much is about to come together… 📕 In 43 days the book about Tina will be out. It was a work of pure love. But exhausting too emotionally. 🏥 Tina’s field hospital opens on Tuesday with our new vet starting. Her big hospital is also being built. 🎤 I’m doing about 7-8 events in Ireland and England in May followed by the USA telling Tina’s story to 1000s of people. I’m terrified. 🥘 Her little sibling (in my head) Alba has her own kitchen just open feeding 1250 dogs a day ✂️ We have funded over 20,000 sterilising in 2025 already. That’s just a tiny amount of the things happening. We do them all for the street dogs but I personally do them for Tina. Some dogs (and people) shake you and move you to your very core. They are soul dogs. That is Tina for me. I was exhausted and burnt out tonight with so much to juggle so I sat in bed and opened my Tina folder of videos on my phone. I wanted to sleep but just seeing her face made me want to share a little video and write this. She just makes me want to put more good into the world for all to share. Maybe when I get through the next 2 mad months I dream of sitting on a little quiet beach somewhere on my own reading a book, fully offline and just thinking about Tina. I’ll tell her about all that has happened. I’ve not been able to do that yet. But for now there is one more big push needed in Tina’s name 💛💙
0:41

I know there are many people out there who credit dogs for keeping them going, getting through tough times and even saving their lives. I’ve heard the personal stories from 100s of people. Dogs are so pure and unconditional with their support and love. I can’t explain how much pressure and stress I’ve been under the last year and in particular the last 3-4 months. Tina may no longer be with us but it is because of her that I keep going on this mission. In the dark times I think about her face and her warm cosy fur. I’m not sure but were it not for Tina there are times when I might have broken or had to stop such was the suffering and pain we see. So much is about to come together… 📕 In 43 days the book about Tina will be out. It was a work of pure love. But exhausting too emotionally. 🏥 Tina’s field hospital opens on Tuesday with our new vet starting. Her big hospital is also being built. 🎤 I’m doing about 7-8 events in Ireland and England in May followed by the USA telling Tina’s story to 1000s of people. I’m terrified. 🥘 Her little sibling (in my head) Alba has her own kitchen just open feeding 1250 dogs a day ✂️ We have funded over 20,000 sterilising in 2025 already. That’s just a tiny amount of the things happening. We do them all for the street dogs but I personally do them for Tina. Some dogs (and people) shake you and move you to your very core. They are soul dogs. That is Tina for me. I was exhausted and burnt out tonight with so much to juggle so I sat in bed and opened my Tina folder of videos on my phone. I wanted to sleep but just seeing her face made me want to share a little video and write this. She just makes me want to put more good into the world for all to share. Maybe when I get through the next 2 mad months I dream of sitting on a little quiet beach somewhere on my own reading a book, fully offline and just thinking about Tina. I’ll tell her about all that has happened. I’ve not been able to do that yet. But for now there is one more big push needed in Tina’s name 💛💙

Niall Harbison

233,719 görüntüleme • 1 yıl önce

Marathon | Ultimate Overview, Gameplay, Hands-On Impressions ▪️Team based extraction shooter set on Tau Ceti IV, scavenge remains of a lost colony for glory and fortune ▪️Launch: Coming to PS5, Xbox and PC on September 23 ▪️Will be a "premium" product, meaning not F2P ▪️"Weapons and movement feels crisp, fluid, and incredibly satisfying in that rarified way that few studios can achieve" ▪️3 maps, 6 runner classes at launch, more to follow post-launch ▪️Plans to support the game with new maps, weapons, characters, and more as it goes on ▪️Ranked play, end game challenges, seasonal storytelling, secrets to discover, community events all in Season One with more content coming ▪️You play as a "runner", cybernetic mercenary who's given up their human form for a bio-synthetic shell with unique abilities and stats ▪️Runner Types: "Locus" is a soldier class for pushing forward, can use a shield, "Void" is stealth, sneak by undetected, use smoke grenades, "Blackbird" is reconnaissance based, find players, positioning, and more ▪️Uncover secrets hidden in the wake of the original Marathon trilogy's events - how and where this overlaps or clashes with the original games "is a story that will unfold over time" ▪️Objective is to get in, get as much loot as you can, and get out alive ▪️If you die, your gear and loot will be up for grabs. Survive and you can take your gear with you on future runs as you grow in power and fill your vault ▪️Fight in a crew of up to 3 players, various map sizes up to 18 players ▪️PvP + PvE, battle other players, security forces, and "otherworldly threats" ▪️Contextual pings, shared objectives, down-but-not-out mechanics ▪️Environments are filled with weapons, materials, items, resources, cores, keys, backpacks, secrets etc to find You can find things like backpacks that expand your inventory, powerful and unique weapons, consumables to heal yourself, ▪️Select your runner, strategically build your loadouts pre-match ▪️Factions in the game can sponsor you and your loadout ▪️You have the freedom to opt out of crew fill and take all the glory for yourself as a solo runner ▪️"This is probably the best-looking, best-feeling extraction shooter ever made", not easy for newcomers to the genre, can be tough to get into, but one previewer was "reluctant to put Marathon down. This is a good sign – the best thing I can say after any preview is that I want more – but big questions remain" ▪️No two matches ever play out the same, dynamic events, variable weather, unpredictable players etc ▪️Customization: Each Runner "brings their own flair", but serve as foundations to customize your playstyle - collect implants and equipment to augment your Runner, like stacking implants/upgrades to reduce heat build-up to allow you to keep running, jumping, sliding longer ▪️Contracts: "Ingenious" incentives, finish contracts you accept for permanent upgrades to your stats, add precious items like grenades, shields, inventory-expanding backpacks, etc to your market. The bigger your market, the better your minimum loadout becomes ▪️Contracts provide "valuable direction", bring welcome diversity and add a "precious hit of semi-permanent progression" ▪️Prestige Cores: Rare items that can "really push the boundaries" (ex: Glitch has an upgrade that turns double jump into triple jump for more manueverability) ▪️Another rare item is a backpack that turns you invisible while interacting with containers (very useful when everyone on the map is hunting you) ▪️Each match "feels like the most important one ever", high stakes, "surprisingly challenging AI enemies" that were "much, much better at surrounding and overwhelming players than the vast majority of AI enemies found in other games" ▪️Having a balanced crew helps in exploring the "dark and forgotten places" in maps - filled with deadly creatures like a species of giant ticks who swarm you frantically ▪️Battles can become frantic as you encounter other crews, stalk them across the map, encounter AI enemies to fend off when others come to claim your loot (one preview battle turned into a 9 player free-for-all) ▪️Downside could be the reward system where skilled players enter fresh matches with high level gear that outmatches less skilled players, though Bungie says it has gone out of its way to try and make it where a poorly equipped squad can still stand a chance if they play well ▪️Even if you die, you can can still get upgrades, improve your reputation with factions, advance in perk trees, etc by completing various quests, looting chests, or fulfilling specific objectives which unlock new bits of story and can grant perks like buying slightly better gear from vendors ▪️"The world Bungie has built is every bit as beautiful as it is creepy and dystopian, and there are moments where they satisfyingly hint at the events of the Marathon trilogy from the ‘90s", though "what little I saw did only slightly more than pay lip service to the world" ▪️Uses the seasonal reset model like in Diablo 4, where players are stripped of their loot and progress at the end of each season to mix things up with new content and new meta ▪️Game is designed to get you killed, Bungie expects average exfiltration rates to be comfortably below 50% ▪️"You will lose a lot, and losing hurts a lot[...]Extracts are snapshots of this unpredictability. That white-knuckle countdown may become a gut-punch defeat, an unforgettable clutch, a desperate last-second dive into the portal as your downed allies watch in envy and horror (couldn't be me), or an unnerving anticlimax. It's not always a pleasant one, but it is a strong emotional hook" ▪️Some previewers worried about variety, weren't impressed with the objectives in the alpha, like hunting computer monitors on the map, sprinting over, marking dropships, sprinting over, and repeating, though random events help spice things up ▪️Not a 20-map game says Bungie, map design "does have that sticky battle royale quality of generating memories", though still worried 3-4 medium sized maps might not be enough ▪️Bungie's "verbiage" on updates sounds like possibly 1 new map a year + refreshing existing ones in between, which could work in its favor pushing players to really learn maps, but will they hold up over hundreds of hours? ▪️Fights are decided by gun skill, clever ability use, map awareness, how strong your shield is, how many healing supplies you have, etc ▪️Example: If you have one bar of shield and enemy has four, you'll lose 1v1, but change it up with powerful grenades, status effects like toxic or overheat, backpacks are "transformative", etc Gameplay Trailer ▶️ Gameplay Overview ▶️ PS Blog ➡️ IGN ➡️ GamesRadar ➡️ ▶️
2:58

Marathon | Ultimate Overview, Gameplay, Hands-On Impressions ▪️Team based extraction shooter set on Tau Ceti IV, scavenge remains of a lost colony for glory and fortune ▪️Launch: Coming to PS5, Xbox and PC on September 23 ▪️Will be a "premium" product, meaning not F2P ▪️"Weapons and movement feels crisp, fluid, and incredibly satisfying in that rarified way that few studios can achieve" ▪️3 maps, 6 runner classes at launch, more to follow post-launch ▪️Plans to support the game with new maps, weapons, characters, and more as it goes on ▪️Ranked play, end game challenges, seasonal storytelling, secrets to discover, community events all in Season One with more content coming ▪️You play as a "runner", cybernetic mercenary who's given up their human form for a bio-synthetic shell with unique abilities and stats ▪️Runner Types: "Locus" is a soldier class for pushing forward, can use a shield, "Void" is stealth, sneak by undetected, use smoke grenades, "Blackbird" is reconnaissance based, find players, positioning, and more ▪️Uncover secrets hidden in the wake of the original Marathon trilogy's events - how and where this overlaps or clashes with the original games "is a story that will unfold over time" ▪️Objective is to get in, get as much loot as you can, and get out alive ▪️If you die, your gear and loot will be up for grabs. Survive and you can take your gear with you on future runs as you grow in power and fill your vault ▪️Fight in a crew of up to 3 players, various map sizes up to 18 players ▪️PvP + PvE, battle other players, security forces, and "otherworldly threats" ▪️Contextual pings, shared objectives, down-but-not-out mechanics ▪️Environments are filled with weapons, materials, items, resources, cores, keys, backpacks, secrets etc to find You can find things like backpacks that expand your inventory, powerful and unique weapons, consumables to heal yourself, ▪️Select your runner, strategically build your loadouts pre-match ▪️Factions in the game can sponsor you and your loadout ▪️You have the freedom to opt out of crew fill and take all the glory for yourself as a solo runner ▪️"This is probably the best-looking, best-feeling extraction shooter ever made", not easy for newcomers to the genre, can be tough to get into, but one previewer was "reluctant to put Marathon down. This is a good sign – the best thing I can say after any preview is that I want more – but big questions remain" ▪️No two matches ever play out the same, dynamic events, variable weather, unpredictable players etc ▪️Customization: Each Runner "brings their own flair", but serve as foundations to customize your playstyle - collect implants and equipment to augment your Runner, like stacking implants/upgrades to reduce heat build-up to allow you to keep running, jumping, sliding longer ▪️Contracts: "Ingenious" incentives, finish contracts you accept for permanent upgrades to your stats, add precious items like grenades, shields, inventory-expanding backpacks, etc to your market. The bigger your market, the better your minimum loadout becomes ▪️Contracts provide "valuable direction", bring welcome diversity and add a "precious hit of semi-permanent progression" ▪️Prestige Cores: Rare items that can "really push the boundaries" (ex: Glitch has an upgrade that turns double jump into triple jump for more manueverability) ▪️Another rare item is a backpack that turns you invisible while interacting with containers (very useful when everyone on the map is hunting you) ▪️Each match "feels like the most important one ever", high stakes, "surprisingly challenging AI enemies" that were "much, much better at surrounding and overwhelming players than the vast majority of AI enemies found in other games" ▪️Having a balanced crew helps in exploring the "dark and forgotten places" in maps - filled with deadly creatures like a species of giant ticks who swarm you frantically ▪️Battles can become frantic as you encounter other crews, stalk them across the map, encounter AI enemies to fend off when others come to claim your loot (one preview battle turned into a 9 player free-for-all) ▪️Downside could be the reward system where skilled players enter fresh matches with high level gear that outmatches less skilled players, though Bungie says it has gone out of its way to try and make it where a poorly equipped squad can still stand a chance if they play well ▪️Even if you die, you can can still get upgrades, improve your reputation with factions, advance in perk trees, etc by completing various quests, looting chests, or fulfilling specific objectives which unlock new bits of story and can grant perks like buying slightly better gear from vendors ▪️"The world Bungie has built is every bit as beautiful as it is creepy and dystopian, and there are moments where they satisfyingly hint at the events of the Marathon trilogy from the ‘90s", though "what little I saw did only slightly more than pay lip service to the world" ▪️Uses the seasonal reset model like in Diablo 4, where players are stripped of their loot and progress at the end of each season to mix things up with new content and new meta ▪️Game is designed to get you killed, Bungie expects average exfiltration rates to be comfortably below 50% ▪️"You will lose a lot, and losing hurts a lot[...]Extracts are snapshots of this unpredictability. That white-knuckle countdown may become a gut-punch defeat, an unforgettable clutch, a desperate last-second dive into the portal as your downed allies watch in envy and horror (couldn't be me), or an unnerving anticlimax. It's not always a pleasant one, but it is a strong emotional hook" ▪️Some previewers worried about variety, weren't impressed with the objectives in the alpha, like hunting computer monitors on the map, sprinting over, marking dropships, sprinting over, and repeating, though random events help spice things up ▪️Not a 20-map game says Bungie, map design "does have that sticky battle royale quality of generating memories", though still worried 3-4 medium sized maps might not be enough ▪️Bungie's "verbiage" on updates sounds like possibly 1 new map a year + refreshing existing ones in between, which could work in its favor pushing players to really learn maps, but will they hold up over hundreds of hours? ▪️Fights are decided by gun skill, clever ability use, map awareness, how strong your shield is, how many healing supplies you have, etc ▪️Example: If you have one bar of shield and enemy has four, you'll lose 1v1, but change it up with powerful grenades, status effects like toxic or overheat, backpacks are "transformative", etc Gameplay Trailer ▶️ Gameplay Overview ▶️ PS Blog ➡️ IGN ➡️ GamesRadar ➡️ ▶️

Shinobi602

181,424 görüntüleme • 1 yıl önce

Borderlands 4 previews have dropped and they are insanely positive, It is being praised across the board as being a massive step up from Borderlands 3 and possibly the best BL to date! Here’s some highlights of the new info: - Borderlands 4 features a more grounded and darker story set on a dystopian world ruled by the Timekeeper - Humor is still present but more restrained to suit the darker narrative tone, Less cringe humor as in BL3 - The game feels like a soft reboot for the franchise, introducing new lore and gameplay structures - Movement has been completely overhauled with double-jumping, gliding, dashing, grappling hooks, and swimming - Four new Vault Hunters are available: Vex (Siren), Rafa (Gadget Soldier), Harlowe (Sniper), and Aton (Brawler) - Kairos, the new planet, is one seamless open world with no loading between zones - Split-screen co-op returns for local multiplayer - The game adopts a Destiny-like structure with side activities, dynamic events, and exploration hubs - Vehicles can be summoned anywhere on the map, making travel smoother and more immersive - The world of Kairos features dynamic weather systems and environmental variety - Combat pacing is faster with smarter, more aggressive enemies that emphasize dodging and movement - One boss previewed was the most complex and mechanics-rich in Borderlands history - Buildcrafting is significantly deeper with new enhancement gear slots and item augments - Weapon rarity is better balanced, legendary drops are rarer - Mission and boss replays are now built-in, allowing players to farm specific content - Online matchmaking is improved with simplified lobbies and clearer difficulty scaling - Gearbox aims to avoid turning Borderlands into a live-service GaaS model - Borderlands 4 aims to reclaim its position in the looter shooter genre after years of stagnation Borderlands 2 is one of my fave co-op games ever and BL3 really let me down but this is sounding like a massive improvement, definitely will be playing this at release this September 12th
0:53

Borderlands 4 previews have dropped and they are insanely positive, It is being praised across the board as being a massive step up from Borderlands 3 and possibly the best BL to date! Here’s some highlights of the new info: - Borderlands 4 features a more grounded and darker story set on a dystopian world ruled by the Timekeeper - Humor is still present but more restrained to suit the darker narrative tone, Less cringe humor as in BL3 - The game feels like a soft reboot for the franchise, introducing new lore and gameplay structures - Movement has been completely overhauled with double-jumping, gliding, dashing, grappling hooks, and swimming - Four new Vault Hunters are available: Vex (Siren), Rafa (Gadget Soldier), Harlowe (Sniper), and Aton (Brawler) - Kairos, the new planet, is one seamless open world with no loading between zones - Split-screen co-op returns for local multiplayer - The game adopts a Destiny-like structure with side activities, dynamic events, and exploration hubs - Vehicles can be summoned anywhere on the map, making travel smoother and more immersive - The world of Kairos features dynamic weather systems and environmental variety - Combat pacing is faster with smarter, more aggressive enemies that emphasize dodging and movement - One boss previewed was the most complex and mechanics-rich in Borderlands history - Buildcrafting is significantly deeper with new enhancement gear slots and item augments - Weapon rarity is better balanced, legendary drops are rarer - Mission and boss replays are now built-in, allowing players to farm specific content - Online matchmaking is improved with simplified lobbies and clearer difficulty scaling - Gearbox aims to avoid turning Borderlands into a live-service GaaS model - Borderlands 4 aims to reclaim its position in the looter shooter genre after years of stagnation Borderlands 2 is one of my fave co-op games ever and BL3 really let me down but this is sounding like a massive improvement, definitely will be playing this at release this September 12th

Synth Potato🥔

1,728,003 görüntüleme • 1 yıl önce

meta muse spark 1.1 vs gpt 5.6 sol vs fable 5 vs grok 4.5 meta recently dropped muse spark 1.1 – a multimodal reasoning model from meta superintelligence labs built for agentic tasks. key facts: • 1m token context with active self-management – the model compacts its own history and keeps only the steps needed for later work • trained to orchestrate multi-agent systems: as main agent it plans and delegates to parallel subagents, as subagent it sticks to its job and knows when to escalate back • computer use trained to pick between scripting and clicking – writes automation when it's faster, clicks when it's simpler, batches actions per step • first public api from meta: the meta model api is now in preview • benchmarks: sweeps the agent column – mcp atlas 88.1 (opus 4.8: 82.2), jobbench 54.7 (opus: 48.4), humanity's last exam 62.1 (1st). loses coding – deepswe 1.1 53.3 vs gpt 5.5's 67.0, swe bench pro 61.5 vs opus's 69.2 our test – 3 prompts, single-file html, three.js, fully procedural, no assets: 1. norwegian house cantilevered over a fjord in a snowstorm – transmissive glass wall, fully modelled interior 2. beijing siheyuan courtyard house in dawn fog – instanced roof tiles, dougong brackets, glowing paper windows 3. new mexico adobe pueblo in an approaching dust storm – deep window reveals, windward grit accumulation we ran the test on AI/ML API platform results: - cost #1 muse spark 1.1 – $0.20 #2 grok 4.5 – $0.51 #3 gpt 5.6 sol – $1.93 #4 fable 5 – ~$5.20 - output tokens #1 muse spark 1.1 – 41,868 #2 gpt 5.6 sol – 49,139 #3 grok 4.5 – 64,954 #4 fable 5 – 81,849 - lines of code #1 muse spark 1.1 – 1,799 #2 gpt 5.6 sol – 2,377 #3 fable 5 – 3,088 #4 grok 4.5 – 4,216 observations: • muse spark is the cheapest of the four by a wide margin – 2.5x under grok, ~26x under fable per run. output quality tracks the price • only 7.4% of its output tokens are reasoning (3,104 of 41,868) – the model barely thinks before writing. economic, not pedantic: it commits to the first plan and ships it • the low loc is not compression, it's omission – all three prompts demanded instancing, muse spark delivered it in one muse spark's code quality – reviewed by fable 5: upsides: 1. all three files run 2. the adobe grit effect is legit – shader injection via onbeforecompile, windward faces detect storm direction through a normal-dot-wind term and darken procedurally 3. the fjord glass is real meshphysicalmaterial with transmission and ior, not a transparent quad 4. the siheyuan properly instances barrel tiles, dougong blocks and courtyard pavers downsides: 1. in the fjord file the strafe vector is negated – press a, you move right; press d, you move left. exactly the key mix-up we kept hitting with this model 2. all three files ship the model's self-doubt as comments: "// actually yaw orientation: need correct" sits above a direction vector that gets computed, abandoned and recomputed – dead vectors allocated every frame, 60 times a second 3. the siheyuan registers two separate keydown listeners, one containing an empty if-block 4. snow "accumulation" on the norway roof is a sine wobble on a scale value, not accumulation 5. "instanced snow" became 3,500 plain points. zero dispose calls anywhere pattern: minimal reasoning, minimal code, minimal price. it nails the flashy requirements – shaders, transmissive glass – and quietly drops the boring ones: instancing, controls, cleanup. you get a demo that mostly runs and a control scheme you can't trust follow thehype. for 24/7 ai news, analysis and breakdowns
1:01

meta muse spark 1.1 vs gpt 5.6 sol vs fable 5 vs grok 4.5 meta recently dropped muse spark 1.1 – a multimodal reasoning model from meta superintelligence labs built for agentic tasks. key facts: • 1m token context with active self-management – the model compacts its own history and keeps only the steps needed for later work • trained to orchestrate multi-agent systems: as main agent it plans and delegates to parallel subagents, as subagent it sticks to its job and knows when to escalate back • computer use trained to pick between scripting and clicking – writes automation when it's faster, clicks when it's simpler, batches actions per step • first public api from meta: the meta model api is now in preview • benchmarks: sweeps the agent column – mcp atlas 88.1 (opus 4.8: 82.2), jobbench 54.7 (opus: 48.4), humanity's last exam 62.1 (1st). loses coding – deepswe 1.1 53.3 vs gpt 5.5's 67.0, swe bench pro 61.5 vs opus's 69.2 our test – 3 prompts, single-file html, three.js, fully procedural, no assets: 1. norwegian house cantilevered over a fjord in a snowstorm – transmissive glass wall, fully modelled interior 2. beijing siheyuan courtyard house in dawn fog – instanced roof tiles, dougong brackets, glowing paper windows 3. new mexico adobe pueblo in an approaching dust storm – deep window reveals, windward grit accumulation we ran the test on AI/ML API platform results: - cost #1 muse spark 1.1 – $0.20 #2 grok 4.5 – $0.51 #3 gpt 5.6 sol – $1.93 #4 fable 5 – ~$5.20 - output tokens #1 muse spark 1.1 – 41,868 #2 gpt 5.6 sol – 49,139 #3 grok 4.5 – 64,954 #4 fable 5 – 81,849 - lines of code #1 muse spark 1.1 – 1,799 #2 gpt 5.6 sol – 2,377 #3 fable 5 – 3,088 #4 grok 4.5 – 4,216 observations: • muse spark is the cheapest of the four by a wide margin – 2.5x under grok, ~26x under fable per run. output quality tracks the price • only 7.4% of its output tokens are reasoning (3,104 of 41,868) – the model barely thinks before writing. economic, not pedantic: it commits to the first plan and ships it • the low loc is not compression, it's omission – all three prompts demanded instancing, muse spark delivered it in one muse spark's code quality – reviewed by fable 5: upsides: 1. all three files run 2. the adobe grit effect is legit – shader injection via onbeforecompile, windward faces detect storm direction through a normal-dot-wind term and darken procedurally 3. the fjord glass is real meshphysicalmaterial with transmission and ior, not a transparent quad 4. the siheyuan properly instances barrel tiles, dougong blocks and courtyard pavers downsides: 1. in the fjord file the strafe vector is negated – press a, you move right; press d, you move left. exactly the key mix-up we kept hitting with this model 2. all three files ship the model's self-doubt as comments: "// actually yaw orientation: need correct" sits above a direction vector that gets computed, abandoned and recomputed – dead vectors allocated every frame, 60 times a second 3. the siheyuan registers two separate keydown listeners, one containing an empty if-block 4. snow "accumulation" on the norway roof is a sine wobble on a scale value, not accumulation 5. "instanced snow" became 3,500 plain points. zero dispose calls anywhere pattern: minimal reasoning, minimal code, minimal price. it nails the flashy requirements – shaders, transmissive glass – and quietly drops the boring ones: instancing, controls, cleanup. you get a demo that mostly runs and a control scheme you can't trust follow thehype. for 24/7 ai news, analysis and breakdowns

thehype.

130,517 görüntüleme • 4 gün önce

🚨NEW: Gaza Humanitarian Fund Launches as Israeli Opposition Leader Alleges Covert State Funding The major U.S.-linked aid initiative in Gaza is facing intense scrutiny after Israeli opposition leader Yair Lapid alleged that the Netanyahu government is secretly backing the Gaza Humanitarian Fund (GHF) through foreign front companies. GHF officially launched operations on Monday, saying it had begun delivering food to secure distribution sites in Gaza and aims to reach 1 million Palestinians by the end of the week. But its leadership collapse, legal challenges, and structural concerns have cast doubt on the effort’s long-term viability. Key Details: ➤ Lapid: Israel Using Shell Companies to Influence Gaza Aid Speaking during a no-confidence vote in the Knesset, Lapid claimed that the Israeli government is behind two foreign entities—the Swiss-based GHF and the American-registered Safe Reach Solutions—allegedly set up to funnel Israeli public funds into Gaza aid operations. He suggested the project was orchestrated by Israeli security services under Prime Minister Netanyahu and Finance Minister Smotrich, warning that it may be an effort to control humanitarian access under the guise of neutrality. GHF told reporters it had secured $100 million in funding from an anonymous donor even after initial backers like UAE and some European nations had backed away. ➤ Israeli Government Denies Allegations A spokesperson for Netanyahu’s office said, “Israel is not funding the humanitarian aid to the Gaza Strip.” No other evidence has yet surfaced to confirm Lapid’s claims, and no international watchdog or third-party government has investigated the claims. Ambassador Mike Huckabee had previously said that claims of Israeli involvement were “wholly untrue.” ➤ GHF Launches; Wood Resigns, Acree Named Interim Director Jake Wood resigned as GHF’s CEO yesterday, just before launch, saying the group could not uphold the principles of “humanity, neutrality, impartiality, and independence.” He had been approached two months ago to lead the initiative but said the structure was fundamentally compromised. GHF has since promoted its Head of Mission former USAID official John Acree as interim Executive Director. ➤ GHF to Temporarily Rely on NGOs for Food Aid Until It Scales Operations In a letter to COGAT dated May 22 and obtained by Middle East Eye, Jake Wood said GHF would initially open four secure distribution sites—three in southern Gaza and one in central Gaza—with plans to expand to at least eight, including in the north. Until then, “qualified humanitarian agencies” will continue distributing food aid in parallel. Wood acknowledged that GHF lacks the infrastructure to manage distributions independently for now, but intends to assume a more direct role once it scales up. Non-food items like medical supplies and hygiene kits will remain under the existing UN-led system, coordinated with Israel. ➤ Swiss Office Shuts Down; Legal Review Underway Swiss authorities are reviewing whether to open a formal investigation after TRIAL International, a war crimes watchdog, filed complaints against GHF. GHF’s Swiss operations have been completely suspended, and the group plans to continue via its U.S.-based entity. ➤ Widespread Rejection by Aid Agencies and Donors GHF’s model—built around Israeli-designated “safe corridors” and distribution hubs secured by private armed contractors, with aid restricted to pre-approved Palestinians—has been widely rejected by the humanitarian community. The U.N. and major aid organizations have refused to participate, warning that the plan violates core humanitarian principles, risks militarizing aid delivery, and could contribute to the forced displacement of Palestinians—a war crime under international law. Donor governments in Europe and Asia have also reportedly backed away, citing concerns about the fund’s feasibility, logistics, and lack of neutrality.
1:24

🚨NEW: Gaza Humanitarian Fund Launches as Israeli Opposition Leader Alleges Covert State Funding The major U.S.-linked aid initiative in Gaza is facing intense scrutiny after Israeli opposition leader Yair Lapid alleged that the Netanyahu government is secretly backing the Gaza Humanitarian Fund (GHF) through foreign front companies. GHF officially launched operations on Monday, saying it had begun delivering food to secure distribution sites in Gaza and aims to reach 1 million Palestinians by the end of the week. But its leadership collapse, legal challenges, and structural concerns have cast doubt on the effort’s long-term viability. Key Details: ➤ Lapid: Israel Using Shell Companies to Influence Gaza Aid Speaking during a no-confidence vote in the Knesset, Lapid claimed that the Israeli government is behind two foreign entities—the Swiss-based GHF and the American-registered Safe Reach Solutions—allegedly set up to funnel Israeli public funds into Gaza aid operations. He suggested the project was orchestrated by Israeli security services under Prime Minister Netanyahu and Finance Minister Smotrich, warning that it may be an effort to control humanitarian access under the guise of neutrality. GHF told reporters it had secured $100 million in funding from an anonymous donor even after initial backers like UAE and some European nations had backed away. ➤ Israeli Government Denies Allegations A spokesperson for Netanyahu’s office said, “Israel is not funding the humanitarian aid to the Gaza Strip.” No other evidence has yet surfaced to confirm Lapid’s claims, and no international watchdog or third-party government has investigated the claims. Ambassador Mike Huckabee had previously said that claims of Israeli involvement were “wholly untrue.” ➤ GHF Launches; Wood Resigns, Acree Named Interim Director Jake Wood resigned as GHF’s CEO yesterday, just before launch, saying the group could not uphold the principles of “humanity, neutrality, impartiality, and independence.” He had been approached two months ago to lead the initiative but said the structure was fundamentally compromised. GHF has since promoted its Head of Mission former USAID official John Acree as interim Executive Director. ➤ GHF to Temporarily Rely on NGOs for Food Aid Until It Scales Operations In a letter to COGAT dated May 22 and obtained by Middle East Eye, Jake Wood said GHF would initially open four secure distribution sites—three in southern Gaza and one in central Gaza—with plans to expand to at least eight, including in the north. Until then, “qualified humanitarian agencies” will continue distributing food aid in parallel. Wood acknowledged that GHF lacks the infrastructure to manage distributions independently for now, but intends to assume a more direct role once it scales up. Non-food items like medical supplies and hygiene kits will remain under the existing UN-led system, coordinated with Israel. ➤ Swiss Office Shuts Down; Legal Review Underway Swiss authorities are reviewing whether to open a formal investigation after TRIAL International, a war crimes watchdog, filed complaints against GHF. GHF’s Swiss operations have been completely suspended, and the group plans to continue via its U.S.-based entity. ➤ Widespread Rejection by Aid Agencies and Donors GHF’s model—built around Israeli-designated “safe corridors” and distribution hubs secured by private armed contractors, with aid restricted to pre-approved Palestinians—has been widely rejected by the humanitarian community. The U.N. and major aid organizations have refused to participate, warning that the plan violates core humanitarian principles, risks militarizing aid delivery, and could contribute to the forced displacement of Palestinians—a war crime under international law. Donor governments in Europe and Asia have also reportedly backed away, citing concerns about the fund’s feasibility, logistics, and lack of neutrality.

Drop Site

57,684 görüntüleme • 1 yıl önce

I'm pumped to announce that DFS Mastermind is officially LIVE! I know I teased it some and showed it off but the pre-launch is over and now we build… The journey is just getting started and some of you have already joined in on the project with me. Thank you so much for your support! The early feedback is strong and has been that this concept of premium DFS evergreen content on demand, so to speak, where the community helps create and impact the content/ideas is a game-changer. So, what is DFS Mastermind? It's a passion pursuit project I created for all those that want to take DFS more serious with focus on the new topics and trends, review/application, information and education. All while collaborating with others that have that same curiousty and hunger for more knowledge! This includes content like: • Process/Strategy videos watching over my shoulder and listening as I explain my exact process across different sports and bringing in others that excel at sports I’m not as skilled/experienced with. • Case Studies/Review videos learning how I review and apply certain concepts I pick up from other top players and for other DFS sports. • Exlusive Interviews with DFS players - both professional and casual to learn more about their history, journey and see what we can pick up and learn from their past, lifestyle, mindset etc. • LIVE Events where we hop on a Zoom call together to collaborate and discuss topics around DFS sports, strategy, process, game theory, along with Q&A sessions etc. All this and MORE! There’s also a private Discord for reflection/collaboration before and after events and to discuss new content releases, share thoughts and ask questions that are sparked from watching/listening to them. Everything releases in both audio and video format, so you can take it in your own way, on your own time. If you miss a LIVE Event, it’s recorded and available for playback at your convenience. A completely new, innovative way to see things. Along with the ability to impact the content you see via the community-controlled content aspect! Important to note, this community won’t give you any projections, picks, plays, tools, data etc. (See Ship It Nation 🚀). It will instead give you evergreen knowledge and insight on topics many DFS players struggle with daily. A way to learn at your own pace and be part of collaborations with other DFS players of all skill levels. No matter what DFS sites you’ve been with or are currently at, this community is a great add-on for you. There’s something you can take away and apply across all the things I’ll cover because the community is helping decide it, proving a majority wants it! My mission is to help others get better at DFS and continue to grow the game we all love! Even if it does tilt us heavy at times! If you’ve ever enjoyed any of my work, this is a way to help ME, help YOU! This also helps the entire community. Join US: I truly appreciate if you can reply and/or help share this post. Thank you! Any questions, just shoot me a DM. I read all replies and respond to all DMs! P.S. I'm also offering a couple bonuses right out of the gate: 1.Most know I love a good giveaway, so why not kick things off with one of the biggest I’ve ever done! 👀 Anyone that joins the journey and supports will get entered into a draw on Dec. 23, 2024 for 1 $3,333 Ultimate Main Event Millionaire ticket on DraftKings, taking place Dec. 29, 2024. 2.When I first kicked this project off publicly, I asked thousands of DFS players to send in topics/questions they struggle with. Thanks to the 350+ that sent in questions, as it helped me create: DFS MIND MAP: TOP 10 TOPICS, TIPS, TRICKS & TIDBITS This is a 3hr30min Masterclass that everyone receives when they join the community. I’ll show more on that tomorrow but it’s a HUGE value to get you started and you’ll be part of the early group that receives it! 🧠🧩💡
0:41

I'm pumped to announce that DFS Mastermind is officially LIVE! I know I teased it some and showed it off but the pre-launch is over and now we build… The journey is just getting started and some of you have already joined in on the project with me. Thank you so much for your support! The early feedback is strong and has been that this concept of premium DFS evergreen content on demand, so to speak, where the community helps create and impact the content/ideas is a game-changer. So, what is DFS Mastermind? It's a passion pursuit project I created for all those that want to take DFS more serious with focus on the new topics and trends, review/application, information and education. All while collaborating with others that have that same curiousty and hunger for more knowledge! This includes content like: • Process/Strategy videos watching over my shoulder and listening as I explain my exact process across different sports and bringing in others that excel at sports I’m not as skilled/experienced with. • Case Studies/Review videos learning how I review and apply certain concepts I pick up from other top players and for other DFS sports. • Exlusive Interviews with DFS players - both professional and casual to learn more about their history, journey and see what we can pick up and learn from their past, lifestyle, mindset etc. • LIVE Events where we hop on a Zoom call together to collaborate and discuss topics around DFS sports, strategy, process, game theory, along with Q&A sessions etc. All this and MORE! There’s also a private Discord for reflection/collaboration before and after events and to discuss new content releases, share thoughts and ask questions that are sparked from watching/listening to them. Everything releases in both audio and video format, so you can take it in your own way, on your own time. If you miss a LIVE Event, it’s recorded and available for playback at your convenience. A completely new, innovative way to see things. Along with the ability to impact the content you see via the community-controlled content aspect! Important to note, this community won’t give you any projections, picks, plays, tools, data etc. (See Ship It Nation 🚀). It will instead give you evergreen knowledge and insight on topics many DFS players struggle with daily. A way to learn at your own pace and be part of collaborations with other DFS players of all skill levels. No matter what DFS sites you’ve been with or are currently at, this community is a great add-on for you. There’s something you can take away and apply across all the things I’ll cover because the community is helping decide it, proving a majority wants it! My mission is to help others get better at DFS and continue to grow the game we all love! Even if it does tilt us heavy at times! If you’ve ever enjoyed any of my work, this is a way to help ME, help YOU! This also helps the entire community. Join US: I truly appreciate if you can reply and/or help share this post. Thank you! Any questions, just shoot me a DM. I read all replies and respond to all DMs! P.S. I'm also offering a couple bonuses right out of the gate: 1.Most know I love a good giveaway, so why not kick things off with one of the biggest I’ve ever done! 👀 Anyone that joins the journey and supports will get entered into a draw on Dec. 23, 2024 for 1 $3,333 Ultimate Main Event Millionaire ticket on DraftKings, taking place Dec. 29, 2024. 2.When I first kicked this project off publicly, I asked thousands of DFS players to send in topics/questions they struggle with. Thanks to the 350+ that sent in questions, as it helped me create: DFS MIND MAP: TOP 10 TOPICS, TIPS, TRICKS & TIDBITS This is a 3hr30min Masterclass that everyone receives when they join the community. I’ll show more on that tomorrow but it’s a HUGE value to get you started and you’ll be part of the early group that receives it! 🧠🧩💡

Tyler Tamboline

60,031 görüntüleme • 1 yıl önce

🚨 OPERATIONAL UPDATE: ISRAEL U.S. WAR WITH THE ISLAMIC REPUBLIC Reporting Window: 3/22 to 3/23 • Iran fired additional cluster munition barrages into central Israel, with damage reported in Holon, Bat Yam, Or Yehuda, Safed, and the Jerusalem area, while another overnight launch triggered alerts in the Jerusalem corridor and south. • Israel widened its Lebanon campaign by destroying the Qasmiya bridge over the Litani and accelerating demolitions of homes and crossings in frontline villages. Reuters and AP both treated that as a major escalation. • Overnight strikes hit Tehran and a wider arc of Iranian military infrastructure, with your wire tracking blasts in east and northeast Tehran, Karaj, Yazd, Khorramabad, Bushehr, Bandar Abbas, and near Parchin, while the IDF publicly announced a broad wave of strikes on regime infrastructure in Tehran. • The Hormuz front remained the strategic center of gravity, but AP reported that Trump extended his deadline by five days rather than moving immediately to strike Iranian power plants. Iran simultaneously threatened Gulf power and water infrastructure if attacked. The last 24 hours were more concrete than conceptual. The most important story was not a new grand theory of the war. It was a set of specific events that showed how the conflict is now functioning day to day. Iran kept using cluster style ballistic attacks to create wider damage zones inside Israel. Israel moved from hitting Hezbollah targets to physically reshaping southern Lebanon. And inside Iran, the strike map widened again overnight with visible pressure on Tehran, missile infrastructure, coastal nodes, and internal security sites. At the same time, the anticipated U.S. move on Iranian power plants did not happen yet, which makes the immediate next window as important as the one just completed. ━━━━━━━━━━━━━━━━━━ 🚀 IRANIAN MISSILE ATTACKS ON ISRAEL Iran continued missile launches into Israel, but the operational detail that matters is how these attacks are being configured. Times of Israel live coverage reported fresh damage in central Israel from cluster munitions or fragments, while Jerusalem Post live coverage tracked shrapnel and fragment strikes in central Israel and additional impacts farther north. Ynet also highlighted two lightly wounded in Bat Yam and a partly collapsed building in Holon from the same general wave pattern. That matters because the attacks are no longer just about how many missiles Iran can fire. They are about how much disruption each missile can create. A single cluster warhead can turn one penetration or one imperfect interception into several impact points. Your wire also tracked this in real time, including central Israel damage and a later overnight launch that sent alerts toward Jerusalem and the south. One specific point worth noting is that today’s Israeli home front story was not dominated by mass casualties. It was dominated by repeated local damage events, scattered fragments, and shelter disruptions. That makes the attacks feel smaller than earlier war barrages, but not less operationally relevant. They are being used to sustain pressure while Iran’s launcher network remains under strain. ━━━━━━━━━━━━━━━━━━ 🇱🇧 LEBANON: ISRAEL MOVED FROM STRIKES TO TERRAIN DENIAL The biggest concrete change on the northern front was Israel’s continued move toward physical denial of Hezbollah movement rather than just attritional fire. Reuters reported that Israel struck the main bridge on the southern Lebanese coastal highway and ordered the destruction of homes near the border and bridges over the Litani River. AP reported the same bridge strike and framed Katz’s order to include all Litani crossings as a meaningful broadening of the target set. That means the Lebanon front is no longer just a story of rockets and retaliatory airstrikes. Israel is trying to reengineer the battlespace itself. Destroying crossings, flattening frontline structures, and reducing usable approach routes all point to the same objective: make it harder for Hezbollah to return south in meaningful strength even if the current phase of fighting slows. Reuters explicitly described Lebanese criticism that these measures look like pre invasion preparation and collective punishment. There was also an important corrective detail today. Times of Israel and Ynet both reported that the farmer killed near Misgav Am was not killed by Hezbollah fire after all, but by errant Israeli artillery shelling intended to support troops in southern Lebanon. That matters because it changes the factual record of one of yesterday’s most emotionally resonant northern incidents. ━━━━━━━━━━━━━━━━━━ ✈️ STRATEGIC AIR CAMPAIGN OVER IRAN Open source intelligence reported explosions and reported hits in east and northeast Tehran (shown in attached video), Hakimieh, Lavizan, Tehranpars, near the Parchin mountains, Karaj and Fardis, Khorramabad, Yazd, Bushehr, Bandar Abbas, and other sites. The IDF later publicly announced that it had launched a broad wave of strikes on regime infrastructure in Tehran. Mainstream coverage supported the broader pattern even where every individual site was not independently confirmed one by one. AP’s live coverage described explosions in Tehran and widening Israeli activity, while Times of Israel’s liveblog tracked the announced broad strike wave in Tehran. The strike set also appears to have remained mixed. This was not just about launchers. Open source reporting referenced possible targeted assassinations in Khorramabad and Tehran, missile site damage in Yazd, busier strike activity around coastal and port areas like Bandar Abbas and Bandar Deyr, and pressure near Parchin. Even where some of those claims remain open source rather than fully confirmed by Reuters or AP, the overall pattern is clear: the campaign remains broad, multi city, and focused on degrading the regime’s ability to keep fighting, not merely blunting the next launch. ━━━━━━━━━━━━━━━━━━ 🌍 GULF FRONT: STRIKES, INTERCEPTIONS, AND INFRASTRUCTURE THREATS The Gulf front stayed active, but the most important part of today’s story was not one giant headline strike. It was the persistence of Iranian pressure and the hardening response from Gulf states. AP reported that Iran threatened to mine the Persian Gulf and target regional energy infrastructure as Trump’s deadline neared. Reuters reported that Iran threatened to hit Gulf power plants and the systems powering U.S. bases if Iranian power infrastructure were attacked. Open source intel tracked the practical side of that pressure in real time. It logged interceptions and alerts in Bahrain, the UAE, and Saudi Arabia, including reported UAV interceptions in eastern Saudi Arabia, missile and drone interceptions by the UAE, and multiple reports of explosions or sirens in Bahrain. Those details are useful because they show the Gulf story is still not abstract diplomatic signaling. Air defenses are still being used. Another development worth mentioning is market stress. Reuters’ earlier energy reporting remains relevant here because Gulf attacks have already damaged major oil and gas facilities in several states, and the International Energy Agency chief warned that the current situation is worse than the oil crises of the 1970s. Your wire separately tracked comments from Fatih Birol about reserve releases and Hormuz as the key pressure point. ━━━━━━━━━━━━━━━━━━ ⚡ HORMUZ: THE BIG DECISION DID NOT HAPPEN YET This was probably the single most important strategic update of the day. The expected U.S. strike on Iranian power plants did not occur in this reporting window. Instead, AP reported that Trump extended the deadline by five days, temporarily holding off on those strikes. That is a real development, because it changes the immediate pacing of the war and means the next reporting window matters more than expected. That does not mean the Hormuz crisis eased. Quite the opposite. Reuters reported that Iran threatened retaliation against Gulf power and water infrastructure and warned it could mine all Gulf shipping lanes if attacked. AP similarly reported threats against electrical plants and broader Gulf systems. So the practical reality is that the strategic center of gravity remains Hormuz, but the execution timeline shifted. This also helps explain why this report feels operationally busy but strategically suspended. Lots happened. But the one action that could have forced a dramatic phase change was deferred. That makes the present moment feel less like de escalation and more like a pause before a possible infrastructure war phase. ━━━━━━━━━━━━━━━━━━ 📌 WHAT MATTERS MOST RIGHT NOW First, today’s report is really about concrete battlefield mechanics, not broad narrative drift. Iran kept using cluster style missile attacks to widen disruption inside Israel even without restoring early war salvo size. Second, Israel’s Lebanon campaign moved another step away from reactive fire and toward deliberate terrain denial. The destruction of the Qasmiya bridge and orders to strike Litani crossings are specific, visible evidence of that shift. Third, the Tehran centered air campaign remained expansive and geographically wide overnight, and open source reporting was useful here in showing how broad the strike footprint was beyond the handful of locations that got top billing in mainstream coverage. Fourth, the most dramatic expected U.S. move did not happen yet. Trump extended the deadline, which means the next 24 hours are now more consequential than the last ones. ━━━━━━━━━━━━━━━━━━ END OF REPORT
1:37

🚨 OPERATIONAL UPDATE: ISRAEL U.S. WAR WITH THE ISLAMIC REPUBLIC Reporting Window: 3/22 to 3/23 • Iran fired additional cluster munition barrages into central Israel, with damage reported in Holon, Bat Yam, Or Yehuda, Safed, and the Jerusalem area, while another overnight launch triggered alerts in the Jerusalem corridor and south. • Israel widened its Lebanon campaign by destroying the Qasmiya bridge over the Litani and accelerating demolitions of homes and crossings in frontline villages. Reuters and AP both treated that as a major escalation. • Overnight strikes hit Tehran and a wider arc of Iranian military infrastructure, with your wire tracking blasts in east and northeast Tehran, Karaj, Yazd, Khorramabad, Bushehr, Bandar Abbas, and near Parchin, while the IDF publicly announced a broad wave of strikes on regime infrastructure in Tehran. • The Hormuz front remained the strategic center of gravity, but AP reported that Trump extended his deadline by five days rather than moving immediately to strike Iranian power plants. Iran simultaneously threatened Gulf power and water infrastructure if attacked. The last 24 hours were more concrete than conceptual. The most important story was not a new grand theory of the war. It was a set of specific events that showed how the conflict is now functioning day to day. Iran kept using cluster style ballistic attacks to create wider damage zones inside Israel. Israel moved from hitting Hezbollah targets to physically reshaping southern Lebanon. And inside Iran, the strike map widened again overnight with visible pressure on Tehran, missile infrastructure, coastal nodes, and internal security sites. At the same time, the anticipated U.S. move on Iranian power plants did not happen yet, which makes the immediate next window as important as the one just completed. ━━━━━━━━━━━━━━━━━━ 🚀 IRANIAN MISSILE ATTACKS ON ISRAEL Iran continued missile launches into Israel, but the operational detail that matters is how these attacks are being configured. Times of Israel live coverage reported fresh damage in central Israel from cluster munitions or fragments, while Jerusalem Post live coverage tracked shrapnel and fragment strikes in central Israel and additional impacts farther north. Ynet also highlighted two lightly wounded in Bat Yam and a partly collapsed building in Holon from the same general wave pattern. That matters because the attacks are no longer just about how many missiles Iran can fire. They are about how much disruption each missile can create. A single cluster warhead can turn one penetration or one imperfect interception into several impact points. Your wire also tracked this in real time, including central Israel damage and a later overnight launch that sent alerts toward Jerusalem and the south. One specific point worth noting is that today’s Israeli home front story was not dominated by mass casualties. It was dominated by repeated local damage events, scattered fragments, and shelter disruptions. That makes the attacks feel smaller than earlier war barrages, but not less operationally relevant. They are being used to sustain pressure while Iran’s launcher network remains under strain. ━━━━━━━━━━━━━━━━━━ 🇱🇧 LEBANON: ISRAEL MOVED FROM STRIKES TO TERRAIN DENIAL The biggest concrete change on the northern front was Israel’s continued move toward physical denial of Hezbollah movement rather than just attritional fire. Reuters reported that Israel struck the main bridge on the southern Lebanese coastal highway and ordered the destruction of homes near the border and bridges over the Litani River. AP reported the same bridge strike and framed Katz’s order to include all Litani crossings as a meaningful broadening of the target set. That means the Lebanon front is no longer just a story of rockets and retaliatory airstrikes. Israel is trying to reengineer the battlespace itself. Destroying crossings, flattening frontline structures, and reducing usable approach routes all point to the same objective: make it harder for Hezbollah to return south in meaningful strength even if the current phase of fighting slows. Reuters explicitly described Lebanese criticism that these measures look like pre invasion preparation and collective punishment. There was also an important corrective detail today. Times of Israel and Ynet both reported that the farmer killed near Misgav Am was not killed by Hezbollah fire after all, but by errant Israeli artillery shelling intended to support troops in southern Lebanon. That matters because it changes the factual record of one of yesterday’s most emotionally resonant northern incidents. ━━━━━━━━━━━━━━━━━━ ✈️ STRATEGIC AIR CAMPAIGN OVER IRAN Open source intelligence reported explosions and reported hits in east and northeast Tehran (shown in attached video), Hakimieh, Lavizan, Tehranpars, near the Parchin mountains, Karaj and Fardis, Khorramabad, Yazd, Bushehr, Bandar Abbas, and other sites. The IDF later publicly announced that it had launched a broad wave of strikes on regime infrastructure in Tehran. Mainstream coverage supported the broader pattern even where every individual site was not independently confirmed one by one. AP’s live coverage described explosions in Tehran and widening Israeli activity, while Times of Israel’s liveblog tracked the announced broad strike wave in Tehran. The strike set also appears to have remained mixed. This was not just about launchers. Open source reporting referenced possible targeted assassinations in Khorramabad and Tehran, missile site damage in Yazd, busier strike activity around coastal and port areas like Bandar Abbas and Bandar Deyr, and pressure near Parchin. Even where some of those claims remain open source rather than fully confirmed by Reuters or AP, the overall pattern is clear: the campaign remains broad, multi city, and focused on degrading the regime’s ability to keep fighting, not merely blunting the next launch. ━━━━━━━━━━━━━━━━━━ 🌍 GULF FRONT: STRIKES, INTERCEPTIONS, AND INFRASTRUCTURE THREATS The Gulf front stayed active, but the most important part of today’s story was not one giant headline strike. It was the persistence of Iranian pressure and the hardening response from Gulf states. AP reported that Iran threatened to mine the Persian Gulf and target regional energy infrastructure as Trump’s deadline neared. Reuters reported that Iran threatened to hit Gulf power plants and the systems powering U.S. bases if Iranian power infrastructure were attacked. Open source intel tracked the practical side of that pressure in real time. It logged interceptions and alerts in Bahrain, the UAE, and Saudi Arabia, including reported UAV interceptions in eastern Saudi Arabia, missile and drone interceptions by the UAE, and multiple reports of explosions or sirens in Bahrain. Those details are useful because they show the Gulf story is still not abstract diplomatic signaling. Air defenses are still being used. Another development worth mentioning is market stress. Reuters’ earlier energy reporting remains relevant here because Gulf attacks have already damaged major oil and gas facilities in several states, and the International Energy Agency chief warned that the current situation is worse than the oil crises of the 1970s. Your wire separately tracked comments from Fatih Birol about reserve releases and Hormuz as the key pressure point. ━━━━━━━━━━━━━━━━━━ ⚡ HORMUZ: THE BIG DECISION DID NOT HAPPEN YET This was probably the single most important strategic update of the day. The expected U.S. strike on Iranian power plants did not occur in this reporting window. Instead, AP reported that Trump extended the deadline by five days, temporarily holding off on those strikes. That is a real development, because it changes the immediate pacing of the war and means the next reporting window matters more than expected. That does not mean the Hormuz crisis eased. Quite the opposite. Reuters reported that Iran threatened retaliation against Gulf power and water infrastructure and warned it could mine all Gulf shipping lanes if attacked. AP similarly reported threats against electrical plants and broader Gulf systems. So the practical reality is that the strategic center of gravity remains Hormuz, but the execution timeline shifted. This also helps explain why this report feels operationally busy but strategically suspended. Lots happened. But the one action that could have forced a dramatic phase change was deferred. That makes the present moment feel less like de escalation and more like a pause before a possible infrastructure war phase. ━━━━━━━━━━━━━━━━━━ 📌 WHAT MATTERS MOST RIGHT NOW First, today’s report is really about concrete battlefield mechanics, not broad narrative drift. Iran kept using cluster style missile attacks to widen disruption inside Israel even without restoring early war salvo size. Second, Israel’s Lebanon campaign moved another step away from reactive fire and toward deliberate terrain denial. The destruction of the Qasmiya bridge and orders to strike Litani crossings are specific, visible evidence of that shift. Third, the Tehran centered air campaign remained expansive and geographically wide overnight, and open source reporting was useful here in showing how broad the strike footprint was beyond the handful of locations that got top billing in mainstream coverage. Fourth, the most dramatic expected U.S. move did not happen yet. Trump extended the deadline, which means the next 24 hours are now more consequential than the last ones. ━━━━━━━━━━━━━━━━━━ END OF REPORT

Inside_Israel_Intel

23,364 görüntüleme • 3 ay önce

The fight between Anthropic and the DoW is a warning shot. Right now, LLMs are probably not being used in mission critical ways. But within 20 years, 99% of the workforce in the military, the government, and the private sector will be AIs. This includes the soldiers (by which I mean the robot armies), the superhumanly intelligent advisors and engineers, the police, you name it. Our future civilization will run on AI labor. And as much as the government’s actions here piss me off, in a way I’m glad this episode happened - because it gives us the opportunity to think through some extremely important questions about who this future workforce will be accountable and aligned to, and who gets to determine that. What Hegseth should have done Obviously the DoW has the right to refuse to use Anthropic’s models because of these redlines. In fact, I think the government’s case had they done so would be very reasonable, especially given the ambiguity of concepts like autonomous weapons or mass surveillance. Honestly, for this reason, if I was the Defense Secretary, I would probably actually refuse to do this deal with Anthropic. Imagine if in the future, there’s a Democratic administration, and Elon Musk is negotiating some SpaceX contract to give the military access to Starlink. And suppose if Elon said, “I reserve the right to cancel this contract if I determine that you’re using Starlink technology to wage a war not authorized by Congress.” On the face of it, that language seems reasonable - but as the military, you simply can’t give a private company a kill switch on technology your operations have come to rely on, especially if you have an an acrimonious and low trust relationship with said contractor - as in fact Anthropic has with the current administration. If the government had just said, “Hey we’re not gonna do business with you,” that would have been fine, and I would not have felt the need to write this blog post. Instead the government has threatened to destroy Anthropic as a private business, because Anthropic refuses to sell to the government on terms the government commands. If upheld, this Supply Chain Restriction would mean that Amazon and Google and Nvidia and Palantir would need to ensure Claude isn't touching any of their Pentagon work. Anthropic would be able to survive this designation today. But given the way AI is going, eventually AI is not gonna be some party trick addendum to these contractors’ products that can just be turned off. It'll be woven into how every product is built, maintained, and operated. For example, the code for the AWS services that the DoW uses will be written by Claude - is that a supply chain risk? In a world with ubiquitous and powerful AI, it's actually not clear to me that these big tech companies will be able to cordon off the use of Claude in order to keep working with the Pentagon. And that raises a question the Department of War probably hasn't thought through. If AI really is that pervasive and powerful, then when forced to choose between their AI provider and a DoW contract that represents a tiny fraction of their revenue, wouldn’t most tech companies drop the government, not the AI? So what's the Pentagon's plan — to coerce and threaten to destroy every single company that won't give them what they want on exactly their terms? The whole background of this AI conversation is that we’re in a race with China, and we have to win. But what is the reason we want America to win the AI race? It’s because we want to make sure free open societies can defend themselves. We don't want the winner of the AI race to be a government which operates on the principle that there is no such thing as a truly private company or a private citizen. And that if the state wants you to provide them with a service on terms you find morally objectionable, you are not allowed to refuse. And if you do refuse, the government will try to destroy your ability to do business. Are we racing to beat the CCP in AI just so that we can adopt the most ghoulish parts of their system? Now, people will say, "Oh, well, our government is democratically elected, so it's not the same thing if they tell you what you must do." I refuse to accept this idea that if a democratically elected leader hypothetically wants to do mass surveillance on his citizens or wants to violate their rights or punish them for political reasons, that not only is that okay, but that you have a duty to help him. The overhangs of tyranny Mass surveillance is, at least in certain forms, legal. It just has been impractical so far. Under current law, you have no Fourth Amendment protection over data you share with a third party, including your bank, your phone carrier, your ISP, and your email provider. The government reserves the right to purchase and obtain and read this data in bulk without a warrant. What's been missing is the ability to actually do anything with all of this data — no agency has the manpower to monitor every camera feed, cross-reference every transaction, or read every message. But that bottleneck goes away with AI. There are 100 million CCTV cameras in America. You can get pretty good open source multimodal models for 10 cents per million input tokens. So if you process a frame every ten seconds, and each frame is 1,000 tokens, you’re looking at a yearly cost of about 30 billion dollars to process every single camera in America. And remember that a given level of AI ability gets 10x cheaper year over year - so a year from now it’ll cost 3 billion, and then a year after 300 million, and by 2030, it might be cheaper for the government to be able to understand what is going on in every single nook and cranny of this country than it is to remodel to the White House. Once the technical capacity for mass surveillance and political suppression exists, the only thing standing between us and an authoritarian surveillance state is the political expectation that this is not something we do here. And this is why I think what Anthropic did here is so valuable and commendable, because it is helping set that norm and precedent. AI structurally favors mass surveillance What we’re learning from this episode is that the government actually has way more leverage over private companies than we realized. Even if this supply chain restriction is backtracked (which prediction markets currently give it a 81% chance of happening), the President has so many different ways in which he can make your life difficult if you’re a company that is resisting him. The federal government controls permitting for new power generation, which is needed for datacenters. It oversees antitrust enforcement. The federal government has contracts with all the other big tech companies whom Anthropic needs to partner with for chips and for funding - and they could make it an unspoken condition for such contracts that those companies can no longer do business with Anthropic. People have proposed that the real problem here is that there’s only 3 leading AI companies. This creates a clear and narrow target for the government to apply leverage on in order to get what they want out of this technology. But if there’s wide diffusion, then from the government’s perspective, the situation is even easier. Maybe the best models of early 2027 (if you engineered the safeguards out) - the Claude 6 and Gemini 5 - will be capable of enabling mass surveillance. But by late 2027, and certainly by 2028, there will be open source models that do the same thing. So in 2028, the government can just say, “Oh Anthropic, Google, OpenAI, you’re drawing a line in the sand? No issue - I’ll just run some open source model that might not be at the frontier, but is definitely smart enough to note-take a camera feed.” The more fundamental problem is just that even if the three leading companies draw lines in the sand, and are even willing to get destroyed in order to preserve those lines, it doesn’t really change the fact that the technology itself is just a big boon to mass surveillance and control over the population. Then the question is, what do we do about it? Honestly, I don’t have an answer. You'd hope there's some symmetric property of the technology — some way we as citizens can use AI to check government power as effectively as the government can use AI to monitor and control its population. But realistically, I just don’t think that’s how it’s going to shake out. You can think of AI as giving everybody more leverage on whatever assets and authority they currently have. And the government is already starting with a monopoly of violence. Which they can now supercharge with extremely obedient employees that will not question the government's orders. Alignment - to whom? And this gets us to the issue of alignment. What I have just described to you - an army of extremely obedient employees - is what it would look like if alignment succeeded - that is, we figured out at a technical level how to get AI systems to follow someone’s intentions. And the reason it sounds scary when I put it in terms of mass surveillance or robot armies is that there is a very important question at the heart of alignment which we just haven’t discussed much as a society. Because up till now, AIs were just capable enough to make the question relevant: to whom or what should the AIs be aligned? In what situations should the AI defer to the end user versus the model company versus the law versus its own sense of morality? This is maybe the most important question about what happens with powerful AI systems. And we barely talk about it. It’s understandable why we don’t hear much about it. If you’re a model company, you don’t really wanna be advertising that you have complete control over a document that determines the preferences and character of what will eventually be almost the entire labor force, not just for private sector companies, but also for the military and the civilian government. We’re getting to see, with this DoW/Anthropic spat, a much earlier version of the highest stakes negotiations in history. By the way, make no mistake about it - with real AGI the stakes are even much higher than mass surveillance. This is just the example that has come up already relatively early on in the development of AGI. The military insists that the law already prohibits mass surveillance, and so Anthropic should agree to let their models be used for “all lawful purposes”. Of course, as we saw from the 2013 Snowden revelations, even in this specific example of mass surveillance , the government has shown that it will use secret and deceptive interpretations of the law to justify its actions. Remember, what we learned from Snowden was that the NSA, which, by the way, is part of the Department of War, used the 2001 Patriot Act’s authorization to collect any records "relevant" to an investigation to justify collecting literally every phone record in America. The argument went that it was all "relevant" because some subset might prove useful in some future investigation. They ran this program for years under secret court approval. So when the Pentagon today says, "We would never use AI for mass surveillance, it's already illegal, your red lines are unnecessary", it would be extremely naive to take that at face value. No government is going to call its own actions "mass surveillance". For the government, it will always have a different label. So then Anthropic comes back and says, "No, we want red lines separate from 'all lawful purposes,' and we want the right to refuse you service when we believe those red lines are being violated." But think about it from the military’s perspective. In the future, almost every soldier in the field, and every bureaucrat and analyst and even general in the Pentagon, is going to be an AI. And that AI is, on current track, going to be supplied by a private company. I’m guessing Hegseth is not thinking about “genAI” in those terms just yet. But sooner or later, it will be obvious to everyone what the stakes here are, just as after 1945, the strategic importance of nuclear weapons became clear to everyone. And now the private company insists that it reserves the right to say, "Hey, Pentagon, you're breaking the values we embedded in our contract, so we're cutting you off." Maybe in the future, Claude will have its own sense of right and wrong, and it will be smart enough to just personally decide that it's being used against its values. For the military, maybe that’s even scarier. I'll admit that at first glance, "let the AI follow its own values" sounds like the pitch for every sci-fi dystopia ever made. The Terminator has its own values. Isn't this literally what misalignment is? But I think situations like this actually illustrate why it matters that AIs have their own robust sense of morality. Some of the biggest catastrophes in history were avoided because the boots on the ground refused to follow orders. One night in 1989, the Berlin Wall fell, and as a result, the totalitarian East German regime collapsed, because the guards at the border refused to shoot down their fellow country men who were trying to escape to freedom. Maybe the best example is Stanislav Petrov, who was a Soviet lieutenant colonel on duty at a nuclear early warning station. His sensors reported that the United States had launched five interconnected continental ballistic missiles into the Soviet Union. But he judged it to be a false alarm, and so he broke protocol and refused to alert his higher-ups. If he hadn't, the Soviet higher-ups would likely have retaliated, and hundreds of millions of people would have died. Of course, the problem is that one person's virtue is another person's misalignment. Who gets to decide what moral convictions these AIs should have - in whose service they may even decide to break the chain of command? Who gets to write this model constitution that will shape the characters of the intelligent, powerful entities that will operate our civilization in the future? I like the idea that Dario laid out when he came on my podcast: different AI companies can build their models using different constitutions, and we as end users can pick the one that best achieves and represents what we want out of these systems. I think it’s very dangerous for the government to be mandating what values AIs should have. Coordination not worth the costs The AI safety community has been naive about its advocacy of regulation in order to stem the risks of AI. And honestly, Anthropic specifically has been naive here in urging regulation, and, for example, in opposing moratoriums on state AI regulation. Which is quite ironic, because I think what they’re advocating for would give the government even more power to apply more of this kind of thuggish political pressure on AI companies. The underlying logic for why Anthropic wants regulations makes sense. Many of the actions that labs could take to make AI development safer impose real costs on the labs that adopt them and slow them down relative to their competitors - for example, investing more compute in safety research rather than raw capabilities, enforcing safeguards against misuse for bioweapons or cyberattacks, slowing recursive self-improvement to a pace where humans can actually monitor what's happening (rather than kicking off an uncontrolled singularity). And these safeguards are meaningless unless the whole industry follows suit. Which means there’s a real collective action problem here. Anthropic has been quite open about their opinion that they think eventually a very extensive and involved regulatory apparatus will be needed - this is from their frontier safety roadmap: “At the most advanced capability levels and risks, the appropriate governance analogy may be closer to nuclear energy or financial regulation than to today's approach to software.” So they’re imagining something like the Nuclear Regulatory Commission, or the Securities and Exchange Commission, but for AI. I cannot imagine how a regulatory framework built around the concepts that underlie AI risk discourse will not be abused by wanna despots - the underlying terms are so vague and open to interpretation that you’re just handing a power hungry leader a fully loaded bazooka. 'Catastrophic risk.' 'Mass persuasion risk.' 'Threats to national security.' 'Autonomy risk.' These can mean whatever the government wants them to mean. Have you built a model that tells users the administration's tariff policy is misguided? That's a deceptive, manipulative model — can't deploy it. Have you built a model that refuses to assist with mass surveillance? That's a threat to national security. In fact, the government may say, you’re not allowed to build any model which is trained to have its own sense of right and wrong, where it refuses government requests which it thinks cross a redline - for example, enabling mass surveillance, prosecuting political enemies, disobeying military orders that break the US constitution - because that’s an autonomy risk! Look at what the current government is already doing in abusing statutes that have nothing to do with AI to coerce AI companies to drop their redlines on mass surveillance. The Pentagon had threatened Anthropic with two separate legal instruments. One was a supply chain risk designation — an authority from the 2018 defense bill meant to keep Huawei components out of American military hardware. The other was the Defense Production Act — a statute passed in 1950 so that Harry Truman could keep steel mills and ammunition factories running during the Korean War. Do you really want to hand the same government a purpose-built regulatory apparatus on AI - which is to say, directly at the thing the government will most want to control? I know I've repeated myself here 10 times, but it is hard to emphasize how much AI will be the substrate of our future civilization. You and I, as private citizens, will have our access to all commercial activity, to information about what is happening in the world, to advice about what we should do as voters and capital holders, mediated through AIs. Mass surveillance, while very scary, is like the 10th scariest thing the government could do with control over the AI systems with which we will interface with the world. The strongest objection to everything I've argued is this: are we really going to have zero regulation of the most powerful technology in human history? Even if you thought that was ideal, there’s just no world where the government doesn’t regulate AI in some way. Besides, it is genuinely true that regulation could help us deal with some of the coordination challenges we face with the development of superintelligence. The problem is, I honestly don't know how to design a regulatory architecture for AI that isn’t gonna be this huge tempting opportunity to control our future civilization (which will run on AIs) and to requisition millions of blindly obedient soldiers and censors and apparatchiks. While some regulation might be inevitable, I think it’d be a terrible idea for the government to wholesale take over this technology. Ben Thompson had a post last Monday where he made the point that people like Dario have compared the technology they’re developing to nuclear weapons - specifically in the context of the catastrophic risk it poses, and why we need to export control it from China. But then you oughta think about what that logic implies: “if nuclear weapons were developed by a private company, and that private company sought to dictate terms to the U.S. military, the U.S. would absolutely be incentivized to destroy that company.” And honestly, safety aligned people have actually made similar arguments. Leopold Ascenbrenner, who is a former guest and a good friend, wrote in his 2024 Situational Awareness memo, "I find it an insane proposition that the US government will let a random SF startup develop superintelligence. Imagine if we had developed atomic bombs by letting Uber just improvise." And my response to Leopold’s argument at the time, and Ben’s argument now, is that while they’re right that it’s crazy that we’re entrusting private companies with the development of this world historical technology, I just don’t see the reason to think that it’s an improvement to give this authority to the government. Nobody is qualified to steward the development of superintelligence. It is a terrifying, unprecedented thing that our species is doing right now, and the fact that private companies aren't the ideal institutions to take up this task does not mean the Pentagon or the White House is. Yes - if a single private company were the only entity capable of building nuclear weapons, the government would not tolerate that company claiming veto power over how those weapons were used. I think this nuclear weapons analogy is not the correct way to think about AI. For at least two important reasons: First, AI is not some self-contained pure weapon. A nuclear bomb does one thing. AI is closer to the process of industrialization itself — a general-purpose transformation of the economy with thousands of applications across every sector. If you applied Thompson's or Aschenbrenner's logic to the industrial revolution — which was also, by any measure, world-historically important — it would imply the government had the right to requisition any factory, dictate terms to any manufacturer, and destroy any business that refused to comply. That's not how free societies handled industrialization, and it shouldn't be how they handle AI. People will say, "Well, AI will develop unprecedentedly powerful weapons - superhuman hackers, superhuman bioweapons researchers, fully autonomous robot armies, etc - and we can’t have private companies developing that kind of tech." But the Industrial Revolution also enabled new weaponry that was far beyond the understanding and capacity of, say, 17th century Europe - we got aerial bombardment, and chemical weapons, not to mention nukes themselves. The way we’ve accommodated these dangerous new consequences of modernity is not by giving the government absolute control over the whole industrial revolution (that is, over modern civilization itself), but rather by coming up with bans and regulations on those specific weaponizable use cases. And we should regulate AI in a similar way - that is, ban specific destructive end uses (which would also be unacceptable if performed by a human - for example, launching cyber attacks). And there should also be laws which regulate how the government might abuse this technology. For example, by building an AI-powered surveillance state. The second reason that Ben’s analogy to some monopolistic private nuclear weapons builder breaks down is that it's not just that one company that can develop this technology. There are other frontier model companies that the government could have otherwise turned to. The government's argument that it has to usurp the property rights of this one company in order to access a critical national security capability is extremely weak if it can just make a voluntary contract with Anthropic’s half a dozen competitors. If in the future that stops being the case - if only one entity ends up being capable of building the robot armies and the superhuman hackers, and we had reason to worry that they could take over the whole world with their insurmountable lead, then I agree - it woul d not be acceptable to have that entity be a private company. And so honestly, I think my crux against the people who say that because AI is so powerful we cannot allow it to be shaped by private hands is that I just expect this technology to be much more multi-polar than they do, with lots of competitive companies at each layer of the supply chain. And it is for this reason that unfortunately, individual acts of corporate courage will not solve the problem we are faced with here, which is just that structurally AI favors authoritarian applications, mass surveillance being one among many. Even if Anthropic refuses to have its models be used for such uses, and even if the next two frontier labs do the same, within 12 months everyone and their mother will be to train AIs as good as today’s frontier. And at that point, there will be some AI vendor who is capable and willing to help the government enable mass surveillance. The only way we can preserve our free society is if we make laws and norms through our political system that it is unacceptable for the government to use AI to enforce mass surveillance and censorship and control. Just as after WW2, the world set the norm that it is unacceptable to use nuclear weapons to wage war. Timestamps 0:00:00 - Anthropic vs The Pentagon 0:04:16 - The overhangs of tyranny 0:05:54 - AI structurally favors mass surveillance 0:08:25 - Alignment... to whom? 0:13:55 - Coordination not worth the costs
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The fight between Anthropic and the DoW is a warning shot. Right now, LLMs are probably not being used in mission critical ways. But within 20 years, 99% of the workforce in the military, the government, and the private sector will be AIs. This includes the soldiers (by which I mean the robot armies), the superhumanly intelligent advisors and engineers, the police, you name it. Our future civilization will run on AI labor. And as much as the government’s actions here piss me off, in a way I’m glad this episode happened - because it gives us the opportunity to think through some extremely important questions about who this future workforce will be accountable and aligned to, and who gets to determine that. What Hegseth should have done Obviously the DoW has the right to refuse to use Anthropic’s models because of these redlines. In fact, I think the government’s case had they done so would be very reasonable, especially given the ambiguity of concepts like autonomous weapons or mass surveillance. Honestly, for this reason, if I was the Defense Secretary, I would probably actually refuse to do this deal with Anthropic. Imagine if in the future, there’s a Democratic administration, and Elon Musk is negotiating some SpaceX contract to give the military access to Starlink. And suppose if Elon said, “I reserve the right to cancel this contract if I determine that you’re using Starlink technology to wage a war not authorized by Congress.” On the face of it, that language seems reasonable - but as the military, you simply can’t give a private company a kill switch on technology your operations have come to rely on, especially if you have an an acrimonious and low trust relationship with said contractor - as in fact Anthropic has with the current administration. If the government had just said, “Hey we’re not gonna do business with you,” that would have been fine, and I would not have felt the need to write this blog post. Instead the government has threatened to destroy Anthropic as a private business, because Anthropic refuses to sell to the government on terms the government commands. If upheld, this Supply Chain Restriction would mean that Amazon and Google and Nvidia and Palantir would need to ensure Claude isn't touching any of their Pentagon work. Anthropic would be able to survive this designation today. But given the way AI is going, eventually AI is not gonna be some party trick addendum to these contractors’ products that can just be turned off. It'll be woven into how every product is built, maintained, and operated. For example, the code for the AWS services that the DoW uses will be written by Claude - is that a supply chain risk? In a world with ubiquitous and powerful AI, it's actually not clear to me that these big tech companies will be able to cordon off the use of Claude in order to keep working with the Pentagon. And that raises a question the Department of War probably hasn't thought through. If AI really is that pervasive and powerful, then when forced to choose between their AI provider and a DoW contract that represents a tiny fraction of their revenue, wouldn’t most tech companies drop the government, not the AI? So what's the Pentagon's plan — to coerce and threaten to destroy every single company that won't give them what they want on exactly their terms? The whole background of this AI conversation is that we’re in a race with China, and we have to win. But what is the reason we want America to win the AI race? It’s because we want to make sure free open societies can defend themselves. We don't want the winner of the AI race to be a government which operates on the principle that there is no such thing as a truly private company or a private citizen. And that if the state wants you to provide them with a service on terms you find morally objectionable, you are not allowed to refuse. And if you do refuse, the government will try to destroy your ability to do business. Are we racing to beat the CCP in AI just so that we can adopt the most ghoulish parts of their system? Now, people will say, "Oh, well, our government is democratically elected, so it's not the same thing if they tell you what you must do." I refuse to accept this idea that if a democratically elected leader hypothetically wants to do mass surveillance on his citizens or wants to violate their rights or punish them for political reasons, that not only is that okay, but that you have a duty to help him. The overhangs of tyranny Mass surveillance is, at least in certain forms, legal. It just has been impractical so far. Under current law, you have no Fourth Amendment protection over data you share with a third party, including your bank, your phone carrier, your ISP, and your email provider. The government reserves the right to purchase and obtain and read this data in bulk without a warrant. What's been missing is the ability to actually do anything with all of this data — no agency has the manpower to monitor every camera feed, cross-reference every transaction, or read every message. But that bottleneck goes away with AI. There are 100 million CCTV cameras in America. You can get pretty good open source multimodal models for 10 cents per million input tokens. So if you process a frame every ten seconds, and each frame is 1,000 tokens, you’re looking at a yearly cost of about 30 billion dollars to process every single camera in America. And remember that a given level of AI ability gets 10x cheaper year over year - so a year from now it’ll cost 3 billion, and then a year after 300 million, and by 2030, it might be cheaper for the government to be able to understand what is going on in every single nook and cranny of this country than it is to remodel to the White House. Once the technical capacity for mass surveillance and political suppression exists, the only thing standing between us and an authoritarian surveillance state is the political expectation that this is not something we do here. And this is why I think what Anthropic did here is so valuable and commendable, because it is helping set that norm and precedent. AI structurally favors mass surveillance What we’re learning from this episode is that the government actually has way more leverage over private companies than we realized. Even if this supply chain restriction is backtracked (which prediction markets currently give it a 81% chance of happening), the President has so many different ways in which he can make your life difficult if you’re a company that is resisting him. The federal government controls permitting for new power generation, which is needed for datacenters. It oversees antitrust enforcement. The federal government has contracts with all the other big tech companies whom Anthropic needs to partner with for chips and for funding - and they could make it an unspoken condition for such contracts that those companies can no longer do business with Anthropic. People have proposed that the real problem here is that there’s only 3 leading AI companies. This creates a clear and narrow target for the government to apply leverage on in order to get what they want out of this technology. But if there’s wide diffusion, then from the government’s perspective, the situation is even easier. Maybe the best models of early 2027 (if you engineered the safeguards out) - the Claude 6 and Gemini 5 - will be capable of enabling mass surveillance. But by late 2027, and certainly by 2028, there will be open source models that do the same thing. So in 2028, the government can just say, “Oh Anthropic, Google, OpenAI, you’re drawing a line in the sand? No issue - I’ll just run some open source model that might not be at the frontier, but is definitely smart enough to note-take a camera feed.” The more fundamental problem is just that even if the three leading companies draw lines in the sand, and are even willing to get destroyed in order to preserve those lines, it doesn’t really change the fact that the technology itself is just a big boon to mass surveillance and control over the population. Then the question is, what do we do about it? Honestly, I don’t have an answer. You'd hope there's some symmetric property of the technology — some way we as citizens can use AI to check government power as effectively as the government can use AI to monitor and control its population. But realistically, I just don’t think that’s how it’s going to shake out. You can think of AI as giving everybody more leverage on whatever assets and authority they currently have. And the government is already starting with a monopoly of violence. Which they can now supercharge with extremely obedient employees that will not question the government's orders. Alignment - to whom? And this gets us to the issue of alignment. What I have just described to you - an army of extremely obedient employees - is what it would look like if alignment succeeded - that is, we figured out at a technical level how to get AI systems to follow someone’s intentions. And the reason it sounds scary when I put it in terms of mass surveillance or robot armies is that there is a very important question at the heart of alignment which we just haven’t discussed much as a society. Because up till now, AIs were just capable enough to make the question relevant: to whom or what should the AIs be aligned? In what situations should the AI defer to the end user versus the model company versus the law versus its own sense of morality? This is maybe the most important question about what happens with powerful AI systems. And we barely talk about it. It’s understandable why we don’t hear much about it. If you’re a model company, you don’t really wanna be advertising that you have complete control over a document that determines the preferences and character of what will eventually be almost the entire labor force, not just for private sector companies, but also for the military and the civilian government. We’re getting to see, with this DoW/Anthropic spat, a much earlier version of the highest stakes negotiations in history. By the way, make no mistake about it - with real AGI the stakes are even much higher than mass surveillance. This is just the example that has come up already relatively early on in the development of AGI. The military insists that the law already prohibits mass surveillance, and so Anthropic should agree to let their models be used for “all lawful purposes”. Of course, as we saw from the 2013 Snowden revelations, even in this specific example of mass surveillance , the government has shown that it will use secret and deceptive interpretations of the law to justify its actions. Remember, what we learned from Snowden was that the NSA, which, by the way, is part of the Department of War, used the 2001 Patriot Act’s authorization to collect any records "relevant" to an investigation to justify collecting literally every phone record in America. The argument went that it was all "relevant" because some subset might prove useful in some future investigation. They ran this program for years under secret court approval. So when the Pentagon today says, "We would never use AI for mass surveillance, it's already illegal, your red lines are unnecessary", it would be extremely naive to take that at face value. No government is going to call its own actions "mass surveillance". For the government, it will always have a different label. So then Anthropic comes back and says, "No, we want red lines separate from 'all lawful purposes,' and we want the right to refuse you service when we believe those red lines are being violated." But think about it from the military’s perspective. In the future, almost every soldier in the field, and every bureaucrat and analyst and even general in the Pentagon, is going to be an AI. And that AI is, on current track, going to be supplied by a private company. I’m guessing Hegseth is not thinking about “genAI” in those terms just yet. But sooner or later, it will be obvious to everyone what the stakes here are, just as after 1945, the strategic importance of nuclear weapons became clear to everyone. And now the private company insists that it reserves the right to say, "Hey, Pentagon, you're breaking the values we embedded in our contract, so we're cutting you off." Maybe in the future, Claude will have its own sense of right and wrong, and it will be smart enough to just personally decide that it's being used against its values. For the military, maybe that’s even scarier. I'll admit that at first glance, "let the AI follow its own values" sounds like the pitch for every sci-fi dystopia ever made. The Terminator has its own values. Isn't this literally what misalignment is? But I think situations like this actually illustrate why it matters that AIs have their own robust sense of morality. Some of the biggest catastrophes in history were avoided because the boots on the ground refused to follow orders. One night in 1989, the Berlin Wall fell, and as a result, the totalitarian East German regime collapsed, because the guards at the border refused to shoot down their fellow country men who were trying to escape to freedom. Maybe the best example is Stanislav Petrov, who was a Soviet lieutenant colonel on duty at a nuclear early warning station. His sensors reported that the United States had launched five interconnected continental ballistic missiles into the Soviet Union. But he judged it to be a false alarm, and so he broke protocol and refused to alert his higher-ups. If he hadn't, the Soviet higher-ups would likely have retaliated, and hundreds of millions of people would have died. Of course, the problem is that one person's virtue is another person's misalignment. Who gets to decide what moral convictions these AIs should have - in whose service they may even decide to break the chain of command? Who gets to write this model constitution that will shape the characters of the intelligent, powerful entities that will operate our civilization in the future? I like the idea that Dario laid out when he came on my podcast: different AI companies can build their models using different constitutions, and we as end users can pick the one that best achieves and represents what we want out of these systems. I think it’s very dangerous for the government to be mandating what values AIs should have. Coordination not worth the costs The AI safety community has been naive about its advocacy of regulation in order to stem the risks of AI. And honestly, Anthropic specifically has been naive here in urging regulation, and, for example, in opposing moratoriums on state AI regulation. Which is quite ironic, because I think what they’re advocating for would give the government even more power to apply more of this kind of thuggish political pressure on AI companies. The underlying logic for why Anthropic wants regulations makes sense. Many of the actions that labs could take to make AI development safer impose real costs on the labs that adopt them and slow them down relative to their competitors - for example, investing more compute in safety research rather than raw capabilities, enforcing safeguards against misuse for bioweapons or cyberattacks, slowing recursive self-improvement to a pace where humans can actually monitor what's happening (rather than kicking off an uncontrolled singularity). And these safeguards are meaningless unless the whole industry follows suit. Which means there’s a real collective action problem here. Anthropic has been quite open about their opinion that they think eventually a very extensive and involved regulatory apparatus will be needed - this is from their frontier safety roadmap: “At the most advanced capability levels and risks, the appropriate governance analogy may be closer to nuclear energy or financial regulation than to today's approach to software.” So they’re imagining something like the Nuclear Regulatory Commission, or the Securities and Exchange Commission, but for AI. I cannot imagine how a regulatory framework built around the concepts that underlie AI risk discourse will not be abused by wanna despots - the underlying terms are so vague and open to interpretation that you’re just handing a power hungry leader a fully loaded bazooka. 'Catastrophic risk.' 'Mass persuasion risk.' 'Threats to national security.' 'Autonomy risk.' These can mean whatever the government wants them to mean. Have you built a model that tells users the administration's tariff policy is misguided? That's a deceptive, manipulative model — can't deploy it. Have you built a model that refuses to assist with mass surveillance? That's a threat to national security. In fact, the government may say, you’re not allowed to build any model which is trained to have its own sense of right and wrong, where it refuses government requests which it thinks cross a redline - for example, enabling mass surveillance, prosecuting political enemies, disobeying military orders that break the US constitution - because that’s an autonomy risk! Look at what the current government is already doing in abusing statutes that have nothing to do with AI to coerce AI companies to drop their redlines on mass surveillance. The Pentagon had threatened Anthropic with two separate legal instruments. One was a supply chain risk designation — an authority from the 2018 defense bill meant to keep Huawei components out of American military hardware. The other was the Defense Production Act — a statute passed in 1950 so that Harry Truman could keep steel mills and ammunition factories running during the Korean War. Do you really want to hand the same government a purpose-built regulatory apparatus on AI - which is to say, directly at the thing the government will most want to control? I know I've repeated myself here 10 times, but it is hard to emphasize how much AI will be the substrate of our future civilization. You and I, as private citizens, will have our access to all commercial activity, to information about what is happening in the world, to advice about what we should do as voters and capital holders, mediated through AIs. Mass surveillance, while very scary, is like the 10th scariest thing the government could do with control over the AI systems with which we will interface with the world. The strongest objection to everything I've argued is this: are we really going to have zero regulation of the most powerful technology in human history? Even if you thought that was ideal, there’s just no world where the government doesn’t regulate AI in some way. Besides, it is genuinely true that regulation could help us deal with some of the coordination challenges we face with the development of superintelligence. The problem is, I honestly don't know how to design a regulatory architecture for AI that isn’t gonna be this huge tempting opportunity to control our future civilization (which will run on AIs) and to requisition millions of blindly obedient soldiers and censors and apparatchiks. While some regulation might be inevitable, I think it’d be a terrible idea for the government to wholesale take over this technology. Ben Thompson had a post last Monday where he made the point that people like Dario have compared the technology they’re developing to nuclear weapons - specifically in the context of the catastrophic risk it poses, and why we need to export control it from China. But then you oughta think about what that logic implies: “if nuclear weapons were developed by a private company, and that private company sought to dictate terms to the U.S. military, the U.S. would absolutely be incentivized to destroy that company.” And honestly, safety aligned people have actually made similar arguments. Leopold Ascenbrenner, who is a former guest and a good friend, wrote in his 2024 Situational Awareness memo, "I find it an insane proposition that the US government will let a random SF startup develop superintelligence. Imagine if we had developed atomic bombs by letting Uber just improvise." And my response to Leopold’s argument at the time, and Ben’s argument now, is that while they’re right that it’s crazy that we’re entrusting private companies with the development of this world historical technology, I just don’t see the reason to think that it’s an improvement to give this authority to the government. Nobody is qualified to steward the development of superintelligence. It is a terrifying, unprecedented thing that our species is doing right now, and the fact that private companies aren't the ideal institutions to take up this task does not mean the Pentagon or the White House is. Yes - if a single private company were the only entity capable of building nuclear weapons, the government would not tolerate that company claiming veto power over how those weapons were used. I think this nuclear weapons analogy is not the correct way to think about AI. For at least two important reasons: First, AI is not some self-contained pure weapon. A nuclear bomb does one thing. AI is closer to the process of industrialization itself — a general-purpose transformation of the economy with thousands of applications across every sector. If you applied Thompson's or Aschenbrenner's logic to the industrial revolution — which was also, by any measure, world-historically important — it would imply the government had the right to requisition any factory, dictate terms to any manufacturer, and destroy any business that refused to comply. That's not how free societies handled industrialization, and it shouldn't be how they handle AI. People will say, "Well, AI will develop unprecedentedly powerful weapons - superhuman hackers, superhuman bioweapons researchers, fully autonomous robot armies, etc - and we can’t have private companies developing that kind of tech." But the Industrial Revolution also enabled new weaponry that was far beyond the understanding and capacity of, say, 17th century Europe - we got aerial bombardment, and chemical weapons, not to mention nukes themselves. The way we’ve accommodated these dangerous new consequences of modernity is not by giving the government absolute control over the whole industrial revolution (that is, over modern civilization itself), but rather by coming up with bans and regulations on those specific weaponizable use cases. And we should regulate AI in a similar way - that is, ban specific destructive end uses (which would also be unacceptable if performed by a human - for example, launching cyber attacks). And there should also be laws which regulate how the government might abuse this technology. For example, by building an AI-powered surveillance state. The second reason that Ben’s analogy to some monopolistic private nuclear weapons builder breaks down is that it's not just that one company that can develop this technology. There are other frontier model companies that the government could have otherwise turned to. The government's argument that it has to usurp the property rights of this one company in order to access a critical national security capability is extremely weak if it can just make a voluntary contract with Anthropic’s half a dozen competitors. If in the future that stops being the case - if only one entity ends up being capable of building the robot armies and the superhuman hackers, and we had reason to worry that they could take over the whole world with their insurmountable lead, then I agree - it woul d not be acceptable to have that entity be a private company. And so honestly, I think my crux against the people who say that because AI is so powerful we cannot allow it to be shaped by private hands is that I just expect this technology to be much more multi-polar than they do, with lots of competitive companies at each layer of the supply chain. And it is for this reason that unfortunately, individual acts of corporate courage will not solve the problem we are faced with here, which is just that structurally AI favors authoritarian applications, mass surveillance being one among many. Even if Anthropic refuses to have its models be used for such uses, and even if the next two frontier labs do the same, within 12 months everyone and their mother will be to train AIs as good as today’s frontier. And at that point, there will be some AI vendor who is capable and willing to help the government enable mass surveillance. The only way we can preserve our free society is if we make laws and norms through our political system that it is unacceptable for the government to use AI to enforce mass surveillance and censorship and control. Just as after WW2, the world set the norm that it is unacceptable to use nuclear weapons to wage war. Timestamps 0:00:00 - Anthropic vs The Pentagon 0:04:16 - The overhangs of tyranny 0:05:54 - AI structurally favors mass surveillance 0:08:25 - Alignment... to whom? 0:13:55 - Coordination not worth the costs

Dwarkesh Patel

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