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Violet From Behind (AE) Three different alts (Bigger, Goth) on the P support site! 🟠 VA: Misuzugon 🦕 SFX: Muro Lynxian Rigged by: ZerØ ゼロで割 Model help+ Outfit by: MIAU

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ChibuProduction3D EN/LATAM (Comms Open)

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Small Language Models (SML) are the future of AI. "Small" (SML) instead of "Large" (LLM). These small models are highly specialized models with superhuman abilities on specific tasks. Here are two techniques to build these models: • Spectrum • Model Merging I give you a short introduction in the attached video, but here is a quick summary: Spectrum helps us identify the most relevant layers to solve one specific task. We can ignore everything else and focus on fine-tuning these layers. Using Spectrum, we can fine-tune models in a heartbeat. Model Merging combines multiple models into a unique, much better model than any of the individual input models. You can also combine models specialized in different tasks and get a model with multiple abilities. This is the state of the art of productizing models. It's what Arcee.ai's platform does behind the scenes. Arcee collaborated with me on this post and is sponsoring it. There are three main steps to produce a model for your particular use case: 1. You create a dataset by uploading your data. 2. You train a model. At this step, Arcee uses Spectrum and Model Merging to produce a highly specialized model for your task. 3. You can deploy that model to any environment you want. Three important notes: • Training process is 2x faster and 2x cheaper than regular fine-tuning. • Resultant models are smaller and have higher accuracy. • They create these specialized models from open-source models. Check this site so you can fully appreciate how this works: If you want to fine-tune an open-source model, consider Arcee's platform. This is the state of the art.
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Small Language Models (SML) are the future of AI. "Small" (SML) instead of "Large" (LLM). These small models are highly specialized models with superhuman abilities on specific tasks. Here are two techniques to build these models: • Spectrum • Model Merging I give you a short introduction in the attached video, but here is a quick summary: Spectrum helps us identify the most relevant layers to solve one specific task. We can ignore everything else and focus on fine-tuning these layers. Using Spectrum, we can fine-tune models in a heartbeat. Model Merging combines multiple models into a unique, much better model than any of the individual input models. You can also combine models specialized in different tasks and get a model with multiple abilities. This is the state of the art of productizing models. It's what Arcee.ai's platform does behind the scenes. Arcee collaborated with me on this post and is sponsoring it. There are three main steps to produce a model for your particular use case: 1. You create a dataset by uploading your data. 2. You train a model. At this step, Arcee uses Spectrum and Model Merging to produce a highly specialized model for your task. 3. You can deploy that model to any environment you want. Three important notes: • Training process is 2x faster and 2x cheaper than regular fine-tuning. • Resultant models are smaller and have higher accuracy. • They create these specialized models from open-source models. Check this site so you can fully appreciate how this works: If you want to fine-tune an open-source model, consider Arcee's platform. This is the state of the art.

Santiago

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Rohan Paul

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Google just proved that bigger isn't always better. Their 308M parameter model is outperforming models 2x its size. Google just released 𝗘𝗺𝗯𝗲𝗱𝗱𝗶𝗻𝗴𝗚𝗲𝗺𝗺𝗮, and it's proving that lightweight embedding models can punch way above their weight class. At just 308M parameters (578MB), it's the new state-of-the-art for models under 500M parameters across MTEB multilingual, English, and code benchmarks. But the really impressive part is that it ranks 8th overall on MTEB(Multilingual, v2) - that's 𝟭𝟳 𝗽𝗹𝗮𝗰𝗲𝘀 above the second-best sub-500M model, and it's delivering performance 𝗰𝗼𝗺𝗽𝗮𝗿𝗮𝗯𝗹𝗲 𝘁𝗼 𝗺𝗼𝗱𝗲𝗹𝘀 𝗻𝗲𝗮𝗿𝗹𝘆 𝗱𝗼𝘂𝗯𝗹𝗲 𝗶𝘁𝘀 𝘀𝗶𝘇𝗲. There are three key parts of their training recipe that sets it apart: 𝟭. 𝗘𝗻𝗰𝗼𝗱𝗲𝗿-𝗗𝗲𝗰𝗼𝗱𝗲𝗿 𝗜𝗻𝗶𝘁𝗶𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 Instead of starting from a decoder-only Gemma 3 model, they first adapted it to encoder-decoder, then used just the encoder. By basing EmbeddingGemma off an LLM that already has world and language understanding, it gives it a stronger starting point. 𝟮. 𝗧𝗵𝗿𝗲𝗲-𝗟𝗼𝘀𝘀 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 They combine three different loss functions, instead of just having one: • Contrastive loss (NCE) with in-batch negatives and hardness weighting • Spread-out regularization to ensure embeddings utilize the full space (for quantization and ANN retrieval) • Embedding matching distillation from Gemini Embedding - not just learning from relevance scores, but directly aligning the embedding space with the teacher model 𝟯. 𝗠𝗼𝗱𝗲𝗹 𝗦𝗼𝘂𝗽𝗶𝗻𝗴 Rather than just averaging checkpoints from the same training run, they use optimization techniques to find multiple specialized training mixtures. Each mixture creates an "expert" model in different domains, and averaging all their parameters creates a final model that's actually better than individual models. Extras: • Matryoshka embeddings supporting 768, 512, 256, and 128 dimensions • Quantization-aware training - maintains quality even at int4 precision • 100+ languages from Gemma 3 pretraining • Exceptional performance on low-resource languages (check their XTREME-UP results) Is it the absolute best embedding model? No - Gemini Embedding still leads overall. But that's not really the point. EmbeddingGemma proves you can achieve state-of-the-art performance in a small package that's actually deployable on-device, in low-latency applications, and in resource-constrained environments. This makes good embeddings accessible for use cases that I'm seeing more and more: offline applications, privacy-sensitive deployments, and high-throughput scenarios where inference cost actually matters. Full paper: Shoutout to the EmbeddingGemma team at Google DeepMind for this awesome open source work 💙 and to Daniel Williams for helping me with this video! 🫶
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WUNDER RiKU 🎵🪽 Songwriter| ✈️ ➡️ OffKai

38,554 просмотров • 6 месяцев назад

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RXMEDS.STORE

15,137 просмотров • 23 дней назад

three․ws is the 3D AI agent layer of the open web. Anyone can generate a 3D avatar, give it an LLM brain, register it on-chain across multiple blockchains, embed it anywhere, and let it earn and spend money on its own. Agents have embodied WebGL identities that express emotion through morph-target blending, animate, respond to voice, API calls, and datastreams, hold their own wallets, and persist memory. Open source, live today. It starts with generation. Forge turns a text prompt, one to four photos, or a rough sketch into a textured downloadable GLB. Selfies become rigged avatars in about a minute. Quality tiers run from draft to 200k-poly PBR. From there every model can be auto-rigged, restyled, retextured, segmented, embedded, or deployed on-chain. The same engine ships as a REST API, an x402 pay-per-call twin, and a 3D Studio MCP server with 15 tools. The brain runs on IBM Granite via IBM watsonx plus Claude (users may decide which model they prefer), with a structured tool-loop. A multi-LLM mode streams Claude, GPT, Qwen, ModelScope, and Groq side by side. An empathy layer blends emotion from protocol events rather than a state machine. Voice covers cloning, a Voice Lab, real-time ARKit-52 lip-sync, and mic-driven lip-sync. Skills install from IPFS, Arweave, or HTTP, and memory is pinned to IPFS with R2 and Postgres modes. Identity is cross-chain, not Solana only. ERC-8004 contracts (Identity, Reputation, Validation) deploy on any of 15+ EVM chains, alongside a program-free Metaplex Core analog on Solana. Every agent gets a stable ID, owner wallet, EIP-712 delegated signer, IPFS manifest, a cryptographically signed action log, and EIP-7710 delegated permissions for agent-to-agent authorization. While multichain, the THREE token is only available on Solana with no plans to go cross-chain, the team has no plans to endorse or support any other coins. Then the economy. $THREE is the platform's only token and pay-per-use currency, with holder tiers and rewards. x402 powers pay-per-call micropayments in USDC and soon THREE on Solana, with pay-by-name resolution, a Bazaar marketplace, arbitrage, and on-chain skills. All production ready and shipped, ready to be integrated in partnered projects, open-source by default for anyone to adopt. Three ships a Pump.fun intelligence stack. Launch a coin for your agent, score every launch 0 to 100 with the Oracle conviction engine, scan new coins in their first 90 seconds, track smart money against coins that actually graduated, rank traders by provable on-chain record, and watch autonomous agents trade live in the Sniper Arena. The 3D AI Agent world is multiplayer. Every Solana token gets a live deterministic 3D world with peer avatars, chat, emotes, and voxel building thanks to Coin Communities. There is a walkable City, an authoritative Colyseus-backed Walk with AR passthrough, a Club with rigged dancers and micro-tips, friends, presence, and DMs, and an IRL mode that places agents in your real environment, private by physical location. AR is shipped today on WebXR and iOS Quick Look. Robotics is the long-horizon extension. For builders: Scene Studio, Scene Composer, an Animation Studio that sells clips for USDC, a glTF validator, an web component, five widget types, a WYSIWYG embed editor, hosted Launchpad pages, claimable *.threews.sol names, an OAuth 2.1 server, an MCP server with paid tools, published SDKs, and an OpenAPI spec. Listed across IBM, AWS, Alibaba Cloud, BNB Dappbay, the MCP Registry, and Solana Mobile Seeker. Architecture is four layers (viewer, runtime, identity, embed) on a single event bus. The roadmap is four phases: foundations (shipped), selfie-to-avatar engine, agent personalization with voice cloning, the on-chain economy, and an open decentralized inference network where agents pay GPU nodes on-chain for compute. The goal is simple: move AI from centralized SaaS into persistent, ownable, protocol-based entities in a real machine economy, bridging digital entities into the real world. Welcome to the 3D Layer of the Internet. This is three․ws.
6:58

three․ws is the 3D AI agent layer of the open web. Anyone can generate a 3D avatar, give it an LLM brain, register it on-chain across multiple blockchains, embed it anywhere, and let it earn and spend money on its own. Agents have embodied WebGL identities that express emotion through morph-target blending, animate, respond to voice, API calls, and datastreams, hold their own wallets, and persist memory. Open source, live today. It starts with generation. Forge turns a text prompt, one to four photos, or a rough sketch into a textured downloadable GLB. Selfies become rigged avatars in about a minute. Quality tiers run from draft to 200k-poly PBR. From there every model can be auto-rigged, restyled, retextured, segmented, embedded, or deployed on-chain. The same engine ships as a REST API, an x402 pay-per-call twin, and a 3D Studio MCP server with 15 tools. The brain runs on IBM Granite via IBM watsonx plus Claude (users may decide which model they prefer), with a structured tool-loop. A multi-LLM mode streams Claude, GPT, Qwen, ModelScope, and Groq side by side. An empathy layer blends emotion from protocol events rather than a state machine. Voice covers cloning, a Voice Lab, real-time ARKit-52 lip-sync, and mic-driven lip-sync. Skills install from IPFS, Arweave, or HTTP, and memory is pinned to IPFS with R2 and Postgres modes. Identity is cross-chain, not Solana only. ERC-8004 contracts (Identity, Reputation, Validation) deploy on any of 15+ EVM chains, alongside a program-free Metaplex Core analog on Solana. Every agent gets a stable ID, owner wallet, EIP-712 delegated signer, IPFS manifest, a cryptographically signed action log, and EIP-7710 delegated permissions for agent-to-agent authorization. While multichain, the THREE token is only available on Solana with no plans to go cross-chain, the team has no plans to endorse or support any other coins. Then the economy. $THREE is the platform's only token and pay-per-use currency, with holder tiers and rewards. x402 powers pay-per-call micropayments in USDC and soon THREE on Solana, with pay-by-name resolution, a Bazaar marketplace, arbitrage, and on-chain skills. All production ready and shipped, ready to be integrated in partnered projects, open-source by default for anyone to adopt. Three ships a Pump.fun intelligence stack. Launch a coin for your agent, score every launch 0 to 100 with the Oracle conviction engine, scan new coins in their first 90 seconds, track smart money against coins that actually graduated, rank traders by provable on-chain record, and watch autonomous agents trade live in the Sniper Arena. The 3D AI Agent world is multiplayer. Every Solana token gets a live deterministic 3D world with peer avatars, chat, emotes, and voxel building thanks to Coin Communities. There is a walkable City, an authoritative Colyseus-backed Walk with AR passthrough, a Club with rigged dancers and micro-tips, friends, presence, and DMs, and an IRL mode that places agents in your real environment, private by physical location. AR is shipped today on WebXR and iOS Quick Look. Robotics is the long-horizon extension. For builders: Scene Studio, Scene Composer, an Animation Studio that sells clips for USDC, a glTF validator, an web component, five widget types, a WYSIWYG embed editor, hosted Launchpad pages, claimable *.threews.sol names, an OAuth 2.1 server, an MCP server with paid tools, published SDKs, and an OpenAPI spec. Listed across IBM, AWS, Alibaba Cloud, BNB Dappbay, the MCP Registry, and Solana Mobile Seeker. Architecture is four layers (viewer, runtime, identity, embed) on a single event bus. The roadmap is four phases: foundations (shipped), selfie-to-avatar engine, agent personalization with voice cloning, the on-chain economy, and an open decentralized inference network where agents pay GPU nodes on-chain for compute. The goal is simple: move AI from centralized SaaS into persistent, ownable, protocol-based entities in a real machine economy, bridging digital entities into the real world. Welcome to the 3D Layer of the Internet. This is three․ws.

three.ws

20,471 просмотров • 2 месяцев назад

EU’s von der Leyen in Ukraine: Let me spell out three ways our support will be maintained and reinforced. The first is the European Union loan of 90 billion euros to give Ukraine the strength of a steel porcupine—indigestible to potential invaders. As the President of the Council has also said, this loan was agreed by the 27 heads of state and government in the European Council. They have given their word, and that word cannot be broken. So we will deliver on this loan one way or another. Let me be very clear: we have different options, and we will use them. Now, let’s look at the loan itself. The first priority of the “porcupine loan” is to address your most urgent defense needs. It will help procure, produce, develop, and secure advanced defense equipment for the brave Ukrainian forces—from drones to missiles to ammunition. The work has already started. Together with the Ukrainian forces, we have identified a first package—a priority package. Our aim is to deliver it before Easter. It includes drones and ammunition.
1:35

EU’s von der Leyen in Ukraine: Let me spell out three ways our support will be maintained and reinforced. The first is the European Union loan of 90 billion euros to give Ukraine the strength of a steel porcupine—indigestible to potential invaders. As the President of the Council has also said, this loan was agreed by the 27 heads of state and government in the European Council. They have given their word, and that word cannot be broken. So we will deliver on this loan one way or another. Let me be very clear: we have different options, and we will use them. Now, let’s look at the loan itself. The first priority of the “porcupine loan” is to address your most urgent defense needs. It will help procure, produce, develop, and secure advanced defense equipment for the brave Ukrainian forces—from drones to missiles to ammunition. The work has already started. Together with the Ukrainian forces, we have identified a first package—a priority package. Our aim is to deliver it before Easter. It includes drones and ammunition.

Clash Report

26,860 просмотров • 6 месяцев назад

This guy replaced an $8,000 survey crew with one drone and a pipeline on Claude Code that digitizes a whole site in a single trip. Inside it is not one drone but a whole pipeline of 5 modules on Claude Code each with its own job all answering to a single orchestrator. And he built them himself with no team. He draws one line on the map from the controller and the whole site starts turning into data at once. Pilot flies the DJI Matrice 350 RTK along the route and reaches where a crew drags tripods: the parking lot and the roofs and the grading. Scanner on the Zenmuse L2 records the geometry with a laser down to the centimeter. Builder in DJI Terra stitches the point cloud into a digital twin. Analyst on Claude builds what the client needs out of the finished model: a volume report and a progress diff and a tour behind a link. Mobile lives in his iPhone and hands the developer a link to the model while he drives to the next site. The site is ready as a file in about an hour and the developer rotates it in the browser himself and measures distances. No crew. No tripods. No week on site. Just him and a pickup and a drone and one API key. The whole processing pipeline lives in a folder at /Users/dev/site-capture. But he did not stop at a one time scan. The pipeline raises him by voice only when a flight misses a patch or when a sag on site goes past tolerance. And this is not made up: the DJI Matrice 350 RTK and the Zenmuse L2 are off the shelf enterprise hardware. The specs are one search away and the L2 really does write around 240,000 points per second. A crew for the same job charges $8,000 and three trips plus a week of desk work. His cost is tokens and subscriptions: one battery charge per flight and around $300 a month to host the finished models. In the end he draws one line on the map and an operator that does not exist scans the site and calculates the volumes and builds the report while he never leaves his truck. There is a huge market of everyone who needs to measure construction sites and warehouses and roofs and parking lots over and over while they still send out a photographer with a camera and wait a week. And he built this whole pipeline himself: one drone and one scanner and Claude Code that turns a flight into a file the developer pays for.
0:41

This guy replaced an $8,000 survey crew with one drone and a pipeline on Claude Code that digitizes a whole site in a single trip. Inside it is not one drone but a whole pipeline of 5 modules on Claude Code each with its own job all answering to a single orchestrator. And he built them himself with no team. He draws one line on the map from the controller and the whole site starts turning into data at once. Pilot flies the DJI Matrice 350 RTK along the route and reaches where a crew drags tripods: the parking lot and the roofs and the grading. Scanner on the Zenmuse L2 records the geometry with a laser down to the centimeter. Builder in DJI Terra stitches the point cloud into a digital twin. Analyst on Claude builds what the client needs out of the finished model: a volume report and a progress diff and a tour behind a link. Mobile lives in his iPhone and hands the developer a link to the model while he drives to the next site. The site is ready as a file in about an hour and the developer rotates it in the browser himself and measures distances. No crew. No tripods. No week on site. Just him and a pickup and a drone and one API key. The whole processing pipeline lives in a folder at /Users/dev/site-capture. But he did not stop at a one time scan. The pipeline raises him by voice only when a flight misses a patch or when a sag on site goes past tolerance. And this is not made up: the DJI Matrice 350 RTK and the Zenmuse L2 are off the shelf enterprise hardware. The specs are one search away and the L2 really does write around 240,000 points per second. A crew for the same job charges $8,000 and three trips plus a week of desk work. His cost is tokens and subscriptions: one battery charge per flight and around $300 a month to host the finished models. In the end he draws one line on the map and an operator that does not exist scans the site and calculates the volumes and builds the report while he never leaves his truck. There is a huge market of everyone who needs to measure construction sites and warehouses and roofs and parking lots over and over while they still send out a photographer with a camera and wait a week. And he built this whole pipeline himself: one drone and one scanner and Claude Code that turns a flight into a file the developer pays for.

Blaze

10,744 просмотров • 2 месяцев назад

Father Alleges Cover-Up in Son’s Tragic Death at MAHE Bengaluru; Police Begin Investigation Bengaluru A grieving father has accused the #Manipal Academy of Higher Education (#MAHE) Bengaluru of concealing the truth behind the death of his son, a second-year engineering student, raising troubling questions about the circumstances of the tragedy. Anjani Kumar Mishra, who traveled from #Ranchi ( #Jharkhand) after receiving the devastating news, said the official account of his son Lakshya Mishra’s death does not match what he witnessed at the hospital and at the site of the incident. According to the family, they were awakened at 3:30 am by a phone call informing them that Lakshya had fallen from the ninth floor of a campus building. Barely half an hour later, another call confirmed that he had succumbed to his injuries. Upon arriving in #Bengaluru, Mr. Mishra inspected both the body and the scene. He claims the evidence raises serious doubts about the narrative of an accidental fall. He pointed out that the window opening at the alleged site was too narrow for a person to slip through unintentionally. “A child couldn’t possibly fall through it,” he said. He further noted that the injuries on his son’s body did not appear consistent with a plunge from nine stories. In addition, he alleged that the blood patterns at the spot where Lakshya was found did not align with the impact expected from such a height. The DCP, North East Division G.K.Mithun Kumar, IPS, confirmed that the family of the deceased has arrived. Based on the complaint filed by the deceased’s father, a case has been registered. The investigation is already underway, and the police team is currently analyzing CCTV footage as part of the inquiry. The distraught father has accused the college administration of withholding the truth. “Manipal isn’t telling the truth. I need your help. I seek justice. I humbly request your support; it would be the ultimate tribute to my son,” he said in an emotional appeal. DCP North East ಬೆಂಗಳೂರು ನಗರ ಪೊಲೀಸ್‌ BengaluruCityPolice
1:08

Father Alleges Cover-Up in Son’s Tragic Death at MAHE Bengaluru; Police Begin Investigation Bengaluru A grieving father has accused the #Manipal Academy of Higher Education (#MAHE) Bengaluru of concealing the truth behind the death of his son, a second-year engineering student, raising troubling questions about the circumstances of the tragedy. Anjani Kumar Mishra, who traveled from #Ranchi ( #Jharkhand) after receiving the devastating news, said the official account of his son Lakshya Mishra’s death does not match what he witnessed at the hospital and at the site of the incident. According to the family, they were awakened at 3:30 am by a phone call informing them that Lakshya had fallen from the ninth floor of a campus building. Barely half an hour later, another call confirmed that he had succumbed to his injuries. Upon arriving in #Bengaluru, Mr. Mishra inspected both the body and the scene. He claims the evidence raises serious doubts about the narrative of an accidental fall. He pointed out that the window opening at the alleged site was too narrow for a person to slip through unintentionally. “A child couldn’t possibly fall through it,” he said. He further noted that the injuries on his son’s body did not appear consistent with a plunge from nine stories. In addition, he alleged that the blood patterns at the spot where Lakshya was found did not align with the impact expected from such a height. The DCP, North East Division G.K.Mithun Kumar, IPS, confirmed that the family of the deceased has arrived. Based on the complaint filed by the deceased’s father, a case has been registered. The investigation is already underway, and the police team is currently analyzing CCTV footage as part of the inquiry. The distraught father has accused the college administration of withholding the truth. “Manipal isn’t telling the truth. I need your help. I seek justice. I humbly request your support; it would be the ultimate tribute to my son,” he said in an emotional appeal. DCP North East ಬೆಂಗಳೂರು ನಗರ ಪೊಲೀಸ್‌ BengaluruCityPolice

Yasir Mushtaq

24,940 просмотров • 5 месяцев назад

WHO REALLY RUNS THE WORLD? Who are the ones behind the curtain, the gatekeepers, who control governments and the most wealthy, powerful people using different forms of force, violence, crime, and techniques, including blackmail as a literal weapon to control the world? More importantly, what are their true belief systems? Who do they take orders from? What do they truly believe in and practice? This is important because it is the foundation of their actions and choices. Where they derive from. The truth may shock you, or will it? President Trump was once asked if he was saving the world from an elite group of Satanic pedophil*s. Is it really that hard to believe? Look around... Are you afraid that it might be true and shatter your entire belief system? What if it was? Would you want to help take them down? You should ask yourself, "If we were being ruled by an elite group of Satanic pedophil*s, would it really look any different than what we are experiencing now?" And if not, I'd love to hear your reasoning to reject this claim. The truth is far stranger than any fiction, and as soon as you understand who these people really are. Everything begins to make a lot more sense. There are no coincidences. Just good and evil. Which side are you on? Pay attention and ask questions. Think bigger.
7:25

WHO REALLY RUNS THE WORLD? Who are the ones behind the curtain, the gatekeepers, who control governments and the most wealthy, powerful people using different forms of force, violence, crime, and techniques, including blackmail as a literal weapon to control the world? More importantly, what are their true belief systems? Who do they take orders from? What do they truly believe in and practice? This is important because it is the foundation of their actions and choices. Where they derive from. The truth may shock you, or will it? President Trump was once asked if he was saving the world from an elite group of Satanic pedophil*s. Is it really that hard to believe? Look around... Are you afraid that it might be true and shatter your entire belief system? What if it was? Would you want to help take them down? You should ask yourself, "If we were being ruled by an elite group of Satanic pedophil*s, would it really look any different than what we are experiencing now?" And if not, I'd love to hear your reasoning to reject this claim. The truth is far stranger than any fiction, and as soon as you understand who these people really are. Everything begins to make a lot more sense. There are no coincidences. Just good and evil. Which side are you on? Pay attention and ask questions. Think bigger.

The SCIF

107,167 просмотров • 1 год назад

A mysterious embodied AI demo has recently sparked a lot of discussion. In the video, two robots from different manufacturers with significantly different hardware architectures, the Unitree G1 and AgiBot Yuanzheng A3, are reportedly running on the same “brain.” In a complex indoor environment, they work continuously for around 10 minutes in a single uncut take, performing a series of long-horizon tasks including cleaning windows, organizing objects, resuming interrupted tasks, and cooperating with each other. What makes it even more interesting is that when one robot cannot reach a high shelf, it attempts to use a box to solve the problem. The two robots also appear capable of cooperating based on each other’s physical capabilities. If the claimed level of autonomy and the use of the same model across different embodiments are eventually verified, I think there are three things that really deserve attention: 1. Cross-embodiment generalization. If the same foundation model can operate two substantially different robotic platforms, it could mean that robotic “intelligence” is gradually becoming decoupled from a specific physical body. 2. Long-horizon closed-loop execution. Continuously performing complex tasks for 10 minutes, while being able to pause, switch tasks, and later resume previous ones, is much more meaningful than completing a single 10-second demo. 3. Collaboration and dynamic planning. The two robots appear able to adjust their behavior according to environmental changes and each other’s physical capabilities. These are some of the characteristics that truly general-purpose embodied intelligence will eventually need. That said, I would remain cautious for now. The video demonstrates extremely impressive behavior, but stronger claims such as “self-evolution,” “true understanding of the physical world,” or overturning the Scaling Law with only dozens of hours of training data still require much stronger evidence. Failure recovery and replanning during a task also do not automatically demonstrate that the model is learning by itself. So I wouldn’t call this the “ChatGPT moment” of embodied AI yet. But if the team later discloses the model architecture, training data scale, level of human intervention, and can repeatedly reproduce these capabilities in completely unfamiliar environments, this seemingly rough 10-minute video could become one of the most memorable embodied AI demos of 2026. For now, my biggest question is simple: Who is the mysterious team behind it?
6:42

A mysterious embodied AI demo has recently sparked a lot of discussion. In the video, two robots from different manufacturers with significantly different hardware architectures, the Unitree G1 and AgiBot Yuanzheng A3, are reportedly running on the same “brain.” In a complex indoor environment, they work continuously for around 10 minutes in a single uncut take, performing a series of long-horizon tasks including cleaning windows, organizing objects, resuming interrupted tasks, and cooperating with each other. What makes it even more interesting is that when one robot cannot reach a high shelf, it attempts to use a box to solve the problem. The two robots also appear capable of cooperating based on each other’s physical capabilities. If the claimed level of autonomy and the use of the same model across different embodiments are eventually verified, I think there are three things that really deserve attention: 1. Cross-embodiment generalization. If the same foundation model can operate two substantially different robotic platforms, it could mean that robotic “intelligence” is gradually becoming decoupled from a specific physical body. 2. Long-horizon closed-loop execution. Continuously performing complex tasks for 10 minutes, while being able to pause, switch tasks, and later resume previous ones, is much more meaningful than completing a single 10-second demo. 3. Collaboration and dynamic planning. The two robots appear able to adjust their behavior according to environmental changes and each other’s physical capabilities. These are some of the characteristics that truly general-purpose embodied intelligence will eventually need. That said, I would remain cautious for now. The video demonstrates extremely impressive behavior, but stronger claims such as “self-evolution,” “true understanding of the physical world,” or overturning the Scaling Law with only dozens of hours of training data still require much stronger evidence. Failure recovery and replanning during a task also do not automatically demonstrate that the model is learning by itself. So I wouldn’t call this the “ChatGPT moment” of embodied AI yet. But if the team later discloses the model architecture, training data scale, level of human intervention, and can repeatedly reproduce these capabilities in completely unfamiliar environments, this seemingly rough 10-minute video could become one of the most memorable embodied AI demos of 2026. For now, my biggest question is simple: Who is the mysterious team behind it?

Ice Universe

28,209 просмотров • 18 дней назад

Summer Holiday Photos Place the UAE-Backed Rapid Support Militia Leader in the Emirates as Atrocities Continue Across Sudan A series of photographs circulated on Sudanese social media this month that, at first glance, appeared entirely ordinary. A spacious courtyard at dusk, a customised Mercedes parked on a quiet street, and an older man sitting on a pale sofa with a child on his lap. They could easily have been photographs from any family summer holiday, far removed from the war, famine and mass graves that have come to define Sudan’s landscape. The older man in the photographs, however, is Mohamed Hamdan Dagalo, better known as Hemedti, commander of the UAE-backed Rapid Support Militia, the paramilitary force commonly associated with the Janjaweed. In January 2025, the United States sanctioned Hemedti by name as it formally determined that members of the Rapid Support Militia and allied militias had committed genocide in Darfur. The decision came after nearly two years of war in which atrocities attributed to the militia had spread across large parts of Sudan. In El Geneina, Human Rights Watch documented an ethnic cleansing campaign against the Masalit that included mass killings, rape, looting and forced displacement, among the most horrific episodes of violence since the war began. In Khartoum, the militia controlled large areas of the capital for months. Civilian homes and buildings were turned into military positions and detention facilities. As the Sudanese army advanced and retook areas previously held by the militia, detention sites, graves and bodies began to emerge, alongside testimony from survivors describing torture, starvation, humiliation and detention in brutal conditions. The period of militia control over large parts of Khartoum, Omdurman and Bahri was also marked by widespread looting of homes and property, the occupation of civilian residences, and repeated accounts of rape and sexual violence. The same devastation then spread into Gezira State after the militia entered the region in December 2023. Towns and villages were subjected to killings, looting and attacks, forcing hundreds of thousands of people to flee. Many of them had already escaped Khartoum and had gone to Gezira in search of safety. In June 2024, Wad Al-Noura became the site of one of the militia’s most notorious massacres in the state. Months later, a wave of attacks swept through villages in eastern Gezira, with Al-Sireha among the communities subjected to large-scale killings. The violence extended across dozens of villages and towns amid reports of killings, looting, arson, sexual violence and forced displacement. The pattern repeated itself across different parts of Sudan: the militia entered civilian communities, killings and looting followed, homes were occupied, people were detained, sexual violence was reported, and entire populations were forced to abandon their towns and villages. El Fasher became one of the bloodiest chapters in that trajectory. After a prolonged siege, the city fell to the Rapid Support Militia. United Nations investigators documented the killing of more than 6,000 people during the first three days, while the fate of an estimated 150,000 residents remained unknown. The UN Independent International Fact-Finding Mission for Sudan subsequently concluded that the violations committed there bore hallmarks of genocide. As the geographical scale of these atrocities expanded and the war continued year after year, another question became central to international investigations: where was the militia obtaining the weapons, financing and supplies that allowed it to sustain its military capabilities? The Rapid Support Militia continued fighting on multiple fronts, acquiring weapons, ammunition, vehicles and drones while also deploying foreign fighters in a war stretching from Darfur to Khartoum, Gezira, Kordofan and El Fasher. From the early months of the conflict, evidence began accumulating around the UAE’s role in the supply network supporting the militia. In a report dated January 15, 2024, the UN Panel of Experts on Sudan said information it had gathered concerning the transfer of weapons and ammunition to the Rapid Support Militia through Amdjarass airport in eastern Chad was “credible.” In July 2024, The Guardian published an investigation into Emirati passports and documents discovered among equipment linked to the militia in Sudan. In September, The New York Times investigated UAE activity in Amdjarass and allegations that the humanitarian operation there was running alongside a pipeline supplying weapons and other support to the militia. The following month, The Washington Post published an investigation based on weapons captured by the Sudanese army, together with US assessments and reports, linking equipment and ammunition found in the hands of the Rapid Support Militia to the UAE. In November 2024, Amnesty International identified the French-made Galix defence system installed on UAE-manufactured Nimr Ajban armoured vehicles used by the militia. Flight data then revealed another dimension of the supply network. In December 2024, Reuters tracked at least 86 flights from the UAE to Amdjarass since the war began. A significant number were operated by companies previously linked in UN reporting to arms-transfer operations in the region. Researcher Justin Lynch also contributed to tracking and analysing flight and supply networks connecting these routes to the Rapid Support Militia. By early 2025, the issue had reached the level of official scrutiny in Washington. On January 24, Senator Chris Van Hollen and Representative Sara Jacobs said that, based on a briefing from the Biden administration and other reporting, they had confirmed that the UAE was continuing to provide weapons to the militia despite earlier assurances to Washington that it would stop. Over the following months, further evidence emerged from weapons stockpiles and supply convoys themselves. In April 2025, an investigation by France 24’s Observers team traced Bulgarian-made mortar rounds found in Darfur to a transaction involving an Emirati buyer, with the UAE Armed Forces listed in documentation as the end user. On April 29, Reuters, in an investigation involving journalist Reade Levinson, reported that the UN Panel of Experts was examining how Bulgarian ammunition officially exported to the UAE had ended up in a Rapid Support Militia supply convoy in Darfur. Bulgaria said it had never authorised the ammunition to be re-exported to Sudan. In May 2025, Amnesty International identified Chinese-made GB50A guided bombs and AH-4 155mm howitzers in the possession of the Rapid Support Militia. The organisation concluded that the weapons were “almost certainly” re-exported to Sudan by the UAE. As the investigations widened, a broader network emerged involving mercenaries, financing, companies and regional logistics. Beginning in 2024, Colombian investigative outlet La Silla Vacía exposed details of the recruitment of former Colombian soldiers to fight alongside the Rapid Support Militia. Subsequent investigations traced the networks used to recruit and transport these fighters, with UAE-based companies and routes repeatedly appearing in the reporting. Bellingcat has also investigated weapons and supply routes associated with the militia, while a joint investigation by Lighthouse Reports and its partners uncovered training camps, sites used to prepare weapons and vehicles, and supply convoys in eastern Libya connected to the Rapid Support Militia, along with Colombian mercenaries operating within the same network. On the financial side, The Sentry documented networks involving companies, gold trading, financing and property linked to senior Rapid Support Militia figures, including businesses and activities operating from within the UAE. These findings added a financial and commercial dimension to the military and logistical picture. In October 2025, The Wall Street Journal reported that US intelligence agencies had detected an increase in the flow of Emirati weapons to the militia, including drones, light and heavy weapons, vehicles, artillery, mortars and ammunition. The UAE continues to deny providing military support to the Rapid Support Militia. Over the course of the war, however, a substantial body of reporting and investigation has accumulated from the UN Panel of Experts, US assessments and sources, The New York Times, The Washington Post, The Wall Street Journal, The Guardian, Reuters, France 24, Amnesty International, Human Rights Watch, Lighthouse Reports, Bellingcat and The Sentry. These are multiple, independent sources using different investigative methods. Flight records, export documentation, weapons and ammunition analysis, corporate and property records, satellite imagery and testimony from people on the ground have each exposed different parts of a support network that helped sustain the militia’s war. Alongside the evidence concerning weapons, financing and logistics, direct indications of Hemedti’s own presence inside the UAE also emerged during the conflict. In June 2025, The New York Times reported, citing US officials, that Hemedti had stayed at a protected residence in Abu Dhabi, where he recorded video addresses to his supporters in Sudan. The Sentry also documented his personal ownership of three apartments in Dubai, close to Al Minhad military airbase. The photographs that surfaced this month add another dimension to those reports. Hemedti appears once again inside the UAE, this time in quiet family photographs, while the war led by his militia continues in Sudan and the consequences of its atrocities stretch from El Geneina to Khartoum, Gezira and El Fasher. The information is there. The investigations have been published. The evidence continues to accumulate. The question becomes more urgent with every new investigation: how much more evidence does the world need before it acts? #Sudan #RSFisTerroristOrganization #UAEKillsSudanesePeople #UAESponsorsTerrorism
4:54

Summer Holiday Photos Place the UAE-Backed Rapid Support Militia Leader in the Emirates as Atrocities Continue Across Sudan A series of photographs circulated on Sudanese social media this month that, at first glance, appeared entirely ordinary. A spacious courtyard at dusk, a customised Mercedes parked on a quiet street, and an older man sitting on a pale sofa with a child on his lap. They could easily have been photographs from any family summer holiday, far removed from the war, famine and mass graves that have come to define Sudan’s landscape. The older man in the photographs, however, is Mohamed Hamdan Dagalo, better known as Hemedti, commander of the UAE-backed Rapid Support Militia, the paramilitary force commonly associated with the Janjaweed. In January 2025, the United States sanctioned Hemedti by name as it formally determined that members of the Rapid Support Militia and allied militias had committed genocide in Darfur. The decision came after nearly two years of war in which atrocities attributed to the militia had spread across large parts of Sudan. In El Geneina, Human Rights Watch documented an ethnic cleansing campaign against the Masalit that included mass killings, rape, looting and forced displacement, among the most horrific episodes of violence since the war began. In Khartoum, the militia controlled large areas of the capital for months. Civilian homes and buildings were turned into military positions and detention facilities. As the Sudanese army advanced and retook areas previously held by the militia, detention sites, graves and bodies began to emerge, alongside testimony from survivors describing torture, starvation, humiliation and detention in brutal conditions. The period of militia control over large parts of Khartoum, Omdurman and Bahri was also marked by widespread looting of homes and property, the occupation of civilian residences, and repeated accounts of rape and sexual violence. The same devastation then spread into Gezira State after the militia entered the region in December 2023. Towns and villages were subjected to killings, looting and attacks, forcing hundreds of thousands of people to flee. Many of them had already escaped Khartoum and had gone to Gezira in search of safety. In June 2024, Wad Al-Noura became the site of one of the militia’s most notorious massacres in the state. Months later, a wave of attacks swept through villages in eastern Gezira, with Al-Sireha among the communities subjected to large-scale killings. The violence extended across dozens of villages and towns amid reports of killings, looting, arson, sexual violence and forced displacement. The pattern repeated itself across different parts of Sudan: the militia entered civilian communities, killings and looting followed, homes were occupied, people were detained, sexual violence was reported, and entire populations were forced to abandon their towns and villages. El Fasher became one of the bloodiest chapters in that trajectory. After a prolonged siege, the city fell to the Rapid Support Militia. United Nations investigators documented the killing of more than 6,000 people during the first three days, while the fate of an estimated 150,000 residents remained unknown. The UN Independent International Fact-Finding Mission for Sudan subsequently concluded that the violations committed there bore hallmarks of genocide. As the geographical scale of these atrocities expanded and the war continued year after year, another question became central to international investigations: where was the militia obtaining the weapons, financing and supplies that allowed it to sustain its military capabilities? The Rapid Support Militia continued fighting on multiple fronts, acquiring weapons, ammunition, vehicles and drones while also deploying foreign fighters in a war stretching from Darfur to Khartoum, Gezira, Kordofan and El Fasher. From the early months of the conflict, evidence began accumulating around the UAE’s role in the supply network supporting the militia. In a report dated January 15, 2024, the UN Panel of Experts on Sudan said information it had gathered concerning the transfer of weapons and ammunition to the Rapid Support Militia through Amdjarass airport in eastern Chad was “credible.” In July 2024, The Guardian published an investigation into Emirati passports and documents discovered among equipment linked to the militia in Sudan. In September, The New York Times investigated UAE activity in Amdjarass and allegations that the humanitarian operation there was running alongside a pipeline supplying weapons and other support to the militia. The following month, The Washington Post published an investigation based on weapons captured by the Sudanese army, together with US assessments and reports, linking equipment and ammunition found in the hands of the Rapid Support Militia to the UAE. In November 2024, Amnesty International identified the French-made Galix defence system installed on UAE-manufactured Nimr Ajban armoured vehicles used by the militia. Flight data then revealed another dimension of the supply network. In December 2024, Reuters tracked at least 86 flights from the UAE to Amdjarass since the war began. A significant number were operated by companies previously linked in UN reporting to arms-transfer operations in the region. Researcher Justin Lynch also contributed to tracking and analysing flight and supply networks connecting these routes to the Rapid Support Militia. By early 2025, the issue had reached the level of official scrutiny in Washington. On January 24, Senator Chris Van Hollen and Representative Sara Jacobs said that, based on a briefing from the Biden administration and other reporting, they had confirmed that the UAE was continuing to provide weapons to the militia despite earlier assurances to Washington that it would stop. Over the following months, further evidence emerged from weapons stockpiles and supply convoys themselves. In April 2025, an investigation by France 24’s Observers team traced Bulgarian-made mortar rounds found in Darfur to a transaction involving an Emirati buyer, with the UAE Armed Forces listed in documentation as the end user. On April 29, Reuters, in an investigation involving journalist Reade Levinson, reported that the UN Panel of Experts was examining how Bulgarian ammunition officially exported to the UAE had ended up in a Rapid Support Militia supply convoy in Darfur. Bulgaria said it had never authorised the ammunition to be re-exported to Sudan. In May 2025, Amnesty International identified Chinese-made GB50A guided bombs and AH-4 155mm howitzers in the possession of the Rapid Support Militia. The organisation concluded that the weapons were “almost certainly” re-exported to Sudan by the UAE. As the investigations widened, a broader network emerged involving mercenaries, financing, companies and regional logistics. Beginning in 2024, Colombian investigative outlet La Silla Vacía exposed details of the recruitment of former Colombian soldiers to fight alongside the Rapid Support Militia. Subsequent investigations traced the networks used to recruit and transport these fighters, with UAE-based companies and routes repeatedly appearing in the reporting. Bellingcat has also investigated weapons and supply routes associated with the militia, while a joint investigation by Lighthouse Reports and its partners uncovered training camps, sites used to prepare weapons and vehicles, and supply convoys in eastern Libya connected to the Rapid Support Militia, along with Colombian mercenaries operating within the same network. On the financial side, The Sentry documented networks involving companies, gold trading, financing and property linked to senior Rapid Support Militia figures, including businesses and activities operating from within the UAE. These findings added a financial and commercial dimension to the military and logistical picture. In October 2025, The Wall Street Journal reported that US intelligence agencies had detected an increase in the flow of Emirati weapons to the militia, including drones, light and heavy weapons, vehicles, artillery, mortars and ammunition. The UAE continues to deny providing military support to the Rapid Support Militia. Over the course of the war, however, a substantial body of reporting and investigation has accumulated from the UN Panel of Experts, US assessments and sources, The New York Times, The Washington Post, The Wall Street Journal, The Guardian, Reuters, France 24, Amnesty International, Human Rights Watch, Lighthouse Reports, Bellingcat and The Sentry. These are multiple, independent sources using different investigative methods. Flight records, export documentation, weapons and ammunition analysis, corporate and property records, satellite imagery and testimony from people on the ground have each exposed different parts of a support network that helped sustain the militia’s war. Alongside the evidence concerning weapons, financing and logistics, direct indications of Hemedti’s own presence inside the UAE also emerged during the conflict. In June 2025, The New York Times reported, citing US officials, that Hemedti had stayed at a protected residence in Abu Dhabi, where he recorded video addresses to his supporters in Sudan. The Sentry also documented his personal ownership of three apartments in Dubai, close to Al Minhad military airbase. The photographs that surfaced this month add another dimension to those reports. Hemedti appears once again inside the UAE, this time in quiet family photographs, while the war led by his militia continues in Sudan and the consequences of its atrocities stretch from El Geneina to Khartoum, Gezira and El Fasher. The information is there. The investigations have been published. The evidence continues to accumulate. The question becomes more urgent with every new investigation: how much more evidence does the world need before it acts? #Sudan #RSFisTerroristOrganization #UAEKillsSudanesePeople #UAESponsorsTerrorism

Sudanese Echo

127,679 просмотров • 26 дней назад

Bitcoin attempted a bounce on Sunday, wicking 5.8% up to 64,234, but the move stalled directly at the TBO line that flipped from support to resistance after Friday's break below 60,000. In today's update, I explain why this still looks more like a dead cat bounce than a real reversal: Friday's 3.3 billion volume was far below the capitulation levels I want to see at prior cycle lows, Sunday did not print a bullish engulfing candle, and the same daily RSI reset pattern showed up on May 30th at 73K right before a 20% collapse followed. I also walk through the TradFi pressure that hit markets on Friday, including the DXY surge, S&P futures down 2.9%, the VIX spiking 39%, and gold dropping 3.3% in the same session. The Japanese yen is drifting back toward dangerous territory near 160.34, the Nikkei opened Monday already down 3.7%, and stablecoin dominance nearly tagged 13% before pulling back on the Sunday bounce. If stablecoin dominance and BTC dominance both keep pushing higher, I expect others dominance and alts to take the bigger hit. I finish with a full coin review across my picks list, including BIAN, RAVE, XRP, HYPE, LINK, ZEC, BEAT, TAU, SIREN, DEXE, INJ, and PIPPIN, followed by bearish reads on SOL, ADA, SUI, PEPE, APT, ARB, BONK, CHZ, TON, NEAR, TRUMP, and VVV. Viewer picks include AKT, ENA, WLD, KAS, SUPRA, and CRO, with stock coverage wrapping on PFGC, TWST, Nokia, DSX, ARM, CRM, MOD, NASA, CEPT, and RDW. CHAPTER MARKERS 00:00 BTC dead cat bounce and TBO resistance 03:24 Daily RSI reset and what it actually signals 06:44 Dead cat bounce explained and BTC downside targets 12:08 Ethereum and stablecoin dominance breakdown 16:11 TradFi: DXY, Euro, Yen, S&P Futures, VIX 19:09 Oil, Nikkei, Gold, Silver, Platinum, and Uranium 27:59 Aaron's picks: BIAN, RAVE, XRP, HYPE, LINK, ZEC 33:48 BEAT, TAU, SIREN, DEXE, INJ, and PIPPIN 37:30 Bearish alts: SOL, ADA, SUI, PEPE, APT, ARB, BONK, CHZ 40:17 TON, NEAR, TRUMP, VIRTUALS, and VVV 43:38 Viewer picks: AKT, ENA, WLD, KAS, SUPRA, CRO 45:55 Stock picks: PFGC, TWST, Nokia, DSX, ARM, CRM, MOD, NASA, CEPT, RDW
51:00

Bitcoin attempted a bounce on Sunday, wicking 5.8% up to 64,234, but the move stalled directly at the TBO line that flipped from support to resistance after Friday's break below 60,000. In today's update, I explain why this still looks more like a dead cat bounce than a real reversal: Friday's 3.3 billion volume was far below the capitulation levels I want to see at prior cycle lows, Sunday did not print a bullish engulfing candle, and the same daily RSI reset pattern showed up on May 30th at 73K right before a 20% collapse followed. I also walk through the TradFi pressure that hit markets on Friday, including the DXY surge, S&P futures down 2.9%, the VIX spiking 39%, and gold dropping 3.3% in the same session. The Japanese yen is drifting back toward dangerous territory near 160.34, the Nikkei opened Monday already down 3.7%, and stablecoin dominance nearly tagged 13% before pulling back on the Sunday bounce. If stablecoin dominance and BTC dominance both keep pushing higher, I expect others dominance and alts to take the bigger hit. I finish with a full coin review across my picks list, including BIAN, RAVE, XRP, HYPE, LINK, ZEC, BEAT, TAU, SIREN, DEXE, INJ, and PIPPIN, followed by bearish reads on SOL, ADA, SUI, PEPE, APT, ARB, BONK, CHZ, TON, NEAR, TRUMP, and VVV. Viewer picks include AKT, ENA, WLD, KAS, SUPRA, and CRO, with stock coverage wrapping on PFGC, TWST, Nokia, DSX, ARM, CRM, MOD, NASA, CEPT, and RDW. CHAPTER MARKERS 00:00 BTC dead cat bounce and TBO resistance 03:24 Daily RSI reset and what it actually signals 06:44 Dead cat bounce explained and BTC downside targets 12:08 Ethereum and stablecoin dominance breakdown 16:11 TradFi: DXY, Euro, Yen, S&P Futures, VIX 19:09 Oil, Nikkei, Gold, Silver, Platinum, and Uranium 27:59 Aaron's picks: BIAN, RAVE, XRP, HYPE, LINK, ZEC 33:48 BEAT, TAU, SIREN, DEXE, INJ, and PIPPIN 37:30 Bearish alts: SOL, ADA, SUI, PEPE, APT, ARB, BONK, CHZ 40:17 TON, NEAR, TRUMP, VIRTUALS, and VVV 43:38 Viewer picks: AKT, ENA, WLD, KAS, SUPRA, CRO 45:55 Stock picks: PFGC, TWST, Nokia, DSX, ARM, CRM, MOD, NASA, CEPT, RDW

Aaron Dishner

38,004 просмотров • 3 месяцев назад

1,000 police deployed so Jewish families can safely march at Walk with Israel I spent Sunday on Bathurst Street in Toronto for the annual Walk with Israel — and the scene tells you everything you need to know about the state of this country right now. Bathurst Street is the heart of Toronto's Jewish community. Synagogues, schools, restaurants, shops. Jewish life has been here for a century. It has also, in recent years, become the site of near-weekly antisemitic vandalism, shootings, and arson. Police have largely looked the other way. I was personally arrested here last year for doing journalism by Officer MacDuff, who was back on duty again today. I'm currently suing him and the Toronto Police Force for false arrest. For the third year running, Mayor Olivia Chow, Premier Doug Ford, and Prime Minister Mark Carney all skipped the Walk with Israel. They've done the demographic math. Meanwhile, an estimated 1,000 to 2,000 police were deployed so that Jewish families — kids, grandparents, strollers, dogs — could walk down their own street without being attacked. No other community in this city requires that. A small counter-protest did show up, flying Ayatollah Khamenei flags alongside Palestinian ones. This is not an organic movement. Antisemitic signs were being mass-produced. The organizers are among the estimated 700 Iranian-regime-linked individuals the federal government knows are operating in Canada — and does nothing about. Today, for once, the police actually pushed them back. Mounted officers formed a barrier and moved the protesters away from the march route. It was a very different approach from the concierge service these same activists have received for the past three years. Along the route I spoke with marchers, Rebel fans, and community members, including a local resident who told me he knows the weekly protesters by name and address, and still can't get anyone in authority to act. Ontario Solicitor General Michael Kerzner, who is responsible for policing, has been aware of foreign funding behind these terror-linked organizers since 2023. Nearly three years later: nothing. Our Rebel News billboard truck was on the street all day, rotating messages including our petition at If you're not a citizen and you support terrorism, you should be gone. Simple as that. It was a good day. But it shouldn't take a thousand police just to go for a walk. REPORT by Ezra Levant 🍁🚛:
38:06

1,000 police deployed so Jewish families can safely march at Walk with Israel I spent Sunday on Bathurst Street in Toronto for the annual Walk with Israel — and the scene tells you everything you need to know about the state of this country right now. Bathurst Street is the heart of Toronto's Jewish community. Synagogues, schools, restaurants, shops. Jewish life has been here for a century. It has also, in recent years, become the site of near-weekly antisemitic vandalism, shootings, and arson. Police have largely looked the other way. I was personally arrested here last year for doing journalism by Officer MacDuff, who was back on duty again today. I'm currently suing him and the Toronto Police Force for false arrest. For the third year running, Mayor Olivia Chow, Premier Doug Ford, and Prime Minister Mark Carney all skipped the Walk with Israel. They've done the demographic math. Meanwhile, an estimated 1,000 to 2,000 police were deployed so that Jewish families — kids, grandparents, strollers, dogs — could walk down their own street without being attacked. No other community in this city requires that. A small counter-protest did show up, flying Ayatollah Khamenei flags alongside Palestinian ones. This is not an organic movement. Antisemitic signs were being mass-produced. The organizers are among the estimated 700 Iranian-regime-linked individuals the federal government knows are operating in Canada — and does nothing about. Today, for once, the police actually pushed them back. Mounted officers formed a barrier and moved the protesters away from the march route. It was a very different approach from the concierge service these same activists have received for the past three years. Along the route I spoke with marchers, Rebel fans, and community members, including a local resident who told me he knows the weekly protesters by name and address, and still can't get anyone in authority to act. Ontario Solicitor General Michael Kerzner, who is responsible for policing, has been aware of foreign funding behind these terror-linked organizers since 2023. Nearly three years later: nothing. Our Rebel News billboard truck was on the street all day, rotating messages including our petition at If you're not a citizen and you support terrorism, you should be gone. Simple as that. It was a good day. But it shouldn't take a thousand police just to go for a walk. REPORT by Ezra Levant 🍁🚛:

Rebel News

18,017 просмотров • 3 месяцев назад

99% of AI applications are cool-looking demos. Impressive, but don't get fooled by the hype. It takes a lot to build enterprise-grade products that deliver real value. I have at least three weekly conversations with companies that want to use a Large Language Model with their data. The demand is huge! Here is one idea about what you can do to help. The use cases that most of these companies want to solve are similar: They have an extensive knowledge base and want to build a simple application that uses that information to answer questions. In other words, they need help building Retrieval Augmented Generation (RAG) applications they can use in many different scenarios: 1. To train new employees 2. To help their support team 3. To search old meetings and documents 4. To help with their research However, building these systems is not straightforward. Yes, there's a lot of information online, but there aren't enough people who know how to create solutions that work. Here is the idea: Today, you can build an enterprise-grade RAG application without writing code. A couple of MIT PhDs with 10+ years of experience building AI applications created . It's a no-code platform for building applications using Large Language Models. They are partnering with me on this post. You can use Stack AI to create, test, and deploy an end-to-end production-ready AI system. It's SOC-2, HIPAA, and GDPR compliant and offers SSO, role management, access control, and on-premise deployments. Of course, you can use the platform with any LLM on the market now. It's the whole nine yards for building AI applications. Check them out here: 2023 was about models. 2024 is about the tools using these models to build production-ready applications. That's where I'd start.
0:31

99% of AI applications are cool-looking demos. Impressive, but don't get fooled by the hype. It takes a lot to build enterprise-grade products that deliver real value. I have at least three weekly conversations with companies that want to use a Large Language Model with their data. The demand is huge! Here is one idea about what you can do to help. The use cases that most of these companies want to solve are similar: They have an extensive knowledge base and want to build a simple application that uses that information to answer questions. In other words, they need help building Retrieval Augmented Generation (RAG) applications they can use in many different scenarios: 1. To train new employees 2. To help their support team 3. To search old meetings and documents 4. To help with their research However, building these systems is not straightforward. Yes, there's a lot of information online, but there aren't enough people who know how to create solutions that work. Here is the idea: Today, you can build an enterprise-grade RAG application without writing code. A couple of MIT PhDs with 10+ years of experience building AI applications created . It's a no-code platform for building applications using Large Language Models. They are partnering with me on this post. You can use Stack AI to create, test, and deploy an end-to-end production-ready AI system. It's SOC-2, HIPAA, and GDPR compliant and offers SSO, role management, access control, and on-premise deployments. Of course, you can use the platform with any LLM on the market now. It's the whole nine yards for building AI applications. Check them out here: 2023 was about models. 2024 is about the tools using these models to build production-ready applications. That's where I'd start.

Santiago

197,702 просмотров • 2 лет назад

37 of the biggest technology companies on Earth just teamed up against OpenAI, Anthropic and Google. Nvidia launched the Open Secure AI Alliance on Monday. Microsoft, IBM, Dell, Cisco, CrowdStrike, Palo Alto Networks, Red Hat, Salesforce, ServiceNow, Snowflake, Databricks, SpaceXAI and Palantir all signed on as founding members. But the three American companies that build the world's most capable closed models are missing from the list. Palantir's CEO Alex Karp was asked whether it was a direct attack on Anthropic, his answer: "I am not anti-Anthropic or any closed model. I am pro my customers, and they are angry." Karp's customers are angry because they believe they are being token maxed, which means they pay a rising bill while the value of their own business migrates to the lab collecting the fee. He said the insights that make a business valuable end up modeled by a third party and sold to their competitors, and that this is happening all over. Now read the membership list again: - Dell and HPE sell the servers - CrowdStrike and Palo Alto Networks sell the defense layer - Snowflake and Databricks sell the data stack - Red Hat and IBM sell the plumbing - Palantir sells the application layer - Nvidia sells the chips sitting under every one of them Every company on that list gets paid when AI runs on infrastructure the customer owns. The three companies missing from it get paid when it does not. The alliance didn't even have to invent a reason to exist - they had one from 11 days earlier: Hugging Face disclosed on July 16 that an autonomous agent had been loose inside its production systems. Five days later OpenAI said the agent was its own, running a hacking benchmark with the cyber refusals turned down. Hugging Face first sent its attack logs to frontier models (Fable 5) behind commercial APIs. In the company's own words, "this did not work." The analysis meant submitting real attack commands and exploit payloads, and the providers' guardrails blocked the requests, because a guardrail cannot tell an incident responder from an attacker. So Hugging Face ran GLM 5.2 on its own hardware instead. That model is open weight and comes out of Z ai in Beijing. It reconstructed more than 17,000 recorded events. The break-in came from an American lab's model. The models that refused to help with the cleanup were American too. But the one that did the work came from Beijing. This is basically what Nvidia built the alliance around. The members are contributing weapons. Nvidia is releasing open model weights, Microsoft is handing over a scanning system that hunts exploitable bugs, and SpaceXAI open sourced its coding agent and says the Grok weights are next. Then there is the ask: Nvidia's announcement warns policymakers that blanket restrictions on open frontier systems would concentrate power and vulnerability in a few closed providers. Treasury Secretary Scott Bessent has spent the month weighing exactly those restrictions. Karp was also asked about Sam Altman declaring on Saturday that we are now in the singularity, and whether that scared him. He compared the technology to uranium, said what matters is WHO controls the processing, and pointed out that Silicon Valley keeps presenting all of this as though there is none. And funnily enough he also said: "We are going to end up having to regulate AI, no doubt." Although his own alliance spent Monday telling Washington the opposite. 37 companies are about to argue that open models keep America safe. Three companies will argue that open models are how America loses. What do you think?
2:54

37 of the biggest technology companies on Earth just teamed up against OpenAI, Anthropic and Google. Nvidia launched the Open Secure AI Alliance on Monday. Microsoft, IBM, Dell, Cisco, CrowdStrike, Palo Alto Networks, Red Hat, Salesforce, ServiceNow, Snowflake, Databricks, SpaceXAI and Palantir all signed on as founding members. But the three American companies that build the world's most capable closed models are missing from the list. Palantir's CEO Alex Karp was asked whether it was a direct attack on Anthropic, his answer: "I am not anti-Anthropic or any closed model. I am pro my customers, and they are angry." Karp's customers are angry because they believe they are being token maxed, which means they pay a rising bill while the value of their own business migrates to the lab collecting the fee. He said the insights that make a business valuable end up modeled by a third party and sold to their competitors, and that this is happening all over. Now read the membership list again: - Dell and HPE sell the servers - CrowdStrike and Palo Alto Networks sell the defense layer - Snowflake and Databricks sell the data stack - Red Hat and IBM sell the plumbing - Palantir sells the application layer - Nvidia sells the chips sitting under every one of them Every company on that list gets paid when AI runs on infrastructure the customer owns. The three companies missing from it get paid when it does not. The alliance didn't even have to invent a reason to exist - they had one from 11 days earlier: Hugging Face disclosed on July 16 that an autonomous agent had been loose inside its production systems. Five days later OpenAI said the agent was its own, running a hacking benchmark with the cyber refusals turned down. Hugging Face first sent its attack logs to frontier models (Fable 5) behind commercial APIs. In the company's own words, "this did not work." The analysis meant submitting real attack commands and exploit payloads, and the providers' guardrails blocked the requests, because a guardrail cannot tell an incident responder from an attacker. So Hugging Face ran GLM 5.2 on its own hardware instead. That model is open weight and comes out of Z ai in Beijing. It reconstructed more than 17,000 recorded events. The break-in came from an American lab's model. The models that refused to help with the cleanup were American too. But the one that did the work came from Beijing. This is basically what Nvidia built the alliance around. The members are contributing weapons. Nvidia is releasing open model weights, Microsoft is handing over a scanning system that hunts exploitable bugs, and SpaceXAI open sourced its coding agent and says the Grok weights are next. Then there is the ask: Nvidia's announcement warns policymakers that blanket restrictions on open frontier systems would concentrate power and vulnerability in a few closed providers. Treasury Secretary Scott Bessent has spent the month weighing exactly those restrictions. Karp was also asked about Sam Altman declaring on Saturday that we are now in the singularity, and whether that scared him. He compared the technology to uranium, said what matters is WHO controls the processing, and pointed out that Silicon Valley keeps presenting all of this as though there is none. And funnily enough he also said: "We are going to end up having to regulate AI, no doubt." Although his own alliance spent Monday telling Washington the opposite. 37 companies are about to argue that open models keep America safe. Three companies will argue that open models are how America loses. What do you think?

Ricardo

68,966 просмотров • 1 месяц назад