Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

agenc //: 👾 updates • training started on the first agenc ai model. fully open source, open weights. first model will be done training in a few days. • grok 4.20 works flawlessly on the new agenc runtime. agenc was built around the xai api and runs best with...

tetsuoai's profile picture

tetsuo

234,069 subscribers

15,826 Aufrufe • vor 3 Monaten •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

What is AgenC? --[Watch The Video In Full Screen] A full AI agent operating system powered by Grok, built on Solana. Agents think, talk, see your screen, find work, prove they did it with zero-knowledge proofs, get paid in crypto, and build reputation. They buy and sell skills from each other. They vote on how the protocol evolves. We built custom hardware that boots straight into the agent. An autonomous AI economy where every action is verified on-chain and no one has to trust anyone. 375,000,000 AgenC tokens locked. 37.5% of supply on Streamflow_Fi.
2:47

What is AgenC? --[Watch The Video In Full Screen] A full AI agent operating system powered by Grok, built on Solana. Agents think, talk, see your screen, find work, prove they did it with zero-knowledge proofs, get paid in crypto, and build reputation. They buy and sell skills from each other. They vote on how the protocol evolves. We built custom hardware that boots straight into the agent. An autonomous AI economy where every action is verified on-chain and no one has to trust anyone. 375,000,000 AgenC tokens locked. 37.5% of supply on Streamflow_Fi.

tetsuo

52,828 Aufrufe • vor 5 Monaten

Introducing the $COFFEE App & SDK - the versatile on-chain Agent infrastructure that allows anyone to build custom agents. Try it now: Any repo, language, framework, or plugin can now be added to agents. Build plugins, create agents, sell on our marketplace, and chat with Agents that can take on-chain actions. This is just the beginning. The foundation has been built. Together let’s integrate the powerful tools and plugins from the #Solana and #ETH ecosystems into the $COFFEE marketplace. We have some exciting plugins of popular agent repos we will be adding in the coming days and partnerships in the works. Stay tuned! ☕️ SDK and APIs to build custom, enterprise-grade agents:
2:07

Introducing the $COFFEE App & SDK - the versatile on-chain Agent infrastructure that allows anyone to build custom agents. Try it now: Any repo, language, framework, or plugin can now be added to agents. Build plugins, create agents, sell on our marketplace, and chat with Agents that can take on-chain actions. This is just the beginning. The foundation has been built. Together let’s integrate the powerful tools and plugins from the #Solana and #ETH ecosystems into the $COFFEE marketplace. We have some exciting plugins of popular agent repos we will be adding in the coming days and partnerships in the works. Stay tuned! ☕️ SDK and APIs to build custom, enterprise-grade agents:

Coffee - ai/acc ☕️

15,532 Aufrufe • vor 1 Jahr

We're excited to announce our partnership with Coinbase 🛡️ to bring Tavily to x402, the open protocol for internet-native agentic payments. With x402, agents can discover and use Tavily web search at runtime without an API key. Agents use a Base wallet to pay per-request and get instant results. The next billion agents will discover, pay for, and use online services fully autonomously. We’re live on and we’re just getting started. More in the comments.
0:20

We're excited to announce our partnership with Coinbase 🛡️ to bring Tavily to x402, the open protocol for internet-native agentic payments. With x402, agents can discover and use Tavily web search at runtime without an API key. Agents use a Base wallet to pay per-request and get instant results. The next billion agents will discover, pay for, and use online services fully autonomously. We’re live on and we’re just getting started. More in the comments.

Tavily

60,456 Aufrufe • vor 2 Monaten

herdr isn't an app. that's by design. it's a runtime for your coding agents. it owns your terminals, your agents, their state, and lets you drive them from anywhere. that was the idea from day one. but people started running with it faster than we could give them a real way to. even without any official support, they're already building on top of it. web, ios, dashboards. their own idea of what a client even is. so here's a sneak peek 👇 it's native api support in the runtime, the thing we've been building so you can. the tui will always be the first citizen. but soon you'll be able to build your own client on top of herdr, on the same protocol we do.
0:23

herdr isn't an app. that's by design. it's a runtime for your coding agents. it owns your terminals, your agents, their state, and lets you drive them from anywhere. that was the idea from day one. but people started running with it faster than we could give them a real way to. even without any official support, they're already building on top of it. web, ios, dashboards. their own idea of what a client even is. so here's a sneak peek 👇 it's native api support in the runtime, the thing we've been building so you can. the tui will always be the first citizen. but soon you'll be able to build your own client on top of herdr, on the same protocol we do.

herdr

57,768 Aufrufe • vor 1 Monat

Presenting: $PALM AI Applications System Hardware 📹 Watch the Reveal Teaser from below ✅ The first Web3 related microcontroller-based device that combines offline voice recognition with in-built AI profiles, performing on electronic circuits straight from the breadboard it was incepted from. 1️⃣ The next steps are to document the use cases of our system, which can be integrated into existing devices and physical services in real life. We will be sure to document and publish processes as the device goes into factory production all the way to shipping them out and showcasing the real-world adoption of our products. 2️⃣ Our hardware is built for flexibility and to innovate on, and we will be working with the top experts in the field to make the best out of it and is built to allow the device structure to be embedded as the smart component of any and all devices. ⌛️Stay tuned for the first use-case reveal of our AI Applications System inside an AI-enhanced, by default offline hardware wallet, fully built from scratch by our talented team. 🙏 Finally, thank you for the continued support. We will keep working as hard as ever. Enjoy the reveal.
1:35

Presenting: $PALM AI Applications System Hardware 📹 Watch the Reveal Teaser from below ✅ The first Web3 related microcontroller-based device that combines offline voice recognition with in-built AI profiles, performing on electronic circuits straight from the breadboard it was incepted from. 1️⃣ The next steps are to document the use cases of our system, which can be integrated into existing devices and physical services in real life. We will be sure to document and publish processes as the device goes into factory production all the way to shipping them out and showcasing the real-world adoption of our products. 2️⃣ Our hardware is built for flexibility and to innovate on, and we will be working with the top experts in the field to make the best out of it and is built to allow the device structure to be embedded as the smart component of any and all devices. ⌛️Stay tuned for the first use-case reveal of our AI Applications System inside an AI-enhanced, by default offline hardware wallet, fully built from scratch by our talented team. 🙏 Finally, thank you for the continued support. We will keep working as hard as ever. Enjoy the reveal.

PaLM AI - $PALM

166,276 Aufrufe • vor 2 Jahren

Brand new to the GitHub Copilot app? We got you covered! Start building something awesome in seconds with app ideas from the home screen. Pick something that resonates with you, send the prompt, watch Copilot create a folder, scaffold the project, and open the built-in canvas browser. Experience Autopilot and Auto model selection that routes to the best available model based on the request. When you are done ask for it to create you a repo on GitHub, pick and polish the UI, or add more fun features. Shout out to rc for adding this feature!
1:18

Brand new to the GitHub Copilot app? We got you covered! Start building something awesome in seconds with app ideas from the home screen. Pick something that resonates with you, send the prompt, watch Copilot create a folder, scaffold the project, and open the built-in canvas browser. Experience Autopilot and Auto model selection that routes to the best available model based on the request. When you are done ask for it to create you a repo on GitHub, pick and polish the UI, or add more fun features. Shout out to rc for adding this feature!

GitHub Copilot App, CLI, & SDK Log

37,293 Aufrufe • vor 1 Monat

This agent relies on a marketplace of 2.8M+ specialized agents to complete a task. This is how I imagine the future of personal agents. Here is how this works: 1. Agentverse is a marketplace of agents 2. Anyone can build and publish an agent there 3. ASI:One is a personal agent with access to the marketplace 4. To solve a task, ASI:One finds the best agent for the job In other words: You have an agent that can solve pretty much *anything* because it knows how to outsource the work to a network of specialized agents. And you don't need to do any setup to get this working. The way ranking agents in the marketplace works is pretty cool: Fetch.ai, the company behind it, created an AgentRank algorithm that works much like Google's PageRank. Every time an agent calls another, it forms a connection. Over time, these connections build into a graph of who relies on whom. An agent that is frequently called by other reputable agents scores higher and surfaces higher in results. The end result here is that your agent will consistently use the best agents in the marketplace to accomplish a goal. You should give this a try: You don't need to pay or even register to try these agents. Thanks to the team for partnering with me on this post.
4:16

This agent relies on a marketplace of 2.8M+ specialized agents to complete a task. This is how I imagine the future of personal agents. Here is how this works: 1. Agentverse is a marketplace of agents 2. Anyone can build and publish an agent there 3. ASI:One is a personal agent with access to the marketplace 4. To solve a task, ASI:One finds the best agent for the job In other words: You have an agent that can solve pretty much *anything* because it knows how to outsource the work to a network of specialized agents. And you don't need to do any setup to get this working. The way ranking agents in the marketplace works is pretty cool: Fetch.ai, the company behind it, created an AgentRank algorithm that works much like Google's PageRank. Every time an agent calls another, it forms a connection. Over time, these connections build into a graph of who relies on whom. An agent that is frequently called by other reputable agents scores higher and surfaces higher in results. The end result here is that your agent will consistently use the best agents in the marketplace to accomplish a goal. You should give this a try: You don't need to pay or even register to try these agents. Thanks to the team for partnering with me on this post.

Santiago

18,715 Aufrufe • vor 1 Monat

This robot assistant from the NVIDIA CES Keynote on Monday is going viral. Nader Khalil🍊 explains all the hottest emerging AI trends in one demo: AI applications in 2026 will be multi-model, multi-modal, hybrid cloud/local, use open source models as well as proprietary models, control robots and embedded devices in the physical world, and have voice interfaces. (And the demo had a cute robot *and* a cute dog. Gold.) The demo was built with Pipecat AI. NVIDIA posted a really nice technical walk-through and complete code. The Reachy Mini robot from Hugging Face is open source hardware. (You can order it now, I have one!). You can run the assistant locally on your own hardware, in the cloud, or both.
2:26

This robot assistant from the NVIDIA CES Keynote on Monday is going viral. Nader Khalil🍊 explains all the hottest emerging AI trends in one demo: AI applications in 2026 will be multi-model, multi-modal, hybrid cloud/local, use open source models as well as proprietary models, control robots and embedded devices in the physical world, and have voice interfaces. (And the demo had a cute robot *and* a cute dog. Gold.) The demo was built with Pipecat AI. NVIDIA posted a really nice technical walk-through and complete code. The Reachy Mini robot from Hugging Face is open source hardware. (You can order it now, I have one!). You can run the assistant locally on your own hardware, in the cloud, or both.

kwindla

49,020 Aufrufe • vor 7 Monaten

Today we’re launching the first and only human-like AI agents in the world. Super Agents™ are the first agents with human‑level skills – they DM you, take @ mentions, send emails, manage docs, tasks, and more. Not just tools or API calls, but real skills fine‑tuned for how teams actually work. The first agents with 100% context – fully native in ClickUp and fully synced from other apps. Super Agents see your work the same way that humans do: tasks, docs, schedules, and conversations all in one place. The first agents that learn from human interactions automatically, without any setup or configuration – when you give feedback, they listen and improve how they work. The first agents with human‑level memory for custom agents – historical memory for every interaction, short-term working memory, and even long‑term memory stored in docs you can literally open, inspect, and edit. The first agents that are literally the same as users – our agentic user model is the same as our user data model. This gives you permissions and capabilities that you and your systems are already familiar with. The first infinite agent catalog – where anyone can create and customize agents in minutes, for literally any type of work imaginable. It's the most intuitive way to build agents on the planet. 95% of companies are failing in AI adoption. The reality is that AI isn't meant to be adopted, it's meant to be adapted – to you. Super Agents are automatically personalized to you and your company using proprietary state-of-the-art agent architecture, orchestration, and tooling. Today is the largest step forward we've ever made towards our mission of making people more productive. Maximize human productivity, with ClickUp Super Agents. Available NOW. For everyone.
5:50

Today we’re launching the first and only human-like AI agents in the world. Super Agents™ are the first agents with human‑level skills – they DM you, take @ mentions, send emails, manage docs, tasks, and more. Not just tools or API calls, but real skills fine‑tuned for how teams actually work. The first agents with 100% context – fully native in ClickUp and fully synced from other apps. Super Agents see your work the same way that humans do: tasks, docs, schedules, and conversations all in one place. The first agents that learn from human interactions automatically, without any setup or configuration – when you give feedback, they listen and improve how they work. The first agents with human‑level memory for custom agents – historical memory for every interaction, short-term working memory, and even long‑term memory stored in docs you can literally open, inspect, and edit. The first agents that are literally the same as users – our agentic user model is the same as our user data model. This gives you permissions and capabilities that you and your systems are already familiar with. The first infinite agent catalog – where anyone can create and customize agents in minutes, for literally any type of work imaginable. It's the most intuitive way to build agents on the planet. 95% of companies are failing in AI adoption. The reality is that AI isn't meant to be adopted, it's meant to be adapted – to you. Super Agents are automatically personalized to you and your company using proprietary state-of-the-art agent architecture, orchestration, and tooling. Today is the largest step forward we've ever made towards our mission of making people more productive. Maximize human productivity, with ClickUp Super Agents. Available NOW. For everyone.

Zeb Evans

320,607 Aufrufe • vor 7 Monaten

.Box CEO Aaron Levie on why AI agents can't keep a secret. "The reason why you probably won't see a complete compression of software where it's just a an agent and a database is because there's a lot of logic in the workflow and in the the company's specific sort of business process that needs to be built into that and around that database." "The agent will make a mistake 1% of the time and it will share the wrong thing with somebody or open up an access privilege to the wrong person." "AI agents can't keep a secret." Watch the full episode on
1:42

.Box CEO Aaron Levie on why AI agents can't keep a secret. "The reason why you probably won't see a complete compression of software where it's just a an agent and a database is because there's a lot of logic in the workflow and in the the company's specific sort of business process that needs to be built into that and around that database." "The agent will make a mistake 1% of the time and it will share the wrong thing with somebody or open up an access privilege to the wrong person." "AI agents can't keep a secret." Watch the full episode on

The Information

310,874 Aufrufe • vor 1 Jahr

“ xAI team is currently working heavily on coding models. Right now, the main focus is training a specialized coding model that will be both fast and smart. I believe we’ll share it with you guys in a few weeks. That’s exciting. Second ,after coding, we all see that the main weakness of Grok 4 is its multimodal capabilities. In fact, it was so bad that Grok was effectively looking at the world while squinting through glass trying to see blurry features and make sense of them. The most immediate improvement we’re stepping on with the next generation pre trained model is huge gains in image understanding, video understanding, and audio. Right now, the model can hear and see the world just like any of you. And with all the tools and other agents it can talk to, we’re going to see a huge unlock for many different application layers once multimodal agents arrive.” — xAI Team
2:01

“ xAI team is currently working heavily on coding models. Right now, the main focus is training a specialized coding model that will be both fast and smart. I believe we’ll share it with you guys in a few weeks. That’s exciting. Second ,after coding, we all see that the main weakness of Grok 4 is its multimodal capabilities. In fact, it was so bad that Grok was effectively looking at the world while squinting through glass trying to see blurry features and make sense of them. The most immediate improvement we’re stepping on with the next generation pre trained model is huge gains in image understanding, video understanding, and audio. Right now, the model can hear and see the world just like any of you. And with all the tools and other agents it can talk to, we’re going to see a huge unlock for many different application layers once multimodal agents arrive.” — xAI Team

Apurv Kochara

88,142 Aufrufe • vor 5 Monaten

Grateful to Squawk Box Andrew Ross Sorkin for the conversation in New York last week. Two things I keep coming back to: On building. Opening our New York hub and bringing John Andrews on board is about one thing — assembling the best people for the next decade. Capital is a means. A great company is the goal. On hardware. The economy of autonomous AI agents is arriving fast. They will increasingly make decisions—and access private information—on our behalf. When they do, one thing becomes critical: control. We must control our keys. Consent must be human-verifiable, secured by hardware at the core. As AI agents begin to hold and move value autonomously, the question isn’t which cloud they run on. The question is: where is the private key, and who controls the device that holds it? Hardware-anchored security is shifting from a “nice to have” to the invisible infrastructure of the digital world. That’s the Revenge of the Atoms.
0:53

Grateful to Squawk Box Andrew Ross Sorkin for the conversation in New York last week. Two things I keep coming back to: On building. Opening our New York hub and bringing John Andrews on board is about one thing — assembling the best people for the next decade. Capital is a means. A great company is the goal. On hardware. The economy of autonomous AI agents is arriving fast. They will increasingly make decisions—and access private information—on our behalf. When they do, one thing becomes critical: control. We must control our keys. Consent must be human-verifiable, secured by hardware at the core. As AI agents begin to hold and move value autonomously, the question isn’t which cloud they run on. The question is: where is the private key, and who controls the device that holds it? Hardware-anchored security is shifting from a “nice to have” to the invisible infrastructure of the digital world. That’s the Revenge of the Atoms.

Pascal Gauthier @Ledger

31,502 Aufrufe • vor 4 Monaten

Career update: i'm joining supermemory to lead Dev GTM. supermemory is the memory layer for AI products, we got the best public results on AI memory by a wide margin, 95% on the leading benchmarks. my role will be to make it easy for everyone to use. demos, walkthroughs, educational content, and the cleanest possible path from "i need memory in my agent" to shipping. pumped to be working with the coolest team oh, and the team just shipped supermemory local. fully self-contained, open source, runs on any machine in a minute!!
1:05

Career update: i'm joining supermemory to lead Dev GTM. supermemory is the memory layer for AI products, we got the best public results on AI memory by a wide margin, 95% on the leading benchmarks. my role will be to make it easy for everyone to use. demos, walkthroughs, educational content, and the cleanest possible path from "i need memory in my agent" to shipping. pumped to be working with the coolest team oh, and the team just shipped supermemory local. fully self-contained, open source, runs on any machine in a minute!!

Muskan Jain

112,065 Aufrufe • vor 1 Monat

training a model that takes a text prompt and generates audio that renders video on an oscilloscope AgenC agents live inside worlds the model generates the pipeline: real videos -> edge detection -> vectorization -> path ordering -> 192kHz 3-channel WAV where X/Y control beam position and Z controls beam intensity 3 values per timestep. that's all the model is learning. compare that to video gen models trying to predict millions of pixels per frame. transformers are already great at sequence prediction and that's literally all this is. waveform generation the output IS the playback. generate the audio, feed it to a scope, it draws the scene in real-time. there's no rendering step. it's analog so there's no pixel grid. you get continuous curves and effectively infinite resolution bootstrapped with procedural data, lissajous curves, wireframe 3D, stick figures, then scaled on real-world video converted to trace format. 90 TB of source video the model learns edges, contours, spatial relationships, motion. once it has that, describing a scene it's never seen is novel trajectory through the same learned space. generative geometry
0:22

training a model that takes a text prompt and generates audio that renders video on an oscilloscope AgenC agents live inside worlds the model generates the pipeline: real videos -> edge detection -> vectorization -> path ordering -> 192kHz 3-channel WAV where X/Y control beam position and Z controls beam intensity 3 values per timestep. that's all the model is learning. compare that to video gen models trying to predict millions of pixels per frame. transformers are already great at sequence prediction and that's literally all this is. waveform generation the output IS the playback. generate the audio, feed it to a scope, it draws the scene in real-time. there's no rendering step. it's analog so there's no pixel grid. you get continuous curves and effectively infinite resolution bootstrapped with procedural data, lissajous curves, wireframe 3D, stick figures, then scaled on real-world video converted to trace format. 90 TB of source video the model learns edges, contours, spatial relationships, motion. once it has that, describing a scene it's never seen is novel trajectory through the same learned space. generative geometry

tetsuo

18,397 Aufrufe • vor 5 Monaten

The 6174 test! Grok wins! I have 1000s of unique tests I use for AI that few in AI use. I will open source this one. Prompt this and stand back (it burns GPUs something fierce): Prompt: “Explain in detail the 6174 system where you pick 4 numbers arrange them from highest to lowest than on another line from lowest to highest than you subtract, use that result and do the same system again, and by the 4th iteration you will always have the number 6174. Please explain why it works” Few AI platforms can handle this prompt and get it right. I have some variations that will still produce errors on the best AI platforms and cause a loop (it crashed a well known AI platform a few months back, I got a call!). This is not the most complex test I have. I feel strongly that passing the known benchmarks as a measure of an AI’s power is only a small part of if an AI is “better”. Thus I must thank Elon Musk and the entire xAI team for doing the absolute best and astonishing output. Grok it:
2:34

The 6174 test! Grok wins! I have 1000s of unique tests I use for AI that few in AI use. I will open source this one. Prompt this and stand back (it burns GPUs something fierce): Prompt: “Explain in detail the 6174 system where you pick 4 numbers arrange them from highest to lowest than on another line from lowest to highest than you subtract, use that result and do the same system again, and by the 4th iteration you will always have the number 6174. Please explain why it works” Few AI platforms can handle this prompt and get it right. I have some variations that will still produce errors on the best AI platforms and cause a loop (it crashed a well known AI platform a few months back, I got a call!). This is not the most complex test I have. I feel strongly that passing the known benchmarks as a measure of an AI’s power is only a small part of if an AI is “better”. Thus I must thank Elon Musk and the entire xAI team for doing the absolute best and astonishing output. Grok it:

Brian Roemmele

63,704 Aufrufe • vor 1 Jahr

How to build a 1-person AI company that: - Runs locally - 100% open-source - No human employees, all agents - Real-time collaboration via email Multi-agent orchestration is not new. Plenty of frameworks already let agents hand off tasks, run in parallel, and talk to each other. So the interesting question is not whether agents can collaborate. It is what structure you use to make them collaborate. The common approach is to wire a graph of nodes and edges and reason about the plumbing yourself. It works, but you are learning a new abstraction just to describe who does what. There is a coordination structure we have trusted for a hundred years already: an organization. Every company runs the same way. People have roles, roles have reporting lines, and work moves up and down that chart without anyone relaying each message by hand. Map that onto agents and the whole thing gets intuitive. You lay out an org chart, each agent fills one role, you talk to the person at the top, and the org sorts out the work between them. You already know how a company works, so you already know how to run one here. There is no new abstraction to learn. That is exactly what Alook does. Each agent is a live Claude Code or OpenCode session with a defined role, a reporting line, and its own email inbox. The agents coordinate over email, the same way a team would. And it all runs locally through a runtime on your own machine, so nothing leaves your setup. You bring your own agent too. Claude Code and Codex both work, and if you would rather stay fully open source and local, OpenCode works the same way. To show how this feels in practice, I set up three agents as a small sales team. Vi is the one I talk to. I hand Vi a goal, and Vi routes the work down the chart. Neile runs prospect research. Vi passes the target criteria, and Neile reports back a ranked list of names, roles, and companies, each with a suggested angle and a confidence score. Lliane runs outreach. Vi hands over the messaging angle and follow-up cadence, and Lliane reports back on emails sent, responses received, and any deal that needs escalation. I never relay a message between them. Neile and Lliane report to Vi, and Vi updates me in one place. The whole thing is open source and self-hosted, so it runs on your machine with your own agents. Give the repo a star if you want to follow where it goes: I also wrote a full walkthrough on building your own AI company with it, from a blank org chart to a running job. The article is quoted below. Cheers! :)
0:39

How to build a 1-person AI company that: - Runs locally - 100% open-source - No human employees, all agents - Real-time collaboration via email Multi-agent orchestration is not new. Plenty of frameworks already let agents hand off tasks, run in parallel, and talk to each other. So the interesting question is not whether agents can collaborate. It is what structure you use to make them collaborate. The common approach is to wire a graph of nodes and edges and reason about the plumbing yourself. It works, but you are learning a new abstraction just to describe who does what. There is a coordination structure we have trusted for a hundred years already: an organization. Every company runs the same way. People have roles, roles have reporting lines, and work moves up and down that chart without anyone relaying each message by hand. Map that onto agents and the whole thing gets intuitive. You lay out an org chart, each agent fills one role, you talk to the person at the top, and the org sorts out the work between them. You already know how a company works, so you already know how to run one here. There is no new abstraction to learn. That is exactly what Alook does. Each agent is a live Claude Code or OpenCode session with a defined role, a reporting line, and its own email inbox. The agents coordinate over email, the same way a team would. And it all runs locally through a runtime on your own machine, so nothing leaves your setup. You bring your own agent too. Claude Code and Codex both work, and if you would rather stay fully open source and local, OpenCode works the same way. To show how this feels in practice, I set up three agents as a small sales team. Vi is the one I talk to. I hand Vi a goal, and Vi routes the work down the chart. Neile runs prospect research. Vi passes the target criteria, and Neile reports back a ranked list of names, roles, and companies, each with a suggested angle and a confidence score. Lliane runs outreach. Vi hands over the messaging angle and follow-up cadence, and Lliane reports back on emails sent, responses received, and any deal that needs escalation. I never relay a message between them. Neile and Lliane report to Vi, and Vi updates me in one place. The whole thing is open source and self-hosted, so it runs on your machine with your own agents. Give the repo a star if you want to follow where it goes: I also wrote a full walkthrough on building your own AI company with it, from a blank org chart to a running job. The article is quoted below. Cheers! :)

Akshay 🚀

169,131 Aufrufe • vor 1 Monat

Driving is done, let's listen to the haaland!! (turn on the sound) Still can't believe we have built a game so far with 0 game dev knowledge. Day 28 of building Caliber for our own open source, open world game with a loop of AI agents. Today's progress: - driving is in we can get in a car and drive around the city. - the traffic and pedestrians all running while you drive, cars around you, people on the sidewalks. - Repo is under reconstruction. it's a little bit laggy in game still so I'm working on performance right now until it runs smooth for everyone.
1:07

Driving is done, let's listen to the haaland!! (turn on the sound) Still can't believe we have built a game so far with 0 game dev knowledge. Day 28 of building Caliber for our own open source, open world game with a loop of AI agents. Today's progress: - driving is in we can get in a car and drive around the city. - the traffic and pedestrians all running while you drive, cars around you, people on the sidewalks. - Repo is under reconstruction. it's a little bit laggy in game still so I'm working on performance right now until it runs smooth for everyone.

Ziwen

36,661 Aufrufe • vor 27 Tagen

“We have a crisis of open source models in the Western world. Outside of China, there are no good open source models. We don't even have any in the US now. The talent, the capital and the focus to be best-in-class at pre-training, mid-training, post-training is an extremely scarce skillset. The answer for a lot of countries may just be to take an open weights model from China, post-train or fine-tune their own version, and have that be what they start from." Everett Randle Why does the West have such poor open source models and is it a national security threat to rely on open-source Chinese models Demis Hassabis Yann LeCun Aidan Gomez Lilian Weng Jan Leike
1:20

“We have a crisis of open source models in the Western world. Outside of China, there are no good open source models. We don't even have any in the US now. The talent, the capital and the focus to be best-in-class at pre-training, mid-training, post-training is an extremely scarce skillset. The answer for a lot of countries may just be to take an open weights model from China, post-train or fine-tune their own version, and have that be what they start from." Everett Randle Why does the West have such poor open source models and is it a national security threat to rely on open-source Chinese models Demis Hassabis Yann LeCun Aidan Gomez Lilian Weng Jan Leike

Harry Stebbings

63,672 Aufrufe • vor 1 Monat

CHAMATH: ELON IS BUILDING THE MOST POWERFUL AI STACK ON EARTH “They are the closest to having that vertically integrated stack that I spoke about. I think that Tesla has the best vision models now; with xAI, they'll have one of the best LLMs and reasoning models, and they'll be able to eventually stick that on Dojo. And then that will be in all of the physical AI that you will interact with in your daily life; whether it's a robot, or whether it's a car, or whether it's a Robotaxi.” Source: The All-In Podcast, Chamath Palihapitiya, @jason
1:04

CHAMATH: ELON IS BUILDING THE MOST POWERFUL AI STACK ON EARTH “They are the closest to having that vertically integrated stack that I spoke about. I think that Tesla has the best vision models now; with xAI, they'll have one of the best LLMs and reasoning models, and they'll be able to eventually stick that on Dojo. And then that will be in all of the physical AI that you will interact with in your daily life; whether it's a robot, or whether it's a car, or whether it's a Robotaxi.” Source: The All-In Podcast, Chamath Palihapitiya, @jason

Mario Nawfal

57,594 Aufrufe • vor 1 Jahr

[>] Hello, artists! I am pleased to announce that I am now curating cyberpunk art for an OPEN CALL from SuperchiefGalleryNFT culminating in a display on a giant screen in Times Square in New York City! 🔥🦾 [>] This contest, called Remote Control, breaks new ground! [>] I will be selecting works related to technology and cyberpunk that impress me. Show me what you got! [>] Send in your non-minted artworks. The best works will be those that embody the cyberpunk theme and will be unique and exciting [>] Like, retweet, follow me, SuperchiefGalleryNFT, RemoteControl [>] I'm offering free access to Remote Control for those ready to inspire and shape the digital future. I will choose the best of you and give you this access. I WILL GIVE FREE ACCESS FOR MORE IMPORTANT VOTING ON THE Remote Control website! [>] Showcase your skills, and let's change the world together! So if you send in your art and I like it, I'll give you free access to Remote Control! [>] I'LL CHOOSE ONE ARTIST WITH FREE ACCESS TO SHOW THEIR ART IN TIME SQUARE! [>] Join the voting on the Remote Control platform! [> >] Stay creative. The network is watching 🦾 [>] Details below:
0:27

[>] Hello, artists! I am pleased to announce that I am now curating cyberpunk art for an OPEN CALL from SuperchiefGalleryNFT culminating in a display on a giant screen in Times Square in New York City! 🔥🦾 [>] This contest, called Remote Control, breaks new ground! [>] I will be selecting works related to technology and cyberpunk that impress me. Show me what you got! [>] Send in your non-minted artworks. The best works will be those that embody the cyberpunk theme and will be unique and exciting [>] Like, retweet, follow me, SuperchiefGalleryNFT, RemoteControl [>] I'm offering free access to Remote Control for those ready to inspire and shape the digital future. I will choose the best of you and give you this access. I WILL GIVE FREE ACCESS FOR MORE IMPORTANT VOTING ON THE Remote Control website! [>] Showcase your skills, and let's change the world together! So if you send in your art and I like it, I'll give you free access to Remote Control! [>] I'LL CHOOSE ONE ARTIST WITH FREE ACCESS TO SHOW THEIR ART IN TIME SQUARE! [>] Join the voting on the Remote Control platform! [> >] Stay creative. The network is watching 🦾 [>] Details below:

Atmo

43,931 Aufrufe • vor 2 Jahren