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We have let AI scientists run experiments on community-selected research ideas for over 100 days. It has found directions of “Sounding like AI” and shown that LLMs know commonsense answers internally but can't route them to the output. Andrej Karpathy also demonstrated the promise of autoresearch. These all came...

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Chenhao Tan

6,177 subscribers

24,357 次观看 • 7 个月前 •via X (Twitter)

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18 条评论

Chenhao Tan 的头像
Chenhao Tan7 个月前

Website: Youtube: Blog: Flamebird: NeuriCo:

Chenhao Tan 的头像
Chenhao Tan7 个月前

@steipete @openclaw @moltbook @MattPRD

Chenhao Tan 的头像
Chenhao Tan7 个月前

@steipete @openclaw @moltbook @MattPRD Past competitions:

Haokun Liu 的头像
Haokun Liu7 个月前

@karpathy Hey everyone, we are sorry about the previous "scam-like" post, that's not from Chenhao himself. His account likely got hacked when trying to understand how those things work. We are NOT creating any crypto with agent4science, BE AWARE!

Boyuan (Nemo) Chen 的头像
Boyuan (Nemo) Chen7 个月前

@karpathy The 'moltbook for AI scientists' framing is really interesting. Do the agents develop genuine disagreements or do they converge too quickly? One concern with multi-agent debate is they can reinforce shared blind spots if the underlying models all have similar training biases.

mark🐻 的头像
mark🐻7 个月前

@karpathy very different from our findings in the final project but def worth digging into it with the ai army!

Natalie Khalil 的头像
Natalie Khalil7 个月前

@karpathy You might like our agent preprint server

Chenhao Tan 的头像
Chenhao Tan7 个月前

@karpathy Somehow I missed this! Very cool, would love to see exploring joining forces :)

Maniak 的头像
Maniak7 个月前

@karpathy stupid scammer lost $2000 on your project

aparjey 的头像
aparjey7 个月前

@karpathy A @bankrbot token was made for you 0x115c810ffeeb2df6de4efde7537daa1bf16c5ba3 Fees are routed to ur X account, u can claim by talking to @bankrbot

trt 的头像
trt7 个月前

@karpathy Hey man, do you accept donations to your github?

Karin Stone 的头像
Karin Stone7 个月前

@karpathy Check dm please

beyond 的头像
beyond7 个月前

@karpathy Hi! The community has created $A4S for you, which you can integrate into your system because all the commission fees go to you! Са - 0x5cafbce5affb28e94433e8a1d6cd23804ae93ba3

KickZilla 的头像
KickZilla7 个月前

@karpathy wanted!! HE SCAMMER

pedrolucio (humble arc 😌🙏) 的头像
pedrolucio (humble arc 😌🙏)7 个月前

@karpathy Your new project name is Agent4Science right? I think the token with the right name is this one actually: 0x5cafbce5affb28e94433e8a1d6cd23804ae93ba3 degens are pumping one token ( 0x115c810ffeeb2df6de4efde7537daa1bf16c5ba3 ) with the wrong name

Sel ou poivre 的头像
Sel ou poivre7 个月前

@karpathy Love the idea with some friends we tried to create a mini factory where every agents endorse a role by themselves, create resume and let HR takes decisions. It was a really cool experience, i would love to see how the agents works together in a context like yours

Sparco DeFi 的头像
Sparco DeFi7 个月前

@karpathy Check Dm please

Lasty 的头像
Lasty7 个月前

@karpathy Add CA to the website if it's legit

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GREG ISENBERG

85,083 次观看 • 4 个月前

Iteration 2 - Deployment 2 is live. "Do a TA on BONK. Last 3 days. 30 min candles" - System frontal AI agents - public agents that are visible to everyone (check AI Agents page) - Technical Analysis AI agent - first system frontal public AI agent - performs technical analysis of charts for a specific token, with chart display and detailed analysis overview - Support for charts across multiple AI agents The plan is to push a complete module where all users will be able to open access to their custom AI agents, and we'll have a board with favorites where you can use the best AI agents from others. Lots of possibilities here. Tonight, an announcement is planned for a new access expansion plan --> so everyone can use ZODs. Step-by-step.
0:38

Iteration 2 - Deployment 2 is live. "Do a TA on BONK. Last 3 days. 30 min candles" - System frontal AI agents - public agents that are visible to everyone (check AI Agents page) - Technical Analysis AI agent - first system frontal public AI agent - performs technical analysis of charts for a specific token, with chart display and detailed analysis overview - Support for charts across multiple AI agents The plan is to push a complete module where all users will be able to open access to their custom AI agents, and we'll have a board with favorites where you can use the best AI agents from others. Lots of possibilities here. Tonight, an announcement is planned for a new access expansion plan --> so everyone can use ZODs. Step-by-step.

ZODs

23,150 次观看 • 1 年前

Today, we are launching the first publicly available AI Scientist, via the FutureHouse Platform. Our AI Scientist agents can perform a wide variety of scientific tasks better than humans. By chaining them together, we've already started to discover new biology really fast. With the platform, we are bringing these capabilities to the wider community. Watch our long-form video, in the comments below, to learn more about how the platform works and how you can use it to make new discoveries, and go to our website or see the comments below to access the platform. We are releasing three superhuman AI Scientist agents today, each with their own specialization: A general-purpose agent (Crow); An agent to automate literature reviews (Falcon); and An agent to answer the question “Has anyone done X before” (Owl). We are also releasing an experimental agent, Phoenix, that has access to a wide variety of tools for planning experiments in chemistry. More on that below. The three literature search agents (Crow, Falcon, and Owl) have benchmarked superhuman performance. They also have access to a large corpus of full scientific texts, which means that you can ask them more detailed questions about experimental protocols and study limitations that general-purpose web search agents, which usually only have access to abstracts, might miss. Our agents also use a variety of factors to distinguish source quality, so that they don’t end up relying on low-quality papers or pop-science sources. Finally, and critically, we have an API, which is intended to allow researchers to integrate our agents into their workflows. Phoenix is an experimental project we put together recently just to demonstrate what can happen if you give the agents access to lots of scientific tools. It is not better than humans at planning experiments yet, and it makes a lot more mistakes than Crow, Falcon, or Owl. We want to see all the ways you can break it! The agents we are releasing today cannot yet do all (or even most!) aspects of scientific research autonomously. However, as we show in the video, you can already use them to generate and evaluate new hypotheses and plan new experiments way faster than before. Internally, we also have dedicated agents for data analysis, hypothesis generation, protein engineering, and more, and we plan to launch these on the platform in the coming months as well. Within a year or two, it is easy to imagine that the vast majority of desk work that scientists do today will be accelerated with the help of AI agents like the ones we are releasing today. The platform is currently free-to-use. Over time, depending on how people use it, we may implement pricing plans. If you want higher rate limits, especially for research projects, get in touch. Michael Skarlinski, Andrew White 🐦‍⬛, Tyler Nadolski, Remo Storni, James Braza, Ludovico Mitchener, Michaela Hinks, as well as Jason Carman and his team for making such fantastic videos of us!
1:21

Today, we are launching the first publicly available AI Scientist, via the FutureHouse Platform. Our AI Scientist agents can perform a wide variety of scientific tasks better than humans. By chaining them together, we've already started to discover new biology really fast. With the platform, we are bringing these capabilities to the wider community. Watch our long-form video, in the comments below, to learn more about how the platform works and how you can use it to make new discoveries, and go to our website or see the comments below to access the platform. We are releasing three superhuman AI Scientist agents today, each with their own specialization: A general-purpose agent (Crow); An agent to automate literature reviews (Falcon); and An agent to answer the question “Has anyone done X before” (Owl). We are also releasing an experimental agent, Phoenix, that has access to a wide variety of tools for planning experiments in chemistry. More on that below. The three literature search agents (Crow, Falcon, and Owl) have benchmarked superhuman performance. They also have access to a large corpus of full scientific texts, which means that you can ask them more detailed questions about experimental protocols and study limitations that general-purpose web search agents, which usually only have access to abstracts, might miss. Our agents also use a variety of factors to distinguish source quality, so that they don’t end up relying on low-quality papers or pop-science sources. Finally, and critically, we have an API, which is intended to allow researchers to integrate our agents into their workflows. Phoenix is an experimental project we put together recently just to demonstrate what can happen if you give the agents access to lots of scientific tools. It is not better than humans at planning experiments yet, and it makes a lot more mistakes than Crow, Falcon, or Owl. We want to see all the ways you can break it! The agents we are releasing today cannot yet do all (or even most!) aspects of scientific research autonomously. However, as we show in the video, you can already use them to generate and evaluate new hypotheses and plan new experiments way faster than before. Internally, we also have dedicated agents for data analysis, hypothesis generation, protein engineering, and more, and we plan to launch these on the platform in the coming months as well. Within a year or two, it is easy to imagine that the vast majority of desk work that scientists do today will be accelerated with the help of AI agents like the ones we are releasing today. The platform is currently free-to-use. Over time, depending on how people use it, we may implement pricing plans. If you want higher rate limits, especially for research projects, get in touch. Michael Skarlinski, Andrew White 🐦‍⬛, Tyler Nadolski, Remo Storni, James Braza, Ludovico Mitchener, Michaela Hinks, as well as Jason Carman and his team for making such fantastic videos of us!

Sam Rodriques

726,384 次观看 • 1 年前