What surprised @polynoamial most about CICERO? Its ability to be a great ally. With built-in strategic reasoning & natural language, #CICERObyMetaAI can understand and help its allies achieve their goals.
AGENTS
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CICERO: Meta AI’s Language Model for Human Cooperation
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Meta AI’s @em_dinan explains what makes CICERO different from other language models. Its ability to cooperate with humans through natural language, Its grounding in specific intentions and plans for the game board.
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CICERO by Meta AI Ranked Top 10% in Online League Games
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…and ranked in the top 10% of participants who played more than one game in an online league. Learn more about CICERO’s win rate: https://
bit.ly/3HigP5J Do you think you could outplay #CICERObyMetaAI? -
CICERO by Meta AI Wins at Diplomacy Against Human Players
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It’s not just that #CICERObyMetaAI can play Diplomacy with humans, it’s also that it often WINS: In online games, CICERO achieved more than double the average score of human players…
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New Requests Chain: LLM Interaction with Web URLs
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@BruceHammer helped add a requests chain This hits a given URL, and then passes the parsed response as context to the LLM. Very useful interacting with the web! See the example of doing a google search here: https://
langchain.readthedocs.io/en/latest/exam
ples/chains/llm_requests.html
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LangChain 0.0.31 Release: New Agents, Bash, and Chains
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LangChain version 0.0.31 @johnvmcdonnell fixed how Agents handle a missing tool (so no longer errors) Bash utility and a LLMBashChain (
@coyotespike
) a generic transformation chain (
@AkashSamant4
) a requests chain (
@BruceHammer
) on these additions: -
Agents Now Self-Correct When Selecting Non-Existent Tools
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Previously, if an LLM chose to use a tool that did not exist the Agent would throw an error @johnvmcdonnell changed it so now we tell the agent that tool does not exist and let it self correct… just one step towards making them smarter
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DeepMind UCL Fine-tune 70B LM for Human-aligned Statements
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DeepMind & UCL Fine-tune a 70B Parameter LM to Generate Statements Agreeable to Humans with Diverse Opinions
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Fast and Slow Thinking for Autonomous Robot Navigation
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Combining Fast and Slow Thinking for Human-like and Efficient Navigation in Constrained Environments Ganapini et al.: https://
arxiv.org/abs/2201.07050 #ArtificialIntelligence #DeepLearning #MachineLearning -
AI Intern Replacing Percentage of VC Fund Employees
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Imagine you're running a VC fund. You asked an intern to review the company called CryptoQuant and got this answer in 3 seconds. This intern can replace how much % of employees?