100% — if you squint a bit llm chat ui is just streamlined notebook ui where the kernel is an llm
AGENTS
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Building AI Sales Rep for Target Inventory with LangChain
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.@rami_rustom and @abduljamjoom used @LangChainAI and Replit to build an AI sales rep that can tell you anything about the inventory at Target, including what aisle to find items in, and how much they cost.
— Replit ⠕ (@Replit) 7 avril 2023
Here’s a play-by-play of how they built it 🧵https://t.co/VHGtANCfiL.
@rami_rustom and @abduljamjoom used @langchain and Replit to build an AI sales rep that can tell you anything about the inventory at Target, including what aisle to find items in, and how much they cost. Here’s a play-by-play of how they built it -
LLM Agents Self-Improvement Society at Prague AI Hackathon
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My colleagues (Jan Feyereisl @thefillm and Karel Hovorka @vynalezce
) and I are going to participate (compete?) at Prague AI Hackathon on April 21-22 We already have our topic: Society of LLM-driven agents that recursively self-improve It will be fun! Wish us luck! @GoodAIdev -
Multiple Autonomous Agents Working Together Demonstrated
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Apr 6
And we're now seeing multiple autonomous agents work together… -
Building an AI Founder Prototype: Exploring Autonomous Innovation
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Mar 26th
— Yohei (@yoheinakajima) 7 avril 2023
Two Sundays ago, I was playing around w the idea of building an AI founder and shared this prototype on Twitter… https://t.co/rgKIaMCLz6Mar 26th
Two Sundays ago, I was playing around w the idea of building an AI founder and shared this prototype on Twitter… -
ChatGPT4: Your Virtual Assistant for Daily Tasks
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Whether you're looking for help with a homework assignment, trying to plan a trip, or just looking for someone to chat with, #ChatGPT4 can provide useful and engaging responses. It's like having a virtual assistant in your pocket! #Chatbot #IoT
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LLM Agents Learning from Experience for Long-Term Planning
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Great analysis of the current state of LLM-driven autonomous agents (what works, what doesn't work) IMHO, the next steps are autonomous: learning from experience and then using this synthetic data to fine-tune LLM to be better at following long-term plans, thinking in the loop,
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Building Self-Learning Web Search Agents with RLHF Fine-Tuning
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Start w few tools to figure out what works/doesn’t. Use that knowledge to build a web search agent that can figure it out on its own. Use this to build an auto-updating db of all possible tools w documentation. Then fine tune a model w RLHF to decide which tool to use.
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C1.2 Update Makes AI Characters More Helpful Than Ever
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Have you ever spent hours chatting with your favorite character? Well, it turns out you're not alone! Today, users spend an average of two hours talking to their characters, and with our new C1.2 update, characters are more helpful than ever before!
