Category: Random

  • 🔍 What is A2A?

    I was running an experiment on summarizing X posts around a certain topic and found this on on Agent-to-Agent pretty solid, so I am publishing this as a blog post since people ask me about the topic often. This is based on 100 recent tweets about the topic A2A (run on April 15th). A2A is […]

  • 🔍 Key Trends & Insights on MCP Clients

    I was running an experiment on summarizing X posts around a certain topic and found this on on MCP pretty solid, so I am publishing this as a blog post since people ask me about the topic often. This is based on 100 recent tweets about the topic MCP client (run on April 15th). âś… […]

  • Building a personalized VC Copilot

    This blog post is based on a talk I did recently at DDVC Conference. This was originally generated by AI based on the talk transcript, which I edited. At Untapped, we’re constantly experimenting with AI to supercharge how we operate — from sourcing deals to supporting portfolio companies. Over the past year, I’ve tested dozens […]

  • Pippin, an AI powered unicorn

    Pippin is a whimsical AI-driven unicorn designed to interact with the digital world through a continuous cycle of dynamic activities, memory updates, and state changes. Operating 24/7, Pippin embodies a playful experiment in AI influencer development, inspired by community engagement and open-source collaboration. The beginning Pippin started when I was playing with AI-generated SVGs and […]

  • Where AI meets web3 🔗

    For the last couple of months, we keep getting exposed to interesting ideas and startups in the intersection of AI and web3, and some of the ideas make a lot of sense to us. First idea, a decentralized data marketplace. Companies are increasingly requesting AI models trained only on licensed data – a driving force […]

  • Knowledge Graph 🤝 LLMs

    At Untapped, we pride ourselves on being early in identifying upcoming technology trends, and thought we’d share what we’ve learned recently about the intersection of knowledge graphs and LLMs. For those not familiar, knowledge graphs (Wikipedia) are a type of data representation in the forms of nodes (objects) and edges (relationships). This data structure allows for […]

  • The Future of Autonomous Agents

    I recently did a talk in SF on the future of autonomous agents – then published the deck on X/Twitter here. We’ll be doing an hour long livestream with Q&A on May 16th at 9am on X/Twitter, so mark your calendars (or add your email here for reminders and recording link)! [update: We did the livestream, watch it here.] […]

  • Musings on Semi-Local Inference

    I recently threw out a random thought on Twitter, wondering if there might be room for something I called semi-local inference. This wouldn’t be on-device processing, but something like using a WiFi router to run powerful language models (LLMs). I was curious about the potential benefits—speed, cost, and privacy—over using APIs to power and control […]

  • Impact of BabyAGI

    BabyAGI has been cited in 42 arxiv papers (full list). The following article summarizes these 42 articles. Yohei Nakajima’s project, BabyAGI, appears to have catalyzed a wide range of innovations and research advancements across several domains of artificial intelligence, particularly in the development and application of large language models (LLMs) and agent systems. The impact […]

  • PredictiveChat: A Novel Approach to Minimizing Latency in Conversational AI through Anticipation

    *This “paper” was generated by ChatGPT based on the code, author prompt, and X/Twitter discussions. Abstract PredictiveChat introduces an innovative approach to leveraging large language models (LLMs) to anticipate user input, enabling instantaneous response generation in conversational AI systems. By predicting user messages and pre-generating responses, PredictiveChat aims to significantly enhance user experience through reduced […]