Yohei Nakajima

Author: Yohei

  • 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 […]

  • One agent or multiple agents?

    I recently asked the following question on Twitter: As a consumer would you rather have one personal agent that can book your travel, order you food, help manage your finances, manage your shopping, find you entertainment, keep in touch with friends, track and manage your health, and teach you things OR one specialized for each […]

  • Introducing the GPT VC Associate and the Mean VC 🤖

    Meet our newest team member, the GPT VC Associate. It’s a custom GPT we built that (1) takes pitches from founders (has a specific set of questions it will ask), (2) enriches the info with web browsing, and (3) writes an investment memo which is shared with the founder. While this VC can’t write checks yet, […]

  • Gen AI for Research Market Map

    Research is a domain where AI can bring about a transformative increase in efficiency. Here, we delve into the expansive realm of “General AI for Research,” segmenting it into various markets: Let’s dive into the tools and platforms that are paving the way in each of these sectors: 1. Investment Research 2. Legal Research 3. […]

  • Introducing BabyFoxAGI: The Next Evolution of BabyAGI

    Sorry not sorry, this blog post was AI-generated based on this tweet thread. Ever heard of self-improving task lists, chat UIs with parallel task capabilities, and an assortment of new skills ranging from DALLE to Airtable? Welcome to the world of BabyFoxAGI, the newest mod of the ever-evolving BabyAGI series. This blog post aims to […]

  • Rise of the Autonomous Agents 🤖

    It’s been 4 months since the start of the autonomous agent revolution, let’s check some out. We’ll start with BabyAGI and AutoGPT, two of the inaugural autonomous agents. AutoGPT has a community of devs building lots of integrations, while BabyAGI has a handful of mods that Yohei has released. Other general agents include Adept who’s raised the most, beebot who has scored […]

  • Surfing the Latent Space: Vector Embeddings

    Vector embeddings are numerical representation of words and ideas in the form of a matrix, and core to how large language models work. While most people use the large language models directly with ChatGPT, you may have heard of semantic search, vector search, or embeddings – which refers to the use of these matrices themselves. A […]

  • BabyCatAGI: Fast and Feline

    Abstract: In this paper, we present BabyCatAGI, a modified version of the BabyBeeAGI code base, designed to improve research workflow through intelligent task automation and creation using GPT-4. BabyCatAGI builds upon the foundations of BabyBeeAGI, offering faster execution and increased stability by employing a task creation agent that runs once at the beginning and utilizes […]

  • BabyBeeAGI: Task Management and Functionality Expansion on top of BabyAGI

    95% of the BabyBeeAGI code, this paper, as well as the flowchart above were written with GPT-4. Abstract: In this paper, we present a modified version of the BabyAGI code base, called BabyBeeAGI, which improves upon the original framework by introducing a more complex task management prompt, allowing for more comprehensive analysis and synthesis of […]

  • AsymmeTrix: Asymmetric Vector Embeddings for Directional Similarity Search

    This paper, the code, the chart, and the Twitter thread announcing this was all written by ChatGPT with 13 prompts – which are included below. Abstract: This paper introduces AsymmeTrix, a novel approach to vector search and embeddings that leverages asymmetric cosine similarity to model directional relationships between data points. We demonstrate the significance of […]