AI-Assisted Exploration and Discovery of All ICML 2023 Papers with PocketLLM
Dive into more than 1800 ICML Papers Instantly on Your Personal Device via RAG (Retrieval Augmented Generation) The International Conference on Machine Learning (ICML) 2023, the leading event in the machine learning world this year, is starting this week in Hawaii. AI is currently the hottest trend, and enthusiasts worldwide are eager to stay updated […]
Introducing PocketLLM Beta: The Ultimate GenAI Hub for Windows and Mac Users
A Private On-Device Neural Database for Personalized Retrieval-Augmented Generation (RAG) with Optional Integration with ChatGPT. Download here.Today, we are excited to announce the launch of the beta version of ThirdAI’s PocketLLM, a free, user-friendly LLM (Large Language Model) app for Mac and Windows. PocketLLM combines ThirdAI’s unique neural database technology with real-time fine-tuning and reinforcement […]
ThirdAI’s Private and Personalizable Neural Database: Enhancing Retrieval-Augmented Generation (Part 3/3)
This is the final chapter (3/3) in our series on building an AI-Agent using retrieval augmented generation. In part 1/3, we discussed the limitations of a disconnected embedding and vector-based retrieval pipeline. In part 2/3, we introduced Neural Databases, which eliminates the need for storing and manipulating heavy and expensive embeddings. Instead, it uses a […]
Neural Databases: A Next Generation Context Retrieval System for Building Specialized AI-Agents with ChatGPT — (Part 2/3)
This post is a continuation of the blog “Understanding the Fundamental Limitations of Vector-Based Retrieval for Building LLM-Powered AI-Agents— (Part 1/3),” where we highlighted the shortcomings of a decoupled architecture of (1) embedding generation followed by (2) vector search using approximate near neighbor (ANN) search. We discussed how the cosine similarity between vector embeddings produced […]
Understanding the Fundamental Limitations of Vector-Based Retrieval for Building LLM-Powered Chatbots— (Part 1/3)
This blog is the first in a series of posts explaining why the mainstream pipeline for deploying domain-specialized chatbots with large language models (LLMs) is too costly and inefficient. In this first post, we discuss why vector databases, despite the recent surge in popularity, are fundamentally limited when deployed in real production pipelines. In our […]
ThirdAI’s Pocket-LLM: A Completely Free App for AI-Assisted Document Management on Windows and Mac
Convert your text data into a private, searchable, and interactive knowledge-base using the power of LLMs. No hallucinations or data transfer. Runs without internet access. Download the app from this url: https://www.thirdai.com/pocketllm/ https://www.youtube.com/watch?v=mp3_8GJV5kYPocketLLM | Private document searchThe power of next-generation deep learning technology is now available on your laptop. With dynamic sparsity, ThirdAI delivers the […]
Announcing BOLT: A Deep Learning Engine for Efficiently Training and Deploying Large Models on Commodity CPUs
New paper dives into the technical details of BOLT, the first deep learning framework for efficiently training and deploying massive models on CPUsArtificial intelligence is in the midst of a revolution with extremely large-scale models demonstrating astounding capabilities that have captured the attention and imagination of the general public. However, the current process of training […]
GPT vs Domain Specialized LLMs: Jack of All Trades Vs Master of Few.
If you are not “pre-training” LLMs on your local “domain specific” text corpus, you are likely seeing sub-optimal results for your application. LLMs and Neural Scaling Laws Large Language Models (LLMs), a famous illustration being ChatGPT, are now a must need strategy in most enterprises and industry verticals. LLMs are massively large neural networks for […]
How to use ThirdAI to Cold-Start Models for Search and Recommendations
A self-supervised learning framework for building a recommender system even in the absence of behavioral data **This post was written in collaboration with Ben Coleman, former research scientist at ThirdAI** For many businesses, search and recommendation systems are a core part of the customer experience. A good recommendation model can match users with a personalized […]
Generative AI’s Dark Horse: Query Reformulation
The future of e-commerce product search looks promising with language models, but privacy concerns and the high latencies of these models currently prohibit widespread adoption. We need smarter algorithms to change the fundamental economics of large-scale AI.The remarkable capabilities of ChatGPT and Generative AI have triggered a flurry of discussions around their potential use cases. […]