Building A Generative AI Platform
After studying how companies deploy generative AI applications, I noticed many similarities in their platforms. This post outlines the common components of a generative AI platform,…
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Extrinsic Hallucinations in LLMs
Hallucination in large language models usually refers to the model generating unfaithful, fabricated, inconsistent, or nonsensical content. As a term, hallucination has been somewhat generalized to…
New paper: AI agents that matter
Rethinking AI agent benchmarking and evaluation
Experiments in Weak-to-Strong Generalization
Writing up results from a recent project
Free Form Least-Squares Concept Erasure Without Oracle Concept Labels
Achieving even more surgical edits than LEACE without concept labels at inference time.
RT Delip Rao e/σ: useful stuff to keep in mind while manipulating tensors and debugging networks in deep learning
RT Delip Rao e/σuseful stuff to keep in mind while manipulating tensors and debugging networks in deep learning
What We’ve Learned From A Year of Building with LLMs
What We’ve Learned From A Year of Building with LLMs
VINC-S: Closed-form Optionally-supervised Knowledge Elicitation with Paraphrase Invariance
Writing up results from a project from Spring 2023
Financial Market Applications of LLMs
The AI revolution drove frenzied investment in both private and public companies and captured the public’s imagination in 2023. Transformational consumer products like ChatGPT are powered…
Measuring personal growth
My founder friends constantly think about growth. They think about how to measure their business growth and how to get to the next order of magnitude…
Diffusion Models for Video Generation
Diffusion models have demonstrated strong results on image synthesis in past years. Now the research community has started working on a harder task—using it for video…
A Brief Overview of Gender Bias in AI
A brief overview and discussion on gender bias in AI
Coordinated Vulnerability Disclosure Dashboard
A regularly updated record of vulnerabilities found by Anthropic and reported to maintainers with cryptographic commitments to each finding at the time of disclosure.
Mamba Explained
Is Attention all you need? Mamba, a novel AI model based on State Space Models (SSMs), emerges as a formidable alternative to the widely used Transformer…
Yi-34B, Llama 2, and common practices in LLM training: a fact check of the New York Times
Setting the record straight regarding Yi-34B and Llama 2.
What I learned from looking at 900 most popular open source AI tools
[Hacker News discussion, LinkedIn discussion, Twitter thread] Update (Feb 2026): The full list of open source AI repos is hosted at Good AI List, updated daily.…
Car-GPT: Could LLMs finally make self-driving cars happen?
Exploring the utility of large language models in autonomous driving: Can they be trusted for self-driving cars, and what are the key challenges?
Do text embeddings perfectly encode text?
'Vec2text' can serve as a solution for accurately reverting embeddings back into text, thus highlighting the urgent need for revisiting security protocols around embedded data.
Unlocking the 3rd Dimension for Generative AI (Part 1)
It would be an understatement to say that generative AI has been taking the world by storm over the past couple of years. While text (1D)…
The Foundation Model Development Cheatsheet
Announcing a new resource, the FM Dev Cheatsheet.
Predictive Human Preference: From Model Ranking to Model Routing
A challenge of building AI applications is choosing which model to use. What if we don’t have to? What if we can predict the best model…
Querying a network of knowledge with llama-index-networks
The new llama-index extension package enables rapid creations of networks of RAG systems. Data suppliers can build powerful RAGs over their data and expose it behind…
LlamaIndex Newsletter 2024–02–27
This week’s llama is cool enough to wear shades for reading.Yo, LlamaIndex Fans 🦙,Dive into a week brimming with thrilling developments at LlamaIndex! The dynamic input…
Why Doesn’t My Model Work?
Have you ever trained a model you thought was good, but then it failed miserably when applied to real world data? If so, you’re in good…