LlamaIndex v0.10
Today we’re excited to launch LlamaIndex v0.10.0. It is by far the biggest update to our Python package to date (see this gargantuan PR), and it…
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Thinking about High-Quality Human Data
[Special thank you to Ian Kivlichan for many useful pointers (E.g. the 100+ year old Nature paper “Vox populi”) and nice feedback. 🙏 ] High-quality data…
Generation configurations: temperature, top-k, top-p, and test time compute
ML models are probabilistic. Imagine that you want to know what’s the best cuisine in the world. If you ask someone this question twice, a minute…
Deep learning for single-cell sequencing: a microscope to see the diversity of cells
On the the pivotal role that Deep Learning has played as a key enabler for advancing single-cell sequencing technologies.
Least-Squares Concept Erasure with Oracle Concept Labels
Achieving even more surgical edits than LEACE when we have concept labels at inference time.
Salmon in the Loop
On fish counting – a complex sociotechnical problem in a field that is going through the process of digital transformation.
Diff-in-Means Concept Editing is Worst-Case Optimal
Explaining a result by Sam Marks and Max Tegmark
The third New England RLHF Hackers Hackathon
Introduction At the third New England RLHF Hackathon, several interesting projects were showcased, each focusing on different aspects of machine learning and reinforcement learning. Participants and…
Adversarial Attacks on LLMs
The use of large language models in the real world has strongly accelerated by the launch of ChatGPT. We (including my team at OpenAI, shoutout to…
Neural algorithmic reasoning
In this article, we will talk about classical computation: the kind of computation typically found in an undergraduate Computer Science course on Algorithms and Data Structures…
Multimodality and Large Multimodal Models (LMMs)
For a long time, each ML model operated in one data mode – text (translation, language modeling), image (object detection, image classification), or audio (speech recognition).…
The Artificiality of Alignment
This essay first appeared in Reboot. Credulous, breathless coverage of “AI existential risk” (abbreviated “x-risk”) has reached the mainstream. Who could have foreseen that the smallcaps…
Open challenges in LLM research
[LinkedIn discussion, Twitter thread] Never before in my life had I seen so many smart people working on the same goal: making LLMs better. After talking…
LLM Powered Autonomous Agents
Building agents with LLM (large language model) as its core controller is a cool concept. Several proof-of-concepts demos, such as AutoGPT, GPT-Engineer and BabyAGI, serve as…
Generative AI Strategy
I had a lot of fun preparing the talk: “Leadership needs us to do generative AI. What do we do?” for Fully Connected. The idea for…
Generative AI and AI Product Moats
Here are eight observations I’ve shared recently on the Cohere blog and videos that go over them.: Article: What’s the big deal with Generative AI? Is…
Prompt Engineering
Prompt Engineering, also known as In-Context Prompting, refers to methods for how to communicate with LLM to steer its behavior for desired outcomes without updating the…
The Transformer Family Version 2.0
Many new Transformer architecture improvements have been proposed since my last post on “The Transformer Family” about three years ago. Here I did a big refactoring…
Large Transformer Model Inference Optimization
[Updated on 2023-01-24: add a small section on Distillation.] Large transformer models are mainstream nowadays, creating SoTA results for a variety of tasks. They are powerful…
Remaking Old Computer Graphics With AI Image Generation
Can AI Image generation tools make re-imagined, higher-resolution versions of old video game graphics? Over the last few days, I used AI image generation to reproduce…
The Illustrated Stable Diffusion
Translations: Chinese, Vietnamese. (V2 Nov 2022: Updated images for more precise description of forward diffusion. A few more images in this version) AI image generation is…
Some Math behind Neural Tangent Kernel
Neural networks are well known to be over-parameterized and can often easily fit data with near-zero training loss with decent generalization performance on test dataset. Although…
Generalized Visual Language Models
Processing images to generate text, such as image captioning and visual question-answering, has been studied for years. Traditionally such systems rely on an object detection network…
Learning with not Enough Data Part 3: Data Generation
Here comes the Part 3 on learning with not enough data (Previous: Part 1 and Part 2). Let’s consider two approaches for generating synthetic data for…