that sounds plausible
There is no word in English that means someone is 30% sure something will happen
Omar Khattab
13.9K posts
Omar Khattab
@lateinteraction
- crazy that they called it context window when attention span was right there
- I'm excited to share that I will be joining MIT EECS as an assistant professor in Fall 2025! I'll be recruiting PhD students from the December 2024 application pool. Indicate interest if you'd like to work with me on NLP, IR, or ML Systems! Stay tuned for more about my new lab.
- It just hit me that sub 1B-parameter models that are way better than 175B GPT-3 are a dime a dozen today. Kinda cool.
- After ~6 years of building these types of architectures (starting with BERT, eg see Baleen), I think calling these multi-agent systems is a distraction. This is just software. Happens to be AI software. It doesn’t seem so complicated once you internalize it’s just a program.
New on the Anthropic Engineering blog: how we built Claude’s research capabilities using multiple agents working in parallel. We share what worked, what didn't, and the engineering challenges along the way. anthropic.com/engineering/bu… - btw Alex is a second-month PhD student; he did this work in 4 weeks i have my suspicions that Alex has secret recursive Alexes that do his work for him, but i haven't been able to confirm that haha really fun post on recursive LMs with interesting trace examples, check it out!What if scaling the context windows of frontier LLMs is much easier than it sounds? We’re excited to share our work on Recursive Language Models (RLMs). A new inference strategy where LLMs can decompose and recursively interact with input prompts of seemingly unbounded length,
- 🔗 Thoughts on Research Impact in AI. Grad students often ask: how do I do research that makes a difference in the current, crowded AI space? This is a blogpost that summarizes my perspective in six guidelines for making research impact via open-source artifacts. Link below.
- Every once in a while, it hits you that word2vec and attention were one year apart.
- Introducing Demonstrate–Search–Predict (𝗗𝗦𝗣), a framework for composing search and LMs w/ up to 120% gains over GPT-3.5. No more prompt engineering.❌ Describe a high-level strategy as imperative code and let 𝗗𝗦𝗣 deal with prompts and queries.🧵 arxiv.org/abs/2212.14024
- DSPy's biggest strength is also the reason it can admittedly be hard to wrap your head around it. It's basically say: LLMs & their methods will continue to improve but not equally in every axis, so: - What's the smallest set of fundamental abstractions that allow you to buildIs this guy talking about DSPy?
- A cool thread yesterday used GPT4 ($50), a 500-word ReAct prompt, and ~400 lines of code to finetune Llama2-7B to get 26% HotPotQA EM. Let's use 30 lines of DSPy—without any hand-written prompts or any calls to OpenAI ($0)—to teach a 9x smaller T5 (770M) model to get 39% EM! 🧵
- We started this project thinking LMs can’t be prompted to do classification tasks with over 10,000 classes — especially when documents are long! But the incredible @KarelDoostrlnck found this elegant DSPy program that, once optimized on ~50 examples, sets the state of the art.
📢Tasks with > 10k classes (e.g. information extraction) are hard for in-context learning: typically a tuned retriever or many in-context calls per input are used ($$$) Infer-Retrieve-Rank (IReRa) is a SotA program using 1 frozen retriever with a query predictor and reranker. - Everyone talks about LLM as a judge. But what about LLM as a witness.
