🎉 The most powerful Open-Source LLM is out! Yes! Smaller than LLaMA 🦙, but Stronger than LLaMA (65B) hands down! 💪 *** The Institute of Technological Innovation of the Arab Emirates released today the most powerful base model ever: FalconLM 🚀 The model is currently

Here is a ChatGPT on the European AI act. Use at your own risk. (Requires ChatGPT+) chat.openai.com/g/g-7ZUMpsavX-…

BERTopic + LLMs + DataMapPlot is an incredibly fun combo!

LLMs passed a Turing Test, of a sort, for doctors. 149 actors playing patients texted live with one of 20 primary care doctors or else Google's new medical LLM, AMIE. Specialist human doctors & the "patients" rated the quality of care. AMIE beat the docs. blog.research.google/2024/01/amie-r…

Here’s a fun demo of long-context understanding. First, we asked the model to find 3 amusing moments in the 402-page pdf transcription of the iconic Apollo 11 mission. Then we uploaded a simple drawing of a boot and it identified the moment we had in mind: Neil’s one small step!

⚠️RAG might be dead, after reading 58 pages of Genimi 1.5 Pro tech report. Here's my thoughts as AI founder, 1. Simple RAG system like similarity search with vector db will be dead. But more customized RAG will still live. The goal of RAG is mostly on retrieval relevant

The most epic AI panel in a while! We at NVIDIA have gathered ALL 8 authors of "Attention is All You Need" for a panel at GTC, hosted by none other than the GOAT himself, Jensen Huang. In 2017, 8 researchers had a flash of genius and invented Transformer, the seminal work that

Groq is a Radically Different kind of AI architecture Among the new crop of AI chip startups, Groq stands out with a radically different approach centered around its compiler technology for optimizing a minimalist yet high-performance architecture. Groq's secret sauce is this

Fun LLM challenge that I'm thinking about: take my 2h13m tokenizer video and translate the video into the format of a book chapter (or a blog post) on tokenization. Something like: 1. Whisper the video 2. Chop up into segments of aligned images and text 3. Prompt engineer an LLM

The new e=mc**2

Sounds like a supervisor answering questions about details in their student’s paper 🤓

Self driving building Janitor. Cleans all bathrooms in a multistory building… Unassisted.

Have you ever wanted to train LLMs in pure C without 245MB of PyTorch and 107MB of cPython? No? Well now you can! With llm.c: github.com/karpathy/llm.c To start, implements GPT-2 training on CPU/fp32 in only ~1,000 lines of clean code. It compiles and runs instantly, and exactly

# explaining llm.c in layman terms Training Large Language Models (LLMs), like ChatGPT, involves a large amount of code and complexity. For example, a typical LLM training project might use the PyTorch deep learning library. PyTorch is quite complex because it implements a very

Bill Clinton On the Palestinians: “And the only time Yasser Arafat didn't tell me the truth was when he promised me he was gonna accept the peace deal that we had worked out, which would have given the Palestinians a state on 96% of the West Bank and 4% of Israel, and they got

I’ve been developing a parameter-efficient FT method that: – Improves in-domain knowledge uptake – Minimizes out-of-domain forgetting – Smaller parameter count than LoRA Initial QA benchmarks are strong. Today, perplexity-based evaluation confirmed efficiency trends. More soon

For a long time, I've struggled with getting deep domain knowledge into LLM chatbots. RAG is powerful, sure, but it often feels like a workaround, not an elegant, integrated solution. I knew there had to be a better way to make LLMs truly learn. 🤔 #LLM #DomainAdaptation #A