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The most popular blog posts about ai & machine learning on Hacker News. 387 posts.
AI is powered by a virtuous circle of data, algorithms (“models”), and compute. Growth in one pushes needs in the others and can grossly affect the developer experience on aspects like usability and performance. Today, we have more data and more AI model research than ever before, but compute isn’t scaling at the same…
The entire team has joined OpenAI.
Introducing our machine learning model for generating CAD models from a text prompt.
UPDATE 10/23: The update to the Paint app for Windows 11 that includes Paint Cocreator is now rolling out to Windows Insiders in the Release Preview Channel (version 11.2309.20.0 or higher
Embeddings, why they’re useful, and how we can store and use them in Convex.
An operational guide on finetuning Llama 2, ready for commercial use.
Introducing MPT-7B, the first entry in our MosaicML Foundation Series. MPT-7B is a transformer trained from scratch on 1T tokens of text and code. It is open source, available for commercial use, and matches the quality of LLaMA-7B. MPT-7B was trained on the MosaicML platform in 9.5 days with zero human intervention…
Scaling GAIA-1: a 9-billion parameter generative world model for autonomous driving
In this update, we are excited to welcome the following models joining the Chatbot Arena:
Researchers mined an old drug forum and fed the entries to an AI. The result could augur a new class of psychedelic-based antidepressants.
The University of Turku and one of Europe’s largest private AI labs Silo AI, with its large language model (LLM) arm SiloGen, are today announcing a large-scale initiative on open and trustworthy L
To keep knowledge open and accessible to all, we must come together to build the future of AI.
We’re kicking off a public discussion across the web and AI communities to develop new machine-readable means to provide web publisher choice and control.
Following up on the work from our previous blog post, we are releasing today an arXiv paper titled “Giraffe: Adventures in Expanding Context Lengths in LLMs”. Giraffe is a new family of models that are...
We are thrilled to introduce Argilla Feedback, completely open-source and designed to enhance the performance, safety and reliability of Large Language Models.
A new feature that generates natural language answers to search queries using Wikipedia.
Chris is cooking up some examples for us on how to use AI inside Postgres. We have a simple demo of using pgvector and Open AI to grab relationships and query for other similar items.
Google Cloud assumes responsibility for potential legal risks of using our generative AI, offering indemnities for training data and generated output.
How we are now leveraging embeddings and vector databases to generate prompts for ChatGPT.
Distribute and run AI workloads on Kubernetes magically in Python, like PyTorch for ML infra. - run-house/kubetorch
Just 14% of all U.S. adults say they have used ChatGPT for entertainment, to learn something new, or for their work.
The latest updates on the Llama ecosystem coming out of Meta Connect 2023
A new paper describes how Google’s Cloud TPU v4 outperforms TPU v3 by 2.1x on a per-chip basis, and improves performance/Watt by 2.7x.
In 2020, we initiated the Meta Training and Inference Accelerator (MTIA) family of chips to support our evolving AI workloads, starting with an inference accelerator ASIC for deep learning recommendation models (DLRMs).
In this blog, we discuss continuous batching, a critical systems-level optimization that improves both throughput and latency under load for LLMs.
We used Multislice Training to run the world’s largest LLM distributed training job on a compute cluster of 50,944 Cloud TPU v5e chips.
