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Generating step-by-step "chain-of-thought" rationales improves language model performance on complex reasoning tasks like mathematics or commonsense question-answering.

hybrid LSTM models, significantly outperform the traditional GARCH models

Anthropic is launching a new subscription plan for its AI chatbot, Claude, catered toward enterprise customers that want more administrative controls and

Anthropic's prompt caching lets users save prompts and call these up for later sessions with additional context for a lower price.

We’re excited to offer the AI/ML community free access to Hermes 3 through Lambda’s new Chat Completions API, fully compatible with the OpenAI API. It provides endpoints for creating completions, chat completions and listing models.

Slack's engineering team recently published how it used a large language model (LLM) to automatically convert 15,000 unit and integration tests from Enzyme to React Testing Library (RTL). By combining

Pulumi claims it has culled bad infrastructure-as-code samples

To help users get better at crafting prompts, Google just published a crash course on the subject in the form of a 45-page handbook.

In this blog post you will learn how to fine-tune LLMs using Hugging Face TRL, Transformers and Datasets in 2024. We will fine-tune a LLM on a text to SQL dataset.

The complaint lays out in steps why the plaintiffs believe the datasets have illicit origins — in a Meta paper detailing LLaMA, the company points to sources for its training datasets, one of which is called ThePile, which was assembled by a company called EleutherAI. ThePile, the complaint points out, was described in an EleutherAI paper as being put together from “a copy of the contents of the Bibliotik private tracker.” Bibliotik and the other “shadow libraries” listed, says the lawsuit, are “flagrantly illegal.”

With a new Fill-in-the-Middle paradigm, GitHub engineers improved the way GitHub Copilot contextualizes your code. By continuing to develop and test advanced retrieval algorithms, they’re working on making our AI tool even more advanced.

Source Latent Space Podcast Ep. 2: Why you are holding your GPUs wrong OpenAI just rollicked the AI world yet again yesterday — while releasing the long awaited ChatGPT API, they also priced it at $2 per million tokens generated, which is 90% cheaper than the text-davinci-003 pricing of the “GPT3.5” family. Their blogpost on how they did it is vague: Through a series

A "Copilot for X" guide from the team that built the first real Copilot competitor!

SPRING is an LLM-based policy that outperforms Reinforcement Learning algorithms in an interactive environment requiring multi-task planning and reasoning.  A group of researchers from Carnegie Mellon University, NVIDIA, Ariel University, and Microsoft have investigated the use of Large Language Models (LLMs) for understanding and reasoning with human knowledge in the context of games. They propose a two-stage approach called SPRING, which involves studying an academic paper and then using a Question-Answer (QA) framework to justify the knowledge obtained. More details about SPRING In the first stage, the authors read the LaTeX source code of the original paper by Hafner (2021)