AI2 closes the gap between closed-source and open-source post-training
Ai2 released Tülu 3, a model that makes fine-tuning open-source LLMs easier and get its performance closer to closed LLMs like GPT-4o.Read More
Ai2 released Tülu 3, a model that makes fine-tuning open-source LLMs easier and get its performance closer to closed LLMs like GPT-4o.Read More
Black Friday deals on Amazon devices have started early. Even the brand-new Kindle lineup is on sale.
A team of computer engineers and AI specialists at Microsoft, working with a pair of colleagues from the University of Chicago, has led to the development of a new language that allows LLMs to speak with one another more efficiently. The group has posted a paper outlining the ideas behind the new language, how it …
Read more “Microsoft collaboration develops DroidSpeak for better communication between LLMs”
Our new AI system accurately identifies errors inside quantum computers, helping to make this new technology more reliable.
Estimating the density of a distribution from samples is a fundamental problem in statistics. In many practical settings, the Wasserstein distance is an appropriate error metric for density estimation. For example, when estimating population densities in a geographic region, a small Wasserstein distance means that the estimate is able to capture roughly where the population …
Read more “Instance-Optimal Private Density Estimation in the Wasserstein Distance”
Swiss Re & Palantir Scaling Data Operations with Foundry Editor’s note: This guest post is authored by our customer, Swiss Re. Authors Lukasz Lewandowski, Marco Lotz, and Jarek Sobanski lead the core technical team responsible for the implementation of Palantir Foundry at the Swiss reinsurer. They have been managing overall platform operations, core architectural principles, site reliability, …
Read more “Swiss Re & Palantir: Scaling Data Operations with Foundry”
As generative AI models advance in creating multimedia content, the difference between good and great output often lies in the details that only human feedback can capture. Audio and video segmentation provides a structured way to gather this detailed feedback, allowing models to learn through reinforcement learning from human feedback (RLHF) and supervised fine-tuning (SFT). …
Large language models (LLMs) give developers immense power and scalability, but managing resource consumption is key to delivering a smooth user experience. LLMs demand significant computational resources, which means it’s essential to anticipate and handle potential resource exhaustion. If not, you might encounter 429 “resource exhaustion” errors, which can disrupt how users interact with your …
Read more “Don’t let resource exhaustion leave your users hanging: A guide to handling 429 errors”
We dive into the most significant takeaways from Microsoft Ignite, and Microsoft’s emerging leadership in the area of AI agents.Read More
Trust between humans and robots is improved when the movement between both is harmonized, researchers have discovered.