CT scans reveal severe battery defects inside Haribo’s 20,000 mAh power bank and earbuds, explaining their quiet removal from Amazon.

16 observations on hospital culture and incentives

We explore the fundamentals of Saltstack and how we use it at Cloudflare. We also explain how we built the infrastructure to reduce release delays due to Salt failures on the edge by over 5%.

Modern cars are collecting more data than ever, raising privacy concerns. The Mozilla Foundation says cars are the worst product category for privacy.

By my count, Linux has over 11% of the desktop market. Here's how I got that number - and why people are making the leap.

A 7-day challenge to create a programming language and then use it to build a game.

Use my code, 2SWAPYT20, for a 20% discount on your first purchase of a Lovable Pro plan before December 26!Click here to automatically apply the discount at ...

A tool to snap pixels to a perfect grid. Designed to fix messy and inconsistent pixel art generated by AI. - Hugo-Dz/spritefusion-pixel-snapper

Boing

AI is being done wrong.

In which I talk about the process involved in switching forges, and how well that went.

🚀 CachyOS is an Arch Linux-based distribution that offers an easy installation, several customization options to suit every user, and special optimizations for improved performance while remaining simple.

The first high-resolution images have been received from Copernicus Sentinel-1D and were shared publicly for the first time at the European Space Agency’s Ministerial Council, held today in Bremen, Germany. Glaciers in Antarctica, the tip of South America, as well as the city of Bremen, are visible in these stunning radar images.

Recently, there has been significant progress in teaching language models to perform step-by-step reasoning to solve complex numerical reasoning tasks. Chain-of-thoughts prompting (CoT) is by far the state-of-art method for these tasks. CoT uses language models to perform both reasoning and computation in the multi-step `thought' process. To disentangle computation from reasoning, we propose `Program of Thoughts' (PoT), which uses language models (mainly Codex) to express the reasoning process as a program. The computation is relegated to an external computer, which executes the generated programs to derive the answer. We evaluate PoT on five math word problem datasets (GSM, AQuA, SVAMP, TabMWP, MultiArith) and three financial-QA datasets (FinQA, ConvFinQA, TATQA) for both few-shot and zero-shot setups. Under both few-shot and zero-shot settings, PoT can show an average performance gain over CoT by around 12\% across all the evaluated datasets. By combining PoT with self-consistency decoding, we can achieve SoTA performance on all math problem datasets and near-SoTA performance on financial datasets. All of our data and code are released in Github https://github.com/wenhuchen/Program-of-Thoughts