October 2025

Introducing Chronos-2: From univariate to universal forecasting In-context learning enables a model that can solve forecasting tasks with an arbitrary number of dimensions in a zero-shot manner. Machine learning Abdul Fatir Ansari Oleksandr Shchur Jaris Kken October 20, 09:53 AM January 06, 09:54 AM Time series forecasting is crucial to numerous applications in business, science, and engineering. Recently, foundation models have led to a paradigm shift in time series forecasting. Unlike statistical models, which extrapolate from a single […]

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It’s hard to keep up with the ever-changing trends of the fashion world. What’s “in” one minute is often out of style the next season, potentially causing you to re-evaluate your wardrobe. Staying current with the latest fashion styles can be wasteful and expensive, though. Roughly 92 million tons of textile waste are produced annually, including the clothes we discard when they go out of style or no longer fit. But what if we could simply reassemble our clothes […]

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I’ve recently been experimenting with one of my favorite old-school neural networks, a tiny program that runs on my laptop and knows only about the data I give it. Without internet training, char-rnn doesn’t have outside references to draw on (for better or for worse) but it still manages to remix the data into interesting new things. In 2017 I asked AI Weirdness readers to help me crowdsource a list of Halloween costumes and then trained char-rnn on […]

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Demystifying AI agents Amazon vice president and distinguished engineer Marc Brooker explains how agentic systems work under the hood and how AWSs new AgentCore framework implements their essential components. Cloud and systems Marc Brooker October 16, 02:04 PM October 22, 11:02 AM Agents are the trendiest topic in AI today, and with good reason. AI agents act on their users behalf, autonomously doing things like making online purchases, building software, researching business trends, or booking travel. By taking […]

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Say a person takes their French Bulldog, Bowser, to the dog park. Identifying Bowser as he plays among the other canines is easy for the dog-owner to do while onsite. But if someone wants to use a generative AI model like GPT-5 to monitor their pet while they are at work, the model could fail at this basic task. Vision-language models like GPT-5 often excel at recognizing general objects, like a dog, but they perform poorly at locating […]

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Amazon and Carnegie Mellon University (CMU) announced today the launch of the CMU-Amazon AI Innovation Hub, reinforcing a shared commitment to advancing cutting-edge research through academic-private sector partnerships. Amazon and Carnegie Mellon University launch strategic AI Innovation Hub The collaboration will advance research in generative AI, robotics, natural language processing and cloud computing while fostering innovation in foundational and emerging technologies. Conversational AI October 15, 08:59 AM October 15, 08:58 AM Amazon and Carnegie Mellon University (CMU) announced […]

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Oct. 16 is World Food Day, a global campaign to celebrate the founding of the Food and Agriculture Organization 80 years ago, and to work toward a healthy, sustainable, food-secure future. More than 670 million people in the world are facing hunger. Millions of others are facing rising obesity rates and struggle to get healthy food for proper nutrition.  World Food Day calls on not only world governments, but business, academia, the media, and even the youth to […]

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TL;DR The memory required to run a model with hundreds of billions of parameters far exceeds the capacity of even the largest available GPUs. Maximizing GPU utilization throughout the inference process is key to efficient LLM operation. The attention mechanism is the main focus of optimization efforts, as it scales the least favorably. While key-value caching reduces computational load, multi-query and grouped-query attention reduce both the number of parameters and the cache size. By employing effective workload-parallelization strategies, […]

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Manufacturing better batteries, faster electronics, and more effective pharmaceuticals depends on the discovery of new materials and the verification of their quality. Artificial intelligence is helping with the former, with tools that comb through catalogs of materials to quickly tag promising candidates. But once a material is made, verifying its quality still involves scanning it with specialized instruments to validate its performance — an expensive and time-consuming step that can hold up the development and distribution of new […]

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As costs for diagnostic and sequencing technologies have plummeted in recent years, researchers have collected an unprecedented amount of data around disease and biology. Unfortunately, scientists hoping to go from data to new cures often require help from someone with experience in software engineering. Now, Watershed Bio is helping scientists and bioinformaticians run experiments and get insights with a platform that lets users analyze complex datasets regardless of their computational skills. The cloud-based platform provides workflow templates and […]

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