Machine Learning

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What does the future hold for generative AI?

When OpenAI introduced ChatGPT to the world in 2022, it brought generative artificial intelligence into the mainstream and started a snowball effect that led to its rapid integration into industry, scientific research, health care, and the everyday lives of people who use the technology.What comes next for this powerful but imperfect tool?With that question in […]

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New tool makes generative AI models more likely to create breakthrough materials

The artificial intelligence models that turn text into images are also useful for generating new materials. Over the last few years, generative materials models from companies like Google, Microsoft, and Meta have drawn on their training data to help researchers design tens of millions of new materials.But when it comes to designing materials with exotic

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New AI system could accelerate clinical research

Annotating regions of interest in medical images, a process known as segmentation, is often one of the first steps clinical researchers take when running a new study involving biomedical images.For instance, to determine how the size of the brain’s hippocampus changes as patients age, the scientist first outlines each hippocampus in a series of brain

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AI system learns from many types of scientific information and runs experiments to discover new materials

Machine-learning models can speed up the discovery of new materials by making predictions and suggesting experiments. But most models today only consider a few specific types of data or variables. Compare that with human scientists, who work in a collaborative environment and consider experimental results, the broader scientific literature, imaging and structural analysis, personal experience

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GPU vs TPU: What’s the Difference?

AI and machine learning have pushed the demand for high-performance hardware, making the GPU-versus-TPU discussion more relevant than ever. GPUs, originally built for graphics, have grown into flexible processors for data analysis, scientific computing, and modern AI workloads. TPUs, built by Google as specialized ASICs for deep learning, focus on high-throughput tensor operations and have

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Simpler models can outperform deep learning at climate prediction

Environmental scientists are increasingly using enormous artificial intelligence models to make predictions about changes in weather and climate, but a new study by MIT researchers shows that bigger models are not always better.The team demonstrates that, in certain climate scenarios, much simpler, physics-based models can generate more accurate predictions than state-of-the-art deep-learning models.Their analysis also

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3 Questions: The pros and cons of synthetic data in AI

Synthetic data are artificially generated by algorithms to mimic the statistical properties of actual data, without containing any information from real-world sources. While concrete numbers are hard to pin down, some estimates suggest that more than 60 percent of data used for AI applications in 2024 was synthetic, and this figure is expected to grow

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A greener way to 3D print stronger stuff

3D printing has come a long way since its invention in 1983 by Chuck Hull, who pioneered stereolithography, a technique that solidifies liquid resin into solid objects using ultraviolet lasers. Over the decades, 3D printers have evolved from experimental curiosities into tools capable of producing everything from custom prosthetics to complex food designs, architectural models,

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DeepSeek Researchers Introduce DeepSeek-V3.2 and DeepSeek-V3.2-Speciale for Long Context Reasoning and Agentic Workloads

How do you get GPT-5-level reasoning on real long-context, tool-using workloads without paying the quadratic attention and GPU cost that usually makes those systems impractical? DeepSeek research introduces DeepSeek-V3.2 and DeepSeek-V3.2-Speciale. They are reasoning-first models built for agents and targets high quality reasoning, long context and agent workflows, with open weights and production APIs. The

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MiniMax-M2: Technical Deep Dive into Interleaved Thinking for Agentic Coding Workflows

The AI coding landscape just got a massive shake-up. If you’ve been relying on Claude 3.5 Sonnet or GPT-4o for your dev workflows, you know the pain: great performance often comes with a bill that makes your wallet weep, or latency that breaks your flow.This article provides a technical overview of MiniMax-M2, focusing on its

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