Coreweave CEO defends AI circular deals as ‘working together’
The CEO of the AI data center provider, which has Nvidia as an investor and a supplier, described the environment as a “violent change” in demand.
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Time Series and Trend Analysis Challenge Inspired by Real World Datasets
See how different time series methods reveal the shifts, surges, and stabilization in inflation expectations.
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TDS Newsletter: How to Design Evals, Metrics, and KPIs That Work
On the challenges of producing reliable insights and avoiding common mistakes The post TDS Newsletter: How to Design Evals, Metrics, and KPIs That Work appeared first on Towards Data Science.
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Google LiteRT NeuroPilot Stack Turns MediaTek Dimensity NPUs into First Class Targets for on Device LLMs
The new LiteRT NeuroPilot Accelerator from Google and MediaTek is a concrete step toward running real generative models on phones, laptops, and IoT hardware without shipping every request to a data center. It takes the existing LiteRT runtime and wires it directly into MediaTek’s NeuroPilot NPU stack, so developers can deploy LLMs and embedding models with a single API surface instead of per chip custom code. What is LiteRT NeuroPilot Accelerator? LiteRT is the successor of TensorFlow Lite. […]
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Kernel Principal Component Analysis (PCA): Explained with an Example
Dimensionality reduction techniques like PCA work wonderfully when datasets are linearly separable—but they break down the moment nonlinear patterns appear. That’s exactly what happens with datasets such as two moons: PCA flattens the structure and mixes the classes together. Kernel PCA fixes this limitation by mapping the data into a higher-dimensional feature space where nonlinear patterns become linearly separable. In this article, we’ll walk through how Kernel PCA works and use a simple example to visually compare PCA […]
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New software designs eco-friendly clothing that can reassemble into new items
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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A woman from Drew County, Arkansas, is sharing her story of being acquitted of drug possession, and she’s now questioning the ASP trooper who arrested her.
submitted by /u/m4moz [link] [comments]
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How to design LLMs that don’t need prompt engineering
Standard LLMs rely on prompt engineering to fix problems (hallucinations, poor response, missing information) that come from issues in the backend architecture. If the backend (corpus processing) is properly built from the ground up, it is possible to offer a full, comprehensive answer to a meaningful prompt, without the need for multiple prompts, rewording your query, having to go through a chat session, or prompt engineering. In this article, I explain how to do it, focusing on enterprise […]
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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 or intuition, and input from colleagues and peer reviewers. Now, MIT researchers have developed a method for optimizing materials recipes and planning experiments […]
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The Machine Learning “Advent Calendar” Day 5: GMM in Excel
This article introduces the Gaussian Mixture Model as a natural extension of k-Means, by improving how distance is measured through variances and the Mahalanobis distance. Instead of assigning points to clusters with hard boundaries, GMM uses probabilities learned through the Expectation–Maximization algorithm – the general form of Lloyd’s method. Using simple Excel formulas, we implement EM step by step in 1D and 2D, and we visualise how the Gaussian curves or ellipses move during training. The means shift, […]
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