AI Research

Does better work always mean better workers?

Microsoft Wants Your PC to Work While You Sleep, Surface Laptop Ultra Pre-Orders Open

Microsoft wants Windows PCs to carry out more AI work locally while using cloud models where they add value. New agent containers, intelligent routing, and RTX Spark hardware connect that vision, and our interviews…

How Wrong Is Your Marketing Mix Model (MMM)?

A well-built MMM can still be wrong, because the spend it learns from never held the information it needs. This article tests whether changing when you spend, not how much, can fix that. The post How Wrong Is Your…

Introduction to Reinforcement Learning: Multi-Armed Bandit Simulation in Python

When machines learn by themselves The post Introduction to Reinforcement Learning: Multi-Armed Bandit Simulation in Python appeared first on Towards Data Science.

The Tiny Ultrasound Chip Behind Butterfly’s Bigger AI Bet

Medical AI depends on the information it receives. Butterfly Network is opening its ultrasound chip and software to developers, with applications ranging from guided procedures to Midjourney’s experimental body scanner.

The Consistency Quadrant: A Visual Guide to LLM Reliability

Mapping structural variance against execution outputs to estimate coding agent reliability without ground truth. The post The Consistency Quadrant: A Visual Guide to LLM Reliability appeared first on Towards Data…

Mistral’s New AI Model Puts a Price on Sovereignty

Mistral Large 4 is competitive with some of the world’s strongest AI models, but its bigger bet is giving enterprises more control over how AI runs. Whether that independence proves practical depends on something…

Q4 TNA Email - Send 2 of 3

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When Do PINNs Beat Classical Numerical Methods? A 1D vs 5D Experiment

I put a physics-informed neural network up against a plain finite-difference solver twice: once in 1D and once in 5D. The winner changed. The post When Do PINNs Beat Classical Numerical Methods? A 1D vs 5D Experiment…

😺 OpenAI’s AI produced 722 math manuscripts

Dario Amodei’s $18 Million Pay Opens a Bigger Question About AI Wealth

Dario Amodei received approximately $18 million in 2025 compensation. Anthropic’s potential IPO raises questions about how founder wealth and voting power could influence its public-benefit mission.

DistDF: Time-Series Forecasting Needs Joint-Distribution Wasserstein Alignment

arXiv:2510.24574v3 Announce Type: replace Abstract: Training time-series forecasting models requires aligning the conditional distribution of model forecasts with that of the label sequence. The standard direct forecast…

Prediction-powered inference for time series across space

arXiv:2610.08715v1 Announce Type: cross Abstract: The following motif is common in spatiotemporal settings: we have a sequence of covariate and label pairs observed for a relatively short, recent time period. We have…

FFR: Forward-Forward Learning for Regression

arXiv:2606.03927v2 Announce Type: replace Abstract: The Forward-Forward (FF) algorithm offers a computationally efficient and biologically plausible alternative to backpropagation (BP) by training neural networks…

Do LLMs Act on What They Know? From Partner Representations to Cooperative Actions

arXiv:2610.08129v1 Announce Type: new Abstract: Cooperation with unfamiliar partners requires adapting to communication conventions that are not known in advance. We study this problem in a controlled Hanabi-derived…

Contact Geometry and Covariance Deficits in Volume-Sampled Least Squares

arXiv:2608.26877v3 Announce Type: replace Abstract: We classify when ordinary fixed-size volume sampling followed by unweighted least squares attains its sharp coefficient-covariance ceiling on a fixed design. For a…

Adaptive Latent Capacity for World Models

arXiv:2609.32921v2 Announce Type: replace Abstract: We introduce Adaptive LeWorldModel (ALeWM), a world model based on a joint-embedding predictive architecture (JEPA) that learns to concentrate predictive information…

Near-Optimal Sample Complexity for Recursive Entropic Risk Reinforcement Learning with a Generative Model

arXiv:2610.06931v1 Announce Type: new Abstract: In this paper, we study the sample complexities of value and policy learning in finite discounted Markov decision processes (MDPs) under recursive entropic risk…

Learning from Hindsight for VLA Reinforcement Learning

arXiv:2607.09042v2 Announce Type: replace Abstract: Reinforcement learning is increasingly used to fine-tune vision-language-action (VLA) models, but robot interaction is expensive and learning becomes highly sample…