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.

Neural Global Optimization via Iterative Refinement from Noisy Samples

arXiv:2604.03614v3 Announce Type: replace Abstract: Global optimization of black-box functions from noisy samples is a fundamental challenge in machine learning and scientific computing. Traditional methods such as…

STOCK-JEPA: Prior-Anchored Latent Revision Representation Learning in Equity Markets

arXiv:2610.07006v1 Announce Type: new Abstract: Learning effective representations helps characterize the structure and dynamics of equity markets from financial data with a low signal-to-noise ratio. Black-box deep…

Causal Effect Estimation under Networked Interference without Networked Unconfoundedness Assumption

arXiv:2502.19741v4 Announce Type: replace Abstract: Estimating causal effects under networked interference from observational data is a crucial yet challenging problem. Most existing methods mainly rely on the networked…

FlowCF: Sparse Counterfactual Explanations for Mixed-Type Tabular Data using Flow Matching

arXiv:2610.08537v1 Announce Type: new Abstract: In the field of Explainable AI (XAI), counterfactual (CF) explanations interpret a model's decision by suggesting the changes to the input that would lead to a more…

Uncertainty Localization in LLM Reasoning via Embedding Perturbations

arXiv:2602.02427v4 Announce Type: replace Abstract: Large Language Models (LLMs) have achieved significant breakthroughs across various domains, but they can still produce unreliable or misleading outputs. For…

Label-Efficient Deep Learning for ECG Delineation: A Multi-Dataset Benchmark against Widely Used Delineation Tools

arXiv:2610.07885v1 Announce Type: new Abstract: Electrocardiogram (ECG) delineation, the identification of waveform boundaries, is a foundational step that translates raw ECG signals into clinically interpretable…

Convergence of Sharpness-Aware Minimization Algorithms using Increasing Batch Size and Decaying Learning Rate

arXiv:2409.09984v2 Announce Type: replace Abstract: The sharpness-aware minimization (SAM) algorithm and its variants, including gap guided SAM (GSAM), have been successful at improving the generalization capability of…

Source-Learned Reliance for Selective Test-Time Adaptation of Multimodal Time Series

arXiv:2610.07499v1 Announce Type: new Abstract: Multimodal wearable systems must remain reliable when sensor streams become noisy or unavailable. Existing multimodal test-time adaptation (TTA) methods often assess…