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.

Extending Pathwise Gradients to Discrete Random Variables via Finite-Order Relaxation

arXiv:2610.07786v1 Announce Type: new Abstract: Pathwise gradients are preferred for continuous random variables because they are unbiased, low variance, and work with a single sample. For discrete variables, however,…

Learning When to Refine: Long-Horizon Reinforcement Learning for Budgeted Neural-Operator PDE Solvers

arXiv:2610.06883v1 Announce Type: new Abstract: Neural operators provide fast surrogates for time-dependent PDEs, but autoregressive deployment creates a refinement-allocation problem: prediction errors vary over space…

Deep Defence on Wheels: A Dual Intrusion Detection System Architecture for Comprehensive In-Vehicle Network Security

arXiv:2610.07489v1 Announce Type: cross Abstract: Increasing connectivity to the outside world and the lack of inbuilt security mechanisms have made legacy intra-vehicular networks vulnerable to cyberattacks. Initial…

Comparative review of hybrid forecasting models for short-term prediction of building thermal load

arXiv:2610.06881v1 Announce Type: new Abstract: In this paper, a comparative review of different hybrid models for short-term forecasting of building thermal demand is carried out. Particularly, the assessment tackles…

EvoHarness-RL: Learning Runtime Harness Coordination for Self-Evolving Agents

arXiv:2608.05446v2 Announce Type: replace Abstract: Long-horizon LLM agents increasingly rely on external execution support to maintain state, track progress, recover from failures, and reuse experience across extended…

RAM-Net: Linear-Time Sequence Modeling with Sparsely Addressable State

arXiv:2602.11958v2 Announce Type: replace Abstract: Linear attention offers an efficient alternative to full attention with a fixed-size recurrent state. However, this state is shared by all tokens, so information from…

On the Computational Tractability of Robust Bandits

arXiv:2610.08740v1 Announce Type: new Abstract: Learning when the environment does not belong to the learner's hypothesis class is typically handled using agnostic learning guarantees. However, for anything beyond…

Rethinking Faithfulness in LLMs: A Pairwise Context-Sensitive Perspective

arXiv:2610.07894v1 Announce Type: cross Abstract: Large language models (LLMs) are expected to answer questions faithfully based on the provided context, abstaining when the context information is insufficient to answer…