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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

Q4 TNA Email - Send 3 of 3

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.

We Need Explanation Cards to Connect Explanation Algorithms to the Real World

arXiv:2606.16786v2 Announce Type: replace Abstract: Algorithmic explanations are intended to help stakeholders understand opaque algorithmic decisions, but in practice, they often fall short. First, the meaning of…

Lock-in EP: An In-Situ Training Algorithm for Oscillatory Hardware

arXiv:2610.07283v1 Announce Type: new Abstract: Analog hardware platforms offer the potential to reduce energy consumption over digital architectures, but in order to succeed, large-scale analog systems must also be…

Which and When to Admit: Gradient Admission for Data-Centric Small Language Model Finetuning

arXiv:2610.07553v1 Announce Type: new Abstract: LoRA fine-tuning adapts small language models (SLMs) to heterogeneous instruction data within a low-rank update subspace, making it vulnerable to three structural…

JIVEAdapter: A Multi-Task Additive Low-Rank Adapter via Joint and Individual Variation Explained (JIVE)

arXiv:2610.07036v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning adapts pretrained models at a fraction of the cost of full fine-tuning, yet most low-rank adapters are single-task and represent each…

ATLAS-AL: Adaptive Trust-Region for Latent Adversarial Searches via Active Learning

arXiv:2610.07323v1 Announce Type: new Abstract: Security evaluation of learning-based systems requires more than just testing the system against a fixed collection of attacks. It requires adaptive mechanisms that can…

Attenuated in-context identification in time-series foundation models: diagnosis under counterfactual inputs and repair by synthetic forced-system fine-tuning

arXiv:2610.08118v1 Announce Type: new Abstract: Covariate-aware time-series foundation models (TSFMs) promise training-free what-if answers for instrumented plants: the change in output that a different future input…

Trustworthy Method Comparison with AI Judges: Estimation and Design under Order, Batch, and Aggregation Effects

arXiv:2610.07755v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as judges for automated AI evaluation. A common practice is to randomize prompt sequences and average the resulting…

Exact Calibration and Sharp Risk Geometry for Volume-Sampled Ridge Regression

arXiv:2610.07721v1 Announce Type: cross Abstract: We study ridge regression from exactly $s$ distinct rows of a fixed design. Responses are fixed, and only the subset is random. The determinant law and selected ridge…