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.

SoloQ: Calibration-Free Quantization for Diffusion Language Models

arXiv:2610.07121v1 Announce Type: new Abstract: Diffusion large language models dLLMs) have emerged as a promising alternative to autoregressive language models through bidirectional diffusion-based token generation.…

Information-Dense Synthesis for Molecular Discovery

arXiv:2610.08495v1 Announce Type: cross Abstract: Machine learning can accelerate molecular discovery by designing molecules and planning experiments. However, many scientific challenges demand molecules with very rare…

Bayesian Optimization on Function Spaces via Sparse RKHS Manifolds

arXiv:2610.07417v1 Announce Type: cross Abstract: Bayesian Optimization (BO) has become an established methodology for minimizing black-box functions of a vector input. Often, however, this parameter vector arises from…

Direct Regret Optimization in Bayesian Optimization

arXiv:2507.06529v2 Announce Type: replace Abstract: Bayesian optimization (BO) is a powerful paradigm for optimizing expensive black-box functions. Traditional BO methods typically rely on separate hand-crafted…

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study

arXiv:2501.18158v4 Announce Type: replace-cross Abstract: Cryptocurrencies are widely used, yet current methods for analyzing transactions often rely on opaque, black-box models. While these models may achieve high…

Reward as Observation: Learning Reward-Based Policies for Rapid Adaptation

arXiv:2610.00729v2 Announce Type: replace Abstract: This paper explores a reward-based policy to achieve zero-shot transfer between source and target environments with completely different observation spaces. While…

SquidAgent: Parallelize Wisely, Coordinate Efficiently

arXiv:2610.08647v1 Announce Type: cross Abstract: LLM-based agents solve complex multi-step tasks, but sequential execution incurs substantial latency. In principle, parallelizing work across multiple agents should…

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…