TTT-Discover optimizes GPU kernels 2x faster than human experts — by training during inference

A new technique from Stanford, Nvidia, and Together AI lets models learn during inference rather than relying on static ...
Quanta Magazine

The Game Theory of How Algorithms Can Drive Up Prices

Imagine a town with two widget merchants. Customers prefer cheaper widgets, so the merchants must compete to set the lowest price. Unhappy with their meager profits, they meet one night in a ...
Semiconductor Engineering

GDDR7 Tackles Massive-Context AI Inference

The AI hardware landscape is evolving at breakneck speed, and memory technology is at the heart of this transformation. NVIDIA’s recent announcement of Rubin CPX, a new class of GPU purpose-built for ...
VentureBeat

The inference crisis: Why AI economics are upside down

As frontier models move into production, they're running up against major barriers like power caps, inference latency, and rising token-level costs, exposing the limits of traditional scale-first ...
Scientific American

The Math Trick Hidden in Your Credit Card Number

You’re at the checkout screen after an online shopping spree, ready to enter your credit card number. You type it in and instantly see a red error message ...
Lifehacker

I Trained My YouTube Algorithm, and You Should Too

If Nielsen stats are to be believed, we collectively spend more time in front of YouTube than any other streaming service—including Disney+ and Netflix. That's a lot of watch hours, especially for an ...
CNBC

Nvidia's inference growth engine

CNBC’s Deirdre Bosa joins 'Money Movers' to discuss AI usage surge fueling Nvidia. Got a confidential news tip? We want to hear from you. Sign up for free newsletters and get more CNBC delivered to ...
Seeking Alpha

MicroAlgo Inc. Develops Classifier Auto-Optimization Technology Based on Variational Quantum Algorithms, Accelerating the Advancement of Quantum Machine Learning

SHENZHEN, China, May 2, 2025 /PRNewswire/ -- MicroAlgo Inc. (MLGO) (the "Company" or "MicroAlgo") announced today the launch of their latest classifier auto-optimization technology based on ...
Scientific Research Publishing

Tan, L. and Guo, K. (2025) Bregman ADMM: A New Algorithm for Nonconvex Optimization with Linear Constraints. Journal of Nonlinear and Variational Analysis, 9, 176-196.

ABSTRACT: The alternating direction method of multipliers (ADMM) and its symmetric version are efficient for minimizing two-block separable problems with linear constraints. However, both ADMM and ...
IEEE

Distributed Variational Inference for Online Supervised Learning

Abstract: This article introduces a scalable distributed probabilistic inference algorithm for intelligent sensor networks, tackling challenges of continuous variables, intractable posteriors, and ...
IEEE

Deep-Variational-Inference-Learning Detection for Cell-Free Massive MIMO With Quantization Error

Abstract: A deep variational inference learning (DVIL) framework is proposed for data detection for cell-free massive multiple-input multiple-output (MIMO). The ...