MIT Technology Review

Deploying a hybrid approach to Web3 in the AI era

Against a backdrop of insatiable demand for compute, Web3 principles and technologies offer enterprises transparent, flexible ...

Meta’s Vision-Language Shift VL-JEPA Beats Bulky LLMs

VL-JEPA predicts meaning in embeddings, not words, combining visual inputs with eight Llama 3.2 layers to give faster answers you can trust.
MIT Technology Review

LLMs contain a LOT of parameters. But what’s a parameter?

Think back to middle school algebra, like 2 a + b. Those letters are parameters: Assign them values and you get a result. In ...

New ‘Test-Time Training’ method lets AI keep learning without exploding inference costs

By allowing models to actively update their weights during inference, Test-Time Training (TTT) creates a "compressed memory" ...

When is it time to jump? The boiling frog problem of AI use in physics education

Generative AI is becoming ubiquitous in everyday life. Large language models like ChatGPT can help answer questions, write ...
RCR Wireless News

Powering robotics: How networks enable the era of ‘Physical LLMs’ (Reader Forum)

Physical AI describes intelligent systems that can sense, interpret, and act in real environments. Think of self-driving cars ...
Unite.AI

LLMs and MCP Servers: A New Blueprint for Secure AI in Remote Access

A growing number of organizations are embracing Large Language Models (LLMs). LLMs excel at interpreting natural language, ...
IEEE

Channel-Agnostic Predictive Beamforming for Crowdsourced Bistatic Satellite ISAC with LLM

Abstract: Integrated sensing and communications (ISAC) systems promise dual use of spectrum and hardware for data transmission and environmental awareness. However, extending ISAC to satellite ...