Category

Research

MIT Technology Review 30 Jul 2026

Researchers say a fundamental flaw makes LLMs inherently vulnerable

A team of researchers argues in a paper presented at the International Conference on Machine Learning that it is impossible to make large language models fully secure against hacks due to a fundamental flaw in how they work. The claim, reported by MIT Technology Review, highlights broad safety implications for LLM deployment.

IEEE Spectrum 29 Jul 2026

NCCU Launches HBCU AI Institute to Boost Campus-wide AI Literacy

Siobahn Day Grady founded the Institute for Artificial Intelligence and Emerging Research (IAIER) at North Carolina Central University in January 2025, backed by a $1 million Google.org grant and partnerships with IBM and Google. The institute requires an AI course for freshmen, has engaged over 2,800 people, funded interdisciplinary seed projects, and is expanding programs while seeking sustainable funding.

MIT Technology Review 27 Jul 2026

Pathways Toward Artificial Superintelligence

MIT Technology Review explores how specialised AI agents could eventually need to coordinate rather than just exchange data. The article outlines a future where domain-specific systems—like symptom assessment, scheduling, insurance, and pharmacy agents—must align objectives to work together effectively.

TechCrunch AI 27 Jul 2026

Researchers explore brain waves to improve physical AI

TechCrunch reports that next‑generation physical AI models will require richer data than public videos, including multi‑angle footage, dense annotations, and potentially brain wave readings. The article frames neural signals as a future data modality for improving embodied AI training and evaluation.

TechCrunch AI 24 Jul 2026

AI guardrails hinder offensive cybersecurity research

Cybersecurity researchers who search for unknown vulnerabilities say OpenAI’s and Anthropic’s guardrails limit their ability to develop and test exploitation tools. TechCrunch AI reported researchers describing how safety constraints interfere with typical offensive research workflows.