Journalism begins where hype ends

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We can only see a short distance ahead, but we can see plenty there that needs to be done.” "

—Alan Turing

NeurIPS 2026 Workshop Lineup Points to AI’s Shift Beyond LLMs and Data Centres

NeurIPS 2026 has selected 102 workshops highlighting AI agents, physical AI, foundation models, robotics, AI for science, safety and evaluation.

NeurIPS 2026 has selected 102 workshops from 454 valid submissions, with workshops in Sydney, Paris and Atlanta highlighting a shift in AI research beyond large language models toward autonomous agents, physical AI, adaptive foundation models, robotics, AI for science and more reliable and efficient systems.

LLMs Alter Meaning of Social Media Posts on Controversial Topics: Oxford Study

Representational image. An Oxford-led study finds AI writing tools systematically shift the stance of social media posts on contested topics. (Image: Freepik)

Large language models often change the direction of social media posts on controversial topics even when explicitly instructed to preserve the original meaning, an Oxford-led study finds.

BharatGen to Represent India in Project Tapestry Under AI Alliance

BharatGen from India joins Project Tapestry under AI alliance.

An initiative of the AI Alliance, Project Tapestry is a global open consortium that aims to build frontier AI capability through distributed model development while allowing participating nations and institutions to retain control over their own data, models, and deployment.

Researchers at Rutgers University Propose Weak AI Models to Guide Stronger Ones

Researchers at Rutgers University have proposed a new study suggesting weaker AI models can train stronger ones through critique

Researchers at Rutgers University have proposed a new study suggesting weaker AI models can train stronger ones through critique

Study Reveals LLMs generated 150,000 Fake Citations in Research Papers

A new study has found out that LLM models are giving fake citations while generating academic papers.

According to the study LLMs generate information which seems to be true but are actually false yet the usage and and consequences of this hallucination problem remain poorly understood in the real world.