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2

RESEARCH · 1 SOURCE · MIT Technology Review AI

MIT Technology Review publishes EmTech Future 2026 on-demand program highlighting AI's cross-sector impact

MIT Technology Review has made the full EmTech Future 2026 program available on demand for subscribers; sessions feature speakers such as Yossi Matias (Google Research), Hartmut Neven (Google Quantum AI), Evelyn Wang (MIT), and Cory Doctorow discussing how AI intersects with biology, energy, quantum, manufacturing, and society. The event frames AI not just as a standalone technology but as one that gains significance when it converges with other fields.

5.0

RESEARCH · 1 SOURCE · MIT Technology Review AI

Opinion: Current LLMs don’t perform the kind of explicit reasoning systems like AlphaGo used

The piece argues that while AlphaGo combined an intuition-like policy network with an explicit search-based reasoning process to produce creative moves, today's large language models operate as iterative next-token predictors and lack a genuine, separate, inspectable reasoning mechanism; techniques such as chain-of-thought improve performance but do not create an independent epistemic state and can be post-hoc rationalizations. The author highlights three core shortcomings—no persistent inspectable beliefs, no separation between knowledge and manipulation, and unreliable chain-of-thought—and warns this limits trustworthiness in high-stakes domains like medicine and science.

7.0