A preregistered behavioral implementation of Newcomb's paradox with 1,305 participants found that framing a predictor as AI increased the odds of forgoing the guaranteed reward by a factor of 3.39 (95% CI: 2.45–4.70) compared with random framing, reducing earnings by 10.7–42.9%. Over 40% of participants treated AI as a predictive authority, and the effect persisted even when predictions failed.
Columbia/MIT/Harvard team used AI protein-language models to redesign all 52 essential ribosomal proteins in E. coli without isoleucine, creating strain Ec19 that stayed above 90% wild-type fitness for 450 generations.
University of Hong Kong engineers demonstrated a world-first silicon carbide transistor that mimics neuron spiking at 10 millikelvin, the temperature range of quantum computers.
Princeton/Flatiron study shows transfer learning cuts cosmological AI simulation costs 10x but risks negative transfer that masks genuinely new physics.
Tufts University researchers combined neural networks with human-like symbolic reasoning to create a hybrid AI that achieved 95% success on a Tower of Hanoi robotic task vs. 34% for standard models, while using only 1% of the training energy required by a standard VLA model.
UPenn physicists created hybrid light-matter particles (exciton-polaritons) that perform all-optical switching for AI chips using only about 4 quadrillionths of a joule per operation — published in Physical Review Letters, May 2026.
Astronomers at the University of Warwick have confirmed more than 100 exoplanets, including 31 newly identified worlds, using a new artificial intelligence system applied to NASA's Transiting Exoplanet Survey Satellite (TESS) data — among them rare ultra-short-period giants in the so-called “Neptunian desert,” a region where few planets are expected to exist.
Sandia computational neuroscientists Brad Theilman and Brad Aimone developed a new algorithm enabling neuromorphic hardware to tackle partial differential equations — the mathematical foundation of fluid dynamics, electromagnetic fields, and structural mechanics.
OIST researchers showed that pairing AI with self-directed inner speech and working memory — invisible to users — improved how their models learned, adapted to new situations, and multitasked, and let the system work with sparse data instead of the extensive data sets usually required.
Researchers are building programmable DNA nanomachines — with rigid joints and molecular logic — designed to move through the bloodstream, deliver drugs, and target cancer cells or viruses, though most remain at the proof-of-concept stage.
Northwestern engineers aerosol jet-printed MoS2/graphene artificial neurons that successfully triggered responses from real neurons in live mouse brain tissue — paving the way for neuroprosthetics and lower-energy brain-like AI chips.
The largest creativity comparison ever (over 100,000 humans vs. AI) finds generative AI surpasses average divergent thinking scores, but the most creative humans — especially the top 10% — still decisively outperform every model.