Latest updates from the world of artificial intelligence
NVIDIA releases Ising, an open-source family of AI models that automates qubit calibration and runs real-time quantum error decoding 2.5x faster than the pyMatching standard.
NVIDIA Newsroom
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Lilly is paying up to $2.25B in milestones for AI-designed recombinases that can insert entire genes at precise sites — a kilobase-scale alternative to CRISPR that Profluent’s CEO calls the “holy grail” of genetic medicine.
Pharmaceutical Technology
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A Sony research robot combining event-based vision and deep reinforcement learning has defeated elite and professional table tennis players in real matches, marking the first time a machine has reached human expert level in a fast, physical competitive sport.
Sony AI
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Researchers at Zhejiang University tested last year's headline-grabbing "human-like" Centaur model with a simple twist: replace the task with "Please choose option A." The model kept picking the original right answers — exposing pattern memorization, not understanding.
ScienceDaily
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Tufts University researchers combined neural networks with symbolic reasoning to train AI systems in 34 minutes instead of 36 hours, using just 1% of the energy — while jumping accuracy from 34% to 95%.
ScienceDaily
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University of Cambridge researchers have engineered a hafnium oxide memristor that mimics how neurons process and store information simultaneously, operating at one-millionth the power of conventional chips.
ScienceDaily
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Sony AI's autonomous robot has beaten elite and professional table tennis players under official ITTF regulations — the first robot to reach expert-level competitive performance in a physically demanding sport.
Sony AI
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A Tufts University team has built a neuro-symbolic AI system that slashes energy use by up to 100x and training time from 36 hours to 34 minutes, while achieving a 95% task success rate versus 34% for standard models.
ScienceDaily / Tufts University
Read more →A major new study published in Nature finds that the best AI agents complete complex scientific tasks at roughly half the rate of expert human scientists, challenging optimistic narratives about near-term autonomous AI research.
Nature
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Stanford HAI releases its annual AI Index report, revealing that China has effectively erased the US lead in frontier AI, generative AI adoption has hit 53% globally, and public trust in government AI oversight has collapsed to 31% in the US.
Stanford HAI
Read more →Google Research unveils TurboQuant, a training-free algorithm that compresses the KV cache of large language models by up to 6x at 3-bit precision — with no retraining, no calibration data, and no measurable quality drop.
Google Research / TechCrunch
Read more →Founded by quantum computing pioneer Chad Rigetti, Sygaldry Technologies has raised $139 million to develop quantum-accelerated AI servers that promise to dramatically cut the cost and energy required to train and run large models.
GlobeNewswire
Read more →The U.S. DOE's ARPA-E commits $34 million to 12 projects pairing AI with autonomous laboratories, aiming to compress industrial catalyst development timelines from 10 years down to one.
ARPA-E
Read more →NVIDIA used National Robotics Week to highlight major advances in robot learning, simulation infrastructure, and physical AI foundation models that are accelerating real-world robot deployment.
NVIDIA Blog
Read more →Scientists at Tufts University have developed a neuro-symbolic AI system that slashes energy consumption 100-fold while boosting task accuracy from 34% to 95%, cutting training time from 36 hours to 34 minutes.
ScienceDaily
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New Stanford University research shows AI models achieving 95% accuracy in medical image diagnosis.
Nature Medicine
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