The nature of thought remains one of philosophy’s greatest mysteries, with deep implications for neuroscience and artificial intelligence.

Two Minute Papers
Amodei stressed that the integration of AI into daily life in the coming years should be a boon to humanity, not a menace or a job-destroying machine.
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In this video I explore how Sam Altman’s hints about GPT-4.5 and GPT-5 are reshaping the AI landscape. You’ll discover the key differences between GPT-4.5 and GPT-5, learn why OpenAI’s next release could unify “fast” and “thoughtful” AI models, and find out how chain-of-thought reasoning could change everything from creative writing to complex problem-solving. I also discuss the biggest challenges OpenAI has faced during GPT-5’s development—from massive data requirements to persistent engineering snags—and why this model might feel closer to AGI than any chatbot yet.
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Chapters:
0:00 — Introduction.
0:24 — Timeline.
3:20 — Release date.
3:38 — Why the Wait?
5:01 — More problems.
7:25 — The Big & The Bigger.
8:41 — A solution.
9:38 — New Architecture.
11:32 — Deeply Multimodal Interaction.
12:34 — Built-in Operator & Scheduling Features.
13:23 — Personalization & Persistent Memory.
14:11 — Larger Context Windows.
14:56 — Visual Planning & Collaboration (Canvas)
16:13 — Will GPT-5 Feel Like AGI?
17:31 — Why GPT-5 Matters.
18:35 — It’s Almost Here
“Surgery means extensive recovery time and can significantly impact patient health. Our system doesn’t require surgery because we use a conventional stent, the catheter, as a delivery vehicle,” said W. Hong Yeo, the Harris Saunders Jr. Endowed Professor and an associate professor in the George W. Woodruff School of Mechanical Engineering.
Made from ultra-thin, flexible silicone, these nanosensors can be embedded in almost anything, from pacifiers to catheters. But size was just one element the researchers needed to consider when developing this device; accuracy was just as important.
Hong Yeo holds an in-stent nanomembrane sensor that can detect intracranial pressure.
A car accident, football game, or even a bad fall can lead to a serious or fatal head injury. Annually, traumatic brain injuries (TBI) cause half a million permanent disabilities and 50,000 deaths. Monitoring pressure inside the skull is key to treating TBI and preventing long-lasting complications.
Most of these monitoring devices are large and invasive, requiring surgical emplacement. But Georgia Tech researchers have recently created a sensor smaller than a dime. The miniature size offers huge benefits.
When exploring their surroundings, communicating with others and expressing themselves, humans can perform a wide range of body motions. The ability to realistically replicate these motions, applying them to human and humanoid characters, could be highly valuable for the development of video games and the creation of animations, content that can be viewed using virtual reality (VR) headsets and training videos for professionals.
Researchers at Peking University’s Institute for Artificial Intelligence (AI) and the State Key Laboratory of General AI recently introduced new models that could simplify the generation of realistic motions for human characters or avatars. The work is published on the arXiv preprint server.
Their proposed approach for the generation of human motions, outlined in a paper presented at CVPR 2025, relies on a data augmentation technique called MotionCutMix and a diffusion model called MotionReFit.