The brain dynamically transforms cognitive information. Here the authors build task-performing, functioning neural network models of sensorimotor transformations constrained by human brain data without the use of typical deep learning techniques.
To expand its GPT capabilities, OpenAI released its long-anticipated o1 model, in addition to a smaller, cheaper o1-mini version. Previously known as Strawberry, the company says these releases can “reason through complex tasks and solve harder problems than previous models in science, coding, and math.”
Although it’s still a preview, OpenAI states this is the first of this series in ChatGPT and on its API, with more to come.
The company says these models have been training to “spend more time thinking through problems before they respond, much like a person would. Through training, they learn to refine their thinking process, try different strategies, and recognize their mistakes.”
I find it weird that black holes would be moving throughout the galaxy because most are stationary.
A fluffy cluster of stars spilling across the sky may have a secret hidden in its heart: a swarm of over 100 stellar-mass black holes.
The star cluster in question is called Palomar 5. It’s a stellar stream that stretches out across 30,000 light-years, and is located around 80,000 light-years away.
Continue reading “Entire Swarm of Black Holes Detected Moving Through The Milky Way” »
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Using a 3D printer that works with molten glass, researchers forged LEGO-like glass bricks with a strength comparable to concrete. The bricks could have a role in circular construction in which materials are used over and over again.
“Glass as a structural material kind of breaks people’s brains a little bit,” says Michael Stern, a former MIT graduate student and researcher in both MIT’s Media Lab and Lincoln Laboratory. “We’re showing this is an opportunity to push the limits of what’s been done in architecture.”
Continue reading “‘Brain-breaking’ glass bricks are 3D printed, reusable, and strong” »
Murine T cells that survived at least four host lifetimes offer insights into immunological senescence.
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AI’s language can intrigue, but mistaking its patterns for deeper wisdom blurs the line between thoughtful insight and mere digital mimicry.
In today’s fast-paced world, speed is celebrated. Instant messaging outpaces thoughtful letters, and rapid-fire tweets replace reflective essays. We’ve become conditioned to believe that faster is better. But what if the next great leap in artificial intelligence challenges that notion? What if slowing down is the key to making AI think more like us—and in doing so, accelerating progress?
OpenAI’s new o1 model, built on the transformative concept of the hidden Chain of Thought, offers an interesting glimpse into this future. Unlike traditional AI systems that rush to deliver answers by scanning data at breakneck speeds, o1 takes a more human-like approach. It generates internal chains of reasoning, mimicking the kind of reflective thought humans use when tackling complex problems. This evolution not only marks a shift in how AI operates but also brings us closer to understanding how our own brains work.
This concept of AI thinking more like humans is not just a technical accomplishment—it taps into fascinating ideas about how we experience reality. In his book The User Illusion, Tor Nørretranders reveals a startling truth about our consciousness: only a tiny fraction of the sensory input we receive reaches conscious awareness. He argues that our brains process vast amounts of information—up to a million times more than we are consciously aware of. Our minds act as functional filters, allowing only the most relevant information to “bubble up” into our conscious experience.
Barbosa, Stein et al. show that rather than operating independently, PFC persistent activity and ‘activity-silent’ mechanisms interact dynamically to produce serial effects in working memory, consistent with attractor models with synaptic plasticity.
