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Category: biological

Tracy R. Atkins on Aeternum Ray: Don’t Wait For The Singularity

“Don’t Wait For The Singularity.”

That was Tracy R. Atkins’ message when I sat down with him 14 years ago, and it lands harder now than it did then.

While almost every story about #ArtificialIntelligence was busy imagining the apocalypse, Tracy wrote a novel that flatly refused to. Aeternum Ray is unapologetically utopian: a series of letters from a 240-year-old father to his newborn son, looking back across centuries of love, loss, and a world watched over by an AI named Ray.

In our conversation, we get into what the #Singularity actually means to him, why he chose to write utopia when dystopia sells, whether humanity’s future is digital or whether biology still matters, and the uncomfortable question of whether we even survive the road to get there.

Fourteen years on, the technology has caught up to much of what we talked about. The harder question is whether our reasons for building it have, and that is the part I keep coming back to.

So is openly imagining a good future naive, or is it the most radical thing a #futurist can do? Watch the interview and decide for yourself.

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Memory, agency, and learning in biological and AI systems with Michael Levin and Katrina Schleisman

What if memory isn’t storage at all — but a message from your past self that has to be interpreted?

In this episode, biologist Michael Levin and cognitive neuroscientist Katrina Schleisman join me to take apart one of the most quietly broken ideas in science and AI: that memory works like a hard drive. It doesn’t. And once you see why, a lot of assumptions about minds, machines, and what it means to \.

How to Build a Synthethic Mind: Brain Inspired AI Exists Now

Further Reading.
Thumbnail image credit: Adobe Stock.

Brains and algorithms partially converge in natural language processing.
https://www.nature.com/articles/s4200…

Strong Prediction: Language Model Surprisal Explains Multiple N400 Effects.
https://pmc.ncbi.nlm.nih.gov/articles…

Foundation model of neural activity predicts response to new stimulus types.
https://www.nature.com/articles/s4158…

Dendrites endow artificial neural networks with accurate, robust and parameter-efficient learning.
https://www.nature.com/articles/s4146…

A Computational Perspective on NeuroAI and Synthetic Biological Intelligence.

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Brain enzyme caught doing something unexpected—it builds polysialic acid on itself

A chance discovery at Nagoya University in Japan has shown that a well-known brain enzyme has a hidden ability: It builds a sugar chain on itself, becomes secreted from the cell and deactivates, then switches on outside the cell once the chain is removed. The finding, published in the Journal of Biological Chemistry, overturns a decades-old assumption about how polysialic acid, a sugar chain critical for brain development and function, is produced and shows a new way an enzyme can regulate its own activity.

The human brain is covered in sugar chains, or glycans, molecular structures that coat cells and regulate how they communicate. One of the most important is polysialic acid, a long chain found mainly in the brain.

Polysialic acid keeps brain cells from adhering too tightly to each other and binds to growth factors and neurotrophins to regulate the presentation of their receptors. Through this, it plays a key role in learning, memory and neural development. Importantly, these sugar chains change rapidly in response to brain activity. The ability to restore them quickly is thought to be essential for normal brain function.

Restless legs syndrome—zebrafish reveal a cerebellar connection

An irresistible urge to move the legs or other areas, often accompanied by unpleasant sensations at night or during rest: Restless Legs Syndrome (RLS) affects millions of people worldwide. Despite being one of the most common sleep-related disorders, its biological causes remain poorly understood.

Researchers led by Professor Alex Schier at the Biozentrum of the University of Basel have discovered new clues about the underlying brain regions and mechanisms. Surprisingly, their findings come from an unlikely model organism: larval zebrafish.

“Studies in humans have implicated many different brain regions, but it remains unclear how they relate to RLS,” says Schier. “Our work highlights possible contributions from the cerebellum, a brain region crucial for coordinating movement.”

Diamond-based particle detector captures one-picosecond electron bursts for high-rate beam diagnostics

Physicists at UC Santa Cruz and other institutes across California and New Mexico have developed a detection system that will allow next-generation particle accelerators to better reveal fundamental biological and chemical processes, as well as advance critical areas such as materials science and energy research.

The Advanced Accelerator Diagnostics Collaboration, a group of two University of California campuses and three U.S. national laboratories, came together to solve a growing need for high-rate beam diagnostics. These accelerators will now jump from 120 pulses a second to 1 million pulses a second, straining current beam diagnostic systems. The results are now published in the journal Physical Review Accelerators and Beams.

“It really highlights the power of collaboration between universities and national laboratories,” said Bruce Schumm, the Long Family Professor of Experimental Physics. “If you took away Lawrence Berkeley Lab, if you took away Los Alamos, if you took away UC Davis, any of those, the whole thing would have fallen apart.”

How to train your magnet: Excitons as a new knob for magnetic control

Scientists can learn a lot about a quantum material by watching how it responds to light. In magnetic semiconductors, one especially useful messenger is the exciton: a pairing of a negatively charged electron and the positively charged “hole” it leaves behind. Until now, excitons in magnetic materials have mostly been used as reporters. They could reveal how spins were arranged or how magnetic waves moved through a material. But Cornell researchers have shown that excitons can do more than observe magnetism. They can actively steer it.

In the paper “Excitonic Spin Torque in a Magnetic Semiconductor,” published June 15 in Nature Materials, Youn Jue (Eunice) Bae, assistant professor of chemistry and chemical biology in the College of Arts and Sciences, and colleagues report that excitons created by light can exert a spin torque in the two-dimensional magnetic semiconductor chromium sulfide bromide, or CrSBr. The finding establishes excitons as a new way to control magnetic motion with light.

“Excitons have been very useful for watching what spins are doing in magnetic materials,” Bae said. “What we show here is that excitons can also act back on the spins. They are not just spectators; they can help drive the magnetic motion.”

What AI Reveals About the Brain

Can AI become smarter than humans?

In this episode, I talk to Chris Summerfield about the frontier of artificial intelligence, neuroscience, LLMs, AI agents, memory, and superintelligence.

We discuss why models like ChatGPT and Claude can feel so human, why today’s AI still does not learn like the brain, and why continual learning may be one of the most important unsolved problems in AI. Chris explains how human memory works, why sleep matters for learning, and what AI research is teaching us about intelligence itself.

We also discuss the future of work, education, creativity, and whether AI could lead to a more human world — or a much stranger one.

Topics covered:
• ⁠ ⁠Artificial intelligence and the human brain.
• ⁠ ⁠⁠LLMs, ChatGPT, Claude and AI agents.
• ⁠ ⁠⁠AI memory and continual learning.
• ⁠ AI alignment, safety and misalignment.
• ⁠. Superintelligence and self-improving systems.
• ⁠ Hallucinations, reasoning and intelligence.
• ⁠. Education, jobs and the future of work.
• ⁠. Why AI may change how humans understand themselves.

TIMESTAMPS:

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