A new type of hologram technology has been developed that uses the motion of light as a key, revealing information only under specific conditions. This is gaining attention as a novel approach that can simultaneously overcome the limitations of existing optical communication and security technologies.
Ever wonder what actually happens inside the AI after you hit “Enter”?
You type a prompt into your favorite generative AI, and within seconds, your screen fills with exactly what you asked for—whether it’s a quarterly report or a cinematic image of a cyberpunk golden retriever. It feels like absolute magic.
But behind that seamless curtain lies a bustling, microscopic economy running entirely on a digital currency you’ve probably heard of but might not fully understand: the token.
Most of us only ever see the input and the output. We don’t see the internal cash register ringing, the mathematical gymnastics, or the sprawling “assembly line” churning through billions of calculations.
What actually happens between the moment you hit send and the moment your final masterpiece appears? In my newest blog post, I peel back the curtain to trace the fascinating journey of an AI token.
I break down this invisible economy—from the “toll booth” of the input phase to the heavy lifting of the output phase—and show you exactly how the machine balances the books.
To try everything Brilliant has to offer—free—for a full 30 days, visit https://brilliant.org/ArtemKirsanov. You’ll also get 20% off an annual premium subscription.
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My name is Artem, I’m a neuroscience PhD student at Harvard University.
🌎 Website and Social links: https://kirsanov.ai/
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A lightning fast catchup on the latest in foundational physics theories, in light of recent news conserning UAP, NHI, and psionics
In 1965, a mathematician who worked alongside Alan Turing wrote a single
paragraph that has haunted AI research ever since. He predicted that one
day, a machine would learn to improve itself, and that everything after
that point would change.
Sixty years later, that loop is starting to close.
In this video, we trace how AI got here: from I.J. Good’s 1965 prediction.
to AlphaGo Zero teaching itself Go in 72 hours, to AlphaEvolve cracking a
math problem that had stood unbeaten for 56 years, and then quietly
speeding up the training of the very model that runs it. We look at the
data behind the trend (autonomous AI task length is doubling every 7
months), the walls AI keeps running into (compute, data, energy), and what
the people building this technology are actually saying about how close
we are.
This video is an honest look at what \.
Now online! A host-filtering and decontamination pipeline was benchmarked and applied to 16,369 tumor genomes, providing a high-resolution atlas of the cancer microbiome. Although most cancer types lacked a detectable microbiome, orodigestive cancers harbored complex multi-kingdom microbial communities that varied by site, subtype, and somatic mutation burden, linking the tumor microbiome to host phenotype and tumor genomic context.
Researchers at the University of Toronto have identified a protein from the quagga mussel that can stick to surfaces underwater, even though it lacks a chemical feature long thought to be essential for this kind of adhesion. The protein, called Dbfp7, is the first freshwater mussel adhesive protein to be functionally characterized.
The finding, published in PNAS, helps explain how some organisms attach themselves in wet environments and could inform the design of future medical glues—such as medical sealants and surgical adhesives—or other materials that need to work reliably in water.
Most studies of underwater adhesion have focused on marine mussels, which use proteins rich in a modified amino acid called 3,4-dihydroxyphenylalanine (DOPA) to bond to surfaces. Freshwater species have been studied less, and whether they rely on the same chemistry has not been clear.
Creating complex molecules usually requires years of experience and countless decisions, but a new AI system is changing that. Synthegy lets chemists guide synthesis and reaction planning using simple language, while powerful algorithms generate and evaluate possible solutions. The AI doesn’t just compute—it reasons, scoring pathways and explaining which ones make the most sense.