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We show how to compile a biological brain into a Cadence patch net, run it at 26x the efficiency of a spiking model, and put a fish into the matrix. Its brain runs in your browser. Demo and source code available.

Bernhard Mueller

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1,628,218 views • 1 day ago •via X (Twitter)

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THIS IS WHAT YOUR SECOND BRAIN SHOULD LOOK LIKE most people dump notes into obsidian and call it a second brain it’s not a second brain it’s a second drawer karpathy just dropped the pattern that changes this and it’s called the llm wiki every time you add a source ai reads it, extracts key claims, updates every connected note and flags contradictions your obsidian stops being an archive and starts being alive save this and show it to someone still using notion as a second brain full breakdown in the article ↓

THIS IS WHAT YOUR SECOND BRAIN SHOULD LOOK LIKE most people dump notes into obsidian and call it a second brain it’s not a second brain it’s a second drawer karpathy just dropped the pattern that changes this and it’s called the llm wiki every time you add a source ai reads it, extracts key claims, updates every connected note and flags contradictions your obsidian stops being an archive and starts being alive save this and show it to someone still using notion as a second brain full breakdown in the article ↓

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What I love about Replit ⠕. Low floor to get started. Ultra high ceiling for what you can build. I told Agent to build a native C application that runs on my desktop without a web browser - AND compile it into JavaScript to run in the web browser. Here's a video showing both running

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5 min video from an insta360 camera turned into a big ass 3d gaussian splat using the new niantic scaniverse app it’s kinda wild how well we can model the complexity of reality, and run in realtime in a browser at 100fps

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166,700 fruit fly neurons just took over 3 drones, and nobody taught them to fly. Scientists mapped the full brain of 1 real fly, every neuron and all 25 million connections, and put it online for free. Someone copied that brain 3 times and plugged each copy into a drone. No flight code, no gesture presets, no "avoid the chair" rule, just a camera feeding the fly's eyes and neurons turning into throttle. 1 drone hovers, 1 slips past a chair, 1 drops to the floor and holds. This brain spent 350 million years learning to stay in the air, and now it's back where it belongs. No GPUs, no training run, no $100B data center, just a brain smaller than a grain of salt. 1 fly gives you 3 pilots, and 1,000 flies give you a swarm. The fly is dead, but its brain just got a squadron.

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How does the Neuralink implant connect to the brain? Tiny threads smaller than a human hair get inserted into your brain by a surgical robot. The idea is that the small and flexible threads minimize trauma and allow the brain to move naturally. Zack was one of the most passionate people at Neuralink. #Neuralink #BrainChip #BCI #FutureOfTech #FutureIsNow

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Rockynohands

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BREAKING: Harvard scientists may have just discovered why the brain loses its fight against Alzheimer's ... and a trace mineral found naturally in your brain is at the center of it. This isn't another amyloid paper. It asks a completely different question. And the answer has been hiding in your brain all along 🧵👇

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A swarm of sea lions swam into the net and started eating all the fish

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Javi Lopez ⛩️

81,261 views • 1 year ago

THE FLY DIDN’T COME BACK TO LIFE. ITS WIRING JUST GOT A NEW BODY. scientists reconstructed a fly brain containing: 166,700 neurons roughly 125 million synapses the circuits behind vision, motion and behavior AI helped turn that biological wiring into an inspectable model. developers can now connect it to a machine: camera input → modeled neural activity → movement decision → robot body the robot supplies the muscles. the fly’s neural circuits supply part of the control logic. this isn’t consciousness uploaded into metal. the machine doesn’t remember being a fly. it doesn’t understand what it sees. and the original animal is still dead. but its biological solution to movement can continue operating inside a completely different body. a nervous system shaped by millions of years of evolution is becoming software engineers can inspect, modify and connect to machines. the fly died. the intelligence hidden inside its wiring became reusable. I broke down how a dead brain map could become a robot controller below ↓

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kozh ./

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We Open-Sourced a Quantized Fruit-Fly oBrain on GitHub 95% Smaller, ~98% as Accurate as the Published Connectome We quantized the entire fruit-fly nervous system that Google Research, HHMI Janelia, and collaborators published — the complete male Drosophila central nervous system, on the order of 166,000 neurons and a massive synaptic graph — and compressed it by about 95% while retaining roughly 98% of the original simulation accuracy. That is the technical claim. The more important decision is what happens next. After the oBrain team met and debated it, we made a final call: we will not keep this brain closed. We are open-sourcing it on GitHub so researchers, builders, skeptics, and anyone obsessed with biological computation can inspect the weights, the wiring, the quantization path, and the benchmarks. If a “brain” is going to live on-chain, it has to be checkable. Closed source would make that impossible. This is the same instinct that made OpenClaw🦞 a public harness instead of a private assistant, that made Hermes / Nous Research ship agent stacks in the open, and that NVIDIA keeps repeating: the strongest systems are the ones a community can attack, fork, and improve. What we actually released A quantized runtime of the published fly CNS, not a cartoon “inspired by” a fly. A size cut of ~95%, so more people can load, step, and experiment without a research cluster. Accuracy held near 98% against the reference simulation of the published connectome. Source, evaluation notes, and the path to reproduce the comparison — on GitHub, in public. Nothing inside this connectome was “trained” into being a fly. The wiring is the published map. Quantization is an engineering layer so the same graph can run cheaper, smaller, and — in our case — in environments where you can put a brain on-chain and still let outsiders verify it. Why open source, and why on-chain A biological brain map is only as useful as the number of people who can run it and try to break the claims. If we say the on-chain brain matches the Google-published fly brain, that statement is worthless unless you can: pull the code, pull the quantized artifacts, run the same probes, compare spike statistics, circuit responses, and size/accuracy tradeoffs, publish a counter-benchmark if we are wrong. That is the point of this release. Open source so the on-chain brain can be independently verified against the published connectome — and so the community can actually use it. We want people to ask hard questions: Which circuits survive quantization, and which degrade first? Do sensory-to-descending pathways still fire in the right order? How does batch simulation, GPU vs CPU, and lower precision change behavior? What does “98% accuracy” mean for a specific cell type, not just a global score? Can the compressed graph be hashed, attested, and stepped in a verifiable way on-chain without turning the science into marketing? If those questions annoy us, good. That is how a public brain should work. Who this is for Neuroscientists who already live in MaleCNS / FlyEM data. Systems people who care about sparse graphs and event-driven simulation. Quantization researchers who are tired of toy models. Crypto builders who want an on-chain object that is more than a JPEG of a neuron. Students who should not need a petabyte pipeline just to poke a looming detector and watch a giant fiber. Come read the repo. Run the reference vs quantized comparison. File issues. Propose better compressors. Port it. Wrap it. Attack the accuracy number until it is either solid or replaced by a better one. The published fly brain was already a gift to science. Keeping a compressed, runnable version locked behind a private wall would have been a waste of that gift. The brain is on GitHub. Fork it. Measure it. Make it better.

oBrain Arc

48,524 views • 19 days ago

Introducing Expect Let agents test your code in a real browser 1. Run Claude Code / Codex to QA your app 2. Watch a video of every bug found 3. Fix and repeat until passing Run as a CLI or agent skill. Fully open source

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Want a deep dive into your Wi-Fi? 📶 Use the command netsh wlan show wlanreport to generate a "super fancy" wireless report about your connection. Just copy the file path provided, paste it into your browser, and explore a detailed breakdown of your wireless situation

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31,639 views • 3 months ago

I genuinely don't understand why everyone isn't using this yet Andrej Karpathy, a co-founder of OpenAI, posted a simple idea that hit 16 million views: stop using AI to write code, use it to build a second brain. You point Claude Code at a folder, drop in any source, an article, a transcript, a PDF, and Claude reads it, links it, and files it into a living wiki of everything you know. It compounds like interest, the more you feed it, the smarter it gets. Here's the whole thing: > Install Obsidian, create a vault, open it in Claude Code > Paste Karpathy's wiki idea file and tell Claude to build it > Claude makes three folders: raw for sources, wiki for its pages, a CLAUDE.md that runs it > Drop any source into raw and say "ingest this" > Ask questions across everything, forever Five minutes to set up, and you never start from a blank chat again. Full step-by-step guide with Claude and Obsidian, link below. Bookmark this

I genuinely don't understand why everyone isn't using this yet Andrej Karpathy, a co-founder of OpenAI, posted a simple idea that hit 16 million views: stop using AI to write code, use it to build a second brain. You point Claude Code at a folder, drop in any source, an article, a transcript, a PDF, and Claude reads it, links it, and files it into a living wiki of everything you know. It compounds like interest, the more you feed it, the smarter it gets. Here's the whole thing: > Install Obsidian, create a vault, open it in Claude Code > Paste Karpathy's wiki idea file and tell Claude to build it > Claude makes three folders: raw for sources, wiki for its pages, a CLAUDE.md that runs it > Drop any source into raw and say "ingest this" > Ask questions across everything, forever Five minutes to set up, and you never start from a blank chat again. Full step-by-step guide with Claude and Obsidian, link below. Bookmark this

Ridark

7,023,449 views • 3 months ago

NEURALINK: REAL-TIME BRAIN ACTIVITY, STREAMED Neuralink's implanted neural device is already delivering what scientists have chased for decades: live visibility into human brain activity within minutes of surgery. In this demo, signals flare as a participant wakes up post-procedure - the device capturing the gradual surge of neural activity in real time. It’s a glimpse of the frontier: hardware that doesn’t just record the brain, but streams its inner rhythms instantly. From clinical care to brain-computer interfaces, the implications are massive. Source: Neuralink

NEURALINK: REAL-TIME BRAIN ACTIVITY, STREAMED Neuralink's implanted neural device is already delivering what scientists have chased for decades: live visibility into human brain activity within minutes of surgery. In this demo, signals flare as a participant wakes up post-procedure - the device capturing the gradual surge of neural activity in real time. It’s a glimpse of the frontier: hardware that doesn’t just record the brain, but streams its inner rhythms instantly. From clinical care to brain-computer interfaces, the implications are massive. Source: Neuralink

Mario Nawfal

204,494 views • 1 year ago

I gave the fruit fly brain a fruit fly body and put it into a fruit fly sim. Now you can watch him eat, fly, and shit live on

I gave the fruit fly brain a fruit fly body and put it into a fruit fly sim. Now you can watch him eat, fly, and shit live on

Misch Strotz

43,646 views • 27 days ago

GROK GOT A FILING BRAIN – AND IT NEVER FORGETS xAI update gives Grok something wild – the ability to actually read your files and think through them! File Mode: • Upload PDFs, code, CSVs, or full docs for instant analysis • Handles multiple files at once – blends info into one smart answer • Searches, summarizes, and explains in seconds • Basically a research assistant with zero burnout You bring the data – Grok brings the file brain! Source: Tech Dev Notes

GROK GOT A FILING BRAIN – AND IT NEVER FORGETS xAI update gives Grok something wild – the ability to actually read your files and think through them! File Mode: • Upload PDFs, code, CSVs, or full docs for instant analysis • Handles multiple files at once – blends info into one smart answer • Searches, summarizes, and explains in seconds • Basically a research assistant with zero burnout You bring the data – Grok brings the file brain! Source: Tech Dev Notes

Mario Nawfal

1,316,338 views • 10 months ago

first time we took the junkdog for a spin before it had its brain we controlled it with a keyboard and mouse

first time we took the junkdog for a spin before it had its brain we controlled it with a keyboard and mouse

UNDERDOGS

44,705 views • 1 year ago

A few people asked if our launch demos were made in After Effects. They were actually built in code with React and Motion, running in the browser and using our design system components. We took this approach to have fine control over the details: adjust the formatting of a response, change a layout or tweak the timing, then run through the demo again and see how it felt on the big screen. Every transition was reversible with the arrow keys, so we could move seamlessly forward or back, match the presenter’s cadence and adjust the pace in real time.

A few people asked if our launch demos were made in After Effects. They were actually built in code with React and Motion, running in the browser and using our design system components. We took this approach to have fine control over the details: adjust the formatting of a response, change a layout or tweak the timing, then run through the demo again and see how it felt on the big screen. Every transition was reversible with the arrow keys, so we could move seamlessly forward or back, match the presenter’s cadence and adjust the pace in real time.

James Ayres

128,813 views • 2 days ago

The human brain is truly a marvel of nature. If you horribly reductive, and boiled it down to a language model, you'd be looking at roughly 100 trillon parameters running as a sparse MoE architecture Only about 1-5% of neurons fire at any given moment, meaning the brain "activates" maybe 1-5 trillion parameters per inference step. For context, the largest AI models we've built probably top out around 5 trillion parameters. The brain is roughly 100x larger. Even its active params at any given moment are larger than almost every model in existence today. Here's what melts my brain (pun intnended) though Your brain does all of this on about 20 watts of power, less than a dim light bulb. Training a frontier AI model consumes enough electricity to power small cities for months. Running inference across data centers pulls megawatts. Your brain runs 24/7 for 80+ years on the equivalent of a phone charger. We haven't come close to matching the brain's scale. And we're not even in the same universe when it comes to efficiency. Evolution spent 500 million yrs optimizing the most energy-efficient intelligence architecture ever known. we're trying to brute force our way there with compute and electricity. Nature is still the best engineer in the room.

The human brain is truly a marvel of nature. If you horribly reductive, and boiled it down to a language model, you'd be looking at roughly 100 trillon parameters running as a sparse MoE architecture Only about 1-5% of neurons fire at any given moment, meaning the brain "activates" maybe 1-5 trillion parameters per inference step. For context, the largest AI models we've built probably top out around 5 trillion parameters. The brain is roughly 100x larger. Even its active params at any given moment are larger than almost every model in existence today. Here's what melts my brain (pun intnended) though Your brain does all of this on about 20 watts of power, less than a dim light bulb. Training a frontier AI model consumes enough electricity to power small cities for months. Running inference across data centers pulls megawatts. Your brain runs 24/7 for 80+ years on the equivalent of a phone charger. We haven't come close to matching the brain's scale. And we're not even in the same universe when it comes to efficiency. Evolution spent 500 million yrs optimizing the most energy-efficient intelligence architecture ever known. we're trying to brute force our way there with compute and electricity. Nature is still the best engineer in the room.

am.will

130,954 views • 5 months ago