JGB @jgb_solutions
Software Engineer | YouTuber | Podcaster jgb.solutions Québec Joined November 2012-
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@jarredsumner Is this for real? Is zig gonna be dead? Is Bun a toy now? Should I switch back to Node for longevity? So many questions.
Finally, @tan_stack Start now supports React Server Components! Start's RSCs are a truly fetchable, cacheable and composable primitive that work with your favorite tools instead of dictating your entire architecture. Oh, and one more thing... "Composite Components" 😉 🔗⬇️🧵
OpenCode Go is a low cost ($10/month) subscription designed to bring agentic coding to programmers around the world it provides generous limits and reliable access to the most capable open source models run /connect and select OpenCode Go to get started
The math on this project should mass-humble every AI lab on the planet. 1 cubic millimeter. One-millionth of a human brain. Harvard and Google spent 10 years mapping it. The imaging alone took 326 days. They sliced the tissue into 5,000 wafers each 30 nanometers thick, ran them through a $6 million electron microscope, then needed Google’s ML models to stitch the 3D reconstruction because no human team could process the output. The result: 57,000 cells, 150 million synapses, 230 millimeters of blood vessels, compressed into 1.4 petabytes of raw data. For context, 1.4 petabytes is roughly 1.4 million gigabytes. From a speck smaller than a grain of rice. Now scale that. The full human brain is one million times larger. Mapping the whole thing at this resolution would produce approximately 1.4 zettabytes of data. That’s roughly equal to all the data generated on Earth in a single year. The storage alone would cost an estimated $50 billion and require a 140-acre data center, which would make it the largest on the planet. And they found things textbooks don’t contain. One neuron had over 5,000 connection points. Some axons had coiled themselves into tight whorls for completely unknown reasons. Pairs of cell clusters grew in mirror images of each other. Jeff Lichtman, the Harvard lead, said there’s “a chasm between what we already know and what we need to know.” This is why the next step isn’t a human brain. It’s a mouse hippocampus, 10 cubic millimeters, over the next five years. Because even a mouse brain is 1,000x larger than what they just mapped, and the full mouse connectome is the proof of concept before anyone attempts the human one. We’re building AI systems that loosely mimic neural networks while still unable to fully read the wiring diagram of a single cubic millimeter of the thing we’re trying to imitate. The original is 1.4 petabytes per millionth of its volume. Every AI model on Earth fits in a fraction of that. The brain runs on 20 watts and fits in your skull. The data center required to merely describe one-millionth of it would span 140 acres.
🚨: Scientists mapped 1 mm³ of a human brain ─ less than a grain of rice ─ and a microscopic cosmos appeared.
@chris_mccord Redo the benchmark and compare the two.
@tannerlinsley @josefbender_ It's X Pro. And I like that he uses that for monitoring TanStack.
@bunjavascript Built-in Markdown is so good.
@sebastienlorber Is the M5 out already? If yeah good buy. M4 is still a good buy too.
🤣 It's so funny when AI is hallucinating like this: @opencode with @GeminiApp 3 Pro. Unbelievable. 🙃
That's one of the projects I'm launching this year. Get ready!
Standing on the shoulders of @jherr' Create TanStack App, TanStack Builder (alpha) is now live 🔗↓🧵
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Schleidens.Dev 🚀 |... @schleidens_dev
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GitHub @github
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