Sean Ong

Mixed Reality, XR, AI, Inventor, Robotics, Husband, Dad. Loving God and Loving People.

[Sean Ong @sean_ong]

@NimaZeighami What happened?

[Sean Ong @sean_ong]

@rolandsmeenk Congratulations! Can't wait hear how it goes!

[Sean Ong @sean_ong]

@summerwoohoo @GeminiApp Maybe we should be using gemini for sports predictions 😅 got the exact score wrong, but the result right

[Sean Ong @sean_ong]

@BartronPolygon I feel like I need to hear more of your personal stories around this one 😂

[Sean Ong @sean_ong]

@BartronPolygon To be expected tbh

[Sean Ong @sean_ong]

Congratulations @jbmcculloch and team for your new Specs by Snap just announced! Love the sleek design 😎

[Sean Ong @sean_ong]

T minus 10 minutes. Several big announcements expected today at #awe! From Android XR to the 2026 Specs and more.

[Sean Ong @sean_ong]

@mixedrealityTV This is true. It's heartbreaking. There is a path forward: one with true impact and value. It's not easy, but it'll be worth it. We've been putting the cart before the horse, but now we need to put the horse before the cart, so to speak.

[Sean Ong @sean_ong]

@nfarina I wondered the same. After many observations of peers, I've come to the conclusion that good devs know what to do on a technical level, and prompt Claude in the right direction. Otherwise tons of tokens are wasted chasing many wrong or suboptimal psthways.

[Sean Ong @sean_ong]

@karanganesan @LumaLabsAI @gravicle Congratulations man!

[Sean Ong @sean_ong]

Ok, this is insane.

[CIX 🦾 @cixliv]

You guys aren't going to believe this (I had to double check it was real).

Unitree has made an actual mecha like Gundam, the GD01.

[Sean Ong @sean_ong]

@nfarina That's scary! Good to know for the future 👀

[Sean Ong @sean_ong]

Today I learned Singapore has #kitkat flavored chocolate milk/drink. Not sure how I feel about it 👀

[Sean Ong @sean_ong]

It's been a wild and fun ride so far! We developed and delivered a bunch of these kits with hardware and software that packs a boatload of incredible tech.

[Rivet Industries @Rivet_US]

The Alpha, not the Omega...

[Sean Ong @sean_ong]

@robinebers Singapore is worth it if you can afford it. Otherwise KL is pretty good too, arguably better food. I've never been to penang, but I heard that place is great.

[Sean Ong @sean_ong]

@BranchBark @nvidia @openclaw Thanks for sharing. Good insights. Are you in the bay area at the moment? If so, let's catch up.

[Sean Ong @sean_ong]

@robinebers Be safe

[Aakash Gupta @aakashgupta]

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.

[Sean Ong @sean_ong]

@slukas Very true