Nick Huber

@schulzb589 @grok See Grok knows

@nhuber @grok Some believe that AI market share in consumer builds market share in AI enterprise. How would you use data to assess this hypothesis?

It’d be kinda funny, after years of decrying the bankers, if the VCs decide, after reviewing their second-order AI infrastructure investments, that OpenAI is “too big to fail” despite its horrendous standalone financials—even funnier if the government ends up footing the bill!

Everyone can use @elonmusk's "Magic Wand Number" and "Idiot Index" They're universal ideas, helpful in any industry.

Didn’t vote for him, but happy about this

LOL, yupppp funded almost primarily by a group “established in January 2026 by prominent Silicon Valley figures, including Google co-founder Sergey Brin and former CEO Eric Schmidt” Can’t help but be in awe at the class solidarity of billionaires! Some good discussion here: reddit.com/r/AskLosAngele… cc @RoKhanna

Just got this in the mail. Without doing any research on this, I assume this is some from kind of billionaire-funded PAC. I think point two here is the important one they are seeking to pre-empt any direct action on: “prohibit […] taxes on money earned in the past”

@OfficialLoganK Wow, chip constrained. Bullish!

PSA: we are turning down Gemini 3 Pro next Monday March 9th. You can upgrade to 3.1 Pro Preview which improves on lots of the things folks gave feedback about on the first Gemini 3 rev. Please keep the feedback coming : )

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.

@hwbhatti Lemon

Think it. Say it. Done. The average person spends 3 hours typing + switches 1,000 tabs per day. That ends today. Meet Lemon: The first voice-to-action AI agent that turns your voice commands into finished tasks. RT + Comment "Lemon" to get free access for 30 days. (must be following so I can DM you)

Any data scientists have advice for writing .ipynbs in Cursor? Getting a bunch of crashes because Cursor is trying to rewrite the entire notebook (I think)

@altcap @TrumpAccounts Just imagine if GWB’s market-based social security reform had gone through! Impossible to run the full counterfactual ofc, but I think this is the kind of policy hopefully everyone can agree is good for America 🇺🇸

90% of families filing taxes early are claiming their $1000 account by simply replying “yes” on their tax form. You can sign up directly on @TrumpAccounts starting this Sunday when we drop our Superbowl Ad just after the natl anthem! 🇺🇸🚀

Mood:

Why yes I did just spend 4h setting custom resolutions, refresh rates, & color temperatures of my two monitors whilst learning about DisplayPort 2.1 vs. 1.4 protocols, my monitors' (non-VESA compliant) EDID signatures, and planning my Clawd Code's Mac Mini home—why do you ask?

@RepThomasMassie Thanks for your service! Keep fighting for truth & transparency!!

Within hours of the Epstein file release, a superPAC funded by Israel-first billionaires Miriam Adelson, Paul Singer, and John Paulson, who himself appears in Epstein’s black book, bought another $800,000 of TV ads against me. I’ll still win, but if I lose, it was worth it.

@Feras_GC Both?

@nhuber Thanks for sharing, @nhuber . Do you think this replaces the need for junior analysts or just makes the senior ones 10x faster?

This is an awesome system, and wonderful write-up; anyone working in data science/data eng should read this -- openai.com/index/inside-o… I'm convinced the field will be transformed in the next 12-18 months

Now I'm going to ask everyone I know who works at OpenAI how much they use it though -- so far 0/1! :-]

Coinbase CEO Explains “Reverse Prompting” and the Rise of the AI CEO @brian_armstrong: “One of the big pushes we made in the last year was we got our own internal hosted AI model that was connected to all of our data sources, right?” “So it's like every Slack message, every Google doc, Salesforce data, Confluence, you know.” “So now the data is all aggregated and I've started to ask it really… it's not just like prompting it, ‘Hey, can you write this kind of memo for me,’ or something.” “I'm asking these AI agents now, ‘As CEO, what should I be aware of in the company that I might not be aware of?’ And it'll tell me, ‘Did you know that there's actually disagreement on this team about the strategy?’ And I was like, actually, I didn't know that.” “This is like reverse prompting. So instead of telling the AI agent what you want it to do, you ask it what you should be thinking more about.” @Jason: “It's a mentor. It's a coach.” Brian: “Yeah. Like, what could make me a better CEO? And it's like, ‘Well, I looked at how you spent your time in the last quarter and here's how you said that you wanted to spend it, but you actually spent 32% of your time on this instead of 20%.’” “I've asked it other questions like, ‘What's the thing that I changed my mind on the most over the last year?’ Things like that.” “It'll prompt you with information you should be thinking about instead of the other way around.” Thanks to our partner for making this happen!: Our episode is sponsored by the New York Stock Exchange - a modern marketplace and exchange for building the future. It all happens at the @NYSE. nyse.com

@bridgemindai Hey I work @poe_platform. We have some upcoming initiatives it would be good to collab on related to our inference gateway product. We love your streams and vibe to them often, and want to surface you to more folks to get you to $1M. Let me know?