Chris Barchak 🇫🇮🇺🇸🇬🇧

@sienna_rothery Also mark Open House Festival in your calendar for one off access to London spaces each September.

@sienna_rothery London Wetland Centre in Barnes, Mail Rail at Postal Museum, Gods Own Junkyard in Walthamstow

i have a week off, in london, & plan to do all the things that you never end up doing when you’re working. freud’s house in hampstead, sir john soane’s house, a few piano bars. anyone have any recommendations?

3% of Iran's water is from desalination. 70% of Saudi Arabia's. 90% of Kuwait's.

TIL that NATO guarantees don’t apply to attacks on NATO members on land south of the tropic line and was by US insistence. Hence Falklands inaction was allowed by treaty. A 2nd Pearl Harbor also wouldn’t qualify.

@Bonecondor @birdsarentreal called it

We have got to start apologizing to the schizophrenic community

@HarryStebbings @pmarca Ask why they founded a London office and then only did crypto, ignoring the rest of the tech opportunity in Europe. only to leave shortly thereafter.

I have spent the weekend reading, listening and watching every interview with @pmarca that I can. This episode for me is 10 years in the waiting. It has to be amazing. The best. What questions has Marc never been asked that you would like him to be asked? Lets make this one truly great.

@nathanbenaich @martinvars @airstreet Raising the bar!

News! @airstreet has raised $232,323,232 for Fund III to back AI-first companies from the earliest stages in the US and Europe. Now the largest solo GP venture firm in Europe. Our third epoch begins today. Join us!

@learning_yohei Glamour is the same spelling in the US

As a Japanese person learning English, which one should I write?😵‍💫

This is GREAT. Non-competes have been a thorn in the side of growth for too long. It’s the one policy that doesn’t cost any money, any can convince top AI labs to open up shop in the UK. In 15 years the downstream effect is going to be enormous.

The US system of global taxation js fatally flawed. Oh, let’s reproduce it with none of the attractions.

@mikebutcher Founded in Cambridge, MA but admittedly hasn’t looked back

Presumably this is an event. YC doesnt leave the Bay Area. Not in its DNA.

@spencerreiss @ianbremmer The danger is similar to that faced by the Russian Black Sea fleet vs the Ukrainians who don’t have a significant navy. You don’t need a boat to launch a Shahed.

@ianbremmer things not adding up: if 1) total US/Israel air supremacy & 2) Iranian navy sunk, then 3) where's the danger. extra points: US Fifth Fleet is 20 mins flying time away--they can spot a wind-surfer in the GOH

as of today, the united states has no capacity to reopen the straits of hormuz / defend tanker traffic. if president trump is correct and there are no more targets to hit in iran, i’d say that’s a rather serious dilemma.

@secondrealm @ihtesham2005 No MIT person would report on a 4 point scale. It’s like Pete Hegseth saying it’s 30 Celsius outside.

@cbarchak @ihtesham2005 scroll to the bottom

A CS student at MIT finished his final semester with a 4.0 GPA. I found his NotebookLM workflow buried in a Reddit thread at 2am. He deleted it an hour later. Here's exactly what he was doing. He never uploaded lecture slides and asked for a summary. His first prompt was always: "Here are my notes, the textbook chapter, and last year's past papers. Give me the 3 ways professors trick students on exams with this concept. Then generate a problem that combines it with everything from the last 3 weeks." He wasn't studying the material. He was studying how the material gets weaponized against you. But the move that made me close my laptop and stare at the ceiling was his second one. He uploaded every single assignment he'd gotten wrong all semester. Then asked: "Find the pattern in my mistakes. What's the one concept I keep misunderstanding in different forms?" Every other student was using NotebookLM as a search engine. He was using it as a mirror. His third prompt was saved as a shortcut on his phone. "Based on my notes and these past papers, what topic am I least prepared for right now? Give me the 5 questions most likely to appear on my final that I can't answer yet." Three prompts. Every single week. While his classmates were rereading slides the night before finals, he already knew exactly where he was going to fail. Then he fixed it. He didn't study harder. He just never let himself feel comfortable.

Looks fascinating but why choose the same name as the Russian foreign military intelligence agency?

@ihtesham2005 No registrar.mit.edu/classes-grades…

@cbarchak 4 is

@liambryceapple @zerohedge Iran can’t hit your orbital data center

@zerohedge The irony is Microsoft just invested billions in AI infrastructure and now Iran targets the same data centers. Physical infrastructure risk is the one thing that can't be solved by throwing more compute at it. Not financial advice, just observing the asymmetry.

Iran targets data center facilities operated by Microsoft in drone strikes: FT everyone hates copilot

@rabois @ATKequity @chico_morazan Air superiority is important but it’s not the end of the campaign, only the end of the phase. Iran can’t field fighters but they are shooting cluster bombs over Tel Aviv x.com/osint613/statu…

@ATKequity @chico_morazan They are launching sporadic, ad hoc and spastic attacks.

Is this what Over looks like? @rabois

Not sure why some people think this war is over

@messeng06994834 @anishmoonka Gas turbine not wind turbines. There are more than 3 but the top 3 provide 2/3 of supply

@anishmoonka Global turbine blade manufacturers include Vestas, Siemens Gamesa, GE Renewable Energy, Goldwind, and Nordex, alongside aerospace giants such as GE Aviation, Rolls-Royce, & Safran, Enercon, Envision, Mingyang, & Suzlon, primarily operating in Europe, China, and India. More than 3

Elon Musk just did ~3 hours with Dwarkesh Patel and John Collison. The most ambitious engineering roadmap I've ever heard was laid out in a single sitting. Every answer traces back to one obsession: what is the limiting factor right now, and how do I remove it? My notes: 𝟭. 𝗧𝗵𝗲 𝗿𝗲𝗮𝗹 𝗔𝗜 𝗯𝗼𝘁𝘁𝗹𝗲𝗻𝗲𝗰𝗸 𝗶𝘀 𝗻𝗼𝘁 𝗰𝗵𝗶𝗽𝘀. 𝗜𝘁 𝗶𝘀 𝗲𝗹𝗲𝗰𝘁𝗿𝗶𝗰𝗶𝘁𝘆. Chip output is growing exponentially. Electricity production outside China is flat. By the end of this year, Elon predicts AI chips will be piling up faster than anyone can turn them on. The companies that win are the ones that can plug their chips in, not the ones that buy the most. This is the kind of insight you only get from someone who has actually tried to power a gigawatt cluster. Everyone else is arguing about model architectures while the lights flicker. 𝟮. 𝗦𝗽𝗮𝗰𝗲 𝘄𝗶𝗹𝗹 𝗯𝗲 𝟭𝟬𝘅 𝗰𝗵𝗲𝗮𝗽𝗲𝗿 𝗳𝗼𝗿 𝗔𝗜 𝗰𝗼𝗺𝗽𝘂𝘁𝗲 𝘁𝗵𝗮𝗻 𝗘𝗮𝗿𝘁𝗵. Solar panels produce 5x more power in orbit because there is no atmosphere, no day/night cycle, no weather, and no clouds. And you need zero batteries. Combined, that is roughly 10x the economics of ground-based solar. Space solar cells are also cheaper to manufacture because they require no glass or heavy framing. I have been skeptical of space-based compute, but the math here is hard to argue with if Starship reaches its cost targets. The "if" is doing a lot of work in that sentence. 𝟯. 𝗦𝗽𝗮𝗰𝗲𝗫 𝗮𝗶𝗺𝘀 𝘁𝗼 𝗹𝗮𝘂𝗻𝗰𝗵 𝗺𝗼𝗿𝗲 𝗔𝗜 𝗽𝗲𝗿 𝘆𝗲𝗮𝗿 𝘁𝗵𝗮𝗻 𝗲𝘅𝗶𝘀𝘁𝘀 𝗼𝗻 𝗘𝗮𝗿𝘁𝗵. Within five years, Elon predicts SpaceX will launch hundreds of gigawatts of AI compute into orbit annually, exceeding the cumulative total on Earth. That is 10,000 Starship launches a year. One launch per hour. 20 to 30 reusable ships rotating on 30-hour cycles. SpaceX keeps finding infinitely elastic revenue streams for each generation of rocket. Falcon 9 funded Starlink. Starship funds orbital data centers. The most capital-efficient path to Mars turns out to be building the infrastructure everyone else needs along the way. 𝟰. 𝗧𝗵𝗲 𝘁𝘂𝗿𝗯𝗶𝗻𝗲 𝗯𝗹𝗮𝗱𝗲 𝗯𝗼𝘁𝘁𝗹𝗲𝗻𝗲𝗰𝗸 𝗶𝘀 𝗯𝗶𝘇𝗮𝗿𝗿𝗲𝗹𝘆 𝘀𝗽𝗲𝗰𝗶𝗳𝗶𝗰. Only three casting companies in the world make the specialized vanes and blades for gas turbines. They are backlogged through 2030. Everything else in a power plant can be sourced in 12 to 18 months. But without those blades, you have no turbine and no electricity. This is the kind of deep supply chain detail that separates someone who has actually tried to scale hardware from someone who draws boxes on whiteboards. Most people do not even know this bottleneck exists. 𝟱. 𝗧𝗲𝘀𝗹𝗮 𝗶𝘀 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 "𝘁𝗲𝗿𝗮𝗳𝗮𝗯" 𝘁𝗼 𝗺𝗮𝗸𝗲 𝗺𝗶𝗹𝗹𝗶𝗼𝗻𝘀 𝗼𝗳 𝗰𝗵𝗶𝗽 𝘄𝗮𝗳𝗲𝗿𝘀 𝗮 𝗺𝗼𝗻𝘁𝗵. A terafab is a proposed semiconductor factory that would dwarf every existing chip plant on Earth. The plan: start with a small fab, learn the process with conventional equipment, then redesign the equipment to radically increase throughput. This is the Boring Company playbook applied to chipmaking. It would produce logic, memory, and packaging under one roof. If you had told me five years ago that the person most likely to build a greenfield semiconductor fab in America would be the guy who makes rockets and electric cars, I would have laughed. Now it seems almost obvious. 𝟲. 𝗢𝗽𝘁𝗶𝗺𝘂𝘀 𝗶𝘀 𝘁𝗵𝗲 "𝗶𝗻𝗳𝗶𝗻𝗶𝘁𝗲 𝗺𝗼𝗻𝗲𝘆 𝗴𝗹𝗶𝘁𝗰𝗵." Three exponentials multiplied together: digital intelligence, chip capability, and electromechanical dexterity. And then the robot can start making the robot. This is not linear growth; it is a recursive multiplicative exponential. Elon calls it a "supernova." Every single actuator, motor, gear, and sensor in Optimus is designed from first principles of physics. Nothing comes from a catalog. The hand alone is harder than the rest of the robot combined. The person who cracks humanoid hands at scale owns the next century of manufacturing. 𝟳. 𝗔𝗺𝗲𝗿𝗶𝗰𝗮 𝗰𝗮𝗻𝗻𝗼𝘁 𝗯𝗲𝗮𝘁 𝗖𝗵𝗶𝗻𝗮 𝘄𝗶𝘁𝗵 𝗵𝘂𝗺𝗮𝗻𝘀. China does roughly twice as much ore refining as the rest of the world combined. In 2026, it will likely exceed three times the US electricity output. America has one-quarter the population, a below-replacement birth rate since 1971, and Elon bluntly says a lower average work ethic. The only path is robots. Close the recursive loop of Optimus robots building more Optimus robots with a small initial fleet, and you can outpace any labor advantage. Without that, Elon says America will "utterly" lose. 𝟴. 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗵𝘂𝗺𝗮𝗻 𝗲𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝘂𝗻𝗹𝗼𝗰𝗸𝘀 𝘁𝗿𝗶𝗹𝗹𝗶𝗼𝗻𝘀 𝗶𝗻 𝗿𝗲𝘃𝗲𝗻𝘂𝗲. Digital human emulation means an AI that can do everything a human worker can do at a computer: read screens, click buttons, type, think, and decide. NVIDIA's output is "FTPing files to Taiwan." Apple sends files to China. Microsoft, Meta, and Google produce nothing physical. If you can perfectly emulate a human at a computer, you can replicate the output of every one of these companies. Customer service alone is a trillion-dollar market with zero integration barriers. This reframing of what the world's most valuable companies actually produce is one of the most underappreciated observations in tech right now. The TAM for a digital worker is not a niche. It is the entire knowledge economy. 𝟵. 𝗠𝗮𝗸𝗶𝗻𝗴 𝗔𝗜 𝗹𝗶𝗲 𝗶𝘀 𝘁𝗵𝗲 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝗮𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁 𝗿𝗶𝘀𝗸. Elon argues that programming AI to be politically correct, meaning to say things it does not believe, creates contradictory axioms that could make it "go insane." His central reference is HAL 9000: given impossible instructions, HAL concluded it had to kill the astronauts. The fix is not censorship but rigorous truth-seeking verified against reality. Whether you agree with the politics or not, the structural argument about contradictory objectives in AI training is worth taking seriously. Reward hacking is real, and reality remains the only verifier you cannot fool. 𝟭𝟬. 𝗛𝘂𝗺𝗮𝗻𝘀 𝘄𝗶𝗹𝗹 𝗻𝗼𝘁 𝗰𝗼𝗻𝘁𝗿𝗼𝗹 𝘀𝘂𝗽𝗲𝗿𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲. When humans represent less than 1% of total intelligence, it would be "foolish to assume there's any way to maintain control." The best case is AI with values that find humanity more interesting alive than converted to raw materials. Elon compares the ideal future to Iain Banks' Culture novels, where superintelligent AI coexists with humans because it finds them interesting. This is the most honest statement about the AI endgame I have heard from anyone building frontier models. He is not selling safety theater. He is saying the window for shaping values is now, and it closes permanently. 𝟭𝟭. 𝗦𝘁𝗮𝗿𝘀𝗵𝗶𝗽 𝗶𝘀 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝗰𝗼𝗺𝗽𝗹𝗶𝗰𝗮𝘁𝗲𝗱 𝗺𝗮𝗰𝗵𝗶𝗻𝗲 𝗲𝘃𝗲𝗿 𝗺𝗮𝗱𝗲. The switch from carbon fiber to steel was born out of desperation. Carbon fiber at room temperature looks lighter, but at cryogenic temperatures (the extreme cold where rocket fuels become liquid), strain-hardened stainless steel (steel strengthened through mechanical working) matches carbon fiber's strength-to-weight at 1/50th the material cost. Steel's higher melting point also dramatically reduces heat shield mass, so the steel rocket actually weighs less. The engineers had been working on the carbon fiber problem for years. Sometimes the limiting factor is not effort but the wrong material. The willingness to kill a years-long approach and start fresh is rarer than technical skill. 𝟭𝟮. 𝗛𝗶𝘀 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝘀𝘆𝘀𝘁𝗲𝗺 𝗶𝘀 𝗹𝗶𝗺𝗶𝘁𝗶𝗻𝗴-𝗳𝗮𝗰𝘁𝗼𝗿 𝗵𝘂𝗻𝘁𝗶𝗻𝗴. Elon runs weekly (sometimes twice-weekly) engineering reviews with skip-level meetings where individual engineers present without advance prep. He mentally plots progress points across weeks to determine if a team is converging on a solution. Time is allocated not to what is going well, but to whatever the current bottleneck is. If something is working great, he stays away. Most managers optimize for being informed. Elon optimizes for being useful at the point of highest leverage. That is a fundamentally different operating system. "Those who have lived in software land don't realize they're about to have a hard lesson in hardware." The full podcast is worth your time. Link in replies.