Niko »» retweeted
Introducing Isometric SF A pixel-art map of the entire SF Bay Area, over 1,300 square miles, all painted by Klein, a 4B-parameter image-to-image model, on @modal.
Explore the map now!
isometricsf.com
Niko »» retweeted
Das Startup Anthropic: keine 6 Jahre alt, fast halb so viel wert wie der DAX.
NVIDIA: 33 Jahre alt, mehr als doppelt so viel.
Die soziale Marktwirtschaft bleibt nur erhalten, solange die Wirtschaft schneller wächst als der Sozialstaat. Gerade ist es umgekehrt.
Also: Reformen. Keine Frage. Und dann Innovation Powerhouse. In Jahren, nicht Jahrzehnten.
Niko »» retweeted
First of Kind: The @rauchg interview
Season 3 starts now. I sat down with Guillermo in San Francisco to talk about layout shift, random acts of AI, and a dragon painted in a single stroke.
00:00 Human Effort Is Still Underrated
00:44 Chief Executive, Chief Designer
02:33 Two Bets: Software and English
05:15 Gmail Was My Siren Call
11:06 Exposure Hours
14:49 Layout Shift / One Stroke Dragon
17:10 No Random Acts of AI
25:17 Can Agents Have Taste?
30:15 Software Factories and Manufacturing Agent Customers
34:59 Everything Is Communication
38:04 A New American Story
41:52 Lifemaxxing
Guillermo Rauch is the founder and CEO of @vercel. Growing up in Argentina, he taught himself English in order to teach himself programming, then went on to create @nextjs and other foundational technology for the real-time web.
In our conversation, Guillermo explains why he designed Vercel’s first command line before writing any code, why layout shift erodes trust, and why his company won’t commit any “random acts of AI.”
G is not just a chief executive. He’s a chief designer.
—
Guillermo Rauch: One Stroke Dragon
First of Kind, S3:E01 @firstofkind
Hosted by @soleio and produced with @room3nyc
Powered by our sponsors:
@framer @noondesign @bot @tryramp @vercel @meetgranola @profound
Niko »» retweeted
Chamath Palihapitiya just raised a pretty serious concern about the AI boom and I think this could become one of the biggest issues facing the bond market over the next few years.
For context, the largest AI companies have accumulated an estimated $340 billion to $400 billion in debt, and the amount of money they need to raise is only getting bigger. Companies like Google, Amazon, and Meta are spending hundreds of billions building data centers, purchasing GPUs, expanding power infrastructure, and developing AI models. The problem is that even some of the most profitable companies in the world are reaching a point where their operating cash flow isn't enough to comfortably finance all that spending.
@chamath estimates that the additional financing these companies will need through the end of 2027 could equal roughly 30% of everything the US Treasury is expected to issue over that same period. Think about what that means. Some of the largest corporations in America are now competing with the U.S. government for capital from the same institutional investors, pension funds, insurance companies, and bond funds. If these companies continue flooding the bond market with hundreds of billions in new debt, investors may demand higher yields to absorb all that supply. That creates the potential for upward pressure on borrowing costs across the economy, including mortgages, corporate loans, and government debt. And higher yields would also put pressure on stock valuations, especially growth companies whose valuations depend heavily on future earnings.
What's particularly interesting is how dramatically the economics of Big Tech have changed. For years, companies like Google and Meta were essentially cash generating machines with relatively modest capital requirements. Now they're becoming some of the most capital intensive businesses in the world. They're spending enormous amounts of money today on infrastructure that may take years to generate sufficient returns, while committing themselves to additional spending as AI demand continues growing. And this extends well beyond Big Tech. Companies like Oracle, CoreWeave, and Nebius are also financing enormous AI infrastructure projects. The more dependent this entire ecosystem becomes on debt financing, the more sensitive it becomes to interest rates, credit conditions, and investors' willingness to provide capital.
S&P just put a number on $META's AI bill, and it's kinda ugly
After the close Friday, S&P cut Meta's credit outlook to NEGATIVE
It kept the AA- rating, but it now sees Meta burning cash for 3 straight years
It models free cash flow at -$22B in 2026, -$71B in 2027 and -$39B in 2028. It used to expect Meta back in the positive by 2028
The reason is capex. S&P now sees over $225B in 2027 and $252B in 2028, way above its old forecasts of $163B and $178B
It also sees leverage topping 1.0x as early as 2027, the level that puts the AA- rating at risk
And S&P says Meta's ability to make money from AI is more limited than its peers. Meta says it "respectfully disagrees"
Yesterday I said the fear right now is the BILL. S&P just made it official
Niko »» retweeted
I recreated subvocal in 9 minutes with one prompt for AirPods Pro 3.
Source: github.com/joeblau/subvox
We’ve raised $1.3M from YC & Afore Capital so you never have to type or speak again.
Typing is slow. Talking into your computer is awkward. Subvocal fixes both
Our glasses give you the speed of speech without you making a sound or touching a keyboard.
It tracks your internal speech muscles with non-contact sensing and decodes silent, almost invisible mouthing into text at more than 200 words/min.
Pre-orders are now live at:
subvocal.co/preorder?utm_sou…
Niko »» retweeted
Germany introduces new sugar and AI taxes within a few months, but when entrepreneurs ask for changes to simplify employee stock options, notary processes, or EU Inc., it takes thousands of people more than 10 years of lobbying to make simple changes.
I’m so fucking sick of our incompetent politicians. It doesn’t matter which party you vote for; it truly feels like we’re governed by a bunch of clueless boomers, too stupid to work together to fix education, healthcare, welfare, mass immigration or anything else that requires more than two brain cells.
I’m ready to either leave permanently or hit the reset button. Afuera!
Jetzt wird es richtig lächerlich: Die Koalition debattiert eine KI-Steuer
Vor zwei Wochen brachte Digitalminister Wildberger im Tagesspiegel die Besteuerung von KI-Umsätzen ins Spiel, um den Umbau des Arbeitsmarkts zu finanzieren. Kurz darauf ruderte er bei RTL zurück, erst müsse Deutschland die Chancen der Technologie nutzen.
Gestern hat CDU-Vize Karin Prien den Vorstoß wiederbelebt. Im Stern: Wenn Wertschöpfung im Wesentlichen über Künstliche Intelligenz funktioniere, müsse das auch besteuert werden, anders gehe es nicht.
Immerhin: Merz steht der Sache kritisch gegenüber. Beschlüsse oder Gesetzentwürfe gibt es keine.
Was es auch nicht gibt: eine Definition.
Was genau ist ein KI-Umsatz?
Der eines Unternehmens, das ein Modell trainiert?
Der eines, das eines nutzt?
Jede Software enthält heute KI-Komponenten. Entweder trifft die Steuer irgendwann jeden Softwareumsatz, oder sie trifft genau die vier US-Konzerne, die hier ohnehin das meiste Geschäft machen.
Und das ist der eigentliche Punkt. Deutschland hat keine Frontier-Modelle, keine nennenswerte Rechenkapazität und rund 5 Prozent Anteil an der globalen KI-Infrastruktur. Diskutiert wird gerade die Verteilung einer Wertschöpfung, die hier niemand erzeugt.
Man beschließt die Ernte, bevor man gesät hat. Mit dem Wissen, dass es am Ende ohnehin nichts zu essen gibt.
Niko »» retweeted
It’s almost incomprehensible how wide the distance is between someone who’s working at the frontier with AI and basically everyone else right now.
The crazy thing is these lines are not converging, but only growing farther apart. If the curve of AI progress had leveled off, it would certainly have given most people and companies time to catch up or implement their workflows in a standardized way. The technology would have neutralized competitive advantage because everyone would be using it the same way.
But what’s happened is the opposite. The curve of AI progress is basically going vertical right now, which means if you had codified your processes 3-6 months ago you’re likely already behind again. Now imagine most companies that kicked into gear a year ago and thought that they were done. Even further behind now.
I’ve never seen a technology in my life and career that improves at this rate, which consequently means you need to upgrade your expectations at a similar rate. Our brains weren’t wired for this, and our organizational change management processes certainly weren’t either.
With any form of recursive self improvement, things just get wilder. It’s a time when you will need to be constantly reevaluating the things that didn’t work just a couple months ago to see if they now can be solved. AI native companies certainly have a strong advantage due to this right now, so now it comes down to can the bigger companies keep up. Wild times.
Niko »» retweeted
America just built a robot factory that makes circuit boards 2x faster than China
which means hardware startups can finally move almost as fast as software startups
here's why this is a bigger deal than you think:
> when you build software, you can change the code and test a new version the same day
> when you build hardware, every new version needs a new circuit board, the brain inside every gadget
> but most of those boards get made in Asia, so every new version means weeks of waiting for a shipment
> getting them made in the US has been slow and expensive because building them by hand costs too much
> that means every new idea costs a hardware team weeks before they can even test it
> but now CircuitHub's new factory, The Grid, fixes this with robots
> each board rides between robots that add the solder, place the parts, melt it all together and check the result
> every board takes its own route through the factory, so nothing ever has to stop and reset
> you upload your design and get your boards back in as little as 3 days, even if you only need one
> CircuitHub says that's twice as fast as a typical quick-turn shop in Shenzhen
> now a robotics or drone startup can test a new version every few days instead of every few weeks
> and more versions means better products, built faster, and built a lot closer to home
the hardware supercycle is starting to heat up and im loving it!!
PCBs made in America. Twice as fast as Shenzhen.
Today @CircuitHub is unveiling The Grid, our factory-scale robot in Massachusetts that builds circuit boards on demand.
No changeovers, no per-design setup. Prototypes and production batches, fully automated.
Niko »» retweeted
@JensenHuang at GTC:
"Here's Trajectory and Harvey using Nemotron, post-trained it and created their own frontier-level capability."
"With customization and with partners in the ecosystem that we work with, you could turn these models into the frontier.
And a result, turn your proprietary data into sovereign intelligence"
It's great to be doing work with such amazing companies like @harvey and @nvidia over here at @trajectorylabs!
Niko »» retweeted
It feels pretty fitting for @JensenHuang & @nvidia to end their European tour with Microducks on stage.
Microduck was designed and engineered in Europe (more precisely Bordeaux, France) by the @pollenrobotics and @huggingface teams. With American capital and ambition + Chinese manufacturing genius, it became the most popular robot of 2026 with over 15,000 sold all over the world!
I believe Europe has more opportunity to shine in AI than in any previous tech wave. We intend to prove it with @huggingface @nvidia and the whole open-source AI community in the coming years!
Let's go European AI 🇪🇺🇪🇺🇪🇺
Niko »» retweeted
Jensen spent 10 min of his keynote asking microducks to sit, then explained Nvidia's roadmap to them 🥹
Niko »» retweeted
I spent 48 hours in SF hanging out with billionaires, data labs and AI founders and execs running $1B to $100B companies.
My observations:
1. Sooo MANY stories of data brokers making like $2M a WEEK selling company data to labs. I can't tell if it's the beginning or a bubble, and I kept wondering which niches are left. Digging into it actively.
2. At dinner, someone asked the table, "If a new model drops next month, does your company get better or worse?" HALF the table went quiet! I think that's the best question to ask about any AI startup right now.
3. The bar people talk about now is hitting $1B in revenue in 12 months (I guess that's the new unicorn?). What I didn't hear much about is retention. AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention.
4. It's pretty clear we're living through the reinvention of the computer. The model is the CPU, the harness is the operating system, and skills and plugins are the apps. Thinking about it that way makes it easier to see where the whitespace is.
5. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now.
6. Agent harnesses feel like the new GPT wrappers, in a good way, especially vertical ones. The best teams I talked to treat the model as swappable. One founder walked me through routing different models to different jobs: one for taste and visuals, a cheaper one for the everyday stuff, another for text.
They use prompts they can move across models over fine-tuning, and A/B test the output on what users actually do with it: do they edit it, export it, share it? A vertical harness is basically four things: the connectors for that industry's data, evals written by people who know the work, rules for what the agent can and can't touch, and a clean screen for a human to review. The model is maybe 20% of it.
7. There's a lot of reverse engineering going on/cloning going on more than I've ever seen. People are decompiling software and rebuilding it with agents, and someone showed a suite of like 10 apps that are worth $5B+ each all that he cloned open source. Me and everyone are still thinking through what it means when software gets this easy to copy.
8. My guess is the value moves to data. If the software can be rebuilt quickly, what's worth paying for in a legacy SaaS company is the years of customer data and workflows inside it. Some SaaS companies are secretly data companies.
Gets me thinking about how do you truly value data for this saas companies? Like if we were buying these dying saas companies at 2x ARR before (as example), maybe there is a better metric. Idk, just thinking out loud here.
9. It feels like a good chunk of legacy software won't make it to the agentic era, especially anything built around people clicking through a lot of screens.
10. Every company I talked to wants to pipe its internal data into one place and expose it to agents through MCP. Then they look at the data and realize it's a mess: five versions of the same customer, old Slack channels, PDFs nobody can search. Cleaning that up feels like a big consulting opportunity!
11. A lot of founders are building the basic building blocks for agents: APIs, data layers and tools. Some of the companies I saw barely have a UI because the main user is an agent. I really believe the startups that build primitives to this agentic era will do extremely well. Building blocks is the best way to think about it.
12. Labs can get plenty of training data, but it's harder to get real examples of agents failing inside companies. Whoever has those logs has something valuable.
13. Someone running a big consumer company told me the next fight is over memory. The model that remembers the most about you wins, and the smartest model matters less than people think.
14. Physical AI came up a lot. Astra I think was the first model that got people into AI can actually do CAD, and I think a lot of people are thinking what does vibe manufacturing really look like. The line I keep thinking about came from a robotics founder: the hardest problems in AI are deployment problems now, not research problems. Their robots work on their own, call a human when they get stuck, and every one of those calls becomes training data.
15. Cybersecurity companies are having a moment and are actually cool companies to build now, especially the ones that clean up after a breach. Every agent with access to your systems is a new door into your company, and a lot of those doors were left open.
16. Some startups are worth more dead than alive now. A shutdown company with 5 years of Slack, email and code can get paid for licensing all of it. I wouldn't be surprised if founders start factoring that into when they shut down.
17. People are starting to talk about monetizing the agent web. It feels really early, but when the most popular user of the internet is an agent, what startups should you be building?
18. I think agent insurance is coming. Once an agent makes an expensive mistake, insurers will want audits before they cover anyone.
19. Several people said the hire they want most is someone with taste who can write evals. The models are getting good at generating ideas, so the hard part is judging which ones are good.
20. New trend I observed: startup raises VC, uses venture dollars to become a creator, startup fails, founder falls back on being a full-time creator and incubates other products bootstrapped.
21. Getting SIGNIFICANT distribution is HARD right now. Founders are sponsoring buses, buying billboards like crazy and throwing parties with famous DJs to get noticed. Kinda feels dotcom era in that sense.
Attention is what's scarce! The growth guy going viral sharing his UGC strategy from Wispr Flow is a good example. It's the sauce everyone wants, and I truly believe there are probably only 50 people on the planet who know how to scale these types of businesses efficiently in this era.
Always good to get that dose of SF. I felt sooo lucky to have such an incredible trip during such an incredible time in building businesses. Surreal in so many ways.
Happy to be home and locked in.
Until next time!
Niko »» retweeted
launched a model
accidentally served trillions of tokens a day
29.4% of the fortune 500 showed up
raised a really big series A from @a16z
it's been 3 weeks
we would like to sleep now
Niko »» retweeted
FLUX 3 is #1 on Physics-IQ, @GoogleDeepMind's benchmark for physical world understanding in video models.
How Physics-IQ works: given the start of a real filmed experiment, can a model predict what physically happens next? Tests span fluid dynamics, optics, solid mechanics, magnetism and thermodynamics, covering how liquids flow, light behaves and objects interact.
In most cases, we substantially outperform all other frontier models, Seedance 2.5, MiniMax H3, Gemini Omni 1.1 Flash, Veo 3.1 and Sora 2, Cosmos3.
The FLUX 3 base model outperforms all other foundation models, while FLUX 3 paired with a physics verification layer scores even higher.
The FLUX 3 backbone, with its strong physics understanding, gives FLUX 3 Action it’s strong action prediction for robotics, while also giving FLUX 3 Video physically accurate motion when you’re creating content, making ads, films and product shots.
Niko »» retweeted
Mehr Behördengänge bei Adler AI:
🏛️ Steuer-ID erneut mitteilen lassen
🙏 Arbeitsuchend melden, Arbeitslos melden und Arbeitslosengeld beantragen
🫰 Unterhaltsvorschuss beantragen
🔤 Namensänderung. Nachnamen und Vornamen aus wichtigem Grund, der Name nach der Scheidung und der Nachname eines Kindes.
🙆♂️ Verpflichtungserklärung abgeben
🏡 Grundbuchauszug beantragen
♿ Schwerbehindertenausweis beantragen
🙋♂️ Bürgergeld (Grundsicherungsgeld), Grundsicherung im Alter und Hilfe zum Lebensunterhalt beantragen
🛑 Halteverbotszone für den Umzug beantragen
🇩🇪 Einbürgerung und Aufenthaltstitel
🙏 Wohngeld beantragen
Weiter Weiter immer Weiter.
