Ramit Sharma

Swift 6.2 concurrency journey: - Start single-threaded. - Introduce asynchrony for latency. - Embrace concurrency for performance - Leverage actors for robust state isolation.

Let's go!

It was the best of times, it was the worst of times. — A Tale of AI

My new SwiftUI book is finally out 🎉 I wrote "The SwiftUI Way" for developers who feel like they are fighting the framework as projects grow in complexity. It will help you align your code with SwiftUI's internal expectations to avoid common pitfalls. books.nilcoalescing.com/the-swiftui-way

More power = more workers More charts: a16z.news/p/charts-of-th…

Jensen Huang just told every college student on Earth the one thing that determines whether they get hired. It is not their GPA. It is not their degree. It is not their internship. Huang: “If I have a choice between two, I would hire the one who’s expert in using AI.” He did not say prefer. He said hire. One gets the job. One does not. The only variable is whether you learned to use the machine. Then he went down the list. Accountant. Hire the one who uses AI. Lawyer. Hire the one who uses AI. Marketing. Supply chain. Sales. Customer service. Every function. Same answer. The person who can command the model does not have an edge. They are the only candidate in the room. Everyone else is applying for a job that no longer exists. Huang: “If you’re a carpenter, if you’re an electrician, go use AI. If I were a farmer, I would absolutely use AI.” That line should demolish every assumption about who this technology is for. This is not a Silicon Valley tool for software engineers. This is infrastructure for anyone who builds anything with their hands or their head. A farmer who uses AI to optimize soil, predict weather, and manage yields is not competing with other farmers. They are operating at a level that used to take an entire department. An electrician who uses AI to model loads, simulate wiring, and quote jobs in seconds does not compete with other electricians. They compete with firms. One person with the model replaces the output of a team without it. That is not a prediction. That is Tuesday. Huang: “Every college student should graduate and be an expert in AI.” Not familiar with it. Not aware of it. Expert. The university system is still training students to execute the work. The market already moved. It wants the person who directs the machine that executes it. Four years of tuition. Thousands of hours of lectures. And if you walk out the door without mastering the one tool that redefines every industry you could enter, you burned all of it. Huang: “I want to see what it could do to elevate my job, so that I could be the innovator to revolutionize this industry myself.” That is the part most people miss. AI does not replace ambition. It multiplies it. The carpenter who learns the model does not lose their craft. They scale it. The pharmacist who learns the model does not become redundant. They become dangerous. One person. Deep skill. Full command of the machine. That used to be called a company. The question is no longer what do you know. It is what can you build with the machine that knows everything. And the people who cannot answer that are not falling behind. They already fell.

Introducing the Anthropic Science Blog. Increasing the pace of scientific progress is a core part of Anthropic’s mission. The Science Blog will feature new research and stories of how scientists are using AI to accelerate their work. Read the intro: anthropic.com/research/intro…

Dario won.

THE APPLE APP STORE IS DROWNING IN AI SLOP people are treating the App Store like a Medium blog spitting out apps one after another. All with zero users and $0 revenue. Apple reviews that used to take hours are now stretching into WEEKS and even months > more than 550k apps were submitted just last year, highest in a decade.

My Mac Mini M4 was boring, so I knew I had to do something about it...

Swift Talk 484 The Layout Protocol (Part 1) We revisit an old layout challenge, and solve it with a custom layout. This episode is free to watch, enjoy! 😊 talk.objc.io/episodes/S01E4…

bro, it's so over for designers google stitch is insane. 🤯

reminder that you’re not behind, it’s just moving too fast

Mercury just launched Insights - an AI view of your company's finances - Tracks where your money is going & why - Flags spend increases & breaks them down by vendor - Ask it anything about your financials directly

"Anywhere from $40 billion to $150 billion of leveraged loans packaged into US collateralized loan obligations could be disrupted by the AI boom," per JPMorgan

Here's how we made ClawHub fast. Next we make ClawHub great for plugins.

26.2 has something for everyone: Large scale MoE's like Kimi2.5, wicked fast diffusion models, MXFP4 perf, consumer AMD/NV incl DGX Spark + Strix Halo, and more. Mojo gets AI skills, cond conformances, TStrings, and ... way more. All in the 7 weeks from 26.1🚀 Check it out!👇

Jensen Huang: “If that $500K engineer isn’t spending $250K a year on tokens, I would be deeply alarmed”

Terence Tao responding to a question on what advice he would give someone considering a career in math in 2026: 'Yeah, so we live in a time of change. It is, as I said, we live in a particularly unpredictable era. And I think things that we've taken for granted for centuries may not hold anymore. So, yeah, the way we... do everything, not just mathematics, will change. In many ways, I would prefer the much more boring, quiet era where things are much the same as they were 10 years ago, 20 years ago. But I think one just has to embrace that there's going to be a lot of change and that, you know, the things that you study, some of them may become obsolete or revolutionized, but some things will be retained. There'll be a lot of opportunities for things that you wouldn't be able to do before. So, I mean, in math, you previously had to basically go through years and years of education to be a math PhD before you could contribute to the frontier of math research. But now it's quite possible at the high school level or whatever, that you could get involved in a math project and actually make a real contribution because of all these AI tools and lean and everything else. So there'll be a lot of non-traditional opportunities to learn. So you need a very adaptable mindset. There'll be one for pursuing things just for curiosity, for playing around. And I mean, you still need to get your credentials. I mean, I think for a while it would still be important to sort of still go through traditional education and learn math and science and so forth the old-fashioned way for a while. Yeah, but you should also be open to very, very different ways of doing science, some of which don't exist yet. Yeah, so it's a scary time, but also very exciting.'

Yep, Composer 2 started from an open-source base! We will do full pretraining in the future. Only ~1/4 of the compute spent on the final model came from the base, the rest is from our training. This is why evals are very different. And yes, we are following the license through our inference partner terms.