been making a single-page app with pocketbase.io this week and it's been a nice experience. I like making single-page JS apps with a Go backend API and this means that I don't have to write the Go backend. Really impressive project given that it's built by one person in their spare time.
OpenAI solving one of the most famous math problems is extremely impressive, and of little impact to most people's lives; Meta's Muse agent launch has the potential to be the exact opposite.
Then there's another possibility which is that it actually already has worked but just the productivity boost isn't as big as would be obvious if people got 10% more productive. That would still be pretty impressive because it's hard to get a 10% across the board uplift.
we tend to describe progress in agents as progress in autonomy: first they could do five minutes of work, then an hour, now we talk seriously about agents running for days. that’s impressive, but autonomy is a capability, not a product direction! the Job To Be Done tells you whether to use it.
making intelligence cheap does not automatically make “agency” cheap. people are constrained by time, money, confidence, health, education, institutions, family, geography; a model does not magic any of that away. there’s a perfectly believable future where these tools mostly compound the advantage of people who already have the skill, taste, money and the spare time to use them well.
Let Over Lambda by Doug Hoyte is perfect for those three people in the world who find The Art of the Metaobject Protocol underwhelming. One of the most impressive books I've read.
But okay, so to begin with, I think when it comes to TypeScript, Rust fits in as the backend language. That's where I would put it. I wouldn't use it in the front end. I think it's a pretty good fit for backends, API servers.
So usually it will never show up in say a backend server. You would have zero uses of unsafe there. Generally when unsafe is used, it's to add a new feature to the language.
My opinion is that the least mature area is front end. There have been some attempts to compile Rust to Web Assembly and then run it on the web as a front end as a replacement for TypeScript. But if I was writing a web server, I would totally use Rust for the back end and TypeScript for the front end. I would not really go the web assembly route.
If I say it reads a bit like fanfic for Neumeier's own work, that sounds like I'm damning it, but I actually enjoyed it, because, I wanted good things to happen for those characters, who'd had drama enough and to spare.
Not every plank in his argument is convincing, and the research has evolved since the book first came out a decade ago, but the ambition is impressive and the framework holds up.
I keep an eye on China’s open models, and it’s impressive how quickly they catch up. GLM 4.6 and Kimi K2.1 are strong contenders that slowly reach Sonnet 3.7 quality
I keep an eye on China’s open models, and it’s impressive how quickly they catch up. GLM 4.6 and Kimi K2.1 are strong contenders that slowly reach Sonnet 3.7 quality
As for me personally, I tend to use these tools as a backend data store and use Jupyter notebooks as well as my own custom built annotation interfaces for most of my needs.
You should remember that the best AIs can perform at the level of a very smart person on some tasks, but current models cannot provide miraculous insights beyond human understanding.
I’ve evaluated agent performance across different languages my workload, and if you can choose your language, I strongly recommend Go for new backend projects.
It's just that Zig, C, C++, all those languages that were being tested, they're all LLVM backends, right? That's the one that actually turns the thing into the executable part. And if there's a variation in speed, it just means in one language you didn't quite express what you are supposed to correctly.
It's easy to get impressive-looking results if you're comparing against a poorly-tuned baseline, and that observation turns out to explain a surprising fraction of supposed improvements.
I think it's even more impressive what OpenAI did in 2022. At the time, no one believed in mixture of experts models at Google who had all the researchers. OpenAI had such little compute and they devoted all of their compute for many months, all of it, 100% for many months to GPT-4 with a brand-new architecture with no belief that, "Hey, let me spend a couple of hundred million dollars, which is all of the money I have on this model." That is truly YOLO.
Where housing costs are moderate, friends and family have bigger homes. When they are higher, friends and family don’t have space to share, and this is often what puts a vulnerable person onto the streets.
A fresh take on navigating the tech the interview process, tailored for frontend engineers. She wrote the book after she found Cracking the Coding Interview to be too Java/backend-focused. The book comes with 1, 2 and 4-week learning plans as well. A great book to start with.
Installed generators cost ~$800/kW, and the data center capital cost, including servers, is ~$40,000/kW, so adding 1% more makeup compute capacity is money ahead of purchasing generators.
Therefore, land sparing is more likely to take place, even at the local level, when yields of staples go up. The situation is different for some internationally traded products like soy and palm oil.
I don’t view Keynes primarily as an economist, rather I see him as a British aesthete rationalist who did economics in his spare time, and fortunately he had lots of spare time.
I think things like MuZero and AlphaGo are so much more impressive because these things are playing beyond the highest human level. The language models are writing middle school level essays and people are like, wow, it’s a great essay.
It’s really impressive how Stapledon just casually scatters around handfuls of jewels that lesser authors might belabor singly throughout an entire book.
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