Palantir making a based AI Sovereignty tweet was not on my 2026 bingo card
> 3. Tokenmaxxing hijacks your value orientation and decreases your institutional fortitude and intelligence. The pursuit of high token usage incentivizes disposable scripts over robust software — with the addictive feeling of false progress. There is a reason why those selling tokens refuse to charge based on value.
Windows 11 has a thing called "Dev Drive".
It uses a different file system - ReFS vs NTFS - which can speed up your builds.
Does it work? We tried it on VS Code...
Paul Graham explains why you shouldn’t try to be a visionary
“Empirically, the way to do really big things seems to be to start with small things and grow them bigger. Want to dominate microcomputer software for decades? Start by writing a basic interpreter for a machine with a couple thousand users. Want to make the universal website and a giant vacuum for people’s time? Start by building a website where Harvard undergrads can stalk one another.”
Paul Graham continues:
“Neither Bill Gates nor Mark Zuckerberg knew how big their companies were going to get. All they knew was that they were onto something… Maybe it’s a bad idea to have really big ambitions initially, because the bigger your ambitions, the longer they’re going to take to realize and the long you’re projecting into the future, the more likely you’re going to be wrong.”
PG suggests starting with something small that works instead.
“I think the best way to do these big ideas is not to try and identify a precise point in the future and say, How do I get from here to there? Like the popular image of a visionary. I think a better model is Columbus who thought there was something to the West—I’ll sail westward. Start with something that works, that you know works, that’s small, and then when the opportunity comes to move, move westward. The popular image of a visionary is someone with a very precise view of the future, but empirically it’s probably better to have a blurry one.”
@ThePrimeagen what if someone else is writing test cases for your code. There will always be edge cases that are missed in the first few iterations but a different person can write tests much faster since he is not attached to the implementation and is only thinking about functionality.
Just a word of advice to all struggling FPL managers out there, if you pick Kane, Haaland will bang, if you pick Haaland, Kane will bang.
If you pick both, the Robertson/Cancelo/Diaz/Saka you sacrificed to get them will all bang.
Whatever happens, you're wrong. Good luck today!
If you want to learn how to deal with structured data using Python, take a look at Kaggle's Pandas Tutorial:
• Creating, Reading, Writing
• Indexing, Selecting, Assigning
• Summary Functions, Maps
• Grouping, Sorting
• Data Types, Missing Values
• Renaming, Combining
ML YouTube Courses (6000⭐️)
I built this repo to help students discover high-quality machine learning courses.
It has helped me to find the right course and expand my knowledge in ML.
There is something for everyone in this collection.
https://t.co/C1Aw41PMEm