1 Trump advisers had been blindsided by Elon Musk’s group’s supply to federal staff
Officers weren’t consulted about plans to induce civil service staff to resign. (WP $)
+ The novel sweeping measures are only the start. (Vox)
+ The e-mail staff obtained cribs from Musk’s controversial Twitter memo. (Ars Technica)
+ If Musk will get his method, the US authorities might find yourself like X. (NY Magazine $)
2 Meta has agreed to pay Trump $25 million
To settle the censorship lawsuit Trump introduced in opposition to it again in 2021. (CNN)
+ Mark Zuckerberg predicts 2025 will likely be an enormous 12 months for Meta’s authorities relations. (Insider $)+ Fb continues to be targeted on successful over creators to make it cool once more. (The Data $)
3 How tech staff are quietly combating the rise of MAGA
Whereas their employers are shifting rightwards, staff are resisting. (NYT $)
4 Microsoft and Meta have defended their AI spending
DeepSeek’s success has raised severe questions on Huge Tech’s AI budgets. (Reuters)
+ Zuckerberg claims to not be nervous by the Chinese language startup’s speedy rise. (The Verge)
+ How a high Chinese language AI mannequin overcame US sanctions. (MIT Know-how Assessment)
5 Mr Beast is getting severe about shopping for TikTok
The YouTuber is part of an investor group that’s secured greater than $20 billion. (Bloomberg $)
6 How the US plans to make use of house lasers to destroy hypersonic missiles
It bears greater than a passing resemblance to Ronald Reagan’s 1983 program. (FT $)
+ Find out how to combat a warfare in house (and get away with it) (MIT Know-how Assessment)
7 Waymo’s autonomous taxi service is increasing to new US cities
San Diego, Las Vegas, and Miami are on the checklist. (WSJ $)
+ Self-driving Tesla taxis will hit Austin’s highway in June, apparently. (TechCrunch)
+ EV batteries boast an extremely lengthy lifespan. (IEEE Spectrum)
8 The right cryptographic machine is feasible
It’s only a little bit of a ache to construct. (IEEE Spectrum)
+ Cryptography could supply an answer to the huge AI-labeling downside. (MIT Know-how Assessment)