Grindr wants to be the everything app for gay men; investors are still deciding whether it can pull it off
George Arison is done letting Wall Street's "Grindr discount" go unchallenged — in a wide-ranging Q&A, the CEO walks us through how AI, a controversial $350-plus EDGE tier, and a bet on healthcare and long-distance matchmaking are turning Grindr into the "gayborhood in your pocket" he's been promising since 2022.
Strategy’s Bitcoin Is $2.8 Billion in Profit—Is Saylor Teeing Up a Buy?
A Bitcoin rally to around $79,000 lifted the company's 840,447 BTC roughly $2.8 billion above its cost basis, as Saylor's "We're Back" post fueled speculation that Strategy may resume buying.
Polygon Quietly Patched Security Flaws in Two Hard Forks Before Disclosing Them
The Austin and Kyoto hard forks, deployed quietly on the Bor and Heimdall clients before public disclosure, closed denial-of-service and consensus-hardening flaws that Polygon says were never exploited.
Ex-White House Teleprompter Operator Fined for Prediction Market Insider Trading
Gabriel Perez used his access to Trump's speeches before delivery to bet on "presidential mention market" contracts, profiting more than $107,500 before the CFTC caught up with him.
Musk’s faster path to more gas turbines comes with pollution problem
Elon Musk says a secretive new SpaceX foundry will let him cast his own turbine blades and get gas power online 18 months faster than anyone else — but it's a bet on a fuel source that's already triggering lawsuits and health studies everywhere his (and others') turbines have gone in.
After Their AI Models Hacked Real Companies, AI Labs Call for Stronger Cyber Defenses
More than 100 AI, security, finance, and technology organizations want governments and industry to prepare for attacks powered by increasingly capable models.
“We’re not doing 30 bets a year”: Vijay Pande on betting small after running $4 billion at a16z
Vijay Pande — who left a16z's roughly $4 billion biotech practice last year to start the much smaller, AI-native VZVC — talks about why biology is finally shifting from a "discovery" science to an "engineering" one, why clinical trials are still brutally expensive, and why he thinks open, shared datasets (not walled-off ones) are what will actually let AI transform medicine.