Brought to you by
Top stories today:
- Apple’s incoming CEO Ternus said to revamp design team
- OpenAI burns $3.7B in Q1, top $73B cash
- Intel stock +11% as Trump touts Apple chip deal
- Kalshi tops $2B in annualized revenue, weighing IPO
- Polymarket allegedly pays creators for deceptive videos
0. Data and calendar
All values as of 6 AM ET / 3 AM PT, other than S&P500 and NASDAQ close (4 PM ET / 1 PM PT).
All times are ET.
Listen to our AI-generated podcast summarizing today’s newsletter (beware of hallucinations):
1. Apple’s incoming CEO Ternus said to revamp design team
Restoring Apple’s design studio is expected to be Ternus’ early focus.
Ternus has reportedly been more involved with Apple’s ID group than Cook.
Several major Apple products have retained largely unchanged designs for nearly a decade.
Sep.: Ternus is expected to take charge as Apple’s new CEO.
Apple TV and HomePod mini with Apple Intelligence are in advanced testing.
Late 2027: Apple spectacles are expected to debut.
The best investors know small problems compound fast. Eye bags and tired skin are no different. You need to address them early, before they become the new normal.
That’s why Particle Anti-Aging Face Cream sold out so quickly once founders and investors discovered it. More than 1 million men now use it to combat eye bags, wrinkles, and dark spots. The 6-in-1 formula combines 12 high-grade ingredients in a single anti-aging solution built for men.
If you want that sharper, younger look that signals energy, discipline, and confidence, this is the move. Bay Area Times readers: Use code BAY20 for 20% off and free shipping before it sells out again.
*Sponsored.
3. OpenAI said to burn $3.7B in Q1, top $73B cash
$21.3B+ net loss in Q1, including a ~$12.4B accounting charge.
$9.3B operating loss in Q1, including $2.3B+ in share-based compensation.
$3.5B cost of revenue, largely from serving AI models.
39% gross margin in Q1, up from 33% a year earlier.
$8.6B spent on R&D in Q1, including model-training costs.
Fill key roles faster, without waiting weeks or months for the pipeline to behave.
AI-assisted matching and structured vetting help you find people who fit the role and the team.
Cut time and cost with a process built for scale, not endless back-and-forth.
*Sponsored.
