〽️alum #goblue, tech investor, 🤖🚗📈 Tesla 🤓
Joined June 2011
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Kristin Hendricks retweeted
Technology is the greatest equalizer. Net worth no longer decides which phone you carry. Everyone uses the same iPhone.
You no longer need a fortune for a chauffeur. Tesla Full Self-Driving does that.
Need a personal assistant? Spin up as many Grok bots as you like. Each is as dedicated as the last.
Not far in the future, Optimus will push this further: the same quality of care for everyone, better with every software update.
Anyone else having random lane changing issues on the highway with v14.3.10 ? The last couple point releases have had this issue for me. FSD on hurry mode randomly turns on the right blinker from the left lane when there is a semi truck or multiple cars in the right lane in the way and could easily pass from the left lane. 🤷🏽♀️🤦🏽♀️ @teslasi @pduan
“Let me be clear,” he said slowly. “This vehicle must be designed as a clean Robotaxi. We’re going to take that risk. It’s my fault if it f–ks up. But we are not going to design some sort of amphibian frog that’s a halfway car. We are all in on autonomy.”-Elon quote from Walter Isaacson’s book. Autonomy has arrived.
I am currently in downtown Austin. There are @Tesla Cybercabs EVERYWHERE. All of the Cybercabs in these clips have no steering wheels or pedals.
Makes the vibe downtown feel so futuristic. Can’t wait for tomorrow! 🤖
Kristin Hendricks retweeted
Just listened to the KeyBanc interview with $MU Chief Business Officer, Sumit Sadana.
The highlights were absolutely INCREDIBLE and VERY bullish. They include:
- “Business continues to be exceptional”
- “Since earnings [on June 24th], demand from our customers has increased even further”
- “Conditions will continue beyond calendar year 2027 and 2027 calendar year will be tighter than 2026 because demand growth is faster than supply”
$250 Billion of investments in coming years
- “We are at such early stages”
- The growth in HBM memory means for every 100 bits, you need 3-400 bits of DDR memory, so it reduces DDR supply even more
- Building a manufacturing fab and ramping it is *significantly harder* than building a data center and takes years
- Every customer is saying #1 constraint they have is DRAM (not power, or other things)
- We expect to have a prolonged excellent financial performance “for a very long time”
- “The nature of our engagement with customers is at levels I have not seen in my entire career.”
- Working on engineering designs with our customers that are planned for beyond 2030
- New Strategic Customer Agreements (SCAs) are far better than previous LTA (Long Term Agreements) because: they cover longer time horizon of 3-5 years, they are binding commitments by year with “Take or PAY” with very stringent and binding terms, backed up by “tremendous amount of up-front cash that we hold on our balance sheet.” The SCAs have pricing that are either “floating” (market price) or a price band that have both a ceiling & floors. Floor pricing provides better gross margins than historical peaks on margins.
Physical AI such as humanoid robots might drive future demand even greater than what we’ve seen. May be astronomical!
Kristin Hendricks retweeted
Elon just said something extremely bullish for memory:
“One must always consider the limiting factor here. The limiting factor currently is memory.
Memory output is increasing by around 20% per year. Normally, that would be fantastically fast and amazing for any large, mature industry.
But ask yourself: Is demand increasing by 20% a year? No. Demand is increasing by 200% a year, maybe higher.
So, if demand is increasing much faster than supply, Economics 101 would suggest that prices increase. They do not decrease.”
Elon said on the SpaceX earnings call that the “limiting factor currently is memory.” He said that even as more memory capacity comes online by 20%, the demand is 200% and that means “prices increase, not decrease” Aka bullish Micron $MU
Kristin Hendricks retweeted
Game theory suggests memory LTAs are likely to be durable.
And yes, Nvidia may have a significant cloud business via revenue shares.
GAVIN BAKER: NVIDIA IS NO LONGER JUST A CHIP COMPANY.
Gavin Baker recently laid out one of the sharpest observations about the current AI hardware cycle, and it explains why Nvidia's multiple looks strange relative to the strategic position the company actually occupies.
The starting point is a shift in how semiconductor supply is being allocated. Historically, buyers with enormous volume like Apple could break long-term agreements with suppliers whenever they wanted. There was no meaningful consequence, because the supplier had nowhere else to go.
That world is over. In the current cycle, there are at least four major memory buyers with genuine scale, plus a wave of AI startups adding to demand. The dynamic has flipped. If a hyperscaler breaks an LTA on price, the supplier can now retaliate by reallocating volume to a competitor. In a cyclical industry where oversupply is always followed by undersupply, breaking an LTA today can cost you your entire allocation the next time capacity gets tight.
That leverage is one reason Nvidia's position is so unusual. Every constraint in the AI buildout tilts in its favor. Nothing on earth is more financeable than an Nvidia GPU. And on land and power, Nvidia is playing the matchmaking chess game between customers, energy suppliers, and infrastructure partners.
The most interesting development Baker highlighted is Nvidia's new business model. He described it as a credit wrapper with a revenue share above a certain GPU price floor. Nvidia is financing customer deployments while retaining upside if GPU prices stay elevated. This converts Nvidia from a pure hardware vendor into something structurally closer to a cloud franchise via royalties on the compute being deployed on its chips.
Nvidia could end up with an effectively massive cloud business very quickly, not through building data centers but through collecting royalties on the compute those data centers produce.
The market is still pricing $NVDA as a semiconductor company. The company itself has already moved beyond that model. The gap between the two will eventually close.
@InvestLikeBest @patrick_oshag @GavinSBaker
Kristin Hendricks retweeted
Market is overreacting to hyperscale credit spreads widening from my perspective. TL;DR Spot pricing for renting GPU compute materially above contracted rates implies hyperscalers are underearning while operating cash flow acceleration is an underestimated source of funds for AI capex.
The fact that spot prices for GPU rentals are at least 2x higher than contracted rates is the missing piece from the discussion about hyperscaler credit, which is the only fundamental factor behind this selloff. Multiple private companies are planning on spending at least 2x more per GPU for compute as contracts roll-off and some have spoken about this publicly.
As contracts roll-off, hyperscale growth rates are going to continue to accelerate as their installed bases of compute reprice higher. Hyperscale operating cash flow growth using a mix of estimates and actuals is modeled to accelerate from 31% in the first quarter of 2026 to 50% in the second quarter. This acceleration should continue for the rest of the year and this is not in estimates which incorrectly model a deceleration in the third quarter from my perspective.
Some math. Consensus estimates are probably for 25-35 gigawatts added by hyperscale and neoclouds in CY28 (using a range as standing up datacenters is hard and a lot of the neos plus labs are still private). At 60b per gigawatt, that is 1.5 to 2.2 trillion in capex. Consensus estimates for hyperscale/neo operating cash flow is 1.3 to 1.4 trillion. I think this gets revised up materially as contracts reprice and growth accelerates so the 100b to 700b that would hypothetically need to be plugged by debt goes away. And their credit profiles materially improve. Not to mention the said 100b to 700b would be less than 1 turn of incremental leverage on consensus EBITDA estimates. And obviously the Nvidia and Broadcom “credit wrappers” help improve creditworthiness as well given their FCF profiles.
OpenAI, Cursor/Grok and the various Open Source inference clouds have accelerated materially over the last two months per public data and Anthropic continues to grow insanely fast while likely generating FCF. This - along with the fact that spot prices for GPU rentals are so far ahead of contract - are the missing pieces from the BofA chart on hyperscale FCF vs. semiconductor FCF.
Hyperscalers are underearning and anyone who signed a contract for GPU compute in 2024 and 2025 is overearning. Operating cash flow will be enough to fund capex but as contracts reprice and cloud growth continues to accelerate then spreads likely come in as well.
Would also note that CDS markets are easy to manipulate - was a huge feature of the GFC - short the stock and then buy the CDS. So I would not put attach much signal to CDS.
Net, net I’m not that concerned about the widening spreads in hyperscale credit. The real risk is that bringing power online and energizing all these GPUs is really hard but we are getting better at this every day.
🤖 Made with AI
Kristin Hendricks retweeted
The single most underrated exercise to improve your health is to get 7000-10,000 steps a day.
Tesla Q3 car backlog is going to get even bigger. Plus “trade in your gas car for 2,000 free Supercharging Miles” is still being offered.
Kristin Hendricks retweeted
Tesla FSD % adoption has been historically touted at single digits to low teens.
Now in North America (largest FSD capable area), 55% of car sales are shipping with the FSD subscription selected by the buyer.
FSD is selling cars. Likely a point of meaningful inflection 👍🏼
