From Evercore ISI’s report:
NVDA’s claimed 35x TCO advantage does not resonate strongly with the average AI engineer, and there is a widespread perception that its 70%+ gross margins are excessive. There is a clear willingness to improve economics by using ASICs or “good enough” alternatives.
Some hyperscalers push back against NVDA’s 35x TCO advantage claim, arguing that the calculation does not account for power consumption around the chip, including cooling. The power component, including cooling, can account for 30–50% of total overhead costs.
No major issues have been observed at the hyperscaler level in the bring-up preparation for Rubin mass production.
Vera Rubin mass-production shipments are expected to be received by hyperscalers in 2Q26, while enterprise OEMs are expected to have access around September–October 2026.
I’m convinced that the people who charge $200 or $2000 just to see their stock picks.
Do so just because their ideas aren’t good enough.
Otherwise they would just go long on them with their own capital and retire.
This is why they get mad when they see others sharing better ideas for free.
Algorithms change but what remains true at the end of the day is: what kind of audience do you want to attract? Is your content good enough to create a conversation amongst your audience? Are you in the right channels to reach your audience? If it is, no matter the algorithm, you will find success.