I recently looked into renting an EV in Spain and instead opted for gas. It seems like the public charging infrastructure is just not all that reliable there (e.g. broken chargers + delivering less power than advertised) and fragmented when it comes to paying across many apps. Maybe this is specific to Spain after all.

Aside from that (and assuming a large enough sample size) I think it's a safe experiment to at least bet on finding profitable use cases. In 1-2 years, after this experiment runs its course, not everyone will have "unlimited" usage.

The author made compelling points regarding capex cycles and supply/demand imbalances. So how does NVDA continue to deliver these returns over the next 10 years? Are the 4 firms driving >60% of NVDA's revenue going to maintain that high capex?

All it will take is a market shock that forces just one of these companies to pivot modes from spending to cost cutting for NVDA's bottom line to see material compression. This is not to say that NVDA will disappear, but it's a very real risk that sets the stage for contagion given how coupled all this growth is.

Was an LLM really necessary to write this article? The LLM fluff glosses over a few interesting points/questions:

- Is the current claude debacle the result of compute supply that cannot match the demand? Or is it that Anthropic is being pressed to monetize its work?

- If LLM inference quality is downshifted because of those constraints, that becomes a very real problem for the end users as it effectively amounts to rug-pulling the product. It is plausible that this eventually materializes itself into the consumer/enterprise plans. E.g. paying up for "high IQ" models and not just token usage.

- As another comment here noted, this is all driving the commodification + privatization of intelligence. The competitive landscape is changing and the effectiveness of "high IQ" models and those that can afford them may very well be table stakes going forward thanks to the (manufactured?) scarcity.

Diesel production capacity is limited and shrinking. Demand is there, albeit sticky (due to certain demand sources that are not easily electronified) and shrinking at a slower pace (due to slowing global economic growth). Rather than discussing a hypothetical blockade of Chinese oil imports, I wish the author would have addressed more probable short term outcomes re: supply/demand shock triggers and possible market plays.

Feel like this was a missed opportunity to look at recent geopolitical events under a more nuanced lens.

Small players have advantages the big guys don't have at scale and vice versa. The same goes for many markets beyond just finance.

- is the schema inferred from the data? - can/does the schema evolve? - are custom partitions supported? - is there a roadmap for future features?

Back in the day how did you find new music? Pre-2000s it was likely MTV/radio for mainstream, or word-of-mouth/local events for niche genres. Nowadays Spotify and streaming services have supplanted the former for mainstream music. Finding new music outside the recommended engines requires a little more effort in knowing where to look. There are a lot of Internet radio programs (shout out to The Lot and Rinse.FM) and smaller record labels that do an amazing job at curating local and diverse sounds.

These days it's never been easier to start your own label or publish a track. Rock-'n'-roll is probably still alive (unfortunately I don't know that modern scene well), but assembling the necessary equipment and people to start a band is a big hurdle requiring practice, space and coordination. So I can see more wanna-be artists opting for pop/electronic having shorter turnarounds to a finished product.

> When you have so many people alive, who can do nothing in exchange for food [...]

AI, for now, only exists in the digital space and that's what it will primarily disrupt (at least initially). You're still going to need real people to mow the grass, maintain homes/buildings, ship goods and perform other basic services that underpin society. None of that changes drastically with AI in the picture.

Some people will be out of jobs or replaced, but fundamentally they will just have to do something more tangible to provide value in order to pay the bills.