there's still some lock-in here: data storage (iCloud), the broader Apple ecosystem, certain apps, user habits (I'm a lifelong Android user and am having trouble using other people's iPhones)
it's astounding how much of human work are tasks like the one you have described here. Dancing around messy interfaces because nobody bothered to properly standardize and automate
please stop being so mean, they also create echo chambers to kill political discourse (i.e. the foundation of democracy) and show the most inflammatory material to their users to pit them into a shouting match against each other
i have trouble understanding these situations, e.g. the AI itself would presumably make the suggestion to write a python script for such a task. It seems to me that there two huge problems right now
* understanding which category of problems an LLM is an appropriate solution for (rather than throwing LLMs at any and all problems)
* matching model capability (and therefore cost) to the problem at hand. You can easily overspend massively by using a model that's too powerful
not sure one would expect huge revenue increases from these internal tools, but maybe dramatic cost savings? Surely a lot of corporate processes could be automated?
I'm still not entirely clear on the problem <-> capability matching. E.g. it seems like Kimi K2.6 with good context would already be able to solve a huge chunk of problems. What share of prompts require frontier models?
not just renewables, also massive nuclear capacity and huge modern coal plants. They can really crank up capacity if they want to. How long will it take to get a new nuclear power plant operational in the US?
if the unit economics are broken (strong competition from other proprietary model providers + open weight models; LLM token race to the bottom) it's not clear how high revenue growth translates to high profits. These companies are valued like monopolists, but the competitive dynamics make them more akin to tomato sauce makers. I understand that the technology is pretty amazing and can lead to significant productivity gains, but from a business perspective, the question is how much of that value Antrophic and others can capture over time.
there are around 140 EV companies in china competing very aggressively, they have excess capacity and are flooding the world market with cheap EVs, tough for Tesla to have a healthy margin in that environment
there was a rush to buy electric cars in the US for as long as the $7500 incentive was in place, so the Q3 2025 number if inflated; it's a pull forward effect.
Sales have been flat for 3 years and the delivery numbers in Europe are catastrophic
on a fully diluted basis, the market cap is above $1.6tn, so at a PE of 20, they'd have to generate something like $80bn in profit per year - hard to do in an industry that is as brutally competitive and low margin as passenger cars.