It's funny to me that these models were created by effectively "distilling" all available content including the proprietary works of many other people, but now it's a problem that someone is doing the same to them.
You're using available information (copyrighted works, or the output of another model) to train a model to encode the information in a new form. Why is the former not theft, but the latter is theft?
I think the author's choice of words is framing the discussion. They did build their own website, but they loved the look of the one they saw, so I'd think a better choice would be "inspired by" rather than "stolen from."
Another factor I don't see mentioned: every Trump policy is inflationary. Deporting the labor base, deterring legal immigration, applying tariffs that were basically derived by taking the trade deficit with a country and dividing by 2, and now locking up 20% of the global oil market by shutting down the Strait of Hormuz.
The Fed's response will have to be to raise rates, which is going to crush the multiple of any stock whose valuation is based on the expectation of massive growth.
> FSD is up to v14 and there is no sense in which it's "Full", or is likely to be "Full" any time soon.
I think the SpaceX IPO is way overvalued, but have you actually tried FSD v14 yourself?
My car has 8-year old hardware running v12, and it handles like 90+% of my driving. When I test drove 14 it blew my mind how good it had gotten in only 8 months of development. In my opinion, there's question that it's "when," not "if."
Which means more Grok degradation, more severe throttling, etc.
I can't understand why xAI charges 50% more per month for Grok over competitors when it doesn't even gracefully downgrade to a cheaper model when paid subscribers hit the limit.
I'm considering Anthropic. I think they will be one of the survivors if/when the AI bubble bursts.
I was dubious about SpaceX (orbital data centers need to solve for extreme radiation and error-correction during training), but then I remembered that xAI is actively working on virtualizing white collar workers ("Macrohard").
In my opinion, this is the only TAM that justifies $1T in data center investment, because the consumer market for ChatGPT-style AI is saturated. There's a lot of enterprise TAM available for AI, but I think what these companies training frontier models are really after is selling a product that allows companies to eliminate the cost of white collar salaries.
I really want Spotify to follow. I feel cheated and deceived when I'm enjoying some music, then I realize that there's no bio for the artist and they released 7 albums in 2025. Users should be empowered to filter out AI content if they choose.
A while back, I discovered by accident that forcing ChatGPT to respond only in zalgotext and then using voice mode generated some really bizarre audio.
Have uploaded the audio files for anyone who's interested. They've since patched the ability to ask for output in zalgotext, but it was pretty strange while it lasted.
My car drives itself. That's a $18T global market.
Also $1T in data center investment makes sense when you realize that companies are racing to create virtual white collar workers. Google spends $9B a year on software engineers.
100%. I have to hold the floor by filling the space with "ummmmmmmm.... uhhhh...." which inevitably distracts me from my point altogether. Poor user experience.
Strongly agree, some of us like to choose our words more carefully when interacting with an LLM.
I've tried to convey this to OpenAI through various available channels (dev forums, app feedback, etc.).
Grok solves this by having an optional push-to-talk mode, but this is not hands-free and thus more cumbersome than just having a user-configurable variable like seconds_delay_before_sending_voice_input.
I agree with your categories. The majority of the usage for me is (1) and (3).
(1) LLMs are basically Stack Overflow on steroids. No need to go look up examples or read the documentation in most cases, spit out a mostly working starting point.
(3) Learning. Ramping up on an unfamiliar project by asking Antigravity questions is really useful.
I do think it makes devs faster, in that it takes less time to do these two things. But you're running into the 80% of the job that does not involve writing code, especially at a larger company.
In theory, this should allow a company to do more with fewer devs, but in reality it just means that these two activities become easier, and the 80% is still the bottleneck.
Tangential, but you used to be able to use custom instructions for ChatGPT to respond only in zalgotext and it would have insane results in voice mode. Each voice was a different kind of insane. I was able to get some voices to curse or spit out Mint Mobile commercials.
Then they changed the architecture so voice mode bypasses custom instructions entirely, which was really unfortunate. I had to unsubscribe, because walking and talking was the killer feature and now it's like you're speaking to a Gen Z influencer or something.
You're using available information (copyrighted works, or the output of another model) to train a model to encode the information in a new form. Why is the former not theft, but the latter is theft?