I found a bug where our system would freeze after playing Tomb Raider 2 on a certain CPU/chipset combo. If I remember correctly, it turned out to be a unacceptable voltage drop somewhere in the south bridge.
In a contemporary interview with Marques Brownlee, Musk said they didn’t currently have the technology and the specs were an extrapolation for what they expected to be available on release.
Oh, just like how they "projected" that the Cybertruck would be able to tow a Porsche faster than the Porsche itself, or they released "simulated" Plaid numbers.
It got to the point where even Tesla's lawyers had to get involved, and numerous reports from Tesla disclaim that "Elon Musk's statements are aspirational and may not reflect engineering realities".
> In a contemporary interview with Marques Brownlee, Musk said they didn’t currently have the technology and the specs were an extrapolation for what they expected to be available on release.
That’s even worse then, because it was supposed to be released by 2020. Here we are in 2026 and I still don’t think it’s possible to cram 200kwh into a sports car. I take this as an admission straight from the horse’s mouth that either: 1) they were lying and had no intention of shipping the car as specified when it was announced, or 2) they’re completely inept at making predictions about the trajectory of technology core to their products. Both are extremely bad.
Etc. This stuff was very real and is a ten second search away, maybe try that before accusing parent of having a faulty memory because it doesn’t agree with yours.
Those weren't advertisements. The browser was packaged with other software and automatically installed if you didn't catch it and prevent it. I'm pretty sure it also made itself the default browser during the installation without user interaction.
There are screenshots of the installers in those links.
Paying a second of CPU time is an inconvenience to a user but trivial for LLM scraping.
The GPU cost to pretrain on that page once will dwarf by 2-3 OOMs the CPU cost to compute Anubis, scrape and post process it. And you’re not going to just train on it once!
At best you’re creating a speed bump for wannabe players scraping with no real plan. The folks training models people use just do not care.
LLMs are also very good at writing code for newly invented languages, especially if they can execute it and iterate. I strongly believe the barrier to switch languages is lowered in a post LLM world.
Ten years ago I was at a startup where we used Datomic, and it was okay, but six months in the sales team was like “ok how do I run SQL queries so I can triage leads”. We had no answer of course.
Today it would simply be: type what you want in natural language and we’ll generate the query with Claude.
I just tried one representative query from that startup against a hypothetical datalog query tool in Rust and it did just fine.
I did this with our team: I created a schema.md document with an LLM-friendly explanation of the schema, and walked the whole team through how to create a Grafana query using an LLM and this document.
Within a couple of weeks we have totally non-technical folks with very sophisticated queries in their dashboards. It works fine.
It was very cut-and-paste, though, and I'm working (when I get the chance) on doing this via a chat interface where the LLM can interact directly with the database and Grafana to make it smoother.
So I think the answer is not necessarily new languages, just better integration with the final interface. In an ideal world we should be able to ask in chat "what were the sales numbers for last quarter for APAC excluding the three largest customers?" and get an answer near-instantly, and then we don't really need to deal with queries or languages at all.
Yeah, but it was a lot of questioning and refining to get it to understand the wrinkles and edge cases. I think we're on about version 5 of the doc now
I agree that an LLM could also generate the code for a new query language. But my point is that fewer people will attempt to author a new query language in the first place because an LLM will be writing the queries either way. So the effort would be less impactful.
I have an implicit belief that SQL isn't the most effective low level language we could have and LLMs will free us up to explore that space, similar to asm.js -> WASM. But I'm open to being wrong about that.
I think it strikes a good balance between still human-readable and low-ish.. any lower I suspect you'd need to dedicate a lot more documentation else where..
What about cases where e.g. there's an earthquake with thousands of incidents and you need to triage help to the worst? It's not common, but there are absolutely cases where small amounts of intelligence applied in parallel is a genuine advantage.
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