maxnevermind
I guess kinda put you in a bubble a little, I wonder how the experience of Anthropic eng who left the company would look like, when such eng would go and spend few $K a day in non AI lab, would that be encourage/allowed/taken as example?
Have you ever worked on existing code base that has components that makes no sense but must be there?
You will have to wait great amount of time for great things just as you did before.
LLMs are not AGI, if so they are not foundational technology, if so we can't really built upon them - we can just use their wrappers as productivity tool, if so we will be bottleneck by what we were bottlenecked before: corporate bureaucracy, slow physical world innovation pipeline, supply chains, just a small number of actual problem solvers/risk takers around, etc.
There will be of course a lot of attach LLM wrapper and improve productivity here / there underwhelming weak fart products, ex: Meta Muse.
I find my self going opposite direction recently. I start using frontier models less and less and smaller models more and more. I recently tried Opus Opus 5 with ultra-code level of effort and I wasted like 2 days on trying to migrate some project to new libs because it spits out a huge wall of text as replies/plans and waste huge amount of time on things I didn't ask it to check and see no point in checking. At the end I just took a smaller model and used it in more controlled fashion playing the role of orchestrator/planner. Smaller models are good enough and also much faster. My collisions from that, frontier models and high reasoning effort levels are for pure vibe-coding when you don't really control or understand what is happening. My application area is not pure SWE though, I didn't churn a lot of code before and I don't now.
Yes, It is not sufficient but I would argue it was necessary. In case of China it allowed them to have a set of domestic copycat companies like Baid, Alibaba and Tencent, that enabled high demand for local engineers to serve their needs and that allowed to have a large pool of competent domestic engineers which now can benefit other emerging sectors too. It keeps surprising how many top contributors to large OSS projects are from China.
Are/were you in a position to make such decisions or it is a guess? I'm not but given certain evidence I doubt that few percent will cut it. I know some of the richest companies on the planet from SF Bay Area who won't give lunch for free to their engineers. So I'm not sure about "few percent" :-D 10x we were promised, now that is more interesting but we all know that 10x engineers is nonsense.
It is a honeymoon still, enshittification is coming, who knows how that will look like given how much more expensive to run LLMs backed user experience. Some back of the envelope calculations: 300 million US users * 20$ a month * 12 months = 72 billion $ a year. 72B$ is some spare change for AI labs. That assuming entire US will be subs which is unlikely and outside of the US there are not many rich countries consuming it, India is the next market, then Brazil and Philippines I think, not super rich counties to say the least. I believe total revenue to just pay for the capex build out by the end 2027 should be on the scale of hundreds of billions a year.
> That's a baseless claim. For example, Germany has invested massively in solar but its electricity prices went up, not down.
> This price of electricity is high because gas, which is still expensive, sets the price of electricity most of the time [1].
1) Am I missing something or the link you provided contradicts your claim? On a chart #2 in the article you can see Germany has only 24% of the times price of electricity set by gas, 24% is not "most of the time", right?
2) Even if that is true, and electricity prices in Germany are set by the price of gas most of the time, it seems like you didn't address the point in a previous message. If the goal is to have lower prices and the goal(outcome) is what really matters not just the process and renewables is the path to get there then why Germany electricity prices rose at the end? And were not all of those because of this ... because of that ... supposed to be a part of that path(plan)? They did the thing, invested in solar, what have they missed and why?
Is not Germany an example of the opposite? I mean their decision to shut down nuclear plants while getting dependant on Russian supply of energy sources?
Many of those points assume LLMs will become amazing in many things very quickly like in a quantum leap, it doesn't seem reasonable to assume that imo. We are actually seeing a confirmation of that atm, LLMs's capability of finding zero days are growing across few months/years, and as you can see concerns are raised about that, that feedback will be taken into account. Well, if AI labs start to hide frontier models or/and lobotomize them for external users then we might be in trouble at some point but I'm not sure if that is possible. They are under pressure to release them due to money incentives, lobotomizing while preserving usefulness for customers might be impossible, hiding internally might spill out in different ways such as Hugging Face incident so not sure hiding is possible neither.
1 what is tesla cybercab plan to address legal implications of accident that will happen? who is going to be responsible for them when they happen? are they covered by tesla insurance or some other insurance? are there any official plan/statements around that?
2 what was the name of the experiment they started in san antonio tx when some cars didn't have a driver? what was the results of it? did they expand the operations? it was much smaller than waymo, is it growing? how it is related to robotaxi?
It is not able to connect the dots that I keep asking about Tesla in 2nd prompt and spit out some unrelated stuff. Really? How it can be that bad? Gemini 3.1 Pro model works fine in this case btw. I thought maybe it is about knowledge cut over date and it doesn't know about those events from 2025 but it seems it has the knowledge up to March 2025. Top 10 in Intelligence on artificialanalysis ladies and gentlemen.