Superscalar is having >1 pipelines, which at its introduction meant needing to optimize your code very carefully to take advantage of it. The scheduling didn't necessarily happen transparently, early superscalar processors frequently punted on hardware detection of pipeline hazards[1] and required the code to just not go there (see branch delay slots).
Transparent scheduling of superscalar execution was a later advance, out of order execution, which came soon after (~1965).
"Opus delivered mediocre, so I did not let it finish"
Mediocre means average / middle of the pack. It sounds like its doing exactly what you would expect nothing more. Why would you stop it? Why would you need exceptional?
But after accounting for maintenance & etc were they more profitable than sinking the equivalent amount of money into something else, such as slower aircraft? Notably there are currently efforts to develop new supersonic passenger liners.
The first assumption is wrong because to really solve a mathematical problem, providing a mere answer (even if formally certified) is not sufficient. What is missing is an intelligible proof that human mathematicians can understand and use to advance the aims of mathematics.
This subjective attitude turns mathematics into nothing more than number-poetry.
I'm hoping to get a mini-split system installed soon and thought I might as well look for something with HA integration. It's not easy. Some manufacturers like Samsung actually want to charge you monthly for cloud integration! Completely out of the question obviously. I came across this, and Mitsubishi is supposed to be good anyway. I would prefer something that's actually supported but I can't seem to find any other options.
I could also very easily wire my units in so no need for WiFi. Maybe I can find a wired ethernet module.
I think I made my point in the original post you responded to: OpenAI heavily subsidized token cost using investor money. If they go under, there will still be demand for that compute, but because OpenAI is paying more for it than it is actually worth (i.e. what the end customers are willing to pay), any company replacing OpenAI will not pay the same amount OpenAI pays.
So when people say "somebody else will buy that compute", they are correct, but they are ignoring that it will still cause a massive decrease in revenue generated by that compute.
If you're asking me what my point about "believing" is, it's this. OpenAI is losing billions every quarter. It's only staying afloat because it can still find investors who believe in its ability to eventually become incredibly profitable. But there are signs that this is starting to change (e.g. it's unlikely that Softbank will be able to find much more money to give to OpenAI). If OpenAI can't keep raising more money and can't IPO at the level they need (as seems to be the case, given that they keep pushing any IPO date forward), OpenAI will eventually run out of money.
I'm not sure how investors believing in things changes any of this, so now it's your turn to explain what the point is you're actually trying to make.
Code in most organizations is a means to an end to produce an actual product.
The job of a SWE is to not produce the most sublime readable code with cute language bells and whistles that you can show off to your other programmer friends. Yes its fun to do and interesting, but the main value in writing code is to express your intent so you and other people that are working with you can actually build something of value.
Software has value to the people on your team reading it. The product that you create with your software has a far wider impact than just that. As such, there is for _sure_ optimization pressure on "professional software engineering" to be more productive and actually make the product better to use, faster, with more features users like. The user typically does not care that you used a new C++26 feature, as much as I enjoyed writing it for them.
If I can produce features for users faster and I can iterate on them faster, this is a boon to me. I can program by hand for fun all I want in my spare time, but if I want to produce value for someone else, it is economically infeasible for me to be a luddite, and I will simply be outcompeted. Previously you were outcompeted by smarter teams who out executed you (and who also worked more), and now you can be out executed by basically anyone using an LLM who actually understands that the end goal is the product, not the code used to make it.
I always had the thought in the back of my mind "what better way to flag content as potentially incriminating then to let the user tell you "this conversation is not to be retained."
Especially the way the "advertise" incognito as some sort of untraceable means of searching/chattig etc, we ought to see these sorts of things from a less trusting-by-default perspective.
The story of the discovery of heliocentricism is a lot more complex than this; the people who didn't immediately accept heliocentric theories (including the ancient Greeks - look up Aristarchus) often had good, scientific reasons for doing so. Or just look up at the sky at night yourself and ask yourself how you, personally, would confirm it if someone told you that what you see in the sky is better explained by the Earth moving around the sun than the sun moving around the Earth.
> Do you think the current state of affairs is GOOD?
Chinese labs releasing open weights models is good.
All of these independent harnesses and model router services are good.
The pricing of memory and accelerators sucks at the moment but hopefully we will see cool local inference computing if memory and accelerator prices normalize.
OpenAI scooping the Navier Stokes problem from researchers already using OpenAI is bad. People conflating OpenAI's team of researchers and extraordinary computing resources as being equivalent to "ChatGPT, solve the Navier Stokes problem" is silly.
OpenAI and Anthropic coming up with non sense tests and letting their agents hack services is ridiculous and they should be charged with computer fraud and abuse crimes.
I think a lot of it is interesting and the bad stuff seems squarely in the domain of OpenAI and Anthropic.
That's the case for open weights models. Hosted Deepseek Flash 731 copy isn't changing randomly one day because the parent company decided to change it.
University of California has licensed zoom accounts with privacy agreements. I install it in Linux. Now I will check if I can replicate this behavior. I am not sure if it is a violation of their agreement or not if they do, but I don't like it.
I'm Gaurav, a product-minded engineer who can take a loosely defined problem through architecture, implementation, and production. I build full-stack products, backend services, AI agents and retrieval systems, and cross-platform mobile applications, with ownership of deployment, monitoring, and production debugging.
Selected work: Coastok, serving 15,000+ users; Alter, an open-source AI runtime; Puzzlyy, a real-time multiplayer puzzle app; and a reusable Kotlin Multiplatform calendar library.
Seeking a full-time remote role with a small team where I can make technical decisions, own delivery, and keep systems reliable as they grow.
I think what matters in this case is how proactive and greedy the model is.
GPT models are extremely proactive and gredy. So when Fable mentions something that may affect some obscure component of the system, GPT will start digging the codebase, execute web searches, re-read AGENTS.md and hit fable on the head.
Fable never does that, it just reads the turns and acknowledges it read them. This also explains why GPT models tend to overengineer things and why they're amazing reviewers if you triage their findings.
I feel like things have changed dramatically overnight. The field of mathematics seems to be moving at an extraordinary pace, especially following the recent developments around the Navier-Stokes problem.
25 Field Medalist and 5000+ mathematicians from leading institutions around the world endorsed an open letter expressing concerns about the impact of AI on mathematics:
Oh it is understandable that they are pissed and protesting, however it seems to me that you are the illogical one. There are two choices, go to the slaughterhouse (losing your job and getting nothing in return), or take the different option, which is less bad, and might even be good (losing your job and potentially getting money without even working).
Transparent scheduling of superscalar execution was a later advance, out of order execution, which came soon after (~1965).
[1] https://userpages.cs.umbc.edu/jtang/archives/cs411.f23/lectu...