My explanation:corporations want to benefit from scale. That means lots of computers with identical specs. Not only everyone gets the same machine, they get the same machine for many years. It's not unthinkable for a spec to stay constant for 5 years. In exchange for this stability, the makers of the machines (Dell, HP) can lower the price significantly. As a corporation you can buy a very powerful machine for something that a regular consumer needs to pay about twice the price. But that's when the spec is new. As years pass, a machine with the same spec gets to be downright sluggish.
Readit Newscredit_guy commented on It is worth it to buy the fast CPU blog.howardjohn.info/post... · Posted by u/ingve
I think it’s a pithy counter to the point you were trying to make.
Sure. It also sounds like you liked the pithy answer opportunity more than you than you care about the substance of what I was saying. Which is a shame, the dialogue on Hacker News is generally better than that.
Which kind of student do you think would be more likely to realize that a single data point is of no consequence: legacy or non-legacy?
Nice roast there, but was it really necessary?
Now fit legacies into this theory.
The wikipedia page on Legacy Preferences is illuminating. Note the Larry Summers quote:
Former Harvard University president Lawrence Summers has stated, "Legacy admissions are integral to the kind of community that any private educational institution is."
Just about a month ago I realized for the first time that legacy admissions result, in many cases, in better candidates rather than worse. Not always. But here's an example (from real life, without names obviously): highly qualified student, with lots of national level achievements, Cornell legacy. Applied in the early admission period to Cornell, got in. But the student had a reasonably high chance for Princeton or Yale, let's say. However, the legacy system incentivized him to apply to Cornell, even if his level was slightly higher. Why? Because if he didn't apply in the early period to Cornell, hoping for Princeton or Yale, and didn't get in, then Cornell would not have given him any preference in regular admissions. So he had to choose between nearly 100% admission at Cornell in the early round, vs 10% chance at Princeton, and then a non-negligible chance to not get into Cornell in regular.
My point: legacies are not always dumber than non-legacies. Sometimes they are stronger, and the legacy system incentivizes them to stick to the school where they are legacy.
> We know from one study that people who played tennis a few times per week lived roughly 10 years longer than average. So we'll use that value going forward.
There has to be some incredible correlation between having the time and money to play tennis “a few times per week” and being significantly wealthier than the average person. And being wealthy is clearly the healthiest thing you can do.
Exactly. Some guy once told me that "research" shows that people who play golf live longer. I still didn't pick up the sport yet. Not sure I'll pick it up anytime soon, although I like the idea of living longer.
credit_guy commented on From GPT-4 to GPT-5: Measuring progress through MedHELM [pdf] fertrevino.com/docs/gpt5_... · Posted by u/fertrevino
Here's my experience: for some coding tasks where GPT 4.1, Claude Sonnet 4, Gemini 2.5 Pro were just spinning for hours and hours and getting nowhere, GPT 5 just did the job without a fuss. So, I switched immediately to GPT 5, and never looked back. Or at least I never looked back until I found out that my company has some Copilot limits for premium models and I blew through the limit. So now I keep my context small, use GPT 5 mini when possible, and when it's not working I move to the full GPT 5. Strangely, it feels like GPT 5 mini can corrupt the full GPT 5, so sometimes I need to go back to Sonnet 4 to get unstuck. To each their own, but I consider GPT 5 a fairly bit move forward in the space of coding assistants.
credit_guy commented on Every Reason Why I Hate AI and You Should Too malwaretech.com/2025/08/e... · Posted by u/vismit2000
These are not the reasons why I hate AI. I hate AI because we still don't have universal housing or healthcare and AI's direct endgame is to eliminate every job that isn't CEO. And what a fucking drab world that will be for all the displaced workers.
But here's the thing you can do: learn to use AI. It's early in the cycle, the barrier of entry is not very high yet. But it is getting higher and higher. If you hop on and start riding the wave, one year from now you will not only be miles ahead of others in terms of productivity, it's going to be hard for them to catch up with you.
AI is happening. It's up to you if you want to be one of those who gets ahead or one of those who gets left behind. Just saying.
credit_guy commented on Challenges Related to the Reprocessing of Spent Nuclear Fuel mdpi.com/1996-1073/18/15/... · Posted by u/PaulHoule
Only a hundred years? At current energy usage rates, even though energy usage increases year-over-year, every year, without fail? And of a fundamentally irreplaceable element that is only forged in supernovae?
How dare you.
It is 100 years of proven reserves. “Proving” a reserve is expensive, mining companies do that in order to secure favorable financing. But when there are 100 of proven reserves, there is little economic incentive to go and prove new reserves. However, if the industry demand increases, because of new build, then initially the proven reserves will suffice only for, say, 80 years, the incentive to prove new reserves appears, and mining companies spend the necessary funds to “prove” new reserves.
In reality, the amount of uranium available on this planet is virtually unlimited. There are billions of tons of it in seawater, and it is estimated it would take onle a 4x market price increase for seawater uranium extraction to be economically profitable.
credit_guy commented on The current state of LLM-driven development blog.tolki.dev/posts/2025... · Posted by u/Signez
If you have 20 years of experience, then you know that number of lines of codes is always inversely proportional to code quality.
> ...thousands of lines of code ... quite high quality
A contradiction in terms.
Here’s an experiment for the two of us: we should both bookmark this page and revisit it one year from now. It is likely that at least one of us will see the world in a different way, or even both.
credit_guy commented on The current state of LLM-driven development blog.tolki.dev/posts/2025... · Posted by u/Signez
> Most of the days nowadays I push thousands of lines of code
Insane stuff. It’s clear you can’t review so much changes in a day, so you’re just flooding your code base with code that you barely read.
Or is your job just re-doing the same boilerplate over and over again?
You are a bit quick to jump to conclusions. With LLMs, test driven development becomes both a necessity and a pleasure. The actual functional code I push in a day is probably in the low hundreds LOC’s. But I push a lot of tests too. And sure, lots of that is boilerplate. But the tests run, pass, and if anything have better coverage than when I was writing all the code myself.