I don't think I've seen a less accessible *font* in my life, including all the dark grey on black and yellow on white ones. Those are hard to read, but this one makes my eyes hurt, they actually started to hurt after I tried reading it despite discomfort. How come? Reading random text for 10 seconds can cause people physical pain? I wear glasses for near-sightedness and slight astigmatism, I wonder if it's related, and if people with 20/20 vision experience it differently.
I thought it was me, I literally think there are things that should no longer be acceptable and this font is one of them. It serves no purpose and I would like to ask medical professionals if it is potentially harmful.
Edit: While fuzzy or blurry text itself is highly unlikely to trigger an epileptic seizure it is a major cause of optical strain, headaches, and reading barriers across various accessibility needs. Given the amount of screen time we all incur in our daily lives, I do not see why this should be a "thing".
My site shows black with yellow background and white text boxes. Highly visible. Maybe you're referring to dead comments? There are options to hide those.
I know this because the first thing I did when I got to the page was hit F12 to bring up the debugging tools and turn these styles off so I could read it. :)
I have 20/20 vision and this presentation hurt my eyes. I'm glad my browser has "reader mode" to normalize things like this. I'm not trying to yuck someone else's yum. I simply appreciate the technical ability to read someone else's post in a way that doesn't cause discomfort.
Paying for an account doesn't opt you out by itself, right? Has he stated anywhere that he actually opted out? But if not, then I also don't understand why OpenAI's communications about this have been so vague, they could've just said that he didn't opt out, using those chats in training data follows their ToS and that's it (whether that's "fair" is a separate discussion).
We don’t need to guess, OpenAI pretty much indirectly they had the chats in their data set. OpenAI responses are the most suspicious part of that whole controversy, the fact they do not provide straight answers is not a sign of a good faith actor here
There has been no statement either way, as far as I could find beyond them only using commercially available models, though given Alpöges employer, I'd be surprised if they didn't opt out. In any case, for such work, ZDR or self-hosting seem to be an absolute must now.
Unless OpenAI can show that training was permitted, this will erode the limited trust that many users have had in such toggles and may lead to further, uncomfortable inquiries.
This is what TrueCrypt/VeraCrypt and similar software do already: you have two passwords to your encrypted drive, one shows the real data, the other one a whole another fake drive with whatever you put there. Additionally, there is no way to forensically prove that there is hidden encrypted data present and that there's a second layer: you have plausible deniability.
Serious question then: if you were the CEO/CTO and were employing 10,000 engineers, what would you do without middle management? Would you have 1k+ line managers each managing <10 ICs and then... yourself? How would you coordinate work, hire, or do anything, really?
I'm not saying corporations execute on this flawlessly, just any time when I wonder what I would've done myself, I end up with a similar structure (maybe a bit flatter)...
I think the answer is, "you don't really need 10,000 engineers". You can do a lot with small teams of engineers. This was true before AI. Macintosh was designed and built from scratch with a team of 3 which eventually peaked at 20-30. Does anyone seriously believe a company building a web app needs 10,000 engineers?
"web app" covers a lot of surface though. Yes, if the web app in question is a static site that AI can shit out in 20 minutes, it doesn't need 10,000 engineers, but what about building, and running, and operating something like, say, Instagram. Which has a web app. End-to-end, all of it, down to racking servers in data centers across the world, 10,000 engineers sounds reasonable. So start by defining what this hypothetical webapp and how much kubernetes is involved.
I heard Microsoft has 14 layers of middle management just for the xbox team.
14 layers!!
There are people whose sole purpose is to have meetings to pass information to other people, who will then have meetings about who to have meetings with.
How fried does someone's brain have to be to say "others on telegram", as if everyone is in the same chatrooms together? If they're on HN, they should at least know why that doesn't make sense, so I have to assume they're in a deteriorated mental state.
Friendly reminder to touch grass on a regular basis... Even virtual grass in a video game is a good pressure valve for excessive social media use.
I get what you mean but the GPU comparison isn't the best here, I think. Money-is-no-object-I-want-the-best approach is questionable, definitely. But no one can argue that an old Nvidia card is objectively better for e.g. 4k gaming than a 4090 if you don't mind the wattage. You can just measure it.
With LLMs the problem is more complex, it's people getting used to how a model works and to the ecosystem. Sure, you can make all your skills harness-agnostic and deal with Anthropic's stubborn refusal to adopt the common naming/directory structure. But most people don't. So then you end up with something closer to the ancient Android vs iOS discussion. Can you prove, in isolation, that iOS is more energy efficient, the hardware is faster? Yeah. But that won't speak to someone who has been on Android for 10 years and would have to migrate and get used to iOS to experience that, first.
I've noticed myself how I get used to common failure modes of particular models in my projects. GPT5.5 tends to create some checks/booleans I don't need, it heavily overcorrects on error handling, etc. While Claude 4.7/4.8 doesn't do those as often but gets derailed on our E2E test suite, forgets to run linting despite guidance. So even assuming fully harness-agnostic working setup, a new LLM model with its own quirks can be a lot friction for heavy users who might be used to Claude specifically and all their skills/guidance pre-address common failure modes.
E.g. I might be a Prius owner, then you gift me an objectively better, more efficient, safer, newer, same-size, physical knobs car ...and I might still swear by my Prius! I'm used to how it turns, how it feels, I can repair some issues myself. Isn't that a normal reaction then?
Mandatory PSA for Android users because people tend to have similar complaints each time in popular threads: ReVanced allows you to have YouTube with Sponsorblock, background play, no ads, Shorts completely hidden, (estimated) dislike counter brought back etc.
Couldn't imagine using YouTube on my phone without it, it's night and day difference – that's despite being a premium subscriber anyway.
> The authors acknowledge funding from the College of Literature, Science, and Arts at the University of Michigan. R. L. P. was supported by an NSF Graduate Research Fellowship (NSF-GRFP) DGE-2241144. M. E. C. was partially supported by the University of Michigan Rackham Graduate School through a merit and predoctoral fellowship. The authors would like to acknowledge the professors and students of the Mapping, Measuring, and Modeling Microplastics in the Atmosphere of Michigan team for their support and helpful discussions. The authors thank Jennifer Connor, Curtis Refior, Amy Pashak, Megan Phillips, Josh Hubbard, Bill Joyce, and David Lee for their community partnership. The authors would also like to thank former Dean Anne Curzan from the College of Literature, Science, and the Arts at the University of Michigan for funding this work through the “Meet the Moment” grant program. The authors acknowledge technical support from the Michigan Center for Materials Characterization.
Is there anything wrong here? Not sure I understood your comment
I'm not 100% convinced, while iterating fast on an early prototype, what's wrong with legitimately not knowing what e.g. the data structure will end up looking? Just let it run, check debugger/stdout/localhost page and adjust: "Oh, right, the entries are missing canonical IDs, but at the same time there are already all the comments in them, forgot they would be there – neat". What's wrong with that? Especially at uni, when working on low-stakes problems.
> what's wrong with legitimately not knowing what e.g. the data structure will end up looking?
But that's not what the above comment said.
> Just let it run, check debugger/stdout/localhost page and adjust: "Oh, right, the entries are missing canonical IDs, but at the same time there are already all the comments in them, forgot they would be there
So you did have an expectation that the entries should have some canonical IDs, and anticipated/desired a certain specific behavior of the system.
Which is basically the meaning of "what will the output be?" when simplified for programming novices at university.
The point of university isn't to get things done - it is to imprint knowledge into your brain. If you are approaching school with the attitude of "how do I get this over with as fast as possible," you are wasting your time and the time of the teacher.
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