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Comment by CSMastermind | Hacker News Reader

For those who weren't alive at the time it's probably hard to understand what an inflection point Windows 95 was.

Both in terms of the number of homes with computers in them and what those computers were able to do things skyrocketed.

The software business went from primarily being targeted at businesses, schools, and hobbyists to being targeted at mainstream consumers in a once ever opportunity to establish a brand name with people who have literally never purchased anything in this class before.

It was the most dramatic shift certainly that I've seen in my life with the adoption of the internet being second and the adoption of mobile phones being third.

It's been more than a decade since we've seen anything like those shifts. The 2010s feel a lot like the 1980s to me. Lots of progress, lots of it incremental, but no inflection point. I do wonder if AI will be the next big paradigm shift like Windows 95, the internet, and the iPhone.

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Or, how hard it is to predict future markets. I remember when I started making games (on CD-ROMS!) and I met a guy who had a "multimedia" company. It sounds so funny now. He felt that soon their would be huge stores, like record stores(!) that had aisles and aisles of CD-ROMs for every need and interest. It didn't sound unreasonable at the time. And now I can't even explain to my kids what record store were like when I was a kid.

He was right though, they just sold other stuff at Best Buy too.

"The App Store" is like a record store that extends for hundreds of miles in every direction. He was right about the concept; but the store is in cyberspace and the media is a file instead of a disc.

I think AI finally is at point where it is. It’s peak hype right now but there is definitely a difference between knowledge workers that use it and one’s that don’t. It’s only going to grow wider in the coming years.

> there is definitely a difference between knowledge workers that use it and one’s that don’t

[citation needed]

I tried out Copilot for months and didn't get much value out of it. The majority of my time and effort is not writing code, which is about the only thing an LLM can generate semi-useful output for. It's not more useful than a tailored search engine experience and it doesn't replace deep dives into text books, code, and white papers. Where are you seeing major benefits?

We've also done some initial experiments, and seen no improvements in productivity, and the comments from the people using it were rather negative.

Maybe it's sector dependent? Maybe systems programming doesn't have enough reference materials for them to learn from?

Certainly not the "Clearly obvious difference" some people seem to be claiming to see in some places online.

The latency is distracting for me tbh. That's something I think could be fixed by running local models, but the quality of output is just not there.

Maybe if you're slinging HTML and JS all day it helps more

I've watched people who claim it is a game changer try to use it and I can see routinely leading them down rabbit holes in real time which they struggle to get out of.

Meanwhile, the stuff it is good at filling in - it was never that hard to google it and copy and paste it in the first place.

I've seen this like 20 times in tech before. We're peak hype cycle for LLMs and the trough of disillusionment has yet to set in. During peak hype cycle for any tech a lot of people defer to the crowd's excitable opinion, disbelieve the evidence in front of their own eyes and express a level of optimism over future developments that is ludicrous.

My experiments with 3.5 say that it does the easy 80% solution that takes 20% of my time.

The advantage, that actually is a game changer[0], is that it can do languages I can't. I'm an iOS dev, I've technically been paid to write JavaScript at various points, but the best of that was about 20 years ago and just before jQuery got popular.

ChatGPT lets me turn my ideas for JavaScript projects into things that almost work and are usually close enough for me to fix — turning me from an iOS dev into a JS project manager.

Likewise Stable Diffusion: I've done some game artwork when I tried self employed for a bit, SD can act like a mostly amazing artist that does a few bits (mostly hands) like it was temporarily high on LSD, and I can just highlight those messed up regions and say "do again five times", and the actual images get to me faster than a real human would notice a message on slack or email or whatever, let alone be able to actually attempt a fix.

As for music… I actually made a procedural music generator back then (for the games while self-employed), and while neither the music nor the generator is going to win any awards, the output was sufficient for the games it went with. All the various new music AI are way better than what I did.

[0] and now I realise the cliché; ugh

This really speaks to me and my experience. It’s not AI’s ability to beat me in my own domain, it’s the ability for me to extend my domain to a different style to achieve the results I want. I think folks that underrate the technology are evaluating on “is it better than me (or the person I know who is great) at this” when what you point out is more: “can it help me do this, like that” — that’s where it shines. Further, I think folks under appreciate how being able to extend what you “know” to a different format (ie different language) enables you to determine the next set of problems that help you either: (a) find the right partners with the right skills or (b) ask the deeper harder questions about your gaps.

For me (solo dev, doing both a project in an unfamiliar framework and a project in on an unfamiliar new microcontroller), GPT-4 has been a lifesaver.

Rather than spending potentially hours to sift through documentation or ask around on the forums to find the magic incantation I need, ChatGPT just spits it out instantly and I can move on to solving actual problems.

That said, in a team environment with experienced devs, it would probably be better for me to just ask someone more experienced. Learn faster and more in-depth.

Also worth pointing out that GPT-3.5 and GPT-4 are completely different beasts. If you were getting the devs to use 3.5, you will get bad results no matter who is using it.

Main benefit is it does boilerplate really well. You type a few letters and then hit tab, and now your test case is done.

I did this as late as yesterday. Type in a case, type in a variant of the case that is more or less symmetric, it fills in what you would have typed. Or you add a member to your object, thus requiring it to be tested. It figures out that you need to check this new thing in all your tests.

Other thing it does well is syntax. Some weird c++ template parameter thing, it does it for you. Little things like "what's that thing that makes the sort go the other way" it will know, and save you a minute of googling.

What there doesn't seem to be is an interface for that I've found is any kind of refactoring. That's still a form of donkey work that a junior guy can do, but you'd think there would be some way for the AI to suggest DRY candidates and re-orgs.

I find that to be true as well.

It's just that boilerplate is usually an indication of a bad design or a bad/verbose language. Both of it are painpoints that should be fixed.

But if that's not possible then Copilot is a good helper.

An alternative idea is that some types of "boilerplate" can be annoying to write but actually helpful for people to read, and these tools might make that type of code more acceptable.

For example, it's helpful to be able to see all the steps a test case is doing in the one function, so you can read that and see what's going wrong if it fails. If a lot of your test cases are similar you might be tempted to refactor and put common parts in separate methods, often with unhelpful names like "assertResult()", etc, but now the reader has to jump about to understand the logic. Whereas this allows you to write the more repetitive but also more readable code easier

It's early days on the product applications, but the fundamental power is being able to find correlations and connections across a huge corpus and output a large variety of rough ideas that can then be selected and polished by humans. It doesn't replace human expertise and creativity, but it will chip away at the bottom where many jobs are essentially rote tasks with very little human-level judgement needed, and more apropos to the GP, it will provide an increasingly powerful assist to human experts who learn how to harness it.

I don't see how that's a better position than general automation, which software has been chipping away at the bottom rung of for decades. Most jobs outside of mass produced SEO Buzzfeed garbage are not about generating large amounts of believable sounding prose. I could see it chipping away at the bottom rung of customer support, but that very quickly turns into work where real decisions have to be made and an 80% correct output is not acceptable. I'd be extremely surprised if any half serious company lets an LLM decide whether a refund should be processed or rejected, for example.

>The software business went from primarily being targeted at businesses, schools, and hobbyists to being targeted at mainstream consumers

The way I remember it, personal computers (initially called home computers) always had a market among individuals with those individuals initially being hobbyists, but becoming more consumer-ish fairly soon, certainly by the early 1980s when the video-game market became a large part of the market for software for personal computers--maybe for a year the major part. Once individuals owned personal computers, they started bringing them in to work, usually against the wishes of the IT department, and the enterprise PC software and professional PC software segments grew faster than consumer PC software--until about 1990.

Video and sound cards became popular around the same time as the CDROM drive, roughly starting in 1990, and the combination led to a "resurgence" in software for consumers--games certainly, but also things like Compton's Multimedia Encyclopedia (1989), The New Grolier Multimedia Encyclopedia (1992), Encarta (1993) and interactive fiction.

San Francisco was the center of the companies trying to reach this "multimedia" software market, and some writers started referring to SOMA and the Financial District as "Multimedia Gulch".

It boggles my mind that you think this "multimedia resurgence" I just described was anywhere as dramatic a shift as the Internet was!

Microsoft's main tag line during the marketing of Windows 95 was, "This way to the Internet." I must have heard that phrase a thousand time in Microsoft's ads. I don't recall Microsoft making any pitches to consumers to the effect that Windows 95 will allow them to take full advantage of their new graphics cards, sound cards or CD drives.

I kind of remember public interest in those things--and the"multimedia" software titles enabled by those things--having subsided by the time Windows 95 hit.

Windows 95 was years behind the state-of-the-art on the day "Chicago" shipped. The technical choice of the backslash for file system paths, and hiding the real disk contents from the user view, caused years of headaches. The architectural design choices for extensibility ended up as a swiss-cheese architecture for malware. MSFT-chairman literally saw himself as the new savior. glad you see this as important?

Important in terms of adoption.

None of your assessment matters regarding how big a deal it actually was. My mom didn’t give a damn about backslashes and my dad had zero use for seeing hidden files. The “state of the art” in 1995 was for nerds doing nerd stuff, Windows 95 was for regular people who couldn’t afford a Macintosh.

I fail to see how a minor choice such as what character to use as path separator has to do with being state of the art.

https://www.os2museum.com/wp/why-does-windows-really-use-bac... does a deep dive into the reasons for the choice, which seems more to do with backwards compatibility with DOS 1.0.

Win95 wasn't built on a base that had security in mind. And when the Win95 feature set was created, the world wide web wasn't in that list. TCP/IP wasn't either iirc. Dialup access was the main onramp to the internet. MSN was supposed to be Microsoft's main way to get users on to the internet (to fight against AOL).

If you don't have internet access, where is your malware coming from?

Floppies? No wifi to attack your printers.

Much easier to deal with a strange poisonous floppy the few times that you are given one than the 24/7 defenses needed when your box is ON the internet.

Well, Win95 was hobbled with the MSDOS base which was mainly concerned with CP/M familiarity when first designed. That's why Microsoft was working on windowsNT.

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