There are more indie games than ever before. The issue is AAA games have become billion dollar projects. They are funded and structured far more like AAA movies than other software. Making games is easy. Getting the money together to spend $500 million on development and $500 million on marketing isn't easy.
Yes, but I am not sure I understand how all this gives us monopsony. If there are so many indie projects, how doesn't it contradict the claim of monopsony?
Employee pay depends on the margins of the industry. High margin industries can afford to pay high wages. Game publishers have nowhere near the margins of Google.
It's very insulting. I don't need them to talk to an AI. I talk to AI all day already. If all a person is doing is forwarding messages to AI why do we need them? Just have an AI do their job.
The current hype cycle is about measurers getting fired. But as far as I can tell there is no new product using AI to track performance going around. What exactly is AI doing to replace the measurers?
I recall working on a project that used (MSVC) VC++ and a coworker found a bug in the compiler. We reported the issue to Microsoft and they eventually patched it.
You may find yourself arguing explicitly for open source dev tools if you continue down this line. There are many commercial cases where "you can fix it" does not apply to the dev toolchain and you will find yourself reliant on a provider. At that point, the trustworthiness of "compiler provider" and "local LLM provider" is the pertinent discussion (e.g. provider vs. provider instead of LLM vs compiler).
Gemma 4 31b is better for coding than Gemini in my limited testing on a small C project single source file project, less than 1000 lines. Setting temperature to 0 gives better results for me. It seems like Gemini ignores the system prompt more and the default reasoning output seems more incoherent.
Their open weight on device models are really impressive. Partly because I think they are the only ones out of all the frontier labs even working on local models.
Yaah I feel the same way. Gemini is great at and Django and AI backends, OpenAI better at making something visually pleasing in React and Claude for everything else or across frontend and backend.
At least, that's my heuristic that tends to work for my workflow. I use a combination of Gemini-CLI, Claude Code, and Github Copilot, but across those, the underlying model choice works best according to which part of the applicaiton I am messing with
It's a toss-up - NB Pro (and NB2) were in the lead for a long time, but gpt-image-1.5 and then particularly gpt-image-2 pretty much closed the gap on my GenAI Image Showdown benchmark site.
NB still generates better looking images though for the most part - gpt-image series is still affected by the yellow saturation issues though its been heavily mitigated.
gpt-image-2 still has a very visible banding/artifacting, but nb2 and gpti2 each have their strengths to the point that its momentarily worth running the same prompt through both and grabbing the better result, then feeding it to the opposite model to tweak it. both of them do a better job of not "getting stuck" regurgitating the same thing over and over when the base image comes from the opposite model. i tend to try and limit how many edits i make with gpti2 because successive iterations degrade the image much much faster.
Apple may be behind, and even getting sued for false advertising around AI features, but at least they haven’t spent hundreds of billions of dollars with no indication of how they’ll make their money back.
You’re right, they’re simply playing a different game. That said, Apple sold millions of phones with the promise that 3 months later users would be able to use AI to automate their phones and use Siri similar to how they use ChatGPT. That was summer 2024, and it still hasn’t shipped.
If by "happened to" you mean pour significant resources for well-over a decade on many different AI research groups then yes, that's accurate. Depending on your definition of AI, it might even be two decades.
In fact, OpenAI was founded largely with the direct goal of preventing Google from being the sole winner in AI...
Yes, you're right, but Google are not an AI company in the same sense Anthropic or OpenAi are and are focused on their products differently and it kind of shows..
> Why is Google the 2nd or 3rd tier player in the AI coding market?
2nd, 3rd? No way. You either use Claude Code or Codex, the 3rd option usually was Github Copilot. The only time I heard someone used google for code writing it was Linux Torvalds in one of his commits.
Because for awhile they had access to infinite money printing press (search ads), and in the situation like this it’s impossible to focus and seriously compete in other areas.
Essentially all Google efforts were in protection of search ad revenue.
Where have you been? Google has always been terrible with enterprise products. They are in the low cost, small company part of the analytics/enterprise market. The medium or large sized customers have been burned by them too many times to ever go back at this point. If you use them, you deserve what you get these days. No idea why you think Google was ever some quality provider of enterprise tools. They were declining even before they entered those markets. It isn't 2008 anymore and the Google you remember hasn't existed in well over a decade.
Because their strategy wasn’t to become leaders but to be as good as it takes to erode the lead of others. They have the cash cow of search so they don’t rely on AI to succeed. All they need is to keep publishing new products/services to keep OpenAI from taking the initiative. Between that and the Chinese models all they have to do is wait for the bubble to burst at which point every major AI lab would go bust.
What lead? Maybe because I'm mostly using AI/LLMs for development, but neither Google, Anthropic, xAI or anyone else has ever been in the lead, OpenAI always had the best models in my mind, as long as you're comparing the "top" plans between all of them.
Besides, they all seem to shoot themselves in the foot, OpenAI included, seems the only thing that differs is how often and how big the damage is.
All the labs astroturf all the social media, HN is not unique and OpenAI wouldn't be the only ones. I even receive offers sometimes on my email put in my HN profile, asking me to post about their project in exchange for money.
Be skeptical of anything you read online, not just what you think is "obvious astroturf".
Wait what? Why don't I get emails like this too? /s
(on a serious note, do you feel comfortable naming and shaming such companies, this is sort of a serious accusation imo and if not then how much money they are trying to give. It would be an interesting discussion and feel free to mail me if its confidential, waiting for your response and have a nice day :-D)
Nah, maybe one day I do a collective public post of it, for now I just try to get their company and/or name first, then forward it to HN themselves so they can ban them and keep an eye out for them.
Could you give us how many companies are trying to do this and also if any of the companies are YC companies themselves or not, I imagine not but still.
and what is the metric for companies sending you messages, like I have never gotten a single message (aside from one/two companies here and there and I even made a HN post about one of the companies)
and what do these companies really have a metric for in terms of sending spam for? karma points, I mean emsh I remember we both had close enough about the same karmas not too long ago, surprised to see you at 13k+ karma, so good to see that but is the metric karma, hype (you had made the rust browser ..) or what exactly? I would be curious to hear your thoughts on that!
I do understand the point of these companies sending mail though, I mean I can't say that if I had a company at the moment I might not do the same either, but I think that you might get frustrated too with it, so what would your recommendation be to people sending you mails in general?
So far just 3-4 at this point, some I guess figure out what I try to do when I ask for their company name and HN username, none of them been YC companies so far AFAIK. I don't know why they send specifically me emails, I guess either some automated system or they themselves see I spend way too much time on HN already, maybe just based on the amount of comments, I do have quite a bit of free-time :)
The HN guidelines explicitly ask you not to make these accusations.
> Please don't post insinuations about astroturfing, shilling, brigading, foreign agents, and the like. It degrades discussion and is usually mistaken. If you're worried about abuse, email hn@ycombinator.com and we'll look at the data.
I probably wouldn’t say they always had the best model but for years OAI was definitely pushing the limits both on model quality and product offerings. It was not until the last year or so that Anthropic started punching above their weight.
> It was not until the last year or so that Anthropic started punching above their weight.
Anthropic's stuff been useful for the last two years I'd say, especially in the beginning of Claude Code, but as soon as the Codex TUI was available, I was daily-driving both of them, literally executing the same prompts for each of them and comparing the final results, and Codex simply writes better code in 9/10 cases (but still not always).
I was a regular Claude Code user but Codex eventually won me over due to a few factors:
1. Less interaction required over long horizon tasks.
2. You actually get the amount of tokens they advertize. It's been an open secret on r/Claude that over the last several months, due to supposed "bugs" in Claude, users on the Max plan have seen over 50% of their tokens used on a single prompt. Super annoying.
3. Really strong image generation capabilities.
That's not to say OpenAI's current generosity will last, but for now I definitely see Codex as the stronger option between the two.
I’ve heard about that “open secret” and I don’t understand.
What’s the incentive for Anthropic to pump up the token usage on their top end plan? Is it to move Pro users up to Max? That’s the only plausible idea I can think of.
Claude Code has only been around for a year and change. At least for our internal tests 2 years ago Anthropic models started to at least become semi-useful but they still were not great, they struggled with structured output. Prior to that their alignment strategy made the products highly unhelpful in an API context. The past 6 months to a year is where Anthropic has really shined, they have model parity and sometimes taking the lead and more importantly their product offering on the consumer side has crushed it.
> Claude Code has only been around for a year and change.
We've been experimenting with "agent harnesses" way before that though, I'm sure the first time I tried building that sort of thing was in 2023 sometime with GPT3, and I'm like 80% confident I tried the same sort of TUI experience as CC from some random user before Claude Code even became public.
There are plenty of shills for all of the major labs on this website. Usually checking a history of comments of a suspicious user reveals that quite fast.
Who wouldn't exists if someone else didn't invent something else, which wouldn't exists...
We're all standing on the shoulders of giants here, I don't think one party is more responsible than someone else, unless you're specifically involved with the specific technology, then you can attribute it to them.
So yes, Google's researchers might have invented the Transformer, but OpenAI researchers invented GPT. Does it matter we credit "LLMs" more to one than the other? I don't think so, especially in this context it's highly irrelevant. Google didn't have the "LLM lead" before LLMs even existed...
This. Neural Nets have existed conceptually since the 1950s. They weren't realized materially and practically until later, but it's astonishing how ignorant people are of the history of AI.
> Great, tell me again who put the Transformer into LLMs?
Google did, as they already said.
OpenAI was better at marketing and a lot more willing to cannibalize the search market as a newcomer. So Google blew their lead in research by not recognizing the product value quickly enough, or failing to win an internal political war on it anyway
Yeah, you're right, maybe needlessly harsh, sorry for that. I guess I'm tired of the same argument that Google somehow had a lead in LLM development because Transformer comes from researchers who worked at Google, yet somehow what comes before/after Transformer doesn't count, coming from Google's researchers (BERT) or others (GPT), or going even earlier so, hence the whole "we stand on the shoulders of giants".
We can go round and round about all this but I think it's pretty clear that google did at one point have a large AI lead in the lead up to covid. They had models that far surpassed the competition from 2018-2022. But they were facing an innovators dilemma, didnt want to cannibalize their search revenue so they sat on LLMs which ended up creating openAI and anthropic.
It's doubtful they have the compute to make mythos publicly available even after the SpaceX datacenter deal. And why sell it publicly if people are still willing to pay for Opus 4.7?
I'm really running into this deep at the edges of content creation. Take, for example, a need to general some kind of legal work. The cost of painstakingly checking and rechecking each case cited is reducing the value of these frontier models immensely.
Coding, however, is solved like magic. Easier to add tests, to be fair.
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