cdcox

I think there are few plausible reasons not mentioned.

We are still early in the tech. 2021 LLMs were not fit for any real purpose outside zany Madlibs. The tech has only really gotten fit for purpose since GPT4 and coherent models only got cheap and fast enough since llama 2 (July 2023). Even then smart models only got affordable around Deepseek v2 (May 2024) which was the first gpt4 level model to consistently serve subdollar per million tokens. You need at least a GPT4 level model to make a really interesting game. That's like a blink of time in game making time, indie games have 2-3 year cycles at best and AAA are like 5+. Even now fast, tool native interaction is only just coming online and there are no cheap models for that. Really fun game playing AI needs something like that to be magical.

There are AI games they just don't look like AI games neal.fun's Infinite Craft made a boat load of money and was very popular and it was powered by a Llama backend. Character ai and it's dozen copycats are like online storytelling/roleplay things. These are fairly popular. That could be a game or like a game platform or maybe it's more like fanfic. It has no fail state but people have made variants with fairly complex rules and states. Skryim and a few other games have pretty popular AI mods that let you add in NPC interactions that can talk, see, and even change their interactions with AI. The Skryim one Mantella has more than ~100k downloads.

We don't really have a northstar yet. Making a good game is really hard and usually takes someone doing something weird and clever. Minecraft is obvious in hindsight but many games on the way failed to make 'legos on the computer' fun. Incorporating AI breaks all the 'rules' of gaming. It operates slowly, it has high potential to break the rules and it has nearly unrecoverable failure states. Indie devs haven't figured out the best way to handle this and I suspect most big companies have just washed their hands of the whole thing until the AI gets faster, cheaper, and more stable.

The B2C case here seems off to me. The market of people who are going to pay the high price tag, have enough storage, and tolerate the extreme limitations and slowness of these machines seems to be: the rich, the elderly, and people with physical disabilities. The latter two categories come with a huge number of liability and regulatory costs that I think most of these companies are not willing to handle. That does not feel like a huge market.

I'll have a stronger belief in these things for consumers when we start seeing B2B adoption. Hotels have routine, highly structured cleaning tasks; hospitals have a need for extra strength, have highly structured cleaning tasks, and need to stock items; grocery stores have highly structured cleaning tasks and need to stock. Hospitals at least could tolerate the slowness of these things.

Without any B2B adoption it's hard to not see this as Roombas all over again. Cool for people who like it but low impact and still a toy 20 years later. I think generative AI makes these things better, though still perhaps struggles with long task adoption, but if you look at their movement they are still slow, weak, cognitively inflexible, and unstable. Maybe this tech is accelerating in some way I don't see and I'd love to be proven wrong here.

While this seems true and I hope these companies get a large fine and some regulatory action takes place to wipe out these third party apps, I'm kind of surprised at the corporate learned helplessness here.

Back in the day McDonald's or one of their fast food competitors would have built their own frozen potato pipeline, made a massive marketing gimmick about cheapest fries and shattered this cartel quickly. It sounds like the companies are taking a high margin and the farmers would love to sell to anyone else. But it feels like the current managers at these fast food companies have gotten so used to outsourcing every part of production they lack the knowledge/remit to even try to set up a competing supply line.

It feels like only it's only efficient to focus core competencies if the people in charge of those stay smaller. Given how big companies can squeeze suppliers I see how they would end up consolidated. But if everyone is doing one thing and consolidating horizontally to negotiate better it becomes kind of red queen race.

Maybe when you have a multi-billion dollar supply chain and complex contract structure you can't just learn to do something new to solve a problem anymore.

The small players can't do much. As mentioned in the article, either potatoes and DIYing are cheaper or they aren't, but medium to large firms presumably could/should do something.

Absolutely, and in picking collabs with people who are willing to work with the weirdness and make it funny. Vedal is definitely a fantastic creator to make it work so well and the amount of fine-tuning and tweaking he must do must be unreal. But I think it still shows there is some hunger for this type of content, though you are probably correct that it still needs to be curated, gardened, worked with, and sometimes faked.

This was probably an okay idea terribly implemented. GenAI creators on social media kind of sense.

Neurosama, an AI streamer, is massively popular.

Silllytavern which lets people make and chat with characters or tell stories with LLMs feeds Openrouter 20 million messages a day, which is a fraction of it's totally usage. Anecdotally I've have non tech friends learn how to install Git and work an API to get this one working.

There are unfortunately tons of secretly AI made influencers on Instagram.

When Meta started these profiles in 2023 it was less clear how the technologies were going to be used and most were just celeb licensed.

I think a few things went wrong. The biggest is GenAI has the highest value in narrowcast and the lowest value in broadcast. GenAI can do very specific and creative things for an individual but when spread to everyone or used with generic prompts it start averaging and becomes boring. It's like Google showing its top searches: it's always going to just be for webpages. Making an GenAI profile isn't fun because these AIs don't really do interesting things on their own. I chatted with these they had very little memory and almost no willingness to do interesting things.

Second, mega corps are, for better or worse, too risk averse to make these any fun. GenAI is most wild and interesting when it can run on its own or do unhinged things. There are several people on Twitter who have ongoing LLM chat rooms that get extremely weird and fascinating but in a way a tech company would never allow. Silllytavern is most interesting/human when the LLM takes things off the rails and challenges or threatens the user. One of the biggest news stories of 2023 was an LLM telling a journalist it loved him. But Meta was never going to make a GenAI that would do self-looping art or have interesting conversations. These LLMs probably are guardrailed into the ground and probably also have watcher models on them. You can almost feel that safeness and lack of risk taking in the boringness of the profiles if you look up the ones they set up in 2023. Football person, comedy person, fashion person, all geared to advice and stuff safe and boring.

I suspect these things had almost zero engagement and they had shuttered most of them. I wonder what Meta was planning with the new ones they were going to roll out.

Too many users, I don't know Hugging Face's rules but they seem to limit how much each demo can use to a ceiling. When I ran it originally it was like 12 people using it, looks like the queue is now around 300 and Hugging Face doesn't spin up more instances. That being said the model is relatively small and can be run locally with at least 5 GB of VRAM according to the Stable Diffusion subreddit.