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Acquisitions, consolidation, and innovation in AI

frontierai.substack.com

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Re: Acquisitions, consolidation, and innovation in AI

#41

Post by mattmanser »

monoid73 wrote: post #36
mattmanser wrote: post #14

Earlier quoted context omitted.

I personally find their UX frustrating, basically a junior developer's attempt at doing a front end. What do you think is so good about it? It's also janky as hell and crashes regularly.

I think the UX of chatgpt works because it's familiar, not because it's good. Lowers friction for new users but doesn't scale well for more complex workflows. if you're building anything beyond Q&A or simple tasks, you run into limitations fast. There's still plenty of space for apps that treat the model as a backend and build real interaction layers on top — especially for use cases that aren’t served by a chat meta…

I wouldn't call it familiar, it's a weird quasi-chat. They didn't even do the chat metaphor right, you can't type more as the AI is thinking. Nor can you really interrupt it when it's off over explaining something for the 20th time without just stopping it.

It's missing obvious settings, has a weird UX where every now and mysterious popups will appear like 'memory updated', or now it spews random text while it's "thinking", it'll every now and then ask you to choose between two answers but I'm working so no thanks, I'm just going to pick one at random so I can continue working.

People had copy pasta templates they dropped into every chat with no way of savings Ng thatz they they added a sort of ability to save that but it worked in a inscrutable and confusing manner, but then they released new models that didn't support that and so you're back to copy pasta, and blurgh.

It's a success despite the UI because they had a model streets ahead of everyone else.

Re: Acquisitions, consolidation, and innovation in AI

#42

Post by bongodongobob »

warkdarrior wrote: post #33
bongodongobob wrote: post #21

Earlier quoted context omitted.

> This is demonstrably untrue. CEOs are chomping at the bit to reorganize their business around AI, as in, AI doing things humans used to do and getting the same effective results or better, thereby they can reduce staff across the board while supposedly maintaining the same output or better. Nah. Maybe tech CEOs. Companies are blocking AI carte blanche at the direction of their security teams and/or only allowing an…

Claiming these AIs "don't do much" overlooks the very real productivity gains already happening – automating tedious tasks and accelerating content creation. This isn't trivial and will lead to the deeper integrations and streamlined (read: downsized) workforces. The reorganization isn't a distant fantasy; it's already here.

I don't disagree, but your average excel jockey isn't going to build out these automation workflows and likely neither will IT. I'm not saying AI isn't useful. I'm saying the average person doesn't know what to do with it.

Re: Acquisitions, consolidation, and innovation in AI

#43

Post by [deleted] »

mattmanser wrote: post #14
nc wrote: post #3

One thing this article gets wrong is how OpenAI isn’t an application layer company, they built the original ChatGPT “app” with model innovation to power it. They’re good at UX and actually have the strongest shot at owning the most common apps (like codegen).

I personally find their UX frustrating, basically a junior developer's attempt at doing a front end. What do you think is so good about it? It's also janky as hell and crashes regularly.

[deleted]

Re: Acquisitions, consolidation, and innovation in AI

#45

Post by luckylion »

no_wizard wrote: post #39
luckylion wrote: post #38

Earlier quoted context omitted.

That's not what GP was saying though. To stay with that analogy, the assertion was that "all processors are kinda the same, there's no real qualitative difference", which sounds pretty strange. It's somewhat accurate if your use-case is covered by the average processor and the faster one doesn't benefit you. They're not equal, but all of them surpass your needs. > If I need more capability or results are substandard,…

That wasn’t the assertion. The results - not the models themselves, not strictly speaking their over all capabilities - if they have no meaningful improvement by moving to a newer model, why then would I want to switch if I’m not getting any tangible improvement in results?

> The big companies in this space doing the research are not making leap over leap with each release, and the downstream open source projects are coming closer to the same quality or in fact can produce the same quality (e.g DeepSeek or LLAMA) hence why it’s becoming a commodity.

This was the assertion. "Open source is close/equal in quality", not "open source is enough for plenty of use-cases, not everyone needs the top of the line".

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