Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Acquisitions, consolidation, and innovation in AI

frontierai.substack.com

Post reply on HN
Print view View original

31–40 of 45 posts

Re: Acquisitions, consolidation, and innovation in AI

#31

Post by no_wizard »

bongodongobob wrote: post #21
no_wizard wrote: post #2

I read the article and while it doesn’t say this nor imply it, this is my takeaway, though correct me if I’m wrong: Model innovation is effectively converging and slowing down considerably. 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 DeepSee…

> 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…

It certainly isn't maybe, look at the recent Shopify memo leak, and the way that lots of companies are talking about AI.

Any company with any sort of large customer service presence are looking at AI to start replacing alot of customer service roles, for example. There is huge demand for this across many industries, not only tech. Whether it actually delivers is the question, but the demand is there.

Re: Acquisitions, consolidation, and innovation in AI

#32

Post by no_wizard »

epistasis wrote: post #30
borski wrote: post #22

Earlier quoted context omitted.

> Companies are blocking AI carte blanche at the direction of their security teams What companies?

I know many IP-heavy and health-centric companies are blocking AI use severely. For example, pharma depends on huge amounts of secrecy and does not want any data leaked to OpenAI, and often has barely-competent IT and security staff that don't know what "threat model" means. Those who deal with controlled health data also block with a heavy hand.

I imagine it'll take time for any of this tech to permeate and the lower barrier of entry will see adoption faster - as is usually the case with new tech - but it'll make its way eventually. On premise AI will be a thing

Re: Acquisitions, consolidation, and innovation in AI

#33

Post by warkdarrior »

bongodongobob wrote: post #21
no_wizard wrote: post #2

I read the article and while it doesn’t say this nor imply it, this is my takeaway, though correct me if I’m wrong: Model innovation is effectively converging and slowing down considerably. 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 DeepSee…

> 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.

Re: Acquisitions, consolidation, and innovation in AI

#34

Post by vonneumannstan »

no_wizard wrote: post #19
vonneumannstan wrote: post #13

Earlier quoted context omitted.

>Model innovation is effectively converging and slowing down considerably. 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. You're just showing how disconnected from the progress of the fiel…

Depends on how they're applied. I've had success using LLama and while we check to see if OpenAI or Google's Gemini would give us any noticeable improvement, it really doesn't for our use case. While certainly newer models are more capable on the whole, it doesn't mean I need all that capability to accomplish the business goal.

This is kind of a useless statement. If your use case is so easy that "old" models work for it then obviously you won't care about or be following the latest developments but its just not accurate to say that Deepseek R1 is equivalent to o3 or Gemini 2.5.

Re: Acquisitions, consolidation, and innovation in AI

#35

Post by no_wizard »

vonneumannstan wrote: post #34
no_wizard wrote: post #19

Earlier quoted context omitted.

Depends on how they're applied. I've had success using LLama and while we check to see if OpenAI or Google's Gemini would give us any noticeable improvement, it really doesn't for our use case. While certainly newer models are more capable on the whole, it doesn't mean I need all that capability to accomplish the business goal.

This is kind of a useless statement. If your use case is so easy that "old" models work for it then obviously you won't care about or be following the latest developments but its just not accurate to say that Deepseek R1 is equivalent to o3 or Gemini 2.5.

Producing quality results is not the same thing as saying Deepseek R1 is the equivalent of o3 or Gemini 2.5

Again, its not about capabilities alone, (on this, many models lag behind, I already said as much). I follow these developments quite closely, and I purposely said results as to not say they're equivalent in capability. They aren't.

However, if a business is getting acceptable results from older models or cheaper models than capability doesn't matter, the results do. Gemini 2.5 can be best of breed but why switch if it shows no meaningful improvement in results for the business?

If I need more capability or results are substandard, I can always upgrade, but its like saying there's no room for cheaper processors and you'd be out of your mind not to be using only the latest at all times no matter the results.

Re: Acquisitions, consolidation, and innovation in AI

#36

Post by monoid73 »

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.

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 metaphor

Re: Acquisitions, consolidation, and innovation in AI

#37

Post by Der_Einzige »

vonneumannstan wrote: post #13
no_wizard wrote: post #2

I read the article and while it doesn’t say this nor imply it, this is my takeaway, though correct me if I’m wrong: Model innovation is effectively converging and slowing down considerably. 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 DeepSee…

>Model innovation is effectively converging and slowing down considerably. 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. You're just showing how disconnected from the progress of the fiel…

[flagged]

Re: Acquisitions, consolidation, and innovation in AI

#38

Post by luckylion »

no_wizard wrote: post #35
vonneumannstan wrote: post #34

Earlier quoted context omitted.

This is kind of a useless statement. If your use case is so easy that "old" models work for it then obviously you won't care about or be following the latest developments but its just not accurate to say that Deepseek R1 is equivalent to o3 or Gemini 2.5.

Producing quality results is not the same thing as saying Deepseek R1 is the equivalent of o3 or Gemini 2.5 Again, its not about capabilities alone, (on this, many models lag behind, I already said as much). I follow these developments quite closely, and I purposely said results as to not say they're equivalent in capability. They aren't. However, if a business is getting acceptable results from older models or cheap…

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, I can always upgrade

You wouldn't be able to upgrade (and see improved results) if the model you use today was close to equal to the top of the line.

Re: Acquisitions, consolidation, and innovation in AI

#39

Post by no_wizard »

luckylion wrote: post #38
no_wizard wrote: post #35

Earlier quoted context omitted.

Producing quality results is not the same thing as saying Deepseek R1 is the equivalent of o3 or Gemini 2.5 Again, its not about capabilities alone, (on this, many models lag behind, I already said as much). I follow these developments quite closely, and I purposely said results as to not say they're equivalent in capability. They aren't. However, if a business is getting acceptable results from older models or cheap…

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?

Re: Acquisitions, consolidation, and innovation in AI

#40

Post by borski »

epistasis wrote: post #30
borski wrote: post #22

Earlier quoted context omitted.

> Companies are blocking AI carte blanche at the direction of their security teams What companies?

I know many IP-heavy and health-centric companies are blocking AI use severely. For example, pharma depends on huge amounts of secrecy and does not want any data leaked to OpenAI, and often has barely-competent IT and security staff that don't know what "threat model" means. Those who deal with controlled health data also block with a heavy hand.

Once upon a time, they blocked docker too. Things change.
Post reply on HN