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Re:Acquisitions, consolidation, and innovation in AI by vonneumannstan on Thursday April 24, 2025 @04:59PM (#43787422)
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 by no_wizard on Thursday April 24, 2025 @05:13PM (#43787578)
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 by luckylion on Thursday April 24, 2025 @05:46PM (#43787860)
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 by no_wizard on Thursday April 24, 2025 @06:03PM (#43788000)
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 by luckylion on Friday April 25, 2025 @06:51PM (#43799236)
> 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".