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Comment by mvkel | Hacker News Reader

My biggest frustration with the frontier AI companies isn't what they're announcing, but that the announced-thing that exists ~6 months later is severely nerfed to reduce compute spend. It doesn't resemble the demo in any way. For example, this was what the 4o voice capability sounded like in 2024(!) https://www.youtube.com/watch?v=vgYi3Wr7v_g. What exists today pales in comparison.

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Pretty much. Always-on doesn't scale as well as JIT access to a massive array of GPUs, because always-on means it's always-using-memory - so you're at least going to paying the cost of a minimum chips VPS for every Dot right?

Maybe people are ok with that, but I feel like it would be nicer to just sell a cheap SBC like a raspberry pi that you can plug in (and unplug!) and just pay for the tokens used instead of having your data stored offsite and paying cloud prices.

100% agree. Every model and launch feel like huge leaps then huge nerfs to the point it doesn’t feel like we’re going anywhere. Especially this year in particular for coding.

However, it is the case that other industries like 3d graphics and so forth have experienced a frontier shift so perhaps there’s still some advancement

After watching the video, I'm not understanding your objection. That's pretty much how the current bidi voice model sounds.

I think Dots just a precursor to their consumer hardware they've been working on with Ive. They could build a small on device model to handle the speech to text and text to speech. Then tie it in to their Dots ecosystem.

The non-transparent limits on subscription plans suck as well. You never know what you're paying for.

It's always about increasing monthly active users, locking them in, and then enshittifying to squeeze out profit.

Thanks. I'll stick with self-hosting.

I'd rather use the best possible model available than permanently relegate my work to an inferior one because it's "open"

It's not only about being open but predictability and unforeseen rug pulling.

Would you rather work with a team that is hit or miss, but has moments of brilliance, or predictably, consistently bad?

Glad someone is saying the quiet part out loud today

How do you afford to do this if you want something resembling the best that's out there right now? The hardware needed to run beefy open source models is like $15,000 to $50,000+ for a robust local multi-GPU rig, and even its performance might lag behind.

More like 2 weeks later. Around 2 weeks after Astra launched they started dropping the juice levels. I was able to run on low or med initially without problem. Now I need to run on xhigh and the results are still not as good as they were on launch.

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