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Open-weight AI is having its Kubernetes moment

tobi.knaup.me

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Re: Open-weight AI is having its Kubernetes moment

#71

Post by danny_codes »

petilon wrote: post #37

Enormous amounts of money is being invested in the development of AI models. Investors expect returns on their investment or they will not continue investing. Open weights make it harder for investors to get their money back, so it harms the industry. Once the weights are out, it makes no sense to ban them in the US while the rest of the world takes advantage of it. But that doesn't mean developers of frontier models…

Ridiculous. If investors wish to set their money on fire investing in over-valued companies, they are welcome to do so. Protectionism to preserve ROI is a dumb policy. Just look at the US car industry. We're building dinosaurs. On this trajectory we'll have 0% market share abroad in 10 years. Chinese EVs will probably get market share at a 100% tariff because US automakers fell so far behind.

Same situation in protectionism in AI. The rest of the world will simply lap us.

Another shill account I gues

Re: Open-weight AI is having its Kubernetes moment

#72

Post by sschueller »

amazingamazing wrote: post #44

Sadly until china scales production of hardware it really isn’t economical to run this stuff yourself. It is good it exists though to put pressure against the labs. Honestly imo this is just proof apple will win in the end. Eventually a phone will be able to run a model good enough to do most things and it then is game over.

Model-on-Chip is coming. GPU are for general computing but have a huge bottle neck for doing model inference.

Even not being able to significantly update a model that is burned on a chip the performance gains are immense. You also don't need the latest chip fabs to make them drastically reducing the cost.

Re: Open-weight AI is having its Kubernetes moment

#73

Post by cheriot »

Open-weight and OSS are wildly different and the article makes a poor comparison.

What's the incentive for the Chinese labs to continue releasing weights 5 years from now? It's not a stable equilibrium and cannot last.

- The lab spending large sums on research and training does not get the inference revenue to fund those efforts.

- Unlike OSS where a single volunteer can keep a project going, training costs run into the $billions.

- OSS is often a two way street where features and integrations are built that the original author benefits from. Open weight models are largely a one way street because the marginal benefit is so much less than training costs.

In the short term, it means Chinese labs can attract talent and, I suspect, funding from their gov. Similar to every other industry the CCP subsidized to take over.

Re: Open-weight AI is having its Kubernetes moment

#74

Post by Aurornis »

firasd wrote: post #2

One of the strangest things in the AI industry is 'tokenomics'. It's not very clear why using GPT-4 in early 2023 was so expensive and then six months later 20 bucks could get you a fair amount of GPT-4 inference. This pattern has continued across various labs/providers for years--there is a continuous see-saw of pricing that doesn't seem related to anything. So what open weight models do is at least provide a baseli…

> It's not very clear why using GPT-4 in early 2023 was so expensive and then six months later 20 bucks could get you a fair amount of GPT-4 inference.

The price is what the market is willing to bear for the available compute capacity and competitive landscape. You can only discover that price after trying different price points and seeing what happens.

Everyone is trying different pricing schemes and discounts as they test the market. The demand is fluctuating at the same time.

It’s probably very confusing if you’re primarily familiar with stable and mature markets. Price fluctuations are a common feature of new and evolving markets.

Re: Open-weight AI is having its Kubernetes moment

#75

Post by yard2010 »

xyzsparetimexyz wrote: post #11
netdur wrote: post #10

why would any software want to have Kubernetes moment? can't count how devop I know that is confused by it

I still don't know what it is tbh. Something for docker?

I was in the same boat as you until I needed to learn how to use it in my $dayjob. It was like discovering a new continent. I couldn't care less about it before, but the moment I realized it's a kind of cloud OS I was astounded by how this thing is genius. It's the kind of thing that gives you dopamine rushes when you use it. Something about how there is a solution to every problem you didn't know even mattered turns it into a magical perfect software. I just love it.

There is something special about complex systems that just-work(tm)

Re: Open-weight AI is having its Kubernetes moment

#76

Post by sschueller »

thih9 wrote: post #16

Is anyone using open weight models for agentic coding? What is your stack (harness, model) and how much do you pay per month? How would you compare your experience to a typical subsidized plan like Claude Code + Pro plan? I’m asking because i keep hearing that open weight models are cheap and efficient - is that really the case in practice?

Kilo code with direct API payment to DeepSeek. It costs pennies per day event at max.

Re: Open-weight AI is having its Kubernetes moment

#77

Post by m4rtink »

spwa4 wrote: post #17
firasd wrote: post #2

One of the strangest things in the AI industry is 'tokenomics'. It's not very clear why using GPT-4 in early 2023 was so expensive and then six months later 20 bucks could get you a fair amount of GPT-4 inference. This pattern has continued across various labs/providers for years--there is a continuous see-saw of pricing that doesn't seem related to anything. So what open weight models do is at least provide a baseli…

Because as per usual it's silicon valley misunderstanding economics. AI is HPC. And how the HPC market worked before: If you're the best performing "computing cluster" (ie. whatever you call the entity that can complete a massive calculation), you get a blank check from Congress. Why? Because you need those calculations to "pump" nuclear weapons. They are needed to calculate both the geometry to make fusion bombs pos…

I'm sure Teller could make you a 10 gigaton nuke with a slide rule if you did not mind some sub scale tests.

Re: Open-weight AI is having its Kubernetes moment

#78

Post by m4rtink »

yard2010 wrote: post #75
xyzsparetimexyz wrote: post #11

Earlier quoted context omitted.

I still don't know what it is tbh. Something for docker?

I was in the same boat as you until I needed to learn how to use it in my $dayjob. It was like discovering a new continent. I couldn't care less about it before, but the moment I realized it's a kind of cloud OS I was astounded by how this thing is genius. It's the kind of thing that gives you dopamine rushes when you use it. Something about how there is a solution to every problem you didn't know even mattered turns…

So Kubernetes is LSD? ;)

Re: Open-weight AI is having its Kubernetes moment

#79

Post by rolymath »

gwbrooks wrote: post #30
julianlam wrote: post #9

Earlier quoted context omitted.

Why do prescription medications cost so much, and generics so little (comparatively)? Artificial inflation to recoup R&D.

Not sure pricing to recoup costs is artificial.

Not sure they're just recouping costs and not lining their execs pockets.

Re: Open-weight AI is having its Kubernetes moment

#80

Post by pianopatrick »

Eventually I think to truly be like Kubernetes, you would need an AI model that has public training data and that a lot of companies collaborate on.

Might make sense eventually. Same logic as companies working on Linux. "An AI model is a business necessity. But making an AI model is so expensive we should not make our own. So let's just use the open one, and contribute the stuff that we need."

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