Haha, their new AI safety strategy is to slow the development of the technology by dumping, to lower the price too much to fund bootstrapped competitors. :-)

I highly doubt it. OpenAI, Google and Meta are not the only ones who can implement these systems. The race for AGI is one for power and power is survival.

LLM can do amazing things, but it’s a basically just an autocomplete system. It has the same potential to take over the world as your phones keyboard. It’s just a tool.

They want this, the interview from their CEO sorta confirmed that to me, he said some crap about wanting to release it slowly for "safety" (we all know this is a lie).

But he can't get away with it with all the competition in other companies coming on top of China, Russia and others also adopting AI development

Yeah we're in an AI landgrab right now where at- or below-cost pricing is buying marketshare, lock-in, and underdevelopment of competitors. Smart move for them to pour money into it.

We have got to find a word for things that are plainly harmful yet advantageous to their perpetrators that's more descriptive than "smart..."

Agree. I didn't want to moralize, just wanted to point out it's a shrewd business move. It's rather anticompetitive, though that is hard to prove in such a dynamic market. Who knows, we may soon be calling it 'antitrust'.

For that you need 2 words: venture capital

Shrewd or cunning

capitalistic, monopolistic

Tactical

Uberly?

I prefer uber-esque

I prefer Webvan-esque. From https://en.wikipedia.org/wiki/Webvan:

> The company's investors pressured it to grow very fast to obtain first-mover advantage. This rapid growth was cited as one of the reasons for the downfall of the company.

IMO, selling at a loss to gain market share only makes sense if there are network effects that lead to a winner-takes-all situation. Of which there are some for ChatGPT (training data when people press the thumbs up/down buttons), but is that sufficient?

Also useful for bootstrapping a dev ecosystem.

If engineers are getting into AI development through OpenAI, they're using tools and systems within the OpenAI ecosystem.

Daily on HN there's a post on some AI implementation faster than chatgpt. But my starting point is OpenAI. If you can capture the devs, especially at this stage, you get a force multiplier.

It's called "predatory pricing".

https://www.ftc.gov/advice-guidance/competition-guidance/gui...

capitalism

Economists call this price dumping

anti-competitive predatory pricing

Yeah, if I was an owner or investor like Jasper.ai (AI written content generation SaaS) I'd be pretty worried right now.

Not very effective considering that it will be remade in open source 1-2 years from now.

> As the cost of GPUs goes down

Has that been happening? I guess there's been a bit of a dip after the crypto crash, but are prices staying significantly lower?

> or they develop at ASIC or more efficient model

This seems likely. Probably developing in partnership with Microsoft.

It's definitely not happening at the high end of the market (NVIDIA A100s with 40GB or 80GB of RAM).

The cards that were used for mining have since crashed in terms of prices, but those were always gamer cards and very rarely Datacenter cards.

The market segmentation is likely a result of Nvidia's monopoly position. They double the RAM and flops, improve the thermals and housing and sell for ten fold the price. It doesn't make sense to me. A cheap 4090 theoretically outperforms even the A6000 RTX Ada. https://timdettmers.com/2023/01/30/which-gpu-for-deep-learni...

Nvidia needs to satisfy gamers, who individually can't spend more than a few $k on a processor. But they also have the server sector on lockdown due to CUDA. Seems they can easily make money in both places. Maybe those H100s aren't such a good deal...

If someone understands these dynamics better I'd be curious to learn!

The main limiter in the data center setting is licensing, interconnects, and ram.

By contract - you can’t sell 4090s in a data center. You’ll find a few shops skirting this, but nobody can get their hands on 100k 4090s without raising legal concerns.

Likewise, nvidia A100s have more than a few optimizations through nvlink which are only available on data center chips.

Lastly, per card memory matters a lot Nvidia has lead the market on the high end here.

Nope, this is about it. They try to force the larger users into the expensive cards by prohibiting datacenter use in the driver EULA. This works sufficiently well in America, but it also means that you can find German companies like Hetzner that will happily rent you lots of consumer cards.

(There are also some density advantages to the SMX form factor and the datacenter cards are passively cooled so you can integrate them into your big fan server or whatnot. But those differences are relatively small and certainly not on their own worth the price difference. It's mostly market segmentation.)

I understood this as $/FLOP, I think it's plausible that that has been happening.

OpenAI doesn't have to make money right away. They can lose a small bit of money per API request in exchange for market share (preventing others from disrupting them).

Maybe I'm just old but back in my day this would be called "dumping" or "anti-competitive" or "market distortion" or "unfair competition". Now it's just the standard way of doing things.

Sure it would be called those things and then nothing would come of it. If a country uses morally compromised methods to win a war history just calls it winning the war.

The winners write the history books

That seems to be changing. I've seen an uptick in criticism against the usa for unnecessarily (according to top military advisors, experts, generals etc at the time) dropping the atom bomb on Japan for example.

Wouldn't stop anyone from doing it again if the stakes were high enough

Absolutely. The bombing of Dresden has been viewed as a mistake - verging on a war crime - in Britain for the last 20 or so years.

By some people - that's certainly not a universal view.

Verging on? It was a mass murder of civilians. The US holocausted Japan and got away with it.

And Japan did similar levels of atrocities to Korea, China, and others in the region.

We can acknowledge that things were historically pretty horrible and strive to be better in the future.

You kidding? What do you think a business loan is? Almost every business needs some form of subsidy to get off the ground.

Microsoft isn't using Nvidia A100s for inference are they? Seems like they'd use their Project Brainwave custom FPGAs.

Who will they be making money from? OpenAI is looking for companies willing to:

- tolerate the current state of the chatbots

- tolerate the high per-query latency

- tolerate having all queries sent to OpenAI

- tolerate OpenAI [presumably] having 0 liability for ChatGPT just randomly hallucinating inappropriate nonsense

- be willing to pay a lot of money for the above

I'm kind of making an assumption on that last point, but I suspect this is going to end up being more small market business to business than mass market business to consumer. A lot of these constraints make it not really useable for many things. It's even somewhat suspect for the most obvious use case of search, not only because of latency but also because the provider needs to make more money per search after the bot than before. There's also the caching issue. Many potential uses are probably going to be more inclined to get the answers and cache them to reduce latency/costs/'failures' than endlessly pay per-use.

Anyhow, probably a lack of vision on my part. But I'd certainly like to know what I'm not seeing.

Sadly, it will likely mostly be used to generate endless streams of SEO spam. Not for interactive use.

> Who will they be making money from?

Videogames maybe?

https://www.youtube.com/watch?v=ejw6OI4_lJw

This prototype is certainly something to have an eye out for

A lot of companies use third parties to provide customer support, and the results are often very low quality and full of misunderstandings and what we now call hallucinations. I think a good LLM could do a better job and I bet it'd be cheaper, too. And as a bonus training the bots to handle new products is practically instant when compared to training humans.

Lots of usecases actually need creative "hallucinations" where they are valuable.

Even e.g. to develop hardware such as planes and cars: https://assistedeverything.substack.com/p/todays-ai-sucks-at...