[ygjb]

Of course they won't. The investment in the Heavy Press Program was the initial build, and just citing one example, the Alcoa 50,000 ton forging press was built in 1955, operated until 2008, and needed ~$100M to get it operational again in 2012.

The investment was made to build the press, which created significant jobs and capital investment. The press, and others like it, were subsequently operated by and then sold to a private operator, which in turn enabled the massive expansion of both military manufacturing, and commercial aviation and other manufacturing.

The Heavy Press Program was a strategic investment that paid dividends by both advancing the state of the art in manufacturing at the time it was built, and improving manufacturing capacity.

A GPU cluster might not be the correct investment, but a strategic investment in increasing, for example, the availability of training data, or interoperability of tools, or ease of use for building, training, and distributing models would probably pay big dividends.

[dmix]

I don't think there's a shortage of capital for AI... probably the opposite

Of all the things to expand the scope of government spending why would they choose AI, or more specifically GPUs?

[devmor]

There may however, be a shortage of capital for open source AI, which is the subject under consideration.

As for the why... because there's no shortage of capital for AI. It sounds like the government would like to encourage redirecting that capital to something that's good for the economy at large, rather than good for the investors of a handful of Silicon Valley firms interested only in their own short term gains.

[hluska]

Look at it from the perspective of an elected official:

If it succeeds, you were ahead of the curve. If it fails, you were prudent enough to fund an investigation early. Either way, bleeding edge tech gives you a W.

[Geezus_42]

Or you wasted a bunch of tax payer money on some over hyped and over funded nonsense.

[ygjb]

Yeah. There is alot of over hyped and over funded nonsense that comes out of NASA. Some of it is hype from the marketing and press teams, other hype comes from misinterpretation of releases.

None of that changes that there have been major technical breakthroughs, and entire classes of products and services that didn't exist before those investments in NASA (see https://en.wikipedia.org/wiki/NASA_spin-off_technologies for a short list). There are 15 departments and dozens of Agencies that comprise the US Federal government, many of whom make investments in science and technology as part of their mandates, and most of that is delivered through some structure of public-private partnerships.

What you see as over-hyped and over-funded nonsense could be the next ground breaking technology, and that is why we need both elected leaders who (at least in theory) represent the will of the people, and appointed, skilled bureaucrats who provide the elected leaders with the skills, domain expertise, and experience that the winners of the popularity contest probably don't have.

Yep, there will be waste, but at least with public funds there is the appearance of accountability that just doesn't exist with private sector funds.

[seunosewa]

You'll be long gone before they find out.

[hluska]

Which happens every single day in every government in the world.

[alickz]

how would you determine that without investigation?

[phatfish]

If it succeeds the idea gets sold to private corporations or the technology is made public and everyone thinks the corporation with the most popular version created it.

If it fails certain groups ensure everyone knows the government "wasted" taxpayer money.

[JumpCrisscross]

> A GPU cluster might not be the correct investment, but a strategic investment in increasing, for example, the availability of training data, or interoperability of tools, or ease of use for building, training, and distributing models would probably pay big dividends

Would you mind expanding on these options? Universal training data sounds intriguing.

[ygjb]

Sure, just on the training front, building and maintaining a broad corpus of properly managed training data with metadata that provides attribution (for example, content that is known to be human generated instead of model generated, what the source of data is for datasets such as weather data, census data, etc), and that also captures any licensing encumbrance so that consumers of the training data can be confident in their ability to use it without risk of legal challenge.

Much of this is already available to private sector entities, but having a publicly funded organization responsible for curating and publishing this would enable new entrants to quickly and easily get a foundation without having to scrape the internet again, especially given how rapidly model generated content is being published.

[mnahkies]

I think the EPC (energy performance certificate) dataset in the UK is a nice example of this. Anyone can download a full dataset of EPC data from https://epc.opendatacommunities.org/

Admittedly it hasn't been cleaned all that much - you still need to put a bit of effort into that (newer certificates tend to be better quality), but it's very low friction overall. I'd love to see them do this with more datasets

[randomdata]

If the public is going to go to all the trouble of doing something, why would that public not make it clear that there is no legal threat to using any data available?

The public is incredibly lazy, though. Don't expect them to do anything until their hand is forced, which doesn't bode well for the action to meet a desirable outcome.

[whimsicalism]

there are many things i think are more capital constrained, if the government is trying to subsidize things.