Commodification of Intelligence: Good, Bad, and Ugly Circular AI Deals

cl42

Observing how the US stock market is behaving this week (up-down-up-down...), I feel like many investors don't appreciate the distinction between good and bad circularity.

andiey

If healthy and risky circular financing deals look similar at first, how can investors or regulators tell when a circular deal has crossed the line into something dangerous...especially when it's off the balance sheets?

firasd

I think the real question in all sorts of financial setups is really “is the dollar actually worth a dollar”. So when company A invests in company B which buys from company A the actual question is whether the valuation of the investment and the valuation of the purchase is correct or are they getting high on their own supply

Animats

Whether inference hardware will be a commodity remains to be seen. We had twenty years of most servers being x86-64. That's commodity compute. Inference hardware isn't a mature architecture yet. There will be progress and obsolescence.

rambambram

> commodification of intelligence Is HN really this fast!? Everybody already skipped the hard questions whether LLMs are intelligent? 'It' can already be commodified? So how much time and effort it took from these companies? A couple of years and millions spent on PR? And LLMs are "intelligent" all of a sudden, is what everybody says nowadays? Especially applicable for programmers: naming things is not only hard, it's also important, and can be very insidious. Remember, marketeers also name things. For example, naming the internet 'the cloud', some 15 years ago. I can't stop thinking about a quote of one of my favorite authors (Theo Kars): "Progress can only be technical in nature, because knowledge is transferable and wisdom is not." [translated from Dutch]

WalterGR

Recently: "Nvidia, CoreWeave, and Nebius: Inside the Circular Financing of the GPU Boom" (io-fund.com) https://news.ycombinator.com/item?id=48873836 370 points| 18 days ago | 182 comments

stego-tech

Excellent piece, but it does hinge on the idea that what we’re building is actual AI (still hotly debated), if it can be successfully commoditized like utilities (very unlikely given compute continuously evolves and the hardware cycles of datacenters relative to power plants or water filtration systems), and if such a healthy cycle - should it develop at all - survives the multiple decades needed to effectively provide ROI. Which is an awful lot of “ifs” to be hedging a bet on, especially at nation-state scales.

jgord

Has a competent economist modeled the circularity of these deals ? [ numerically or analytically ] It seems a healthy economy has a lot of wide circularity .. money circulating is a good thing, a result of a functioning market, tracking the flow of real goods / services. But large corps circulating paper 'self-deals' or debt-swaps seems like a bad thing - a creative accounting practice designed to pump up their stock price/valuation. How can we _quantify_ the difference ? I guess it would need to match the cash / debt flows against the movement of actual goods and services ?? Not an economist, feel free to weigh in, suggest links.

unjuno

The problem with circular transactions is that they can make companies look healthier than they really are, distort investment decisions, and cause widespread damage when the cycle breaks.

Stitch4223

So, companies are just prepaying with seemingly large parts of their livelihood for (use of) potential value. Expecting demand to stay equal over longer stretches of time in IT is an interesting bet as both hardware and software tend to depreciate in value extremely rapidly, unlike oil from the example. Or water. Both are limited in nature. Commodifying something that is the fraction of its value the next year might be possible, but I don’t see how. Perhaps MS Windows or Office are such things, but might not compare. There are more limits to demand. For example what humans can process. The AI might write the finest prose and the best software but have nobody to read or use it.

doodlebugging

We don't have an Artificial Intelligence yet. It is not intelligent, yet. Here's a quick reality check. Several companies have formed with a goal of creating and AI engine that can think for itself and reason through difficult or previously intractable problems. In order to accomplish this goal they have used scrapers to hoover up content from a multitude of sources, many of which can be seen as being the ground truth source for their discipline. A lot of this content, most of it, was copied and is being used without attribution to the original sources, without permission from the content owners or publishers, and in violation of copyright laws. Look at all of this for what it is. It is a knowledge base, like a collection of Lego parts, each of which is important to the goal but none of which will get you there without the other parts in the proper relative position. Once you have collected all these parts and stuck them together you have an LLM. If you are careful in your parts selection, that LLM can be useful for answering specific questions that are properly framed so that the LLM can make use of the contextual information in formulating a response. There's nothing intelligent about being able to answer a question correctly when the answer is effectively right on the tip of your tongue. You're just drawing from your knowledge base and regurgitating. Glomming all of it together only gives you a huge knowledge base. There is nothing intelligent about that knowledge base. Knowledge is not intelligence. You have an AK today, an Accumulated Knowledge base. We may never reach the point where it is ever intelligent enough to reason alongside of, or better than those whose life's work went into the foundation of the AK base.