Artificial Intelligence – Expected unreality

Mr Altman’s agenda continues to defy gravity and reality.

• Sam Altman and Open AI appear to be intending to take over both the entire technology industry and everyone’s personal devices with schemes that sound as outlandish as those attached to the Internet in 2000 and autonomous driving in 2017.
• Sam Altman is currently on a tour in the Middle East where he appears to be looking to raise $5tn – $7tn ($6tn) (see here) which would be used to build the infrastructure to run all of the algorithms that completely take over users’ devices (see here).
• Both of these ideas sound great when they are first voiced but neither of them stands up to any double-checking with reality.
  • First $6tn: to invest in AI and AI infrastructure which is a number that beggars belief.
  • For example, the capital expenditure of the entire semiconductor and data centre industry is currently around $275bn per year Mr Altman intends to raise enough money for 22 years of industry capex.
  • Investors who invest in start-ups expect much higher returns given the elevated risks that are present in early-stage companies.
  • Typically, a VC would look for a return of 10x – 20x on an early-stage investment given how high the failure rate is when investing at this stage.
  • Consequently, Mr Altman would need to be promising returns in the order of $60tn which is 1.5x the entire printed money supply of the world, 25% of the wealth of the whole planet and 10x the market cap of Apple and Microsoft combined.
  • I don’t think much more needs to be said.
  • Second, device takeover: where according to The Information, Open AI is working on a new product which would combine complex tasks to become a super assistant.
  • The idea here is that the agent resides on the device and can carry out all of the tasks that the user would normally perform as part of his or her daily digital life or digital work.
  • For example, this could be choosing the best photo from a day out, writing the commentary and then posting it on all of the available social media channels without the user doing anything.
  • Another example would be downloading bank statements, analysing them, creating spreadsheets, conducting analysis and then entering the findings into a corporate accounting system.
  • This would be feasible if the large language models (LLMs) actually understood what it is that they are doing but the reality is that they are simply sophisticated pattern recognition systems and nothing more.
  • Furthermore, these machines have been shown to leak data and giving them unfettered access to personal and corporate systems and accounts is a gold mine of a hack waiting to happen.
  • These machines are unable to draw pictures of rooms without elephants or tell the time properly or reason anything that is outside of what they have been explicitly taught.
  • Consequently, I think the idea that rational humans and corporations are going to be willing to put them in charge of their digital lives and corporate operations does not hold water.
  • The problem is that to achieve the kind of returns being alluded to (see above), Mr. Altman will need to be promising situations where LLMs take over to this degree.
• The net result is that both the idea of raising $6tn to invest in AI and the use case that is now being promoted by Open AI are outlandish in the extreme.
• The problem is that the hype has gotten to such a level that this is now the degree that one needs to go to be seen as new or different as opposed to more of the same.
• The reality is that I don’t think that Sam Altman will raise even a tiny fraction of this sum and to me, this looks like the peak of inflated expectations as Gartner would put it.
• I continue to think that as the number of services based on LLMs grows, the price that the market will pay for these services will fall precipitously.
• It is when the start-ups look for more money, having missed their targets, that the inevitable reassertion of reality will begin.
• I suspect that this bubble will have a similar trajectory as autonomous driving with the difference that LLMs are able to generate good revenues and profits now.
• The key here is just that LLMs will generate much less of both than anyone thinks.
• Furthermore, there is no empirical evidence to suggest that these machines can reason, and they continue to hallucinate and make obvious mistakes at a frightening rate obviating them from most of the use cases currently being touted.
• Consequently, those looking for the dawn of the super-intelligent AI age are going to have to wait a very long time.
• I suspect that one will be able to acquire AI engineers and assets will be able to get much better prices over the next 12 – 18 months.