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I am a bit surprised that it hasn't been more weaponized yet for elections and wars. But it will be, no doubt about it.
That, to me, is not true. There are plenty of examples where a 10% incorrect answer is perfectly useful. For example in software with good test harnesses you can trust functions that pass tests whether they are written by staff, an intern or a bot.
But I do think that we have an AI bubble and need a brush fire to refocus on today's solvable problems. A 5-10% of industry effort going to moonshots is fine, 90% is crazy.
I for one am paying for generative AI in multiple areas such as image generation and code autocompletion. It's anecdata but it doesn't seem like I'm the only one willing to pay for this. I believe these valuable use cases that I legitimately think are worth paying for will stick around, and I think there are plenty more to still be discovered in the product space.
Finally, generative AI does have costs that makes it scale worse than the prices of the products using it in many cases (hence a lot of startups burning up their VC money too quickly on API costs), but there's a clear path to optimizing these costs by orders of magnitude, so again doesn't seem like an argument to say it's all a scam.
To me it seems that AI is not even priced into the market cap of the big tech companies yet. Since GPT-3 came out in mid 2020: Alphabet's market cap doubled. But their earnings more than doubled. Same for Microsoft. In other words: Their p/e ratio did not increase. The future potential of AI is not yet priced in. The cost of all human labor is something like $70 trillion per year. Automating 1% of that per year would…
- technological change, consumer benefit
- investing opportunity.
If you compare to internet revolution consumer benefit increased steadily, but as a general investment category it was total bust. During the internet revolution, Top 5 internet companies were Yahoo.com, AOL.com, Geocities.com, MSN.com, and Lycos.com. It took almost 10 years to Amazon stock to recover from 1999 average price longer to become a good investment. Cisco was the Nvidia of late 90s.
How about personal computer revolution? Tandy, Commodore, Atari, Apple, Acorn, Sinclair, IBM, ...
I can do basic back-on-the-envelope math as a retail investor. I pick investment forecasts for the global AI impact from a13z, Goldman Sachs, Nvidia, for the next 5 to 10 years. Then I do basic cash flow discounting. How the fuck these valuations make sense?
At some time in next 2-4 years there can be a crash and "dark fiber" equivalent for compute. Tensor compute prices crater and are dominated by energy prices. That's when the high impact innovations emerge to exploit all that available compute.
Earlier quoted context omitted.
> Has been shocking to see YC double down on LLMs so much in the last two batches. They also doubled down on blockchain sufficiently late in the game that it was obvious to most that there was zero value in all of it. Either they’re really getting high on their own supply, or there’s some kind of model where you hedge against missing out on a unicorn, even if all indicators point to the fact it’s vaporware.
Probably some of each. To me I see a lot of similarities to cloud computing early on (broadly defined). There were a lot of twists and turns in the road and a lot of things didn't tuen out as many predicted--and it was, naturally, much messier than earlier visions. But companies that decided to sit back and see how things played out mostly paid for it while the winners--so far--have mostly been companies that made be…
There is no comparison at all to AI which is fundamentally untrustworthy and may remain so for a while/ever.
https://archive.is/R5zkq It is relevant to point out that NYT is engaged in a legal battle with OpenAI. This article refers to "AIs like ChatGPT" which clearly shows who it is targeted at. For people thay don't read arxiv every day, the actual advancements are difficult to sift out of all the hype. The dilution of the meaning of AI will contribute to the bubble's contraction when the general public realises that "AI"…
The article is from WSJ
You can still make money selling shovels for a few years tho?
It’s the best demo-able software today that lets the customers’ minds go wild with the possibilities. But then the nuances of human abilities in commercial settings, like call center, become realities and obstacles that the software can’t surmount. Costs rise, productivity not so much, and then legal gets involved and it’s even more costly.
At least load on NVIDIA options....
This has been going on since the mid '60s. Last time the hype-cycle bust took with it the entirety of Lisp, which technology is gonna be killed this time around?