ChatGPT went all in on increasing the amount of data to work with to boost the AI capabilities, but just like all other tech sectors, it seems pretty clear that we find diminishing returns with each doubling in the amount of data.
Currently we have reached that point where only trillion dollar companies are capable of building better and better AI fast.
General AI even now can regurgitate the best answers, but it hasn't shown the capacity to create something truly new, that comes with the randomness that emerges from biological evolution.
General AI is limited by the total knowledge of humanity being fed into it, beyond which it cannot grow no matter what. It is the world's smartest answering machine.
Will AI be able to replace humanity? No.
Will AI be able to make robotic equivalents to human labor? Yes.
Today, the most advanced AI in the world is Gemini by google.
It is taking the efforts of the 4th most valued company in the world to keep developing and upgrading AI further.
The current AI boom was a random discovery and it will slow down as fast as it rose up.
General AI will very likely peak at being 2-3 times smarter than the smartest human, then go no further.
This is because it cannot create anything new, it can only pattern match all the data that already exists out there.
Until and unless we give AI the ability to "mutate" like human DNA does, it will reach an upper limit and stagnate at that point.
Conclusion:
AI won't take over the world. It will be another tool to help humans create more things faster, and finish up all the current backlog of research projects.
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I have bet a good chunk of my net worth that successful AI use cases will be essentially a replacement for industry/operation analysts. Feed large sets of data into the system and it gives you optimal results or multiple options for directives.
Generative AI for writing media is a fun parlor trick but like the article discusses, it misses the little quirks that fundamentally come from human error/ambiguity.
Faster thought horsepower is the real use case and will long term eat away at the middle management tier decision makers, which is why I am invested in Palantir, Microsoft, C3.ai and Oracle. Okay, that last one is because SAP exists only by rent seeking strategies and their AI development is smoke and mirrors (personal experience).
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!ghosts
Make note of this for your investments.
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This is a good bet, but it's also not really AI specific. Computers have been crunching data better, faster for generations. Excel meant a lot of analysts had to upskill or lose their jobs. How many hedge funds trade mainly based on signals from their computer models? Was it Renaissance Technologies that pretty much said "we just buy what the computer tells us to and it somehow makes money"?
Anyway I guess this is another chapter of defining-down AI so we claim what the computer is doing isn't "intelligence"
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That is a very good point. The "AI" that I've seen as actually useful is machine learning models that are able to collect otherwise inaccessible data. Like for instance, using machine learning to scan every purchase order and invoice a given company processes in their supply chain, where every vendor and customer uses different formats. Now that data can be readily synthesized and then it's just a matter of defining the optimizing equation and constraints, and that's just linear algebra. But wrapped all together i know many would call that "AI"
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This shit drives me fricking crazy.
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Yeah predictive AI through not ChatGPT was and is still better than ChatGPT.
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People are going to scream at me insider trading and other nonsense when stocks like Palantir pop off, but the knowledge is here, today.
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