Former Google chief Eric Schmidt warns electricity shortages, not semiconductors, pose the biggest threat to AI superintelligence development. Here's what that means.
“Superintelligence is intelligence beyond the sum of all humans,” he wrote in a LinkedIn post Thursday. “It is reasonable to predict that we are going to have specialized AI savants in every field within five years.”
That is insane. I can’t even get one of these things to tell me “no, that API doesn’t exist”, it always makes one up that would be perfect for what I need if it existed, then apologizes profusely when I tell it it was wrong. It can’t write any original or novel code, just boilerplate that matches what it has seen before. What’s going to change in 5 years to suddenly give it creativity and a sense of self-awareness of its own knowledge?
The really crazy part is that it’s been like that for 4 years now, the models have improved based on arbitrary metrics the people making the models have decided upon, but in terms of real world usability they’re basically the same. Marginal improvement from running it twice to have it check its self, but only a marginal improvement by doubling the compute.
It’s insanity that they’re burning billions upon billions to keep this charade going.
At least with the dot com bubble there was a clear and obtainable use case to match the amount of hype. It got over invested in before it was fully ready, but there was at least an obvious path to something worth the cost of running.
This is definitely true for code but in terms of information retrieval and explaining complex topics, they have gotten much better in the sense that they can cite real sources (with links) now.
The analysis and synthesis that they do of those sources is still often bogus though. I’ve had one explain some simple Magic the Gathering rules with real-looking words but completely bogus interpretations and conclusions, but it did cite the correct rulebook with a link. I’ve also had one give a pretty strong overview of the construction and underlying theory of a particular compiler (a specific compiler, not the language it compiles) that matches up quite well with my own fairly deep understanding of that compiler.
Overall the real information is better, but the hallucinations look more real too. And they’re still pretty unhelpful for programming in my experience.
A marginal improvement for a limited use case, and often by having it generate a critical response to the output internally and use that to weed out particularly glaring errors, which, increases the amount of compute used significantly.
Not a revolutionary jump forward in capability. not a trillion dollar industry that justifies this level of investment or obsession.
That is insane. I can’t even get one of these things to tell me “no, that API doesn’t exist”, it always makes one up that would be perfect for what I need if it existed, then apologizes profusely when I tell it it was wrong. It can’t write any original or novel code, just boilerplate that matches what it has seen before. What’s going to change in 5 years to suddenly give it creativity and a sense of self-awareness of its own knowledge?
The really crazy part is that it’s been like that for 4 years now, the models have improved based on arbitrary metrics the people making the models have decided upon, but in terms of real world usability they’re basically the same. Marginal improvement from running it twice to have it check its self, but only a marginal improvement by doubling the compute.
It’s insanity that they’re burning billions upon billions to keep this charade going.
At least with the dot com bubble there was a clear and obtainable use case to match the amount of hype. It got over invested in before it was fully ready, but there was at least an obvious path to something worth the cost of running.
This is definitely true for code but in terms of information retrieval and explaining complex topics, they have gotten much better in the sense that they can cite real sources (with links) now.
The analysis and synthesis that they do of those sources is still often bogus though. I’ve had one explain some simple Magic the Gathering rules with real-looking words but completely bogus interpretations and conclusions, but it did cite the correct rulebook with a link. I’ve also had one give a pretty strong overview of the construction and underlying theory of a particular compiler (a specific compiler, not the language it compiles) that matches up quite well with my own fairly deep understanding of that compiler.
Overall the real information is better, but the hallucinations look more real too. And they’re still pretty unhelpful for programming in my experience.
A marginal improvement for a limited use case, and often by having it generate a critical response to the output internally and use that to weed out particularly glaring errors, which, increases the amount of compute used significantly.
Not a revolutionary jump forward in capability. not a trillion dollar industry that justifies this level of investment or obsession.