Now that ChatGPT4o is out, it's time to revisit my previous thoughts on AI, and discuss what might be happening in the future, and what evidence we have of what might happen.

00:00 Current brief status of AI
03:21 ChatGPT-4o is faster. at least
03:30 The Multi-modal interface isn't new
04:00 What matters for disruption?
04:48 Science and measurement
05:46 What counts as evidence?
07:54 ChatGPT-4o benchmarks
10:39 Psychology of Humans and AI
11:28 Dark Patterns
12:35 History of AI demos
18:40 New article about AI Hype
19:54 Conclusion

Sources from Video have been moved to a pinned comment, since the description field ran out of characters.

https://www.youtube.com/watch?v=VctsqOo8wsc&lc=UgxfeL871kHWrc5-S154AaABAg

Denis Bolkovskis

Anthropic

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The post discusses the overhyped expectations surrounding AI, particularly with the recent release of ChatGPT-4o. It raises concerns about the potential short-term and long-term impacts on the job market, especially in software development. The author critically evaluates the current advancements and limitations of AI technologies, highlighting evidence of both progress and deception in the industry. Ultimately, the post encourages readers to focus on factual evidence rather than hype when assessing AI's future impact.

AI Hype is completely out of control - especially since ChatGPT-4o

There’s no where near enough hype. People are massively underestimating the power of the current models, never mind the next ones.
The issue, and the reason that people feel these models aren’t living up to expectations, is because the software isn’t there.
To get a good outcome, you need to write your own scripts. You need to be manipulating temperature during a conversation - marking what is and is not meant to be ‘creative’.
Using Mixture of Agents, good prompting, client-side tokenization, a carefully manipulating the creativity settings, I have been able to do some amazing things.
The guys working on Open-WebUI have some early days tech that is really wild. Using their tool, I had no difficulty writing a program that iteratively improved itself.
We haven’t begun to scratch the surface of what something like Claude 3.5 can do, much less what the more robust tool-using models can do. Anyone suggesting that this tech is over-hyped simply does not know how to use it.

So real. It’s a technology that’s been around for years that’s suddenly gained massive notoriety, and is just overhyped. It’s never gonna go away, but it’s just a tool, just like traditional algorithms. Just like how we went from gcc to rustc, we’ve gone from Translate to ChatGPT. It’s the refinement of tech. It’s not a miracle worker, it’s just linear algebra.

Maybe the hype will get at least a handful of more people to prepare?.. ie. get on the other side of the divide that will grow rapidly, I guess? The hype is just a wake-up call, if anything. Today it’s hype. 5 years from now it’s over before most people saw it coming?