Done. In the next few weeks we'll make some bug fixes and performance improvements, and most importantly: pointwise revision. This will demonstrate an interactive machine that can fulfill commands, in a way never seen before.
In the slightly longer term: additional language
"can solve any problem"? Really?? Let's read the abstract in the image attached to the post, and see if the quote is correct. Ah wow! Somehow he forgot to quote the rest of the sentence! How is that possible?
The full quote is "can solve any problem solvable by boolean circuits
Show me one blockchain project which is not just more of the same thing. Show me one AI project which is not just more of the same thing. I'll show you one that ticks both boxes: @TauLogicAI$AGRS. Read my two recent articles here to see why it's the case
New achievement today: managed to constructively support Henkin quantifiers in the theory of Boolean algebras, which virtually concludes the main effort of jumping from software specification language to distributed network specification language.
Social media is in its stone age. When I post something, I can't see who agrees or disagrees with me, so I could engage in further deeper conversation. Using LLM to implement that? A joke. Mathematically impossible. But on #TauNet this will be just a small feature.
There's a fundamental problem with metacognition. If you have metacongnition, then you also need meta-metacongnition, otherwise the metacongnition will not be controlled. And so on ad infinitum. Unless the metacongnition reasons about itself. But no logician was ever able to do
Completely agree! We might see two more useful rounds of scaling, but after that we will need new techniques.
Add @billgates to list of people who see that scale is not enough.
& we need metacognition; don’t think we can get there without bringing symbols back in the mix.
Everyone's talking about safe AI. This is ridiculous: how can you even start speaking about safety without speaking about accuracy? We don't need an AI that doesn't kill people 99% of the time... Probabilistic AI (Machine Learning) will never be accurate, and this should be
"How did we get to the doorstep of the next leap in prosperity? In three words: deep learning worked. In 15 words: deep learning worked, got predictably better with scale, and we dedicated increasing resources to it."
Mark my words: it may take some time but machine learning (in
Right. Because software development is too in the dark ages. We're about to change it by bringing formal methods to the forefront, with better logics and better collaboration abilities. #TauNet
At least they don't go backward, but they still go to the left instead of forward:
1. If first order logic theorem provers could practically verify nontrivial programs, they'd revolutionize the swdev world long ago. In fact the only reasonable swspec lang, not only for
"The results show that a four-way interaction is difficult even for experienced adults to process without external aids."
Yes, we humans suck. But LLMs suck even more: you can do better than LLM with only some minutes of work. The only way to surpass the human capabilities is
