tyronehed

This is a great book. I thoroughly enjoyed reading. She was extremely fair to Facebook executives.

So, you oppose their desire to diversify their funding? NPR gets 10% of their funding from tax dollars. Who you are harming is small rural public radio stations in red areas.

archive org. Look for the audiobook "Mawson's Will: The Greatest Survival Story Ever Told"

Especially if they are all me-too copies of a Transformer.

When we arrive at AGI, you can be certain it will not contain a Transformer.

As soon as you need to start leaning heavily on error correction, that is an indication that your architecture and solution is not correct. The final solution will need to be elegant and very close to a perfect solution immediately.

You must always keep close to the only known example we have of an intelligence which is the human brain. As soon as you start to wander away from the way the human brain does it, you are on your own and you are not relying on known examples of intelligence. Certainly that might be possible, but since there's only one known example in this universe of intelligence, it seems ridiculous to do anything but stick close to that example, which is the human brain.

This is actually a lazy approach as you describe it. Instead, what is needed is an elegant and simple approach that is 99% of the way there out of the gate. Soon as you start doing statistical tweaking and overfitting models, you are not approaching a solution.

When an architecture is based around world model building, then it is a casual outcome that similar concepts and things end up being stored in similar places. They overlap. As soon as your solution starts to get mathematically complex, you are departing from what the human brain does. Not saying that in some universe it might be possible to make a statistical intelligence, but when you go that direction you are straying away from the only existing intelligences that we know about. The human brain. So the best solutions will closely echo neuroscience.

Since this exposes the answer, the new architecture has to be based on world model building.

The alternative architectures must learn from streaming data, must be error tolerant and must have the characteristic that similar objects or concepts much naturally come near to each other. They must naturally overlap.

Any transformer based LLM will never achieve AGI because it's only trying to pick the next word. You need a larger amount of planning to achieve AGI. Also, the characteristics of LLMs do not resemble any existing intelligence that we know of. Does a baby require 2 years of statistical analysis to become useful? No. Transformer architectures are parlor tricks. They are glorified Google but they're not doing anything or planning. If you want that, then you have to base your architecture on the known examples of intelligence that we are aware of in the universe. And that's not a transformer. In fact, whatever AGI emerges will absolutely not contain a transformer.

Only Transformer based architectures are over.

It amazes me that everyone so fetishizes Transformer architectures that they cannot imagine alternative--when the alternative is obvious.

The first thing you need to understand is that no current llm based, transformer architected AI is going to get to agi. The design in essence is not capable of that kind of creativity. In fact no AI that has at its root a statistical analysis or probabilistic correlation will get us past the glorified Google parlor trick that is the modern llm in every form.

A great leap in IP but unfortunately is too important to blab about widely, is the solution to this problem and the architecture that will be contained in the ultimate AGI solution that emerges.

You need to start looking for big problems to solve. It was once said by a guy named Bruce Williams who knew what he was talking about that the way to get rich is to solve a problem.

So what you need to do is start looking for big problems. Not big problems that are only seen by developers, but big problems that are seen by the general public. People will pay for solutions. You will be motivated by solutions, something that you need to research the hell out of. Something you need to make connections that no one else has made before to solve. That's it

In life it's often more important what you don't do, then what you do do

I used to follow SpaceX so closely but now, given the behavior of Elon Musk, I cannot take any interest in any company connected to him.