Readit NewsBlender cannot do that as far as I understand.
Something like that for example: [1]
I asked GPT which one is the most scriptable CAD software, it's answer was Freecad. Blender is not a CAD software as far as I understand, the user cannot make measurements like Freecad.
Unfortunately Freecad's API is a little bit scattered and not well organized, GPT has trouble remembering/searching and retrieving the relevant functions. Blender is a lot more popular, more code on the internet, and it performs much better.
We used to have deterministic systems that required humans either through code, terminals or interfaces (ex GUI's) to change what they were capable of.
If we wanted to change something about the system we would have to create that new skill ourselves.
Now we have non-deterministic systems that can be used to create deterministic systems that can use non-deterministic systems to create more deterministic systems.
In other words deterministic systems can use LLMs and LLMs can use deterministic systems all via natural language.
This slight change in how we can use compute have incredible consequences for what we will be able to accomplish both regarding cleaning up old systems and creating completely new ones.
LLMs however will always be limited by exploring existing knowledge. They will not be able to create new knowledge. And so the AI winter we are entering is different because it's only limited to what we can train the AI to do, and that is limited to what new knowledge we can create.
Anyone who work with AI everyday know that any idea of autonomous agents is so beyond the capabilities of LLMs even in principle that any worry about doom or unemployment by AI is absurd.
What LLMs can't replace is network effects. One LLM is good but 10 LLMs/agents working together creating shared history is not replaceable by any LLM no matter how smart it becomes.
So it's simple. Build something that benefit from network effects and you will quickly find new ideas, at least it worked for me.
So now I am exploring ex. synthetic predictions markets via https://www.getantelope.com or
Rethinking myspace but for agents instead like: https://www.firstprinciple.co/misc/AlmostFamous.mp4
AI want's to be social :)
Bayesian epistemology is an attempt to model why science works--it relies on science, not the other way around.
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Deutsch is confused by this situation because he doesn't have the scientific background to understand the usefulness of negations of hypotheses.
Historically, for example, a lot of people believed the sun revolved around the earth. If we treat this as T, then ~T is "the sun does not revolve around the earth".
~T certainly lacks details, but to say it's a "bad explanation" is rather silly. Obviously it's an incomplete explanation, which is why Galileo presented a full explanation ("the earth revolves around the sun") rather than just saying, "the sun does not revolve around the earth". But in fact, "the sun does not revolve around the earth" was the part that was controversial because it was the bad explanation being presented by the church (who happened to be closer to philosophers than scientists).
Basically, Deutsch is just making a straw man argument. In Deutsch's mind, the fact that "the sun does not revolve around the earth" is an incomplete theory of heliocentrism is somehow a refutation of all science, when in fact that's simply not the sort of hypothesis scientists even explore typically.
I can assure you Deutsch is no confused by anything in that matter and it's obvious you don't know who he is.
He is literally the guy who created quantum computation and IS a scientist.
And no that's not his argument against the the sun is revolve around the earth.
Too bad China has neither of those things!