Recent submissions

Comment · 1 year ago
I no longer take limitations seriously regarding the future of AI. If evolution created our brain, then the same law applies to what we are building also. Hence, more of less whatever written in this paper is some nuanced case which can be solved by some approach.
Comment · 1 year ago
thanks for sharing. Your blog looks like a old forum board.
Comment · 1 year ago
I think may be i am not with the right model. the reasoning looks so good here. May be the default model in chatgpt free is not the one which you used.
Comment · 1 year ago
I asked it 'find two primes whose sum is 123' .. it is in deep thought from 5 minutes just looping and looping over seemingly repeated hallucinations of right path. (btw, chatgpt immediately answers 61 and 62 lol.. so much for intelligence)
Comment · 1 year ago
depends on the tasks.
Comment · 1 year ago
Are there any social aggregator networks? TBH I don't care about politics or anything - I just need latest updates on topics i like summarised.
Comment · 2 years ago
It's not very scientific but ->

I feel I am an abstract mesh of "virtual sensory nodes" inside the network of my brain. These nodes are free flowing in the abstract multi-dimensional network - but in varying degrees of freedom. While the inner core of this abstract sensory entity is the "me" I have total perfect grasp on, the outer nodes sway here and there a little bit. When I start meditating - I start to access the information touching these outer sensors. They are by default moving "a little", I just get more aware of them. But I being the core of this entity, can easily sway them to any other place.

I guess meditation is fun.

Comment · 2 years ago
Hi simon, is there a way to run the vision model easily on my mac locally?
Comment · 2 years ago
I would love to see some work on duality i.e. code to neural network back and forth. Reason being - I can't debug a neural network but if it can be linearized into a if-else case with help of the token information => I can validate what it's doing -> fix it and then move it back to it's compressed neural representation.

Just another thought experiment -> sometimes I imagine neural networks as a zip of the training data where compression algorithm is backpropagation. Just like we have programs which let us see what files inside the zip are -> I imagine there can be programs which will let us select certain inference path of the neural net and then see what data affected that => then we edit that data to fix our issues or add more data there => and we have live neural network debugging and reprogramming in the same way we edit compressed zips

Comment · 2 years ago
thank you for sharing this!

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