lowyek

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.

thanks for sharing. Your blog looks like a old forum board.

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.

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)

depends on the tasks.

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.

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.

Hi simon, is there a way to run the vision model easily on my mac locally?

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

thank you for sharing this!

TFA = The Freaking Article; wow! what a full form.

I find it fascinating that while in other fields you see lot of theorums/results much before practical results are found. But in this forefront of innovation - I have hardly seen any paper discussing hallucinations and lowerbound/upperbound on that. Or may be I didn't open hacker news on that right day when it was published. Would love to understand the hallucination phenomena more deeply and the mathematics behind it.

thank you. yes I meant that.

Must be fun working on cutting edge competitive stuff for all these 3 major teams. It's exciting to live in this times and see this all unfold in our eyes.