And the best part, most people shallow read all of them and decide the details are needless till they are forced to deal with the details and then their understanding falls apart in front of them
And in other places/times, gulping down your emotions and being stoic is all that matters. Also no one likes a person who is inert all the time, so there's also prepping for that.
I've noticed if at all there is any advice that is universally applicable overarching discipline, motivation, ... is growth.Plain and simple.The way to grow is so subtle, so easy to miss, negligent from afar and in the long run catches up to you. I've noticed going from someone who used to sweat profusely while ordering food to able to go and talk to anybody. But it didn't come consciously, it...
Iterative progress gives people the illusion of progress most of the time. Iterative progress is more a soother of emotions than an actual solution. Most of human problem solving techniques are based around soothing the anxious mind than tackling the problem
I'm always curious to know other folks' heuristics for better decision making whether it be "ask questions after action" or top-10 ways this will fail list and throw out the last 5. It helps to understand people in general and general forecasting of decisions
Efficiency and the real world will eat them(comp scientists who think like this) up for breakfast
Rule of thumb: if business folks drop a AI term that becomes the vogue lingo to use, be assured it is a fad that will meet it's doom in days to come
I don't think the bitter lesson is an absolute, but the current investment in agents is what you get when you ignore the bitter lesson
You're probably aware of things like hyping up your resume, hyping up your stories and the existence of people on the other side who know of this dog and pony show and continue to play along? What you're going through in my opinion is the AI age analogue of that: everyone probably uses them but the people who come on top are the people who are able to pretend they don't
"Humanity is a just a small step in the giant staircase of intelligence" - Geoffrey Hinton
I think you miss the aspect of how insignificant existence is locally.
Sure the odds are astronomical but you weren't there to experience that measure in it's entirety i.e the the billions of years for you to experience the specialness of the blip. Also compare that with billions of people current existing at the same time as you who are also the product of this astronomial odds. The awe of the statement of the specialness of existence quickly fades away when you take the former statement into consideration
One could take this in the opposite way, we're so special that we are barely get to live long enough to experience reality for what it is and have to make do with such a tiny drop. The unfairness of it is misery inducing. We are so special that we get to appreciate this specialness only if we're lucky enough to be born in a first world country and to decent parents and born healthy. Aside from that we have spent a very significant time sleeping, pooping, dealing with BS, dealing with things out of our control etc etc
Existing is truly miserable if you aren't living in a first world country.
Man your statement is just hollow. The astronomical odds of existence is nothing celebrate by itself just as hope by itself is useless
Finetuning has been looked down upon because all it does is rearrange weight to learn style of the finetuning dataset. It does not teach the model anything which is in contrast to the hopes behind finetuning
If a model was able to ace the arc-test just by the merit of being finetuned, does it not imply there is something of absolute substance here? i.e the model is capable of meta-learning and all it needs to adapt to a new-task is a bit of finetuning which again I emphasize is the loweest tier in the ranks of types of training models
From 1.criticism of how inadequate the transformer architecture is 2.depletion of training data 3.improvements to the attention mechanism 4. AGI supposedly being miles awaywhere does the new results put the field and what avenues need more focus and what others need less focus to the point of complete cutoff?
From criticism of how inadequate the transformer architecture is, depletion of training data, improvements to the attention mechanism, AGI supposedly being miles away; where does the new results put the field and what avenues need more focus and what others need less focus to the point of complete cutoff?
With all due respect, that is none of your damn business
"Interesting. I have no more questions"
Given how we live in transformer-led AI revolution seeing positive results on an unprecented scale, what did we as a species get wrong in our past attempts at AI? Why did GOFAI fail to produce the same level of results? Is it purely because the folks of the past lacked scale be it hardware and data? Attention seemed to be around for atleast a decade, but it was only recently did it gain...
A nice list of what bad problem solving looks like may help people identity it at the get-go and may help make the world a better placeI think a bad problem solving habit is the utter lack of tinkering with the problem and just expecting answers to pop up from continuously ruminating about the problem. Usually driven by stress and I've noticed this in some parents while child-rearing,...