Taha Bouhsine
@TahabsnML GDE @GoogleDevExpert | Deep Learning 2.0 Researcher | Aspiring Farmer . ChillEO @mlnomads | ML nomad, from the gradient dunes of the lost epochs
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bruh shii is working lol ViT results {'test': 0.7078999876976013, 'val': 0.722599983215332}
most people don't know that the original research on scaling laws came from Baidu in 2017 – not OpenAI in 2020 they characterized the effects of model params and dataset tokens on loss. also tested on images, and audio they just used LSTMs instead of Transformers, and didnt…
Change my mind: we won't reach agi without solving the xor problem with one neuron
d3js is the best viz tool ever created we gotta create a library of deployable components that can be used to understand nns
bruh if you wanna live the american dream live it to the fullest i officially created my first startup lol amma start looking for investors soon any recommendations or advice?
Why are people surprised that scaling is slowing down? Power laws for LLMs tell us that exponential increase in compute / data / model size yields linear decrease in test loss. This trend (researched since pre-2020) clearly tells us that LLM performance plateaus with scale.
one of the underated resources I found this year that helped me revisit tons of basics and translate my knowledge to english terminology openstax.org
If you can't find a good place to do research, guess what? you can still create an r&d company and do just that
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