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selimonder

252 karma · joined August 31, 2018

https://twitter.com/selimonder
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selimonder··on Jev-Leftpad
github.com/f is more impressive to me than jev-leftpad lol
selimonder··on Cerebras CS-4
That "GPU" comparison is the vaguest i seen so far
selimonder··on Want your images back? Sure... That'll be $5!
Wow this is a next level scam lol
selimonder··on Statement on US government directive to suspend access to Fable 5 and Mythos 5
Why Nations Fail? Lol
selimonder··on Vercel's CEO offers to cover expenses of 'Jmail'
Boo is the only think i can imagine when I hear about Vercel
selimonder··on Is Slack Down?
Seems to be down.
selimonder··on Towards General Auditory Intelligence
Full title is, Towards General Auditory Intelligence: Large Multimodal Models for Machine m
selimonder··on Ask HN: Is Google Slowly Dying?
They already died imho.

Lets admit it - previous research loop was going for a google search then iterating on results, which takes time and effort. LLM based research (although could be misleading) is just much faster and more suitable for natural language.

It happened.

This doesn't mean that Google will be obsolete, if it leverages its collected data so far it will be a strong competitor. But Google isn't leading at the moment.

selimonder··on I am dyslexic
align these ideas and check out the autism spectrum and get ready for your mind to be blown.
selimonder··on I am dyslexic
that’s inspiring.
selimonder··on Microsoft's Linux Kernel
Microsoft gained a lot of respect back! Great move executives, well done. But I believe in your intentions, keep it right, people like this.
selimonder··on Austrian government seeks to eliminate internet anonymity, with severe penalties
like people can actually breath while being spied by multiple big brothers.
selimonder··on Visualizing Memorization in RNNs
Great post. Long sequences are a problem I have been dealing with long enough now. Even though GRU outperforms LSTM in longer sequences, it still isn't enough and vanishing gradients problem is still experienced. Currently, one-dimensional convolution units are effective while dealing with longer time steps, but sadly it's not the precise unit people wish to use while processing longer time-steps.