#PyTorch just released an awesome tool to visualize matrices and what's happening inside them. Matrix multiplications (matmuls) are the building blocks of today’s #ML models.
It can run in browser: https://t.co/Budpu0YVQ0
#AI#datascience#machinelearning#GenerativeAI
If you are thinking about joining in this #ML frenzy, stop trying to think how to best do it; just do it! Just pick a book or write some code, make mistakes, and move from there! See you on the other side!
#AI#datascience#GenerativeAI#MachineLearning
To prove this, researchers tested GPT-3 and LLaMA on made-up facts in one direction and then test them on the reverse. Result: "near 0% accuracy on reversals"
New paper is shaking the world of LLMs. The "Reversal Curse".
Language models trained on “A is B” cannot generalize to “B is A”, a complete failure of logical deduction.
Code: https://t.co/ga6og2gw4B
Paper: https://t.co/Pjwbq52kpi
#AI#ML#Datascience#GenAI#machinelearning
If a model was trained on: “Jack Dorsey was the first president of twitter" It will not automatically be able to answer the question: “Who was the first twitter president?”
At @Bloomberg they paid >1 million $ in training costs for something that is outperformed by a 100$ model only six months later.
This gives you an idea about the pace that LLM training and development has been moving at this year.
https://t.co/eIxgIMD3Um
https://t.co/gDs2M7wRzK
The researchers from Microsoft find that this leads to a much broader skill set learned by the model than simply continuing pre-training on domain specific data. Despite the financial domain, they've also evaluated their technique for Law and Medicine.
Nougat: OCRing scientific papers with a deep net trained end to end. From @Meta
Website: https://t.co/XdAaFjpaSS
Paper: https://t.co/XxAlHmzzdn
Code: https://t.co/40MTlfTsn1
Trained on: * a whooping 3.5 trillion params * ~4096 GPUs * 7M GPU hours (4x more compute than LLama 2) License: Can be commercially used but under restrictive terms apparently
Falcon 180B model has just been released! This makes it the largest (BLOOM 176B, OPT 175B) and the most capable (comparable with PaLM 2 Large) "openly" available language model!
TII is doing some serious engineering feats here!
Check the model here:
https://t.co/D7mZJyAPZD
#AI
This information is then combined with inertial sensors to estimate the drone’s position, orientation, and speed on the race track. Then, a neural network controller trained with deep reinforcement learning in simulation, combined with data collected in the physical world,