George Hutchings

Statistics and Machine Learning PhD student at @UniofOxford previously at @imperialcollege

[Jascha Sohl-Dickstein @jaschasd]

Have you ever done a dense grid search over neural network hyperparameters? Like a *really dense* grid search? It looks like this (!!). Blueish colors correspond to hyperparameters for which training converges, redish colors to hyperparameters for which training diverges.

[Nataniel Ruiz @natanielruizg]

We are 🔥super excited🔥 to release the Platypus family of finetuned LLMs 🥳🥳. Platypus achieves the top score in the Hugging Face Open LLM Leaderboard 🏆! The main focus of our work is to achieve cheap, fast and powerful refinement of base LLMs.
page: https://t.co/QHJ6kDoCYa

[Geoffrey Hinton @geoffreyhinton]

The University of Toronto made a video for a non technical audience in which I explain how deep learning works, the enormous promise of this technology and some of the potential risks. https://t.co/d0Izl3RYbS

[Julian Togelius @togelius]

So that paper about how GPT-4 could ace MIT's curriculum turns out to be deeply flawed in multiple ways. A great reminder that preprints are not peer-reviewed, but also that public volunteer review can be excellent (in this case, by a group of undergrads).
https://t.co/3LEc4Gp0Gw

[Marc Andreessen 🇺🇸 @pmarca]

Why AI Will Save The World -- my new megapost on why you should be excited, not scared, about AI. Enjoy!

https://t.co/GyWVLACezb

[Jan Leike @janleike]

Really interesting result on using LLMs to do math:

Supervising every step works better than only checking the answer.

Some thoughts how this matters for alignment 👇

https://t.co/foK7NCN1IV

[Paul Couvert @itsPaulAi]

ChatGPT has now a big problem.

Google just updated its free competitor, Bard.

Here are 8 things impossible on ChatGPT but that Bard can do (for free):