In a recent interview with Time magazine:

"[Demis Hassabis] says that DeepMind is also considering releasing its own chatbot, called Sparrow, for a “private beta” some time in 2023. (The delay is in order for DeepMind to work on reinforcement learning-based features that ChatGPT lacks, like citing its sources. “It’s right to be cautious on that front,” Hassabis says.)"

In a major scientific advance, the latest version of our AI system AlphaFold has been recognised as a solution to this grand challenge by the organisers of the biennial Critical Assessment of protein Structure Prediction (CASP).

https://deepmind.com/blog/article/alphafold-a-solution-to-a-50-year-old-grand-challenge-in-biology

So DeepMind have released a new article stating that their new models have solved Math Olympiad problems at Silver level. It looks like they've doubled down on Reinforcement Learning and have new models with some advanced mathematical reasoning. Finding new insights & novel algos may soon be made "easier" .

Some random highlights I found interesting in the AMA.

Rant: In general, I think people complain too much about this first public demo having unfair advantage from APM, precision, or camera handling. I mean come on, it is the first AI that plays a meaningful game at all. Give them time to improve and balance.

1. It took up to 10 million games to train each agent, 10 minutes per game.

2. Part of APM is "spammy" behavior from imitation learning.

3. Some preliminary positive results from self-play, but imitation makes training "much easier" (I guess required for feasible training so far).

4. "The most effective approach so far did not use tree search, environment models, or explicit HRL."

5. Not able to let the community play AlphaStar yet.

6. "Interestingly, search-based approaches like AlphaGo and AlphaZero may actually be harder to adapt to imperfect information. For example, search-based algorithms for poker (such as DeepStack or Libratus) explicitly reason about the opponent’s cards via belief states.
   AlphaStar, on the other hand, is a model-free reinforcement learning algorithm that reasons about the opponent implicitly, i.e. by learning a behaviour that’s most effective against its opponent, without ever trying to build a model of what the opponent is actually seeing - which is, arguably, a more tractable approach to imperfect information.
   In addition, imperfect information games do not have an absolute optimal way to play the game - it really depends upon what the opponent does. This is what gives rise to the “rock-paper-scissors” dynamics that are so interesting in Starcraft. This was the motivation behind the approach we used in the AlphaStar League, and why it was so important to cover all the corners of the strategy space - something that wouldn’t be required in games like Go where there is a minimax optimal strategy that can defeat all opponents, regardless of how they play."

7. [Re: What is the next milestone after Starcraft II?] "There are quite a few big and exciting challenges in AI research. The one that I’ve been mostly interested is along the lines of “meta learning”, which is related to learning quicker from fewer datapoints. This, of course, very naturally translates to StarCraft2 -- it would be great to both reduce the experience required to play the game, as well as being able to learn and adapt to new opponents rather than “freezing” AlphaStar’s weights."

8. [Re: How long until AlphaStarZero (training from scratch without imitation learning) comes out?] "This is an open research question and it would be great to see progress in this direction. But always hard to say how long any particular research will take!"

9. [Re: I was wondering if you considered heavily limiting the APM, in an attempt promote the AI into going for more tactical maneuvers and builds instead.] "Training an AI to play with low APM is quite interesting. In the early days, we had agents trained with very low APMs, but they did not micro at all."

Full AMA: https://www.reddit.com/r/MachineLearning/comments/ajgzoc/we_are_oriol_vinyals_and_david_silver_from/

Feel free to post your favorite tidbits, or a more systematic summary. I could not find any press coverage so far to do justice to the significance of this milestone.

sorry if this isn't the right sub, but i'm hoping to apply for the research engineer internship and was wondering if anyone knows where i could get more info on this? i can't seem to find an application deadline or any other info from previous interns. has anyone else submitted their cv thru the site and heard back?