Advameg, Inc. CEO
There is a new CFTC-regulated prediction market to add to this list: https://kalshi.com/.
There is a new study out that found that 40% of Copilot's code contributions in high-risk scenarios were vulnerable: https://arxiv.org/abs/2108.09293
According to https://www.sciencedirect.com/science/article/pii/S0896627321005018?dgcid=coauthor
"Cortical neurons are well approximated by a deep neural network (DNN) with 5–8 layers "
"However, in a full model of an L5 pyramidal neuron consisting of NMDA-based synapses, the complexity of the analogous DNN is significantly increased; we found a good fit to the I/O of this modeled cell when using a TCN (my note: temporally convolutional network) that has five to eight hidden layers "
For best performance, the width was 256.
Since L5 neurons can perform as small neural nets, this might have implications for the computational power of brains.
Yet-you-participate-in-society fallacy? Based on https://knowyourmeme.com/memes/we-should-improve-society-somewhat
I think your scheme might not be most effective if you write your daily updates without getting any input, even if you somehow know that people read them. I think I would give up at some point unless I was getting relevant feedback (it is better than nothing though).
What might work better is a buddy-type system with two or more people with the same procrastination problem, preferably also interested in the same subject, to keep each other accountable. If you'd like, I can do this with you for a period of time in addition to your updates and you'd get an idea of what's better.
I see that there is already a paid service https://actionbuddy.io/ that somehow matches people (no endorsement). I could set up a free site that does matching based on expressed interests if people are interested.
Have you read "Free Will" by Mark Balaguer https://mitpress.mit.edu/books/free-will ? Your argument is similar in some ways.
Related development: https://www.nature.com/articles/d41586-021-01968-y
"Meanwhile, an academic team has developed its own protein-prediction tool inspired by AlphaFold 2, which is already gaining popularity with scientists. That system, called RoseTTaFold, performs nearly as well as AlphaFold 2, and is described in a paper in Science paper also published on 15 July "
When it comes to medical diagnosis, I agree that the regulations will slow the adoption rate in the U.S. But then there is China. The Chinese government can collect and share huge amounts of data with less worry about privacy. And looking at the authors of ML papers, you cannot miss Chinese names (though some are U.S.-based, of course).
Your statement about AI copy editors is definitely true (I have some first-hand knowledge about what's possible but not yet publicly available).
I'd recommend posting about your challenge on http://talkchess.com/forum3/index.php. You will find people who are experienced in testing old and new chess programs and some might be interested in the prizes. If you don't have an account there, I can post a link for you.
Stockfish 12 and newer have neural network (NNUE)-based evaluation enabled by default so I wouldn't say that Stockfish is similar to other non-NN modern engines.
https://nextchessmove.com/dev-builds is based on playing various versions of Stockfish against each other. However, it is known that this overestimates the ELO gain. I believe +70 ELO for doubling compute is also on the high side, even on single-core computers.