This year is quite vibrant on new AI tech, with papers coming out in inspiring abundance. October was no exception. A multitude of papers on meta-learning, new SotA language models and techniques, advances in generative AI in various media formats. This post is an attempt to summarise and project some consequences of the recent developments.

The following submission statement was provided by /u/SpaceDepix:

This year is quite vibrant on new AI tech, with papers coming out in inspiring abundance. October was no exception. A multitude of papers on meta-learning, new SotA language models and techniques, advances in generative AI in various media formats. This post is an attempt to summarise and project some consequences of the recent developments.

Please reply to OP's comment here: https://old.reddit.com/r/Futurology/comments/yk3892/multiple_breakthrough_papers_from_google_deepmind/iur01en/

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We haven't had significantly better algorithms since 1969? That seems far fetched?

As per the official deepmind article (source provided in my article):

“In our paper, published today in Nature, we introduce AlphaTensor, the first artificial intelligence (AI) system for discovering novel, efficient, and provably correct algorithms for fundamental tasks such as matrix multiplication. This sheds light on a 50-year-old open question in mathematics about finding the fastest way to multiply two matrices.”

“…Beyond this example, AlphaTensor’s algorithm improves on Strassen’s two-level algorithm in a finite field for the first time since its discovery 50 years ago. These algorithms for multiplying small matrices can be used as primitives to multiply much larger matrices of arbitrary size.”

matrix multiplications require doing additions (and subtractions) and multiplications.

GPUs can do additions (and subtractions) faster than multiplications.

by rejiggering the way the matrix multiplication is written you can use less multiplications and more additions thus it runs faster on the same hardware.

https://en.wikipedia.org/wiki/Strassen_algorithm

>Volker Strassen first published this algorithm in 1969

.....

>In late-2022, AlphaTensor was able to construct a faster algorithm for multiplying matrices for small sizes (e.g. specifically over the field Z 2 \mathbb {Z} _{2} 4x4 matrices in 47 multiplications versus 49 by the Strassen algorithm, or 64 using the naive algorithm).[2] AlphaTensor's results of 96 multiplications for 5x5 matrices over any field (compared to 98 by the Strassen algorithm) was reduced to 95 a week later with further human optimization.

>Interestingly enough, AlphaTensor is a successor to AlphaZero - DeepMind’s algorithm developing strategies for games that cannot be solved or heuristically optimized. This once again outlines a powerful pattern for AI training - simplify and regularize a real-world problem into a game, then let AI master this abstract but interpretable environment.

this was my simply observation when i gave the question some thought a few years ago, and as I've continued to observe the nature of intellect. I don't consider myself to be a super genius, just very mentally patient, it's something that anyone can do, Anyone can introspect and observe the principles of our thinking. When people argue for free markets they don't mean literally anything goes, they just mean that, as hayek observed, that people's natural manifestations of what to do, to supply ourselves with what we want and need tends to be the best. central planning as never succeeded, not because in a utopist sense it wouldn't be nice for everyone to be equal, but because it's impossible to execute. It leads to shortages, price hikes, and still a hierarchial priviledge, just one based on who you know. Open societies with few top down restrictions tend to be more egalitarian, even if they aren't perfect, with openness comes risk, but still it's better than expecting that leaders can be built up to an understanding of all the problems, in the attempt to control things they don't understand, leaders make problems worse

>Open societies with few top down restrictions tend to be more egalitarian

that's not true. Nordic countries have above average top-down controls and outperform "more free" markets like the US in spite of the much higher overall wealth of the US. there is clearly a middle ground that is ideal, simply by looking around the world at developed countries and which ones are most stable, happy, educated, etc.