Through Complexity to Emergence/ A Dyson Swarming Civilization/ DeepMind Predicts The Weather/ Work on Complex System Earns Nobel Prize/
Massimo Portincaso
Founder & CEO at Arsenale, Industrial Romantic and Antidisciplinarian Stoic
Through Complexity to Emergence. I was particularly pleased by the choice of the Nobel Prize winners for this year, both in Physics and Economics, for different but converging reasons. And I somehow hope they signal a tipping point in our relationship with complexity, starting to bring it into the mainstream and making the study and embracing of it a core tenet of our society.?
I have written already how I believe complexity is core to really understand and shape not only the environment we live in but also our future. In fact, Steve Hawking was 100% right when he was pointing to the 21st?century being the century of complexity.?
What I really liked by this’ year choice of the Physics Nobel Prize winners (more on it below in the newsletter) is that it awarded multiple scientists that all contributed massively to a better understanding of deep complex problems, advancing the science behind it. And, in the case of the Economics Prize, I liked that it awarded scientists that introduced an empirical revolution in economics. Empiricism is a prerequisite to really understand and manage complex adaptive systems. I really hope that we are seeing more and more such kind of work being rewarded and awarded, as this is what we need to design and shape a different world, one that goes from exploitative to generative.
I believe that we need to abandon as quick as possible the “fallacy of reductionism”, in which we think that through reductionism we can somehow control the environment in which we operate and manage complex adaptive systems. And truly hope that we manage soon to embrace complexity and make it one of the core tenets of our society, eventually abandoning the false idea of “mechanical control” (you cannot mechanically control a complex adaptive system)??and instead starting to embrace emergence.
Traveling at nearly 300 million meters per second, our civilization's early radio, TV, and radar waves would have reached thousands of neighboring stars by now. Does the lack of any response (at least, nothing "intelligent") help resolve the Fermi paradox? Not exactly - as Microsoft research scientist?Rohit Pandey ?points out, "detecting them at those distances would require antennas thousands of acres in size" for one; and the dozen intentional radio messages we've sent in the past 50 years, many will take thousands of years to reach their destinations. But we won't be so undetectable for long, because we're already on the road to?a Dyson swarm?- a collection of crafts orbiting the sun and collecting its energy (there are?already a few up ).
Pandey theorizes that since the swarm is a logical milestone of any civilization, and that the outgoing radiation from these crafts will be possible to detect, we would have been able to infer the existence of a Dyson swarm. Except, we haven't found one: "the fact that this hasn’t happened despite billions of opportunities in the galaxy is the root of the dilemma." It helps to figure out the preceding milestones that need to happen before Dyson swarms are even possible - from abiogenesis, to tool use, to space exploration - and how long these milestones might take. Is it a clear resolution to the paradox? Of course not. But it's a very fun read.
News items:
Plastic is an environmental scourge, and most isn't recycled. Enzymes, nature’s catalysts, may be able to help.
AlphaFold 2 -?DeepMind's protein-folding prediction system ?- broke the mold of your typical toy AI milestones. It showcased deep learning's biggest real-world impact since the?2012 ImageNet moment ?(actually, bigger). And it's what CEO?Demis Hassabis ?was aiming at for decades. DeepMind continues to tackle hard science problems, including something that's always been tricky for meteorologists: predicting the likelihood of rain in the next 90 minutes.
Outdoor events, filming, aviation, emergency services, and other industries rely on weather forecasts. But weather is hard: "Figuring out how much water is in the sky, and when and where it’s going to fall, depends on a number of weather processes, such as changes in temperature, cloud formation, and wind. All these factors are complex enough by themselves, but they’re even more complex when taken together." DeepMind developed DGMR, a deep learning tool that is able to predict the location, extent, movement, and intensity of rain 90% of the time. In a blind comparison with 56 forecasters, 89% preferred DGMR's results over both a state-of-the-art physics simulation and a rival deep-learning tool.
News items:
The Energy Department has a little-known investment operation, the Loan Programs Office, with a focus on backing innovative clean technologies in early commercial development - and it has more than $40 billion to lend.
When physicists have to describe slightly complicated systems, they simplify - as Quanta puts it, "a ball rolls the same way down a ramp whether it’s red or blue." But in chaotic systems, small details are vital components, as they can spiral into massive changes. New methods had to be developed to model these systems, and the people who pioneered them have recently been awarded the Nobel Prize in Physics.
Syukuro Manabe , a climatologist at Princeton University, and?Klaus Hasselmann , at the Max Planck Institute for Meteorology, were awarded half the prize. The two researchers built climate models in the 60s and 70s that have correctly predicted the effects of CO2 on the atmosphere. The other half went to?Giorgio Parisi , a physicist at Sapienza University of Rome, who discovered spin glasses, "a material containing magnetic particles — iron atoms, for instance — which you can think of as tiny bar magnets pointing either up or down"
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"Spin glasses have captivated physicists like Parisi because of a phenomenon known as 'frustration.' Imagine a simple spin glass consisting of three spins at corners of a triangle. Adjacent spins prefer to point in opposite directions. But the three spins, as they flip back and forth trying to attain a stable configuration, can’t all satisfy that constraint simultaneously; the system is what physicists call 'frustrated'.... Parisi’s studies of how this plays out in spin glasses 'were so deep,' according to the Nobel committee, 'that they not only influenced physics, but also mathematics, biology, neuroscience and machine learning, because all these fields include problems that are directly related to frustration.'"
News items:
How can something as small as a mouse make a such big impact in Microsoft’s commitment to sustainability? It all starts with plastic water bottles and the desire to make positive change.
UNXD , a "curated marketplace for the best of digital culture," recently auctioned off Dolce & Gabbana's Collezione Genesi NFT collection, said to be the "most complex fashion NFT created and offered so far." NFT collectors, a crypto company, and a?DAO ?bought the collection for a total of 1,885.719 Ether (north of $6M).?Nick Jushchyshyn , program director for Virtual Reality and Immersive Media at Drexel University, says the prices weren't surprising, given the NFT's star-power and attention to detail.
"Five of the pieces were physical creations, designed and executed by Dolce & Gabbana, with virtual iterations by UNXD for the metaverse: two versions of The Dress from a Dream... The Glass Suit... and two gold-plated and gem-studded silver crowns, called The Lion Crown and The Doge Crown. The four other pieces were solely digital: three richly embroidered men’s jackets and The Impossible Tiara, made of 'gems that can’t quite be found on Earth,' as Dolce & Gabbana?explained on Twitter ."
News items:
A researcher exploring Arxiv discovered an NLP paper purporting to have developed a framework to automate the summarization and extraction of data from scientific papers; in this blog, he dissects the challenge.
WEF suggests a few reasons why chief AI ethics officers (or, somehow even more of a tongue twister, CAIEO) are a necessity for some organizations. The role's primary goal is to "make AI ethics principles part of operations within a company, organization or institution. A CAIEO advises and builds accountability frameworks for CEOs and boards on the unintended risks posed by AI to the organization." Additionally, the CAIEO helps companies comply with existing AI regulations.
"At a very high level, companies need an AI ethics framework to ensure that AI-enabled solutions are developed in ways that mitigate the chances of harm to relevant stakeholders. More specifically, a CAIEO should lead the definition of broad AI ethics goals and then help the company understand how to meet these. They need to ensure that the AI technology being developed has suitable properties (fairness, robustness, explainability) and that developers have the right tools and training to easily embed these properties in what they produce."
News items:
China released the country’s first set of guidelines on AI ethics, emphasizing user rights and data control.