AI Tools for Skill Improvement

 Chess and other game playing as a means to have access to tools to improve skills.  How does this translate to more general skills?

AI Helps Humans Level Up Chess players and programmers now have access to tools that can improve skills and unleash creativity   By Harry Goldstein  In IEEEiOrg

BACK IN THE mid-1970s, IEEESpectrum senior editor Phil Ross played one of the first chess programs capable of vanquishing humans. He capitulated quickly—too quickly, it turned out: Although the program that beat him was good at openings and the middle game, it was terrible at the end game. Fast forward 50 years and the highest-ranked chess players in the world are AIs, with humans trailing far behind.

As Ross points out in his online piece “ AI’s Grandmaster Status Overshadows Chess Scandal,” the recent brouhaha involving world champion Magnus Carlsen and up-and-comer Hans Niemann highlights how chess-playing AIs, referred to as “engines” by the cognoscenti, have overtaken humans in terms of raw game-playing accuracy. The scandal also shows how AIs are being used by players at all levels to get better faster, fostering a boom in the sport.

If you were born a few decades ago, your best shot at playing and learning from grandmasters was either to be lucky enough to know one or to somehow qualify for the high-level tournaments in which they participated. Nowadays, chess newbies can log in and play engines that far exceed their own abilities, learning strategies and moves in days or weeks that in the past might have taken months or years. Engines can also help neophytes and grandmasters alike analyze their own games to give them an edge against human opponents. 

In fact, if you burrow down the rabbit holes of chess YouTube or Twitch, you’ll find grandmasters giving move-by-move analyses of games that engines played against each other. These AI tools, along with the humans who use them, are readily accessible: You can play the cybernetic versions of super grandmasters, like the open-source, current top-ranked chess engine Stockfish 14.1, not to mention tens of millions of human opponents on sites like Chess.com, a global community of some 93 million players and a central player in the cheating controversy.

While it is certainly true that bad actors use AI to cheat at chess—potentially posing an existential threat to the game, as Carlsen has suggested—it is equally true that the chess world has openly embraced AI and has been thriving as a result. Similar risk/reward calculations will need to be made in other domains.  .... ' 

Drug Discovery When it Matters

 Also an interesting story about how collaboration can work.

Can AI and Automation Deliver a COVID-19 Antiviral While It Still Matters? Researchers are betting that new tools can cut drug discovery from five years to six month.  By Megan Scudellari

Within moments of meeting each other at a conference last year, Nathan Collins and Yann Gaston-Mathé began devising a plan to work together. Gaston-Mathé runs a startup that applies automated software to the design of new drug candidates. Collins leads a team that uses an automated chemistry platform to synthesize new drug candidates.

“There was an obvious synergy between their technology and ours,” recalls Gaston-Mathé, CEO and cofounder of Paris-based Iktos.  In late 2019, the pair launched a project to create a brand-new antiviral drug that would block a specific protein exploited by influenza viruses. Then the COVID-19 pandemic erupted across the world stage, and Gaston-Mathé and Collins learned that the viral culprit, SARS-CoV-2, relied on a protein that was 97 percent similar to their influenza protein. The partners pivoted.

Their companies are just two of hundreds of biotech firms eager to overhaul the drug-discovery process, often with the aid of artificial intelligence (AI) tools. The first set of antiviral drugs to treat COVID-19 will likely come from sifting through existing drugs. Remdesivir, for example, was originally developed to treat Ebola, and it has been shown to speed the recovery of hospitalized COVID-19 patients. But a drug made for one condition often has side effects and limited potency when applied to another. If researchers can produce an ­antiviral that specifically targets SARS-CoV-2, the drug would likely be safer and more effective than a repurposed drug.

There’s one big problem: Traditional drug discovery is far too slow to react to a pandemic. Designing a drug from scratch typically takes three to five years—and that’s before human clinical trials. “Our goal, with the combination of AI and automation, is to reduce that down to six months or less,” says Collins, who is chief strategy officer at SRI Biosciences, a division of the Silicon Valley research nonprofit SRI International. “We want to get this to be very, very fast.”   ... "