Since the discovery of DNA in the 1950s, biologists have sought to tie lengths of genetic code to a range of cellular parts and processes—including, for example, the mRNA transcription of specific antibodies that powers the now-famous mRNA vaccines. Despite the progress in sequencing and understanding the genome since the discovery of DNA, one big missing link remained. Biologists lacked a way to accurately and efficiently predict the 3-D shape of an unknown protein using just its DNA or RNA source code. In biology, structure determines function. What a protein does in a cell depends on its shape. Cylindrical with a hollow middle makes for a good membrane receptor, while U-shaped enzymes catalyze chemical reactions in their fjord-like cavities. Being able to predict or even design proteins would be a leap forward in our understanding of human disease and unlock new treatments for a range of diseases.
But for more than 70 years, scientists have been stuck with slow methods that strained computers and relied largely on their own guesswork to tease out a protein’s structure. Despite knowing which stretches of DNA code for each of the amino acids that form the building blocks of every protein, biologists lacked a repeatable, generalizable formula to solve this so-called “protein-folding problem.” They needed a systematic understanding of how any string of amino acids, once linked, would fold into a 3-dimensional shape to unlock the vast universe of proteins.
In 2020, Google’s AI team DeepMind announced that its algorithm, AlphaFold, had solved the protein-folding problem. At first, this stunning breakthrough was met with excitement from most, with scientists always ready to test a new tool, and amusement by some. After all, wasn’t this the same company whose algorithm AlphaGo had defeated the world champion in the Chinese strategy game Go, just a few years before? Mastering a game more complex than chess, difficult as that is, felt trivial compared to the protein-folding problem. But AlphaFold proved its scientific mettle by sweeping an annual competition in which teams of biologists guess the structure of proteins based only on their genetic code. The algorithm far outpaced its human rivals, posting scores that predicted the final shape within an angstrom, the width of a single atom. Soon after, AlphaFold passed its first real-world test by correctly predicting the shape of the SARS-CoV-2 ‘spike’ protein, the virus’ conspicuous membrane receptor that is targeted by vaccines. Read More
Daily Archives: June 9, 2022
Why it’s time for “data-centric artificial intelligence”
Machine learning pioneer Andrew Ng argues that focusing on the quality of data fueling AI systems will help unlock its full power.
The last 10 years have brought tremendous growth in artificial intelligence. Consumer internet companies have gathered vast amounts of data, which has been used to train powerful machine learning programs. Machine learning algorithms are widely available for many commercial applications, and some are open source.
Now it’s time to focus on the data that fuels these systems, according to AI pioneer Andrew Ng, SM ’98, the founder of the Google Brain research lab, co-founder of Coursera, and former chief scientist at Baidu.
Ng advocates for “data-centric AI,” which he describes as “the discipline of systematically engineering the data needed to build a successful AI system.” Read More
Smartphones Blur the Line Between Civilian and Combatant
In Ukraine, civilians are valiantly assisting the army via apps—and challenging a tenet of international law in the process
AS RUSSIA CONTINUES its unprovoked armed aggression, reports from Ukraine note that the smartphones in civilians’ pockets may be “weapons powerful in their own way as rockets and artillery.” Indeed, technologists in the country have quickly created remarkable apps to keep citizens safe and assist the war effort—everything from an air-raid alert app to the rapid repurposing of the government’s Diia app. The latter was once used by more than 18 million Ukrainians for things like digital IDs, but it now allows users to report the movements of invading soldiers through the “e-Enemy” feature. “Anyone can help our army locate Russian troops. Use our chat bot to inform the Armed Forces,” the Ministry of Digital Transformation said of the new capability when it rolled out.
Naturally, the Ukrainian people want to defend their country and aid their army in whatever ways they can. But certain uses of digital technology pose fundamental challenges to the traditional distinction between civilians and combatants in modern times. Read More
Soul Machines Announces New Entertainment Division
Partners with Nicklaus Companies to launch inaugural Digital Twin of Jack Nicklaus to engage with fans and brands to bring interactive sporting and entertainment experiences online
Soul Machines, the groundbreaking company pioneering the creation of autonomously animated Digital People in the metaverse and the digital worlds of today, announced today the launch of a new Entertainment division with the goal of creating unique and highly personalized experiences redefining fan engagement and entertainment enterprise. On the heels of a recent US$70 million Series B1 round (led by new investor SoftBank Vision Fund 2), this new business division will launch its inaugural Digital Person – an avatar of legendary American professional golfer Jack Nicklaus through a partnership with the Nicklaus Companies. Read More
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