Here’s one way to deal with the A.I. talent shortage

April 26, 2022, 8:56 PM UTC

Artificial intelligence’s potential to revolutionize life sciences is so big that biotechnology companies are on a hiring spree for A.I. talent.

The only problem is that not many technologists are skilled in both deep learning and biotechnology-related tasks like drug discovery, making it a huge challenge for companies to find qualified candidates.

Sean McClain, the founder and CEO of the A.I.-powered drug discovery company Absci, estimates that there are about 150 A.I. researchers worldwide who have the exact skill set in A.I. and biotechnology that his company requires. It’s possible for A.I. researchers to learn biotechnology skills on the job, but those with existing expertise are more coveted, he explains.

Last week, Absci opened an A.I. research center in New York City to help attract talent. Former Meta A.I. research engineer Joshua Meier, who helped Facebook conduct research into A.I. and life sciences, will lead and recruit talent for the lab.

McClain acknowledges that Absci will have challenges hiring in New York. Many of the potential candidates in the area already work in the research labs of Facebook parent Meta and Google’s DeepMind unit, where they study the intersection of A.I. and life sciences, he says.

Like many companies, Absci cannot compete with Google and Meta when it comes to compensation. Conventional A.I. researchers at these tech giants can earn up to $500,000 annually, tech recruiters have previously told Fortune, while top-tier researchers with life sciences experience can earn up to $1.4 million annually from these tech giants, McClain says.

He hopes to lure A.I. talent with the pitch that Absci, which went public last summer, stands to benefit in a big way if its technology leads to breakthroughs in drug discovery.

“So the upside is a huge motivator,” McClain says.

Like other companies that must compete with the tech giants for A.I. researchers, McClain must sell potential recruits on the idea that they will be working on cutting-edge research rather than perfecting online ads. He also hopes that A.I. researchers will be attracted to and find inspiration in the idea of being part of the A.I. lab’s “founding team.”

Companies have historically debuted research labs to lure technologists who may find the idea of working for a business boring and soul-sucking. 

Absci chief strategy officer Nikhil Goel notes that technologists once considered Microsoft to be a “sleepy company.” But Microsoft was able to change its image starting in 1991 by creating Microsoft Research Lab, which helped it “attract the best PhD students from all the top universities,” he says.

Technologists and A.I. researchers may be worried that working at a big company can become very politicized, Goel notes. For this reason, many techies find it more comforting to work at a small unit that is exclusively focused on research.

Maybe it’s time for more companies to consider creating their own A.I. research labs.

Jonathan Vanian 


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A.I. as a spy tool. Intelligence agencies are increasingly using A.I. to aid in espionage and related tasks, Wired reported. The report detailed how the Ukrainian army used the A.I. services of the company Primer to listen in and transcribe the conversations of Russian soldiers who were communicating via unencrypted channels.

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Venezuela is playing an important role in A.I. Venezuela is home to a rising data labeling industry in which local workers annotate the data needed to train A.I. systems, the MIT Technology Review reported. But data labelers are hoping that their employers take better care of them and pay them higher wages. From the article: “Over the last five years, crisis-ridden Venezuela has become a primary source of this labor. The country plunged into the worst peacetime economic catastrophe facing a country in nearly 50 years right as demand for data labeling was exploding. Droves of well-educated people who were connected to the internet began joining crowdworking platforms as a means of survival.”


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A.I. and drug discovery. MIT researchers have published a paper as part of The International Conference on Learning Representations that details a technique involving the use of deep learning to improve the process of drug discovery. The technique addresses a common problem that researchers face when using A.I. to develop novel molecular structures: life sciences experts can often face challenges synthesizing A.I.-created molecular structures  The paper discusses a way for A.I. to create molecular structures that experts have an easier time developing in the lab.

“This process reformulates how we ask these models to generate new molecular structures. Many of these models think about building new molecular structures atom by atom or bond by bond. Instead, we are building new molecules building block by building block and reaction by reaction,” MIT professor and senior author of the paper Connor Coley, said in a statement.


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From the article: The challenge here is that photos are captured from above and overlook an incredibly dense forest of green. Depending on when the images are taken, shades of green change throughout the day and with the island’s constant climate shifts, from sun to overcast to rain. In certain lights, many of the greens look like ginger and vice versa.

"It is really challenging. But that's where we use local science to see what's in the image and what can we drill down into to get the green nuances of that image that translate to a program or an algorithm or A.I.," Swami explains.


Story updated on April 27 to correct Nikhil Goel's title to Absci chief strategy officer. 

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