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Exploring ‘chemical space’ with Professor Anatole von Lilienfeld

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Professor Anatole von Lilienfeld (Chemistry, MSE) navigates space — but rather than exploring the depths of the universe, his work is here on Earth in “chemical space.”

And instead of hunting for unknown stars, galaxies and other celestial objects, his focus is on the untapped potential of undiscovered chemical combinations. To do this work, he is not equipped with a powerful telescope — his tool of choice is artificial intelligence (AI).

Von Lilienfeld is the inaugural Clark Chair in Advanced Materials at the Vector Institute and the University of Toronto, and a pivotal member of U of T’s Acceleration Consortium (AC). Appointed jointly to the Department of Chemistry in the Faculty of Arts & Science and the Department of Materials Science & Engineering at U of T Engineering, he is a leading expert on the use of computers to understand the vastness of chemical space.

Von Lilienfeld, who was recently named a Canada CIFAR AI Chair, was a speaker at the AC’s first annual Accelerate conference last month at U of T.

This four-day program centred around the power of self-driving labs (SDLs), an emerging technology that combines AI, automation, and advanced computing to accelerate materials and molecular discovery. The Accelerate conference brought together over 200 people and featured talks and panels with more than 60 experts from academia, industry, and government who are shaping the emerging field of accelerated science.

Erin Warner, communications specialist at the Acceleration Consortium, recently spoke with von Lilienfeld about the conference and the digitization of chemistry.

How big is ‘chemical’ space?

We are surrounded by materials and molecules. Consider the chemical compounds that make up our clothing, the pavement we walk on, and the batteries in our electric cars. Now think about the new possible combinations that are out there waiting to be discovered, such as catalysts for effective atmospheric CO2 capture and utilization, low-carbon cement, lightweight biodegradable composites, membranes for water filtration, and potent molecules for treatment of cancer and bacterial-resistant disease.

In a practical sense, chemical space is infinite and searching it is no small feat. A lower estimate says it contains 1060 compounds — more than the number of atoms in our solar system.

Why do we need to accelerate the search for new materials?

Many of the most widely used materials no longer serve us. Most of the world’s plastic waste generated to date has not yet been recycled. But the materials that will power the future will hopefully be sustainable, circular and inexpensive.

Conventional chemistry is slow, a series of often tedious trial and error that limits our ability to explore beyond a small subset of possibilities. However, AI can accelerate the process by predicting which combinations might result in a material with the set of desired characteristics we are looking for (e.g., conductive, biodegradable, etc.).

This is but one step in self-driving laboratories, an emerging technology that combines AI, automation, and advanced computing to reduce the time and cost of discovering and developing materials by up to 90%.

How can human chemists and AI work together effectively?

AI is a tool that humans can use to accelerate and improve their own research. It can be thought of as the fourth pillar of science. The pillars, which build on each other, include experimentation, theory, computer simulation and AI.

Experimentation is the foundation. We experiment with the aim of improving the physical world for humans. Then comes theory to give your experiments shape and direction. But theory has its limitations. Without computer simulation, the amount of computation needed to support scientific research would take far longer than a lifetime. But even computers have constraints.

With difficult equations come the need for high-performance computing, which can be quite costly. This is where AI comes in. AI is a less costly alternative. It can help scientists predict both an experimental and computational outcome. And the more theory we build into the AI model, the better the prediction. AI can also be used to power a robotic lab, allowing the lab the ability to run 24/7. Human chemists will not be replaced; instead, they can hand off tedious hours of trial and error to focus more on designing the objectives and other higher-level analysis.

Professor Anatole von Lilienfeld at the Accelerate Conference at the University of Toronto. (Photo: Clifton Li, Acceleration Consortium)

Are there any limitations to AI, like the ones you described in the other pillars of science?

Yes, it is important to note that AI is not a silver bullet, and that there is a cost associated with it that can be measured in data acquisition. You cannot use AI without data. And data acquisition requires experimenting and recording the outcome in a way that can be processed by computers. Like a human, the AI then learns by reviewing the data and making an extrapolation or prediction.

Data acquisition is costly, both financially and in terms of its carbon footprint. To address this, the goal is to improve the AI. If you can encode our understanding of physics into the AI, it becomes more efficient and requires less data to learn but provides the same predictive qualities. If less data is needed for training, then the AI model becomes smaller.

Rather than just using AI as a tool, the chemist can also interrogate it to see how well its data captures theory, perhaps leading to the discovery of a new relative law for chemistry. While this interactive relationship is not as common, it may be on the horizon and could improve our theoretical understanding of the world.

How can we make AI for discovery more accessible?

The first way is open-source research. In the emerging field of accelerated science, there are many proponents of open-source access. Not only are journals providing access to research papers, but also in many cases to the data, which is a major component for making the field more accessible. There are also repositories for models and code like GitHub. Providing access could lead to scientific advancements that ultimately benefit all of humanity.

A second way to expand AI for discovery is to include more students. We need to teach basic computer science and coding skills as part of a chemistry or materials science education. Schools around the world are beginning to update their curricula to this effect, but we still need to see more incorporate this essential training. The future of the sciences is digital.

How do initiatives like Acceleration Consortium, and a conference like Accelerate, help advance the field?

We are at the dawn of truly digitizing the chemical sciences. Coordinated, joint efforts, such as the Acceleration Consortium, will play a crucial role in synchronizing efforts not only at the technical but also at the societal level, thereby enabling the worldwide implementation of an ‘updated’ version of chemical engineering with unprecedented advantages for humanity at large.

The consortium also serves to connect academia and industry, two worlds that could benefit from a closer relationship. Visionaries in the commercial sector can dream up opportunities, and the consortium will be there to help make the science work. The groundbreaking nature of AI is that it can be applied to any sector. AI is on a trajectory to have an even greater impact than the advent of computers.

Accelerate, the consortium’s first annual conference, was a great rallying event for the community and was a reminder that remarkable things can come from a gathering of bright minds. While Zoom has done a lot for us during the pandemic, it cannot easily replicate the excitement and enthusiasm often cultivated at an in-person conference and which are needed to direct research and encourage a group to pursue a complex goal.

What area of ‘chemical space’ fascinates you the most?

Catalysts, which enable a certain chemical reaction to occur but remain unchanged in the process. A century ago, Haber and Bosch developed a catalytic process that would allow the transformation of nitrogen — the dominant substance in the air we breathe — into ammonia. Ammonia is a crucial starting material for chemical industries, but also for fertilizers. It made the mass production of fertilizers possible and saved millions of people from starvation. Major fractions of humanity would not exist right now if it were not for this catalyst.

From a physics point of view, what defines and controls catalyst activity and components are fascinating questions. They might also be critical for helping us address some of our most pressing challenges. If we were to find a catalyst that could use sunlight to turn nitrogen rapidly and efficiently into ammonia, we might be able to solve our energy problem by using ammonia for fuel. You can think of the reactions that catalysts enable as ways of traveling through chemical space and to connect different states of matter.

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Slack researcher discusses the fear, loathing and excitement surrounding AI in the workplace

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SAN FRANCISCO (AP) — Artificial intelligence‘s recent rise to the forefront of business has left most office workers wondering how often they should use the technology and whether a computer will eventually replace them.

Those were among the highlights of a recent study conducted by the workplace communications platform Slack. After conducting in-depth interviews with 5,000 desktop workers, Slack concluded there are five types of AI personalities in the workplace: “The Maximalist” who regularly uses AI on their jobs; “The Underground” who covertly uses AI; “The Rebel,” who abhors AI; “The Superfan” who is excited about AI but still hasn’t used it; and “The Observer” who is taking a wait-and-see approach.

Only 50% of the respondents fell under the Maximalist or Underground categories, posing a challenge for businesses that want their workers to embrace AI technology. The Associated Press recently discussed the excitement and tension surrounding AI at work with Christina Janzer, Slack’s senior vice president of research and analytics.

Q: What do you make about the wide range of perceptions about AI at work?

A: It shows people are experiencing AI in very different ways, so they have very different emotions about it. Understanding those emotions will help understand what is going to drive usage of AI. If people are feeling guilty or nervous about it, they are not going to use it. So we have to understand where people are, then point them toward learning to value this new technology.

Q: The Maximalist and The Underground both seem to be early adopters of AI at work, but what is different about their attitudes?

A: Maximalists are all in on AI. They are getting value out of it, they are excited about it, and they are actively sharing that they are using it, which is a really big driver for usage among others.

The Underground is the one that is really interesting to me because they are using it, but they are hiding it. There are different reasons for that. They are worried they are going to be seen as incompetent. They are worried that AI is going to be seen as cheating. And so with them, we have an opportunity to provide clear guidelines to help them know that AI usage is celebrated and encouraged. But right now they don’t have guidelines from their companies and they don’t feel particularly encouraged to use it.

Overall, there is more excitement about AI than not, so I think that’s great We just need to figure out how to harness that.

Q: What about the 19% of workers who fell under the Rebel description in Slack’s study?

A: Rebels tend to be women, which is really interesting. Three out of five rebels are women, which I obviously don’t like to see. Also, rebels tend to be older. At a high level, men are adopting the technology at higher rates than women.

Q: Why do you think more women than men are resisting AI?

A: Women are more likely to see AI as a threat, more likely to worry that AI is going to take over their jobs. To me, that points to women not feeling as trusted in the workplace as men do. If you feel trusted by your manager, you are more likely to experiment with AI. Women are reluctant to adopt a technology that might be seen as a replacement for them whereas men may have more confidence that isn’t going to happen because they feel more trusted.

Q: What are some of the things employers should be doing if they want their workers to embrace AI on the job?

A: We are seeing three out of five desk workers don’t even have clear guidelines with AI, because their companies just aren’t telling them anything, so that’s a huge opportunity.

Another opportunity to encourage AI usage in the open. If we can create a culture where it’s celebrated, where people can see the way people are using it, then they can know that it’s accepted and celebrated. Then they can be inspired.

The third thing is we have to create a culture of experimentation where people feel comfortable trying it out, testing it, getting comfortable with it because a lot of people just don’t know where to start. The reality is you can start small, you don’t have to completely change your job. Having AI write an email or summarize content is a great place to start so you can start to understand what this technology can do.

Q: Do you think the fears about people losing their jobs because of AI are warranted?

A: People with AI are going to replace people without AI.

The Canadian Press. All rights reserved.

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Biden administration to provide $325 million for new Michigan semiconductor factory

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WASHINGTON (AP) — The Biden administration said Tuesday that it would provide up to $325 million to Hemlock Semiconductor for a new factory, a move that could help give Democrats a political edge in the swing state of Michigan ahead of election day.

The funding would support 180 manufacturing jobs in Saginaw County, where Republicans and Democrats were neck-in-neck for the past two presidential elections. There would also be construction jobs tied to the factory that would produce hyper-pure polysilicon, a building block for electronics and solar panels, among other technologies.

Commerce Secretary Gina Raimondo said on a call with reporters that the funding came from the CHIPS and Science Act, which President Joe Biden signed into law in 2022. It’s part of a broader industrial strategy that the campaign of Vice President Kamala Harris, the Democratic nominee, supports, while Republican nominee Donald Trump, the former president, sees tariff hikes and income tax cuts as better to support manufacturing.

“What we’ve been able to do with the CHIPS Act is not just build a few new factories, but fundamentally revitalize the semiconductor ecosystem in our country with American workers,” Raimondo said. “All of this is because of the vision of the Biden-Harris administration.”

A senior administration official said the timing of the announcement reflected the negotiating process for reaching terms on the grant, rather than any political considerations. The official insisted on anonymity to discuss the process.

After site work, Hemlock Semiconductor plans to begin construction in 2026 and then start production in 2028, the official said.

Running in 2016, Trump narrowly won Saginaw County and Michigan as a whole. But in 2020 against Biden, both Saginaw County and Michigan flipped to the Democrats.

The Canadian Press. All rights reserved.

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The Internet is Littered in ‘Educated Guesses’ Without the ‘Education’

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Although no one likes a know-it-all, they dominate the Internet.

The Internet began as a vast repository of information. It quickly became a breeding ground for self-proclaimed experts seeking what most people desire: recognition and money.

Today, anyone with an Internet connection and some typing skills can position themselves, regardless of their education or experience, as a subject matter expert (SME). From relationship advice, career coaching, and health and nutrition tips to citizen journalists practicing pseudo-journalism, the Internet is awash with individuals—Internet talking heads—sharing their “insights,” which are, in large part, essentially educated guesses without the education or experience.

The Internet has become a 24/7/365 sitcom where armchair experts think they’re the star.

Not long ago, years, sometimes decades, of dedicated work and acquiring education in one’s field was once required to be recognized as an expert. The knowledge and opinions of doctors, scientists, historians, et al. were respected due to their education and experience. Today, a social media account and a knack for hyperbole are all it takes to present oneself as an “expert” to achieve Internet fame that can be monetized.

On the Internet, nearly every piece of content is self-serving in some way.

The line between actual expertise and self-professed knowledge has become blurry as an out-of-focus selfie. Inadvertently, social media platforms have created an informal degree program where likes and shares are equivalent to degrees. After reading selective articles, they’ve found via and watching some TikTok videos, a person can post a video claiming they’re an herbal medicine expert. Their new “knowledge,” which their followers will absorb, claims that Panda dung tea—one of the most expensive teas in the world and isn’t what its name implies—cures everything from hypertension to existential crisis. Meanwhile, registered dietitians are shaking their heads, wondering how to compete against all the misinformation their clients are exposed to.

More disturbing are individuals obsessed with evangelizing their beliefs or conspiracy theories. These people write in-depth blog posts, such as Elvis Is Alive and the Moon Landings Were Staged, with links to obscure YouTube videos, websites, social media accounts, and blogs. Regardless of your beliefs, someone or a group on the Internet shares them, thus confirming your beliefs.

Misinformation is the Internet’s currency used to get likes, shares, and engagement; thus, it often spreads like a cosmic joke. Consider the prevalence of clickbait headlines:

  • You Won’t Believe What Taylor Swift Says About Climate Change!
  • This Bedtime Drink Melts Belly Fat While You Sleep!
  • In One Week, I Turned $10 Into $1 Million!

Titles that make outrageous claims are how the content creator gets reads and views, which generates revenue via affiliate marketing, product placement, and pay-per-click (PPC) ads. Clickbait headlines are how you end up watching a TikTok video by a purported nutrition expert adamantly asserting you can lose belly fat while you sleep by drinking, for 14 consecutive days, a concoction of raw eggs, cinnamon, and apple cider vinegar 15 minutes before going to bed.

Our constant search for answers that’ll explain our convoluted world and our desire for shortcuts to success is how Internet talking heads achieve influencer status. Because we tend to seek low-hanging fruits, we listen to those with little experience or knowledge of the topics they discuss yet are astute enough to know what most people want to hear.

There’s a trend, more disturbing than spreading misinformation, that needs to be called out: individuals who’ve never achieved significant wealth or traded stocks giving how-to-make-easy-money advice, the appeal of which is undeniable. Several people I know have lost substantial money by following the “advice” of Internet talking heads.

Anyone on social media claiming to have a foolproof money-making strategy is lying. They wouldn’t be peddling their money-making strategy if they could make easy money.

Successful people tend to be secretive.

Social media companies design their respective algorithms to serve their advertisers—their source of revenue—interest; hence, content from Internet talking heads appears most prominent in your feeds. When a video of a self-professed expert goes viral, likely because it pressed an emotional button, the more people see it, the more engagement it receives, such as likes, shares and comments, creating a cycle akin to a tornado.

Imagine scrolling through your TikTok feed and stumbling upon a “scientist” who claims they can predict the weather using only aluminum foil, copper wire, sea salt and baking soda. You chuckle, but you notice his video got over 7,000 likes, has been shared over 600 times and received over 400 comments. You think to yourself, “Maybe this guy is onto something.” What started as a quest to achieve Internet fame evolved into an Internet-wide belief that weather forecasting can be as easy as DIY crafts.

Since anyone can call themselves “an expert,” you must cultivate critical thinking skills to distinguish genuine expertise from self-professed experts’ self-promoting nonsense. While the absurdity of the Internet can be entertaining, misinformation has serious consequences. The next time you read a headline that sounds too good to be true, it’s probably an Internet talking head making an educated guess; without the education seeking Internet fame, they can monetize.

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Nick Kossovan, a self-described connoisseur of human psychology, writes about what’s

on his mind from Toronto. You can follow Nick on Twitter and Instagram @NKossovan.

 

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