I am a machine learning researcher. With a team of scientists, I have developed a tool to make identification of microplastics using their unique chemical fingerprint more reliable. We hope that this work will help us learn about the types of microplastics floating through the air in our study area, Michigan. The term plastic refers to a wide variety of artificially created polymers. Polyethylene, or PET, is used for making bottles; polypropylene, or PP, is used in food containers; and polyvinyl chloride, or PVC, is used in pipes and tubes. Just as fingerprinting uniquely identifies a person, scientists use spectroscopy to determine the chemical identity of microplastics. In spectroscopy, a substance either absorbs or scatters light, depending on how its molecules vibrate. The absorbed or scattered light creates a unique pattern called the spectrum, which is effectively the substance's fingerprint. Just like a forensic analyst can match an unknown fingerprint against a fingerprint database to identify the person, researchers can match the spectrum of an unknown microplastic particle against a database of known spectra....

Machine learning is now widely used to guide decisions in processes where gauging the probability of a specific outcome ' such as whether a customer will repay a loan ' is sufficient. But because the technology, as traditionally applied, relies on correlations to make predictions, the insights it offers managers is flawed, at best, when it comes to anticipating the impact of different choices on business outcomes.1 Consider leaders at a large company who must decide how much to invest in R&D in the coming year. Using traditional ML, they can ask what will happen when they increase their spending. They might find a strong correlation between higher levels of investment and higher revenue when the economy is growing. And they might conclude that, since economic conditions are favorable, they should increase the R&D budget. But should they really' If so, by how much' External factors, such as levels of consumer spending, technology spillover from competitors, and interest rates, also influence revenue growth. Comparing how different levels of investment might affect revenue while considering these other variables is useful for the manager who is trying to determine the R&D budget that will deliver the greatest benefit to the company....

Recalls in the food and beverage industry due to contamination incidents can have catastrophic effects. Not only do companies have to pay fines and damages, but the impacts on the brand's reputation can be long-lasting. That's why Spore.Bio, a Paris-based deeptech startup, is trying to reinvent microbiology testing to avoid the next PR crisis in the food industry. After raising an '8 million pre-seed round ($8.3 million at current exchange rates) a little bit more than a year ago, the company just secured a $23 million Series A round. Singular is leading the round. Point 72 Ventures, 1st Kind Ventures (the family office of the Peugeot family), Station F and Lord David Prior are also participating. Existing investors LocalGlobe, No Label Ventures and Famille C are putting more money in the company as well. The reason why Spore.Bio managed to raise so quickly after its pre-seed round is that there's real customer interest. The startup has already signed a few commercial contracts that can cover up to 200 factories. Spore.Bio had to open a waitlist to make sure it can keep up with demand....

Consider muscle movement. Your body releases a molecule called acetylcholine to trigger your muscle cells to contract. If acetylcholine sticks around for too long, it can paralyze your muscles ' including your heart muscle cells ' and, well, that's that. This is where the enzyme acetylcholinesterase comes in. This enzyme can break down thousands of acetylcholine molecules per second to ensure muscle contraction is stopped, paralysis avoided and life continued. Without this enzyme, it would take a month for a molecule of acetylcholine to break down on its own ' about 10 billion times slower. You can imagine why enzymes are of particular interest to scientists looking to solve modern problems. What if there were a way to break down plastic, capture carbon dioxide or destroy cancer cells as fast as acetylcholinesterase breaks down acetylcholine' If the world needs to take action quickly, enzymes are a compelling candidate for the job ' if only researchers could design them to handle those challenges on demand....