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AI Creates Killer Drug

Researchers in Canada and the United States have used deep learning to derive an antibiotic that can attack a resistant microbe, acinetobacter baumannii, which can infect wounds and cause pneumonia. According to the BBC, a paper in Nature Chemical Biology describes how the researchers used training data that measured known drugs’ action on the tough bacteria. The learning algorithm then projected the effect of 6,680 compounds with no data on their effectiveness against the germ.

In an hour and a half, the program reduced the list to 240 promising candidates. Testing in the lab found that nine of these were effective and that one, now called abaucin, was extremely potent. While doing lab tests on 240 compounds sounds like a lot of work, it is better than testing nearly 6,700.

Interestingly, the new antibiotic seems only to be effective against the target microbe, which is a plus. It isn’t available for people yet and may not be for some time — drug testing being what it is. However, this is still a great example of how machine learning can augment human brainpower, letting scientists and others focus on what’s really important.

Neuralink Begins Human Trials!

Last video: The 2023 Tesla AI Update Is Here!

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Ultra-Processed Foods: AI’s New Contribution to Nutrition Science

Summary: Researchers developed a machine learning algorithm, FoodProX, capable of predicting the degree of processing in food products.

The tool scores foods on a scale from zero (minimally or unprocessed) to 100 (highly ultra-processed). FoodProX bridges gaps in existing nutrient databases, providing higher resolution analysis of processed foods.

This development is a significant advancement for researchers examining the health impacts of processed foods.

AI-Descartes: A Scientific Renaissance in the World of Artificial Intelligence

The system demonstrated its chops on Kepler’s third law of planetary motion, Einstein’s relativistic time-dilation law, and Langmuir’s equation of gas adsorption.

AI-Descartes, a new AI scientist, has successfully reproduced Nobel Prize-winning work using logical reasoning and symbolic regression to find accurate equations. The system is effective with real-world data and small datasets, with future goals including automating the construction of background theories.

In 1918, the American chemist Irving Langmuir published a paper examining the behavior of gas molecules sticking to a solid surface. Guided by the results of careful experiments, as well as his theory that solids offer discrete sites for the gas molecules to fill, he worked out a series of equations that describe how much gas will stick, given the pressure.

Welcome to the augmented future. Watch it bring you to your knees

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Back on New Year’s Day, I wrote a piece for VentureBeat predicting 2023 as the year of mixed reality. On Monday of next week, the world will see why I still believe this is true. That’s the day Apple is expected to unveil its long-awaited mixed reality headset, a product rumored to be called the “Reality Pro” and certain to set the standard for immersive experiences.

This is a big deal.