Test your science knowledge
High-performance computing drives innovation across many industries, including energy, manufacturing, and life sciences. With its help, Cold Spring Harbor Laboratory (CSHL) neuroscientists and biologists have made several pioneering discoveries about the brain and artificial intelligence. This research often comes in one of two flavors. One deals with building machines or algorithms to study the brain and body. The other uses biology and neuroscience as an inspiration to build better AI. Take this short quiz to plug into CSHL’s ongoing research in AI and computational biology!
Our brains tally sights, smells, and other senses so we can respond to them quickly in the future. CSHL scientists have created a computer program that mimics this process in fruit flies. They suspect that fly brains work similarly to which of the following technology platforms in this regard?
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Online streaming platforms, like YouTube and Netflix, track what you’ve watched to make personalized recommendations. CSHL Professor Saket Navlakha and collaborators took inspiration from a classic computer science method called a count sketch to figure out how fly brains keep a similar tally.
AI has come very far, from self-driving cars to defeating chess grandmasters. But it still has a ways to go to match human intelligence. Which of the following activities do AI programs still have trouble learning?
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Artificial intelligence-based machines can outperform humans in mathematics and pattern recognition but still have trouble replicating basic human capabilities, such as walking and interacting with the world. Through a program called NeuroAI led by CSHL Professor Anthony Zador, scientists are working on creating better AI by taking lessons from how the brain works.
Algorithms come with different shapes, sizes, and functions. Recently CSHL scientists built an algorithm to help users pick the one that best suits their needs. It was named after a cute critter seen around the Laboratory. What is the name of their AI?
AI’s recent popularity surge has led to an overflow of innovation. CSHL Assistant Professor Peter Koo’s newest invention, GOPHER, allows scientists to determine which AI algorithms work best for analyzing the genome. It systematically compares AI algorithms’ reliability, accuracy, and performance.
In the future, AI “diagnosticians” may assist doctors during patient visits. Thanks to AI, which of the following may become a new source for medical diagnoses?
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Some studies have suggested animals, including dogs and rats, can sniff out diseases such as cancer and tuberculosis. CSHL Professor Alexei Koulakov is developing an electronic smelling machine called “Deep Nose” that can diagnose diseases similarly through scent.
Learning to walk isn’t easy, at least not for AI. Scientists are still trying to create artificial nervous systems that can learn this basic human behavior. Which type of AI was used to emulate human “walking” as seen in this video clip?
Some behaviors, like walking, are thought to be encoded in animals’ DNA so that newborns can quickly learn them for survival. CSHL neuroscientists are trying to get algorithms to replicate these fundamental behaviors using artificial neural networks. But the task is challenging. CSHL NeuroAI Scholar Nikhil Bhattasali recently had some success in building an algorithm that can learn how to swim like a worm.
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