![]() This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other. The cookies is used to store the user consent for the cookies in the category "Necessary". The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". The cookie is used to store the user consent for the cookies in the category "Analytics". These cookies ensure basic functionalities and security features of the website, anonymously. Necessary cookies are absolutely essential for the website to function properly. Written by: Luis Sandoval, Communications Specialist | | 51 Thankfully, Koo’s new tool can help bring scientists out of the darkness and into the light. He thinks it’s a widespread affliction among computational processes involving similar types of data. Koo believes noise disturbance affects more than AI-powered DNA analyzers. One-off nucleotides that are deemed to be very important all of a sudden disappear.” “We end up seeing sites that become much more crisp and clean, and there is less spurious noise in other regions. In other words, we’re feeding AI an input it doesn’t know how to handle properly.īy applying Koo’s computational correction, scientists can interpret AI’s DNA analyses more accurately. But image data in the form of pixels can be long and continuous. DNA data, unlike images, is confined to a combination of four nucleotide letters: A, C, G, T. The digital dark matter is a result of scientists borrowing computational techniques from computer vision AI. And so we show that this problem actually does introduce a lot of noise across a wide variety of prominent AI models.” But DNA is only in a small subspace of that. “The deep neural network is incorporating this random behavior because it learns a function everywhere. Even worse, those blind spots get factored in when interpreting AI predictions of DNA function. Similarly, Koo and his team discovered the data that AI is being trained on lacks critical information, leading to significant blind spots. So, what causes the meddlesome noise? It’s a mysterious and invisible source like digital “dark matter.” Physicists and astronomers believe most of the universe is filled with dark matter, a material that exerts gravitational effects but that no one has yet seen. But scientists won’t see the signals if they’re drowned out by too much noise. Those features might just signal the next breakthrough in health and medicine. That means they can continue chasing down genuine DNA features. Now, with just a couple new lines of code, scientists can get more reliable explanations out of powerful AIs known as deep neural networks. While we can’t trust AI to be perfect, it turns out that sometimes we can’t trust ourselves with AI either.Ĭold Spring Harbor Laboratory (CSHL) Assistant Professor Peter Koo has found that scientists using popular computational tools to interpret AI predictions are picking up too much “noise,” or extra information, when analyzing DNA. Now, it’s AI-generated pizza and beer commercials. ![]() Center for Humanities & History of Modern BiologyĪrtificial intelligence has entered our daily lives.Business Development & Technology Transfer. ![]()
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