In this episode you will get a look at deep neural networks and how they are being used to identify unattended baggage for new security. How deep learning could be used to discover crypto-currency trader sentiment. You'll also learn what Intel student ambassador Panuwat is doing in AI research.
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I'm David Shaw. And welcome to AI News. In this episode, we take a look at deep neural networks and how they're being used to identify unattended baggage for new security, how deep learning could be used to discover cryptocurrency trader sentiment, and finally, find out what Intel Student Ambassador , Panuwat, is doing in AI research. Don't forget to check out the links provided to learn more.
Security threats are never good news. These days, the need for smart security systems is increasing. Unattended bags left in public areas like railway stations and airports is a top security concern. Read this article from the Intel AI Academy to see how developers are working to use deep neural networks to create a robotic eye for accurate, real-time detection of these bags.
Trader sentiment is a key factor in being able to determine cryptocurrency price movements. For those who are looking at this emerging currency, the article Deep Learning for Cryptocurrency Trading discusses one developer's journey in developing a sentiment analyzer that could yield valuable insights about the market. Using data pulled from news headlines and social media posts, this project could be the stepping stone needed to make a cryptocurrency trading bot. Take a look.
Lastly, watch Intel Student Ambassador, Panuwat, of Florida International University, present his research on functional connectivity of epileptic brains. By using machine learning and AI to analyze data, his research is helping in epileptic diagnosis, classification, and prediction of seizures. Check out the presentation to get inspired.
Thanks for watching. Don't forget to like this video and subscribe to the Intel software channel.