This week, we speak with arguably one of the best-known folks in the domain of neural networks: Jurgen Schmidhuber. He's working on a lot of different applications now in heavy industry, self-driving cars, and other spaces.
The Department of Homeland Security (DHS) routinely handles large amounts of data. Its mandate is to “keep America safe,” and that encompasses many fronts. This includes anything to do with potential threats to the nation, ranging from border security to cybersecurity, so “big data” would be an understatement. Using machine learning and artificial intelligence technology for Homeland Security was inevitable.
The facilitation of research and development (R&D) is perhaps the most common use case for AI applications in the pharmaceutical industry. There are numerous solutions for extracting and organizing research data from clinical trial notes and other medical documents. Additionally, there is software that can purportedly analyze data from images of drug compounds at the molecular level.
In the final installment of the "Pitfalls to AI Adoption" series, we talk about predicting the ROI of AI. There are a lot of misconceptions running rampant around the ability to gauge the return on investment of artificial intelligence. In this article, we talk about what can and can't be done when it comes to investing in artificial intelligence and predicting what the return might be.
According to the National Institute of Mental Health, the United States is currently battling a mental health epidemic. One in every five Americans struggles with mental illness in one form or another. According to the National Institute on Drug Abuse, opioid abuse claims about 115 American lives every day. According to the Center for Workplace Mental Health founded by the American Psychiatric Association, up to 7% of full-time workers in the U.S. suffer from major depressive disorder, the economic cost of which is estimated to be $210.5 billion per year.
The AI In Industry podcast is often conducted over Skype, and this week's guest happens to be one of its early developers. Jaan Tallinn is recognized as one of the technical leads behind Skype as a platform.
The finance industry has been an early adopter of AI. It is likely that the use of algorithms in trading and the fact that most large financial firms already have teams of software developers aided the transition into data science and AI applications in the industry.
Large volumes of data, managed properly, are a boon for many industries, including the military. It would not be possible to mount effective military operations without knowing the when, where, and what in deploying resources. Big data, therefore, helps the military make better decisions, provided it is not “dark data.”
Machine vision has numerous use cases within the healthcare industry, including clinical solutions such as medical imaging and medical diagnostics. There are also possibilities in white collar automation such as medical transcription.