Registration open for symposium on AI, machine learning in science and society Penn State NewsUNIVERSITY PARK, Pa. – Registration is now open for the Institute for CyberScience (ICS) Symposium 2019, a one-day conference that will explore the…
Why Big Data And Machine Learning Are Important In Our Society ForbesThe singularity is near, or maybe we’re already in it. Whatever the case is, machine learning and big data will have a tremendous influence on our society.
Centre looks to set up 20 cyber physical centres Hindustan TimesThe future of science will be in intelligent machines and the connection between the cyber and the physical systems, and India is ready for the challenge, said …
5 ways AI will influence our lives in 2019 AndroidPITAI may have been the main buzzword of 2018, but it’s this year that will really see the implementation of the technology into many aspects of our daily lives.
Microsoft, Google Use Artificial Intelligence to Fight Hackers FortuneLast year, Microsoft Corp.’s Azure security team detected suspicious activity in the cloud computing usage of a large retailer: One of the company’s …
Machine-Learning Wizards Vie for Zillow’s $1 Million Prize IEEE SpectrumEarly this year, the real-estate giant will reward the team that best predicts home prices.
AI Will Converge With Physician-Directed Care OncLiveImprovements and greater familiarity with artificial intelligence will lead to systems of checks and balances that will create trust and fulfill the promise of …
Give the Robots Good Eye Contact and a Firm Handshake BloombergMachine learning is helping auto lenders make better decisions, which is likely more accurate than using humans who are unpredictable and prone to bias.
Supply Chain Trends To Watch In 2019 ForbesKey trends to watch for 2019 will be watching how trade and tariff issues fall out, particularly the negotiations with China, the Digital Supply Chain, Machine …
Could Machine Learning Be the Key to Better Plant Conservation? Pacific StandardA multi-institutional research team used the power of open-access databases to predict the conservation status of more than 150000 plants.
