“Microsoft on Monday launched a free, online AI Business School to help business leaders navigate creating an AI strategy.
“Introduction to AI technology for business leaders,”
“Define an AI strategy to create business value,”
“Discover ways to foster an AI-ready culture in your business,”
“Identify guiding principles for responsible AI in your business.”
“This school is a deep dive into how you develop a strategy and identify blockers before they happen in the implementation of AI in your organization,” Mitra Azizirad, corporate vice president for AI marketing at Microsoft, wrote in the post.
The AI Business School is non-technical, and designed to help executives lead their organizations through AI transformations, according to the post.”
“How should young technology professionals train themselves to work better with AI and virtual assistants?
Honestly, I think there’s little likelihood that we’ll need to learn to work with bots. As I said earlier, we already interact with AI in countless ways, without realizing it.
I actually think the big challenge ahead of us lies in teaching our AIs and virtual assistants and bots how to work with each other. Integrating software programs has always been hard, and we’ve solved the problem by forcing the use of inflexible, hard-wired APIs.
The Good, Bad and Ugly about AI that you have heard or predict –
We are witness to the ugly every day. The lack of good training data is a major obstacle to the deployment of AI systems everywhere.”
Artificial Intelligence Market by Technology, and Industry Vertical – Global Opportunity Analysis and Industry Forecast, 2018-2025, the global Artificial Intelligence market size is expected to reach $169,411.8 million in 2025, from $4,065 million in 2016 growing at a CAGR of 55.6% from 2018 to 2025.
ARTIFICIAL INTELLIGENCE PREDICTIONS FOR THE YEAR 2019
Look to IBM, Google, Microsoft, Amazon and providers of Machine Learning APIs to release more inclusive datasets to combat embedded discrimination and bias in AI
Adoption of AI within healthcare and financial services will go up as products that make previously blackbox AI decisions more interpretable start to become mainstream
Algorithms v. algorithms. There will be successful AI-powered hacks of AI systems that go beyond “fake news”
Transfer learning and simulation become mainstream and help businesses overcome cold start problems and the high cost of amassing training data
Increasing demands for privacy will push more AI to happen on the edge and large internet giants will invest in edge AI to gain a competitive advantage
What makes AI different from earlier technologies is its ability to learn.
“A big challenge now is being able to learn more from less,” Dr. John Smith, Manager of AI Tech at IBM Research, told me. “For example, in manufacturing there is often a great need for systems to do visual inspections of defects, some of which may have only one or two instances, but you still want the system to be able to learn from them and spot future instances.”
“We recently published our research on a new technique called few-shot or one-shot learning, which learns to generalize information from outliers”, he continued. “It’s still a new technique, but in our testing so far, the results have been quite encouraging.” Improving a system’s ability to learn is key to improving how it will perform.
One of the most frustrating things about AI systems is their inability to understand context.”