07 Jun 2019 || 12:00 pm - 1:00 pm || Eastern Time (USA)
The future of technology lies in the hands of the most knowledgeable and skilled among us.
When it comes to leading edge technologies, that used to mean you needed to be trained at a top university or think tank, and spend years in apprenticeships. Now, Google, Apple, Microsoft, Amazon, IBM and every other leading technology company looks at it quite differently.
At Google, Dr. Fei-Fei Li, the chief scientist of artificial intelligence and machine learning at Google Cloud, recently said:
“Speaking of democratization and reaching many people. If you can imagine combining the reach of this platform with the power of AI. Making it available to everyone. We can witness a greater improvement in quality of life than at any other time in history. This is why delivering machine learning and AI through Google Cloud excites me.” He was referring to AI with machine learning APIs.
Similarly, at Microsoft, the philosophy of “democratization” is summarized in their philosophy:
- We’re going to harness artificial intelligence to fundamentally change how we interact with the ambient computing, the agents, in our lives.
- We’re going to infuse every application that we interact with, on any device, at any point in time, with intelligence.
- We’ll make these same intelligent capabilities that are infused in our own apps — the cognitive capabilities — available to every application developer in the world.
- We’re building the world’s most powerful AI supercomputer and making it available to anyone, via the cloud, to enable all to harness its power and tackle AI challenges, large and small.
Each of the players have launched key “toolkits” to empower you to do your job better, and more powerfully. For you to dream a dream, and then make it happen in powerfully useful, scalable and vital tools.
Apple’s Core ML 2, a new and improved version of its machine learning software development kit for iOS;
Google’s ML Kit, an AI framework for the search giant’s Firebase development platform;
Microsoft’s Azure Machine Learning Studio that enables you to easily build, deploy, and share predictive analytics solutions; and,
Facebook’s PyTorch, an open source deep learning framework built to be flexible and modular for research, with the stability and support needed for production deployment.
Historically, that meant you needed training
In this webinar, you will learn about some of the many AI and ML tools available to make your software smarter, and what steps you need to take to implement them.
You do not want to miss out on this, come take advantage of this opportunity, and come ready with your questions and feedback. You will have plenty of time to ask and have answered any questions you have.
This webinar is being facilitated by Mark Kerzner, an expert in the field. Mark Kerzner is an experienced, hands-on software architect, practicing and teaching AI, Machine Learning, Blokchain, Spark, Hadoop, NoSQL, and more. He worked in a variety of verticals (Hightech, Healthcare, O&G, Legal, Fintech). His classes are hands-on and draw heavily on his industry experience. Mark is certified in Google Cloud (GCP), Amazon (AWS), and Hadoop. He is also an author and maintainer for a popular open source project for lawyers and researchers, FreeEed, which deals with search and massive scalability