As device sensors proliferate across every company's value chain – from new product development through inspection, tracking, and delivery – tinyML is surfacing to provide actionable insights, transforming business as we know it. There are sound economic reasons for all this interest and activity. McKinsey researchers predict IoT will have a potential economic impact of US $4-11 trillion by 2025, identifying manufacturing as the largest vertical (US $1.2-3.7 trillion). The rise of tinyML to collect data from edge devices at worksites anywhere was inevitable given the explosion of sensors in pretty much every industry across global supply chains. The tinyML community was established in 2019.

Adam Scraba: I think we're on a path where AI is actually going to become kind of like a utility. It's going to be accessible to pretty much everyone. James Kotecki: This is Machine Meets World, Infinia ML's ongoing conversation about artificial intelligence. I am James Kotecki and my guest today is Adam Scraba, Director of Product Marketing at NVIDIA. James Kotecki: So Adam, NVIDIA, which I should say is not Infinia, these are two totally separate companies that we work for here.

Automation has become one of the most critical factors for successful businesses these days. By saving time and reducing costs, it helps increase operational efficiency and productivity and helps companies focus on their core competencies. But how are businesses utilizing automation for better results and sustainable growth? Take a look at how they do it so that you can follow their suit and grow your business. Every business has various tasks on its daily plate that are necessary for making the organization run smoothly.

Grammarly, which predicts what a user is writing and what corrections are required DuoLingo which is using Amazon's text to speech service to generate customized language lessons Liberty Mutual, which is using Amazon conversational API Bundesliga has chosen AWS as its technology platform to deliver more in-depth insight into live broadcasts of Bundesliga soccer games and enable new personalized fan experiences. Bundesliga wants to automate processes, increase operational efficiency, and enhance fans' experience. Bundesliga also wants to process 150 000 hours of video and tag them automatically. It will help Bundesliga to search across its entire history of football footage. NFL wants to improve players' safety and uses AWS to study injuries.

This guidance is part of a wider collection about using artificial intelligence (AI) in the public sector. The SQ team is responsible for reviewing the sale of financial products for regulatory compliance. Currently the team is required to check a sample of 10% to 15% of completed sales. A team of 120 reviewers had to look at more than 10 different data sources and 180 data points to find and extract the information they needed to complete the audit. Each review took around 4 hours.

Cloud for Good, a Salesforce partner that creates transformational value with technology." Tal Frankfurt is the Founder and CEO of Cloud for Good, a Salesforce partner that creates transformational value with technology. Artificial Intelligence is an area of computer science that trains machines to preform tasks that would normally be done by humans. There has been a lot of buzz -- both positive and negative -- around AI over the last few years. In 2016, Microsoft CEO Staya Nadella declared that "bots are the new apps."

Tuesday of this past week was quite fortuitous: In my Data Science Cohort at Lambda School, we are working a predictive maintenance competition on Kaggle regarding Water pumps in Tanzania. And, I went to a Data Science networking event at a defense contractor who spoke of the importance of Predictive Maintenance Solutions -- in their case, they were predicting the failure rates of parts of the F35 Joint Strike Fighter. According to IoT world, The Predictive Maintenance report forecasts a compound annual growth rate for Predictive Maintenance of 39% between 2016–2022, with annual technology spending reaching US$10.96 This has a large positive impact on Data Science and Machine Learning if the industry can keep up with the needs of predictive maintenance problems. What is predictive maintenance and why is it so important to different domains?

With artificial intelligence integrated into building systems and IoT devices, buildings become more than their brick-and-mortar shells. They begin to operate in new ways, creating personalized experiences for their occupants, and providing energy and cost savings for their owners. In the report'Building intelligence into buildings', the Institute of Business Value (IBV) explores the potential of buildings that think for themselves. Below are some of the key learnings and action points. What if buildings owners could see exactly how their building is being used at any given time?

There has been no shortage of promises recently about how deeply the application of machine-driven artificial intelligence is expected to change our society in the next decade. Microsoft announced its ambition to conquer cancer using natural language processing to analyze research papers in close to real time. Google--now a self-proclaimed AI-first company--will make computers sound just like humans by applying machine learning to a vast corpus of human voice samples. Facebook is using AI to analyze satellite footage to locate all human life and fulfill its promise to bring the internet to the world's entire population. And the list goes on.