AI Sector Overviews Articles and Reports
Artificial intelligence “sector overview” reports are designed to help business leaders explore the possibilities and important AI trends across industries. Search our sector overview reports below:
This is a contributed article by Kristóf Zsolt Szalay. Kristóf is Founder and CTO at Turbine.AI, and holds a PhD in molecular biology and bioinformatics. To inquire about contributed articles from outside experts, contact email@example.com.
Our AI Opportunity Landscape research clearly demonstrates how chatbots are relatively over-hyped in the marketplace, and most buyers drastically overestimate their effectiveness as a result. Some of our press releases about the bloviated claims about chatbot deployments have ruffled the feathers of conversational interface vendors.
The hypothesis is simple:
Equipment breakdowns or downtime is extremely expensive (imagine a train broken down on isolated tracks, hundreds of miles from the nearest depot)
Heavy equipment (engines, wind turbines, manufacturing machines) produce various streams of data (heat, vibration, time-series, etc)
Machine learning could be used to detect "failure patterns" in that data, helping businesses to maintain equipment health more effectively
This article is based on a presentation at the 2017 AI Applications Summit conference in Boston, entitled “Artificial Intelligence in the Hospital Setting” (slide deck embedded below) delivered by Emerj CEO Daniel Faggella - updated with recent insights and interviews from Emerj's podcast and AI Opportunity Landscape data.
We interviewed Karine Perset, from the OECD Directorate for Science, Technology and Innovation in France about the informational pillars that make up strong AI governance for governments worldwide. She offered us numerous insights into how the OECD developed the AI Principles and works with governing bodies to design policies that will keep AI safe and trustworthy into the future.
In July 2017, The State Council of China released the “New Generation Artificial Intelligence Development Plan," outlining China's strategy to build a US$150 billion Chinese AI industry in a few short years, and to become the leading nation in AI by the year 2030. Other nations followed suit quickly with national AI strategies of their own - with the US trailing behind by nearly two years before developing a semblance of an AI initiative. The proposed 2021 budget for the national security budget in the US is $740 billion - with a billions of dollars being earmarked for AI specifically (learn more: US Public Sector AI Opportunity Report).
We see evidence dating back to 2017 that Johnson & Johnson has been regularly publishing about their investments and initiatives related to artificial intelligence. At present, Johnson & Johnson does not seem to boast any mature, deployed applications with the firm itself, but its AI-related investment initiatives indicate their aspirations.
Leading retailers - like Walmart, Stop & Shop, and Home Depot - are enhancing their payment and fraud detection systems, using artificial intelligence that learns transaction norms and infers risk from the context of each transaction.