Latest AI Articles:

Episode Summary: This week, we're going to be talking about the defense sector. We interview Ryan Welsh, CEO of Kyndi, a company working on explainable AI. We focus specifically on the unique data challenges of the defense industry, as well as the general use case of AI in defense writ large. Many of the challenges that the defense sector has to deal with transfer to other spaces and sectors. Business leaders that deal with extremely disjointed text information, what is sometimes called "dark data," and information in various languages or different dialects, will be able to resonate with some of the unique challenges talked about in this episode, and maybe even gain some insights for how to handle them.

Event Title: NITI Aayog-ORF AI for All Conference

Event Host: NITI Aayog, Observer Research Foundation

We've seen a lot of what we call "fake AI rebrands" in the last 18 months, and I suspect that as long as AI is a buzzword, we will only see more and more of this. Business leaders are going to have to keep their eyes peeled for these kinds of companies in their midst.

According to Accenture, approximately 66% of A&D executives polled indicated they are looking at investing in AI for 2019, particularly on security, production, and R&D. 80% believe that AI-based decisions will have a direct impact on the workforce by 2021.

This report attempts to highlight the wide array of real-world use cases of machine vision in the military. Several militaries claim to leverage machine learning, working with contractors and companies in some cases to deliver AI solutions. We found that these solutions help highlight the wide breadth of current and near-term military applications of machine vision. The companies and organizations discussed in this report help various militaries with at least one of the following:

Accenture reports that in 2017, the 16 top biopharmaceutical companies in the world had an aggregate global revenue of $428 billion, which was nearly half the global pharmaceutical market by net sales. The report also revealed a shift to specialty drugs for hard-to-treat diseases.

It seems that the majority of AI solutions for payment processing are focused on fraud detection and prevention. Some companies claim to offer straight-through processing software as well. Below, we detail four companies that all claim to offer artificial intelligence to banks and payment processors looking for solutions in two key areas:

Several companies offer AI-based credit scoring applications to banks and enterprise creditors looking to better understand the risk associated with their potential borrowers. Traditional methods of credit scoring take into consideration the credit histories of potential borrows, but this might not allow certain people access to credit despite the fact that they could pay their loans back when their payments are due.

Episode Summary: Whether we're talking about customer service, marketing, or building developer teams, what we try to do on our AI in Industry podcast is bring to bear lessons that are transferable. There are few more transferrable ideas than what makes a company ready to adopt AI. When it comes to the willingness and the ability to integrate AI into a company strategy and to fruitfully adopt the technology to really see an ROI, what do the companies that do so successfully have in common? What do the companies that are not ready or too fearful to do it have in common?

One of the biggest problems facing business executives when it comes to adopting AI is determining whether a company is truly leveraging AI or simply using the term as a marketing strategy. We have discussed rules of thumb for assessing the authenticity of AI companies in previous articles based on insights derived from hundreds of interviews with industry experts and AI researchers over time.