AI Articles and Analysis about Business intelligence and analytics

Explore articles and reports related to artificial intelligence for business intelligence and analytics, including applications in forecasting, predictive analytics, text analysis, and more.

How to Apply Machine Learning to Business Problems 4

Machine Learning Industry Predictions: Expert Consensus

In July of 2016, we sent out a series of survey questions to past guests who have been featured on the Emerj podcast, including academic researchers, founders, and executives who are experts in the machine learning domain. In this article, we focus on responses to the following question:

How to Apply Machine Learning to Business Problems

Five Year Trends in Medical AI Applications

Episode Summary: I remember reading an article in Scientific American years ago about a poster of a person looking in the direction people sitting in a school dining room, and that this poster would make people sitting in the dining room less likely to litter. This seems like an absurd example of holding people accountable for their actions, but as it turns out, there are a lot more serious consequences to ensuring behavior change through observation, and one area where this matters is medicine.
Today, there’s a major issue with people who don't adhere to their medical regimens, only to relapse or experience more serious symptoms later on. This week's guest, Cory Kidd, CEO of Catalia Health and known for his work at MIT on human-robotic interaction, is working to help solve this problem by developing a robot that adds some of that physical presence and accountability. This is likely one of many novel medical AI applications that we're likely to see roll out in healthcare over the next decade.

Google Algorithm Disrupts Medical Field, Intel Launches Automated Driving Group, and More  - This Week in Artificial Intelligence 12-02-16 3

Future Applications of Machine Vision – an Interview with Cortica’s CEO

Episode Summary: Right now, you can take a picture of a flower in your garden and post it on social media to see if anyone knows its proper name. Wouldn’t it be nice, though, if a machine could identify the correct name and species in the picture you just took? Solving this problem in applications of machine vision is something that CEO Igal Raichelgauz and his team are working on at Cortica, a machine learning company that is not focused on deep learning, but is instead taking a more "shallow" approach. In this episode, Raichelgauz articulates Cortica's approach, which is based on neurology and goes against some of the current approaches in getting machines to learn. We discuss some of these primary differences and dive into Cortica's goals for applying machine vision in consumer products.

The Economic Impact of Artificial Intelligence - An Interview with Accenture's CTO

The Economic Impact of Artificial Intelligence – An Interview with Accenture’s CTO

Episode Summary: Accenture is a leading global professional services company in the tech space, providing services to many of the Fortune 500 and their global equivalents. The company recently conducted a study, combined with expertise from economists and AI researchers, about the longer-term economic impact of artificial intelligence around the world. In this episode, I spoke with Chief Technology Officer Paul Daugherty, who has been with Accenture since 1986, and who was joined by Global Technology R&D Lead Marc Carrel-Billiard. We met up at a coffee shop after an AI Summit in San Francisco, and I asked Paul and Marc about what they had learned from this newly-published study and what they consider to be the significant impacts of *AI and automation on the future job market.

Google Algorithm Disrupts Medical Field, Intel Launches Automated Driving Group, and More  - This Week in Artificial Intelligence 12-02-16 1

Crowdsourcing a Machine Learning Hedge Fund

Episode Summary: Crowdsourcing is a relatively common term in technical vernacular today. Even if you're not a self-identified "techie", you may very may well have leveraged crowdsourcing in journalism, the sciences, public policy, or elsewhere. One area in which this concept hasn’t really taken off is in finance and hedge funds. In this episode, we speak with Numerai Founder Richard Craib, whose company is crowdsourcing a machine learning hedge fund. Their model is based on pooling data science talent from all over the world and using "anonymous" models to train financial data. These models compete against one another, and the winning models' creators are rewarded in bitcoin - a process based entirely on encryption and anonymity. Craib speaks about his overarching vision for the company, and also delves into his thoughts on the past, present, and future of AI applications in finance.
 

Google Algorithm Disrupts Medical Field, Intel Launches Automated Driving Group, and More  - This Week in Artificial Intelligence 12-02-16 7

Where Healthcare’s Big Data Actually Comes From

While there have been and continue to be innovative and significant machine learning applications in healthcare, the industry has been slower to come to and embrace the big data movement than other industries. But a snail's pace hasn't kept the data from mounting, and the underlying value in the data now available to health care providers and related service providers is a veritable goldmine. In this editorial, we provide an overview of where healthcare's big data actually comes from, and why providing robust data analytics services in this sector matters.

Skymind Machine Learning Applications for Enterprise 2

Skymind Machine Learning Applications for Enterprise

Episode Summary: CEO Chris Nicholson speaks on Skymind machine learning applications, which integrate with Hadoop and Spark. In this episode, Nicholson sheds light on current machine learning trends that he sees across industries and best practices for implementing AI solutions in order to gain consistent return on investment. For our readers who enjoyed out consensus on future trends in artificial intelligence consumer applications, it may be interesting to hear some of Chris's specific use cases in industry.

Where to Apply Machine Learning First in Your Business: Expert Consensus 1

Where to Apply Machine Learning First in Your Business: Expert Consensus

Busy and multitasking are understatements for today's executives and entrepreneurs. Machine learning has the potential to help make businesses more efficient, competitive, and profitable, but learning how it works and finding the resources to implement this technology takes time. Where to apply machine learning when first getting started is dependent on a number of factors - industry, structure, current problems - but having an idea of which solutions have proved most efficient for others and derived maximum return on investment is a helpful jumping off point.

Business intelligence and analytics

Explore articles and reports related to artificial intelligence for business intelligence and analytics, including applications in forecasting, predictive analytics, text analysis, and more.