Search Results for: machine learning

AI and machine learning have promising potential in the field of healthcare. However, there is one significant hurdle healthcare companies often encounter when trying to implement AI and machine learning. The data architecture of current legacy systems in healthcare settings prevents implementing many use cases and limits a company’s ability to benefit from these technologies fully.

The coronavirus pandemic has ushered in a new era of digital payments; those who once mailed checks and made purchases in person are now paying their bills electronically and shopping online. As the economy is rattled by the coronavirus, there are some AI startups in the payments space that will succeed and others that will fail. All are pivoting rapidly to eCommerce, if that wasn't already their focus to begin with.

Many business leaders make the mistake of believing that AI and machine learning are like regular IT, but this could not be further from the truth. In large part, this is because, unlike simple software solutions for discreet business problems, it can be very difficult to measure the ROI of machine learning.

Many of the top Fortune 500 retailers have begun using AI and ML to solve business problems for various departments. Walmart and Costco share one in grocery stocking, which includes the freshness and condition of the products along with timing the restocks for peak hours.

We spoke with Jonathan Ross, CEO and founder of Groq, an AI hardware company, about software defined compute. This interview is part of a series we did in collaboration with Kisaco Research for the AI Hardware Summit happening in Mountain View, California on September 17 and 18. 

The advent of machine learning in finance ushered in a keen interest in using AI to automate processes from fraud detection to customer service. While some use-cases aren’t nearly as established as others, our research leads us to believe that in the coming five years, banks will continue to invest in machine learning for risk-related processes, including underwriting.

We interviewed Jay Budzik, CTO at Zest AI, about the business value of machine learning for auto lending. We speak with Budzik about how underwriting, lending, and credit scoring is evolving as a result of advances in machine learning - both in terms of new data sources, and more advanced algorithms.

The healthcare industry holds perhaps the most responsibility of any industry when it comes to ensuring data privacy. A breach in electronic medical records (EMRs) could tarnish a healthcare company's reputation, put undue stress on patients, and render the company in violation of regulations.

McKinsey estimated that embarking on digital transformation to restructure value chains and drive R&D innovation across the pharmaceutical industry could be worth $50–150 billion of earnings before interest, taxes, depreciation, and amortization. In particular, machine learning is likely to continue finding a place in the pharmaceutical industry. Pharmaceutical companies have found applications for machine learning ranging from drug discovery to clinical trial retention.
The State of AI in the Asian Pharmaceutical Industry
AI seems to be making its way into the pharmaceutical space in Asia over the last two or three years, particularly in China and Japan. For the most part, the companies offering or using AI for drug discovery are just starting to acquire funding and talent. XtalPi seems to have the highest density of talent with a decent likelihood of being able to work with machine learning.

There are few companies claiming to offer artificial intelligence solutions to orthopedics companies. We found that these solutions are intended to help orthopedics companies with at least one of the following business problems: