Remove Artificial Intelligence Remove Development Remove Pharmaceuticals
article thumbnail

Can developer productivity be measured? Better than you think

CIO Business Intelligence

Measuring developer productivity has long been a Holy Grail of business. In 2020, McKinsey surveyed 440 large companies about their “ developer velocity” — meaning the practices that best tap the full potential of development talent. Right now, there are roughly 27 million developers on the job, 4.4 That isn’t easy.

article thumbnail

CIOs look beyond ‘Big 3’ cloud providers for AI innovation

CIO Business Intelligence

The sheer variety and volume of data used for precision therapeutics requires Athos to build its own AI algorithms and AI models, which it may commercialize to other biotechnology and pharmaceutical companies when fully baked. The Vultr-Dell cloud partnership has helped pave the way. We dont have even have any legacy data, code, or platform.

Cloud 323
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

How to prioritize AI initiatives: A strategic framework for maximizing ROI

CIO Business Intelligence

This quote sums up the need for companies to prioritize artificial intelligence (AI) initiatives and also captures the state of the AI race today. Developing a clear and comprehensive strategic vision is the starting point of prioritizing AI initiatives with business goals. Theres no avoiding it. Mark Cuban.

How To 302
article thumbnail

Data Management in the Healthcare Industry

CIO Business Intelligence

Among the exciting possibilities to cure illness and save lives are artificial intelligence (AI), blockchain, and telemedicine. AI could fuel the development of personalized medicine, in which treatments are closely matched to the needs of individual patients, according to Elitsa Krumova @Eli_Krimova.

article thumbnail

Knowledge graphs: the missing link in enterprise AI

CIO Business Intelligence

Large enterprises have long used knowledge graphs to better understand underlying relationships between data points, but these graphs are difficult to build and maintain, requiring effort on the part of developers, data engineers, and subject matter experts who know what the data actually means.

article thumbnail

The startups Nvidia thinks are the future of AI

Dataconomy

Nvidia has expanded its influence in the artificial intelligence (AI) sector by investing in six emerging AI companies. Nvidia builds AI portfolio with investments in six startups Nvidia’s investments include Applied Digital Corp , Arm Holdings , Nano-X Imaging , Recursion Pharmaceuticals , Serve Robotics , and SoundHound AI.

article thumbnail

Generative AI usage gains traction among enterprises: McKinsey

CIO Business Intelligence

The findings also showed that the most commonly reported uses of generative AI are in marketing, sales, product development, and service operations. Artificial Intelligence, Enterprise Applications, Generative AI