AI Articles and Analysis about Research and development

GlaxoSmithKline (GSK) is a multinational pharmaceutical company headquartered in Brentford, UK. The company operates in over 150 countries. GSK offers a wide range of pharmaceutical products, vaccines, and consumer healthcare products, including over-the-counter medications, oral care and nutritional products.

Founded in 1833 and headquartered in Irving, Texas, since 2019, McKesson is a leading distributor of pharmaceuticals and medical supplies. They also provide health information technology and care management tools.

Cardinal Health is a global healthcare services company with a rich history and a strong focus on providing integrated solutions to the healthcare industry. Established in 1971, the company has become a leading player in the healthcare sector, offering a wide range of products, services, and technologies to enhance patient care, optimize supply chain efficiency, and drive value-based outcomes.

Bosch is a German multinational technology and engineering company headquartered in Gerlingen, Germany. Bosch manufactures products across various industries, including aerospace, automotive, energy and utilities, healthcare and others.

As nearly every American household has realized over the last year, large language models combined with generative AI abilities pose tremendous challenges and opportunities for enterprises of every shape and size. Just ask anyone who has heard of ChatGPT.

AI initiatives that cannot find ROI have no use in modern business. However, the path to ROI from enterprise-wide digital transformations is never a straight and narrow road. A pre-pandemic survey from MIT Sloan Management Review and Boston Consulting Group found that 70% of companies among those surveyed reported no value from their AI investments. 

As AI becomes increasingly interwoven in the fabric of our everyday lives, the insurance sector is finding new business challenges and opportunities in all of the ways these emerging technologies bring increased risk - and security - to our lives.

As a business practice, model development aims to create a dataset, tailored through machine learning, that can accurately predict outcomes or classify data based on input variables. By following a structured approach, developers can ensure that the model development process is efficient, effective, and reproducible.