Pharmaceutical industry leaders are adopting new artificial intelligence (AI) technologies and increasing process efficiency. The Infosys report on AI adoption shows that pharmaceuticals are among the most mature industries in Al adoption. In the same report, 40 percent of the respondents claimed their organizations had deployed Al and that it was working as expected. AI-powered features help them manage massive volumes of pharmaceutical data with great accuracy and speed.

Many organizations struggle with fragmented testing approaches covering only individual components or features, leading to gaps in the system’s reliability and user experience.

IFrames were used, and are still used, in many embed frameworks. After much experimentation, including many unsuccessful platforms, iframes have proven themselves to be a simple and powerful way to let partners customize your experience. However, their limitations are also known: Consequently, platform teams have tested and continue to test alternatives. Certain platforms now exclude iframes entirely, while others combine iframes with non-iframe alternatives.

Retrieval Augmented Generation (RAG) is an intelligent assistant that helps you find exactly what you’re looking for in a pile of medical records. Like an X-ray shows you hidden details inside the body, RAG helps you quickly extract precise information from complex data. RAG provides instant, accurate answers—often visualized in charts or summaries that require analysts to produce manually. RAG combines two AI capabilities—retrieval systems and generative models.

The open data lakehouse is quickly becoming the standard architecture for unified multifunction analytics on large volumes of data. It combines the flexibility and scalability of data lake storage with the data analytics, data governance, and data management functionality of the data warehouse.

Banking automation has become a key driver of efficiency and innovation in the financial services industry. As the banking sector strives to meet the demands of customers while managing costs, they’re turning to technology to streamline operations. But what exactly is banking automation, and how does it work? Let’s break it down. Banking automation refers to the use of technology by financial institutions to perform tasks that would traditionally require human intervention.

Generative AI in manufacturing refers to using advanced AI algorithms and generative models to optimize various aspects of the production process. This technology enables manufacturers to create innovative product designs, streamline workflows, predict maintenance needs, and boost efficiency in frontline operations. By integrating generative AI, manufacturers can enhance decision-making, collaboration, and data insights, ultimately improving overall performance.

The dynamic landscape of product development continuously increases the scope of what is demanded from quality engineering (QE) professionals. So, it is not surprising that workplace learning and upskilling are critical to the organizational success, as highlighted by Workplace Learning Report: Without a doubt, the more technical side of the skill spectrum - e.g.

For iPhone and iPad app development, one of the main aspects is the app’s performance. Performance is about your application not crashing, but also how quickly and smoothly it can carry out its functions when users interact with it. An application whose functions consume a lot of battery life, or an application that doesn’t like to wait too long until it finishes whatever it wants to do, can lead to users uninstalling the app.

It’s no secret that more and more organizations are turning to solutions that can provide benefits of real time data to become more personalized and customer-centric, as well as make better business decisions.