Time may be right for professionalizing artificial intelligence practices
"It's unlikely that you'd trust a 'citizen architect' to build your home in the same way that you wouldn't visit a 'citizen doctor' when you get sick."
"It's unlikely that you'd trust a 'citizen architect' to build your home in the same way that you wouldn't visit a 'citizen doctor' when you get sick."
Latest Cloud Native Computing Foundation survey finds release cycles have continued to speed up, and continuous integration and continuous deployment methods are now embedded in most enterprises. Containers rule
Latest annual Puppet survey shows platforms making inroads, making application teams more efficient, providing a balance between standardization and team autonomy. Another benefit: smoother change management
Don't just replace technology; reimagine your business
AI teams not only need to have cutting-edge skillsets to build, test and refine AI models and applications, but they also need to step up as transformational leaders, a new study finds.
There's no doubt that "EA is growing up." Still, only seven percent of companies are at the point where they can break down business technology into digital processes and components.
Digital transformation, DevOps and delivery mechanisms now front and center for software teams. And unexpected effect: bursts in productivity.
Two in five companies see lack of technical expertise as a roadblock to AI. It couldn't come at a worse time.
Code rot leads to under-performing enterprise systems. In today's device-laden edge world, it can be devastating. Another issue lurking: inaccurate AI algorithms.
For developers, code releases are "emotional" events. Many have fear and anxiety at the moment they release code or submit it for review --and fear breaking dependencies