Interest in generative AI and large language models (LLMs) has exploded in popularity thanks to a slew of announcements and product releases, such as Stable Diffusion, Midjourney, OpenAI’s DALL-E, and ChatGPT. The arrival of ChatGPT in particular was a bellwether moment, especially for developers. For the first time, an LLM was readily available and good enough that even non-technical people could use it to generate prose, re-write emails, and generate code in seconds.

We recently ran our first hackathon in quite some time. Over two days, our team collaborated in groups on various topics. By the end of it, we had 12 demos to share with the rest of the team. These ranged from improvements in debugging HTTP request responses to the delightful “automatic swag sharer.” Within our groups, a number of us tried integrating with OpenAI’s GPT to see what smarts we could bring to our product.

D2iQ has introduced an AI assistant that helps organizations resolve problems more quickly and easily, including coding errors and system failures. The new DKP AI Navigator can help reduce the duration and cost of system and application bottlenecks, misconfigurations, and downtime, and ultimately help organizations overcome the Kubernetes skills gap.

In a fast-evolving world, adopting a hyperautomation strategy is the best way to future-proof your workplace. But how does hyperautomation affect your workforce, and what will it mean for the future of your business? Hyperautomation is the combination of intelligent technologies to expand automation. It incorporates AI, machine learning, robotic process automation (RPA), integration, document processing, and more.