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Data engineers, data scientists and other data professional leaders have been racing to implement gen AI into their engineering efforts. But a successful deployment of LLMs has to go beyond prototyping, which is where LLMOps comes into play. LLMOps is MLOps for LLMs. It’s about ensuring rapid, streamlined, automated and ethical deployment of LLMs to production. This blog post delves into the concepts of LLMOps and MLOps, explaining how and when to use each one.

Learn how Fivetran and Databricks work in unison to enable AI-powered upgrades to marketing ROI.

Investment in AI for manufacturing is expected to grow by 57% by 2026. That’s hardly surprising — with AI’s ability to augment worker productivity, improve efficiency and drive innovation, its potential in manufacturing is vast. AI’s predictive capabilities can help manufacturing leaders anticipate market trends and make data-driven decisions, creating financial opportunities for suppliers as well as customers.

In an iconic Top Gun scene, Charlie tells Maverick that a maneuver is impossible. Maverick replies, “The data on the MIG is inaccurate.” In the more recent sequel, despite his extensive, firsthand knowledge, Maverick is told “the future’s coming and you’re not in it.” While flying may be more automated now, the importance of accurate and diverse data for aviation safety remains — and is likely even more critical.

The global software development firm builds a scalable data stack that reduces the time to acquire data by 92% and supports predictive AI.

Keboola's availability on Google Cloud Marketplace opens up the potential of Google Gemini, allowing users to tackle advanced data tasks in just a couple of keystrokes. This integration marks the next step for AI-powered data processing and unlocks new opportunities for Keboola and Google Cloud users, language model enthusiasts, data scientists, application builders, and data engineers.

Generative AI tops every list of major financial services trends for 2024. And it’s no wonder — this new technology has the potential to revolutionize the industry by augmenting the value of employee work, driving organizational efficiencies, providing personalized customer experiences, and uncovering new insights from vast amounts of data.

It’s not hyperbole to say that generative AI (gen AI) is radically transforming the advertising, media and entertainment industry. There has been widespread excitement about the potential of gen AI to open brand-new creative opportunities and unlock unprecedented efficiencies. At the same time, there has been understandable concern about issues such as inherent bias, deep fakes and the impact of gen AI on jobs.

For decades, the sci-fi dream of simply speaking to your device and having it perform tasks for you seemed far-fetched. In the realm of test automation and quality assurance, this dream is inching closer to reality. With the evolution of generative AI, we’re prompted to explore what’s truly feasible. Embedding AI into your quality engineering processes becomes imperative as IT infrastructures become increasingly complex and integrated, spanning multiple applications across business processes.