Domino Data Science Blog

Kjell Carlsson

Kjell Carlsson is the head of AI strategy at Domino Data Lab where he advises organizations on scaling impact with AI technologies. Previously, he covered AI, ML, and data science as a Principal Analyst at Forrester Research. He has written dozens of reports on AI topics ranging from computer vision, MLOps, AutoML, and conversation intelligence to augmented intelligence, next-generation AI technologies, and data science best practices. He has spoken in countless keynotes, panels, and webinars, and is frequently quoted in the media. Dr. Carlsson is also the host of the Data Science Leaders podcast and received his Ph.D. from Harvard University.

Generative AI

OpenAI’s Wake-up Call to the World: Future-Proof Your Generative AI Strategy Now

OpenAI’s board appears to have fatally stabbed the organization. Whether or not Sam Altman did or did not deserve to be let go, the organization will never be the same in the eyes of its customers, employees, investors and society at large. The unfolding debacle reveals the dangers of heavily relying on individual AI partners and the limits of outsourcing AI capabilities generally.

By Kjell Carlsson3 min read

A small tree with ripe, low hanging fruit
Generative AI

Set Yourself Up for Generative AI Success with the Top “Low Hanging” Use Cases

For most companies, Generative AI (GenAI) is no longer a question of if but how. Companies now face a critical decision that may determine whether their GenAI endeavors thrive or peter out in disillusionment.

By Kjell Carlsson4 min read

2023 Generative AI Survey Report Research
Generative Models

What The Experts Expect of Generative AI: Domino's 2023 REVelate Survey

Generative AI is moving swiftly from intriguing novelty to top priority for your digital transformation strategy. It is hijacking conversations everywhere, from the boardroom to the dining room. But what do the top data science leaders and practitioners from the world’s most advanced AI companies really think? How transformative do they believe Generative AI really is? What problems and risks do they see, and how are they going about turning Generative AI into tangible business value? We surveyed them to find out.

By Kjell Carlsson7 min read

Machine Learning

Domino’s Spring 2023 Release Drives Faster Innovation with Cutting-Edge AI for Every Enterprise

In today's economic environment, all organizations need to unlock greater AI value, faster. 98% of CDOs and CDAOs say the companies that bring AI and ML solutions to market fastest will be the ones who survive and thrive in the upcoming times of economic uncertainty. More than ever, organizations need to scale the creation and operationalization of ML models across their businesses and bring to bear the latest, most powerful AI methods and tools.

By Kjell Carlsson10 min read

Data Science

Python is the New Excel

It's becoming clear that the traditional “citizen data scientist” approach, focusing on no-code tools, has become an evolutionary dead end. Organizations who have pursued this route have little to show beyond PoCs and one-off successes despite years of investment in training and underutilized, proprietary tools. The best that can be said is that these efforts have been a costly way of democratizing data prep and business intelligence. In reality, they have been a step in the wrong direction for analytics and data science maturity.

By Kjell Carlsson7 min read

Perspective

Why Hybrid Cloud is the Next Frontier for Scaling Enterprise Data Science

An exciting new trend is rising in enterprise data science, and it’s breaking down the silos between on-premises and cloud environments to unlock the benefits of each, all while improving collaboration and regulatory compliance. Advanced, model-driven companies—especially the ones that are out-innovating their competitors with machine learning and AI—are adopting hybrid cloud strategies for their data science initiatives. The most advanced are even repatriating data science workloads back on-premises, while simultaneously exploiting the flexibility of multiple cloud environments.

By Kjell Carlsson9 min read

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