Clemens MewaldinTowards Data ScienceCrossing the AI Chasm: How OpenAI turned LLMs into a mainstream successAnd why LLMOps will suffer the same fate as MLOps15 min read·Oct 19, 2023--9--9
Clemens MewaldinTowards Data ScienceWhy Data Is *Not* the New Oil and Data Marketplaces Have Failed UsHow a real-time programmatic data exchange would change everything13 min read·Jul 13, 2023--21--21
Clemens MewaldinTowards Data ScienceThe Golden Age of Open Source in AI Is Coming to an EndNC, SA, GPL, and other acronyms you don’t want to see in the open source license of the model you are using7 min read·Jun 7, 2023--15--15
Clemens MewaldinTowards Data ScienceThe problem with AI developer tools for enterprises (and what IKEA has to do with it)How a dominant design, appropriate form factors, and awareness of the IKEA effect will help enterprises realize their AI strategies12 min read·Aug 18, 2020--6--6
Clemens MewaldinThe LaunchpadYour Deep-Learning-Tools-for-Enterprises Startup Will FailI usually write about how to integrate and launch ML/AI in consumer-facing products. However, a large part of my job is building ML/AI…12 min read·Jan 31, 2019--11--11
Clemens MewaldinThe LaunchpadHow to protect your Machine Learning product from time, adversaries, and itselfUnlike traditional products, the launch of ML/AI-driven features or products is just the start of a Product Manager’s role. ML models…7 min read·Nov 30, 2018--2--2
Clemens MewaldinThe LaunchpadData: A key requirement for your Machine Learning (ML) productAs Product Managers, we have to play the product-equivalent of three-dimensional chess by trying to solve for user, engineering, marketing…8 min read·Sep 27, 2018--2--2
Clemens MewaldinThe LaunchpadNo Machine Learning in your product? Start hereAdvice from the trenches of machine learning integration9 min read·Aug 16, 2018--5--5
