Clemens MewaldinTowards Data ScienceCrossing the AI Chasm: How OpenAI turned LLMs into a mainstream successAnd why LLMOps will suffer the same fate as MLOpsOct 19, 20239Oct 19, 20239
Clemens MewaldinTowards Data ScienceWhy Data Is *Not* the New Oil and Data Marketplaces Have Failed UsHow a real-time programmatic data exchange would change everythingJul 13, 202315Jul 13, 202315
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 usingJun 7, 202315Jun 7, 202315
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 strategiesAug 18, 20206Aug 18, 20206
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…Jan 31, 201911Jan 31, 201911
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…Nov 30, 20182Nov 30, 20182
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…Sep 27, 20182Sep 27, 20182
Clemens MewaldinThe LaunchpadNo Machine Learning in your product? Start hereAdvice from the trenches of machine learning integrationAug 16, 20185Aug 16, 20185
