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Carsten Riggelsen
Explo(r|it)ing Data and Co. - MSc, PhD in ML/AI
Who is Carsten Riggelsen?
Carsten Riggelsen is the Head of Data & AI at PCG DACH (PCG Germany / PCG International). He has a background in computational statistics, machine learning (ML), artificial intelligence (AI), and data mining.3
In his current role at PCG, Riggelsen focuses on operationalizing "Data & AI" and providing no-nonsense expertise in these areas.1 He is passionate about topics such as AI democratization, data democratization, and modern data strategies.27
Riggelsen holds an MSc and PhD in ML/AI from Utrecht University.3 He frequently shares his insights and experiences on LinkedIn, discussing trends and best practices in the world of data and AI.12467
Some of Riggelsen's key areas of focus include:
- Composability in AI: Exploring how composability can address the diverse needs of supporting various AI applications, from assembly to agility7
- AI Democratization: Noting that "AI Democratization" is happening faster than many expected, even before "Data Democratization"2
- Sustainable AI: Emphasizing the importance of taking a sustainable route with AI, beyond just proof-of-concept (POC) level due to fear of missing out (FOMO)4
Riggelsen's LinkedIn posts showcase his expertise in navigating the evolving landscape of data and AI, offering valuable insights to his professional network.58
Highlights
Obwohl der AI Act in EU in allermunde ist soll es bitte niemanden davon abhalten sich mit KI auseinanderzusetzen. Viele bzw sogar die meisten KI-Anwendungsfälle sind Minimal Risk (ausnahmsweise Limited Risk) und (kaum) reguliert.
Ein Anwendungsfall wie zB "Visual Quality Inspection" (kann man mittels Amazon Lookout for Vision und/oder Amazon Recognition abbilden) ist insofern nicht sonderlich reguliert (und übrigens gar nicht personenbezogen).
Es gibt wirklich unendlich viele sogenannte "Narrow AI" Use-Cases womit man also schon heute loslegen kann ohne sich Sorgen zu machen.
In DACH sollten wir mal ins doing kommen statt immer Hürden zu sehen und zu definieren.
Wir helfen gerne - PCG DACH / PCG International.
× Nobody saw "AI Democratization" happening before "Data Democratization".
Ever since "Big Data" has been a topic (at least the last 15 years), democratizing access/usage of vast amounts of data via self-service solutions has been at the center of data strategy initiatives. However, it never really worked seamlessly due to technical challenges, heterogeneous data landscapes and overly complex solutions for users.
For AI, entire SaaS solutions and websites/apps provide a fairly complete AI experience/entry point even for non-experts, at least when it comes to use-cases mostly associated with GenAI, e.g. various QA bots/assistants, text summarization, image gimmicks, etc., even combined with own data.
× Now the next level is to up the game on "AI/Data Literacy" , making users aware of limitations and pro/cons, risks etc. of such solutions.
