AI experts - Everywhere and nowhere: a look behind the scenes
**Just a reminder: The content was written by me and is not AI-generated. However, it has been corrected in grammar and spelling by DeepL Write and the picture was done by DallE.
On LinkedIn, they seem to be everywhere - self-proclaimed AI experts. But a closer look reveals a different reality. Out of five "experts" I recently interviewed, only one had knowledge that could just about pass for expertise.
In a world where using tools like ChatGPT or Bing is already considered expertise, you have to ask yourself: what really makes an AI expert? Formulating good prompts in a chatbot is certainly a skill, but far from true expertise.
A true expert in AI should have a fundamental understanding of how different aspects of AI - from image processing technologies to large-scale language models - interact and influence real-world processes. It's less about seeing the forest for the trees (Insider Joke: Random Forrest) and more about understanding the entire ecosystem. For example, an expert who knows the importance of Tamagotchis for the Turing test is often more valuable than someone who can only code TensorFlow libraries.
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Let's take Hod Lipson, a pioneer in the development of Eureka, as an example. Lipson epitomizes the type of expert who not only masters the technical aspects, but also understands the profound impact of his developments on society. His work shows that true expertise is a combination of technical know-how and an understanding of the broader implications.
True experts who see the big picture are rare. They are not always popular, because what they have to say is not always what people want to hear. But it is precisely these perspectives that help us to understand the full potential and limitations of AI.
What experiences have you had with self-proclaimed AI experts? Share your stories and let's paint a more realistic picture of real AI expertise together.
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Der erprobte Weg für Mittelst?ndler durch Künstliche Intelligenz Gewinn- und Effizienzsteigerung zu erzielen | 20+ KI Projekte | Gründer | 6 + Jahre KI Erfahrung
7 个月Deine Worte sind Balsam für meine Ohren! Momentan wimmelt es von (ich bezeichne sie als) ChatGPT Cowboys. In my opinion sind Studium, mehrj?hrige Berufserfahrung, unterschiedliche Projekte etc. die Vorraussetzung, um sich KI Experte nennen zu dürfen. Zumindest sollte für den Random Forest Witz ausreichen.
?? Problem finder | ?? Enterprise Software Delivery ?? | Enduro Rider ??
7 个月It's challenging to define expertise in a field that is so new and progressing so rapidly. I guess the easiest way to filter would be to focus on the pragmatic experience and real-life implementation vs the theoretical (purely) approach. At the end of the day, it depends on what one is looking for, I guess.
Gefühlt schon weiter | Co-Founder @ Vor Der Welle Ai | Vor der Welle Podcast | Initiatorin @ Raumgeber:innen Movement
7 个月So wahr. "They are not always popular, because what they have to say is not always what people want to hear." Es ist ein schmaler Grad zwischen Enthustiast und Experte. Und es ist eine Basistechnologie und damit einhergehend brauchen wir KI-Literalit?t. Zukünftig fl?chendeckend. KI-Experten sind für mich die jenigen, die KI sowohl als Werkzeug selbst nutzen, aber eben auch in der Lage sind KI-Technologien kritisch zu hinterfragen, Limitationen erkennen und "ernsthaft" und klug antizipieren k?nnen. Bereit sind, die kurzfristige Bereicherung mit der langfristigen Verantwortung abzuw?gen. Ich finde es gut und richtig, wenn KI-Enthusiasten auch Trainer werden. Workshops geben. Dafür Geld nehmen. Sie ?ffnen Türen und l?sen bei der breiten Ma?e Neugierde aus. Das brauchen wir. KI-Enthusiasten sind m.E. auch pr?destiniert dazu KI-Experte zu werden. (Ich wünsche es mir) Trotzdem tue ich mich ganz allgemein mit dem Wort KI-Experte schwer. Gerade weil es eine Basistechnologie ist. Es für alle in seiner Komplexit?t neu ist und weil ich mir im Grundsatz erhoffe (uotpisch), dass jeder "KI-Experte" wird.