Amidst the AI/GenAI revolution, a new breed of "gurus" has emerged, often with inflated claims and limited practical experience. While genuine expertise is essential, it's crucial to distinguish between true AI practitioners and those who simply capitalize on the hype. It's important to critically evaluate the claims and contributions of such individuals, as superficial understanding can lead to misguided implementations and missed opportunities.
Often during my conversations these days with the IT people and leaders from different markets within the Asia-Pacific, everyone is learning AI, since not being able to spell that out correctly means you are legacy.
On the flip side, interestingly enough, less than 1% people actually understand what AI really is and perhaps 0.1% are able to talk and follow through with the details around:
- AI Strategy
- AI project life cycle
- AI infrastructure
- AI Algorithms
- AI Governance
- AI Ethics
While over simplification is good way to communicate effectively with the non-technical audience, but then we are talking about IT folks and industry. Just getting familiar with the lingo likely give the false sense of mastery.
There seems to be significant gaps in terms of how IT industry folks are getting trained on these topics (outside the old traditional DS community people).
If people tells you that they understand what GenAI is and how it works, but haven't heard of "Semantic Model, Ontology & Knowledge Graphs", very unlikely they know anything beyond the lingo.
Further Readings:
HTH...
A Tech Artist 🎨
