The Recipe for Achieving Aspirational AI
There has been a lot latest buzz about AI’s potential decline. Articles corresponding to “AI Stock Market Bubble May Be
Read moreAI Ethics
Small Language Models: A Strategic Opportunity for the Masses
In the evolving panorama of enormous language fashions (LLMs), it’s more and more evident that their immense dimension and broad
Read moreESG: The “Vital Signs” for Responsible and Ethical AI Outcomes
While Artificial Intelligence (AI) fashions can doubtlessly rework our private and skilled lives, they pose important challenges and dangers for
Read moreGlobal AI Trends In Business and Humanity – Show 12
Interview with Egle B. Thomas, PhD, MBA After a pleasant 4 week break, the AI Think Tank (*12*) is again for its
Read moreAvoid GenAI Model Collapse and Death by Averages
The Harvard Business Review article “Has Generative AI Peaked?” raised a troubling concern regarding Generative AI (GenAI): “This brings us
Read moreSynergy of Generative, Analytical, Causal, and Autonomous AI
The present fascination with Generative AI (GenAI) – particularly as manifested by OpenAI’s ChatGPT – has raised public consciousness of
Read moreNine Categories of Innovation-Driven Prompt Engineering
In my earlier weblog, “GenAI Maturity: From Productivity To Effectiveness,” I mentioned the dramatic disparities between the organizational mindset of
Read moreGenAI Maturity: From Productivity To Effectiveness
As I work with extra organizations utilizing Generative AI (GenAI) instruments like OpenAI’s ChatGPT and Microsoft’s Copilot, I see an
Read moreCritical Importance of Stakeholder-centric Design with AI
“It’s not the AI applied sciences that fail; it’s the group.” That is likely to be a considerably controversial viewpoint,
Read moreFrom chaos to creation: How data labeling drives success in generative AI
Training data is the cornerstone of AI algorithms – the standard of outputs is contingent on the data the AI
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