Discover the four decision-making paradigms that make agents useful in business by Andreas Welsch’s featured article.
Copyright: intelligencebriefing.substack.com – “Machine Teaching: How AI Agents Learn New Tricks”
On June 11, Kence Anderson (Founder & Machine Teaching Expert) joined me on “What’s the BUZZ?” and shared how AI agents acquire knowledge about new things in a world that keeps constantly evolving. Don’t Generative AI and LLM already contain all the relevant knowledge? Here is what we’ve talked about…
The Essence of Machine Teaching
Machine Learning has been a buzzword for years, but the latest frontier is MachineTeaching. Machine learning involves systems learning from data to identify patterns and make predictions. But if machines can learn, they can and should be taught. Teaching is about breaking down tasks into manageable chunks and guiding the learning process to ensure efficiency and effectiveness.
Teaching in AI is akin to training in sports or music. Expert teachers break down complex tasks into smaller, practiceable skills. This approach ensures that AI systems learn efficiently, focusing on promising areas rather than wasting resources on less productive ones. By drawing on human analogies, machine teaching makes AI systems more robust and adaptable.
Moreover, addressing objections to this approach, it’s emphasized that drawing boundaries around what AI learns doesn’t limit its potential. Just as humans benefit from structured learning environments, so do machines. Teaching, therefore, is about enhancing AI’s capability to perform high-value tasks by leveraging structured guidance and expertise.
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
The Role of Intelligent Agents
Intelligent agents are a step beyond basic AI models. Defined as systems that can perceive their environment, make decisions, and act upon those decisions, agents are integral to the next generation of modern AI applications. Unlike simple predictive models, agents engage in complex decision-making processes, making them invaluable in high-stakes environments.[…]
Andreas Welsch is an internationally recognized AI leader in the software industry with over 21 years of experience. Andreas has led regional business development teams for AI, built and led an AI Center of Excellence, and currently leads product marketing and go-to-market strategy for AI at SAP, the world’s leading business application provider. He has successfully managed stakeholder relationships with business leaders and technology teams across Fortune 500 companies in more than 80 innovation projects, and helped create an AI mindset across organizations.
Andreas is best known as the creator of the Intelligence Briefing series on LinkedIn and the popular “What’s the BUZZ?” live stream and podcast. He is a frequent keynote speaker and guest on expert panels and podcasts.
Industry focus: High Tech
Previous awards by SwissCognitive:
Discover the four decision-making paradigms that make agents useful in business by Andreas Welsch’s featured article.
Copyright: intelligencebriefing.substack.com – “Machine Teaching: How AI Agents Learn New Tricks”
The Essence of Machine Teaching
Machine Learning has been a buzzword for years, but the latest frontier is Machine Teaching. Machine learning involves systems learning from data to identify patterns and make predictions. But if machines can learn, they can and should be taught. Teaching is about breaking down tasks into manageable chunks and guiding the learning process to ensure efficiency and effectiveness.
Teaching in AI is akin to training in sports or music. Expert teachers break down complex tasks into smaller, practiceable skills. This approach ensures that AI systems learn efficiently, focusing on promising areas rather than wasting resources on less productive ones. By drawing on human analogies, machine teaching makes AI systems more robust and adaptable.
Moreover, addressing objections to this approach, it’s emphasized that drawing boundaries around what AI learns doesn’t limit its potential. Just as humans benefit from structured learning environments, so do machines. Teaching, therefore, is about enhancing AI’s capability to perform high-value tasks by leveraging structured guidance and expertise.
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
The Role of Intelligent Agents
Intelligent agents are a step beyond basic AI models. Defined as systems that can perceive their environment, make decisions, and act upon those decisions, agents are integral to the next generation of modern AI applications. Unlike simple predictive models, agents engage in complex decision-making processes, making them invaluable in high-stakes environments.[…]
Read more: www.intelligencebriefing.substack.com
Share this: