In this episode of Profound, I talk with Dr. Khai Minh Pham, whose unique approach to artificial intelligence challenges conventional paradigms and opens new frontiers in AI research and application. Dr. Pham, with his extensive background in both medicine and artificial intelligence, shares his journey towards creating a distinctive AI framework that prioritizes knowledge over data, steering clear of the traditional data-centric methodologies that dominate the field.
Dr. Pham recounts his early realization of the limitations inherent in human cognitive processes and how this propelled him to explore AI as a means to augment human memory and decision-making capabilities.
Central to this episode is Dr. Pham's critique of the prevailing AI models that rely heavily on data processing and pattern recognition. He introduces his concept of "macro connectionist AI," a system that mimics human reasoning more closely by forming high-level knowledge representations rather than merely processing data inputs. This approach, according to Dr. Pham, not only enhances AI's problem-solving capabilities but also significantly reduces the computational resources required, challenging the current industry trend towards increasingly complex and energy-intensive AI systems.
you can find Dr. Pham's LinkedIn below:
https://www.linkedin.com/in/khai-minh-pham/
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