Prioritize Understanding Over Memorization

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Assessing understanding and intelligence requires presenting novel problems that cannot be solved through memorization. The current educational system often favors memorization, which fails to accurately gauge understanding and intelligence. While some educators may be inclined towards the convenience of memorization, it often leads to laziness and does not truly reflect a student's grasp of the material. A shift towards problem-solving that focuses on creativity and originality is essential for an authentic evaluation of intelligence. This approach has been conceptualized in initiatives such as the ARC benchmark for machine intelligence, emphasizing the importance of abstraction and reasoning as measures of true intelligence.

Which is more intelligent, ChatGPT or a 3-year old? Of course this depends on what we mean by "intelligence." A modern LLM is certainly able to answer all sorts of questions that require knowledge far past the capacity of a 3-year old, and even to perform synthetic tasks that seem remarkable to many human grown-ups. But is that really intelligence? François Chollet argues that it is not, and that LLMs are not ever going to be truly "intelligent" in the usual sense -- although other approaches to AI might get there.

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Blog post with transcript: https://www.preposterousuniverse.com/podcast/2024/06/24/280-francois-chollet-on-deep-learning-and-the-meaning-of-intelligence/

François Chollet received his Diplôme d'Ingénieur from École Nationale Supérieure de Techniques Avancées, Paris. He is currently a Senior Staff Engineer at Google. He has been awarded the Global Swiss AI award for breakthroughs in artificial intelligence. He is the author of Deep Learning with Python, and developer of the Keras software library for neural networks. He is the creator of the ARC (Abstraction and Reasoning Corpus) Challenge.

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