Tell me about Prof. Richard Sutton, who wrote the short essay: The Bitter Lesson in 2019 # ChatGPT Answer Richard S. Sutton is a Canadian computer scientist who is currently a distinguished research scientist at DeepMind, a British AI company owned by Alphabet Inc. He is also a professor in the Department of Computing Science at the University of Alberta, Canada. Sutton is considered one of the founding fathers of modern computational reinforcement learning and has made significant contributions to the field of artificial intelligence (AI). He completed his Ph.D. in Computer Science from the University of Massachusetts Amherst in 1984, and since then, he has held several academic and industrial positions including working at AT&T Labs. Sutton is well-known for his work on Temporal Difference Learning which is a key part of many reinforcement learning algorithms used today. He has authored and co-authored numerous papers in his field, and his book 'Reinforcement Learning: An Introduction', co-authored with Andrew Barto, is widely regarded as a seminal text on the subject. In 2019, he wrote an essay titled "The Bitter Lesson", where he argues that in AI research, raw computing power combined with general-purpose learning algorithms has often proved to be more effective than systems built on extensive human expertise and domain knowledge. This essay has been influential in AI research circles. Sutton's work has been recognized with several awards including the IJCAI-16 Computers and Thought Award for his contributions to reinforcement learning and neural networks. # Gemini Answer Prof. Richard Sutton is a prominent figure in the domain of reinforcement learning. Here's a look at him and his influential essay, "The Bitter Lesson": **Who is Prof. Richard Sutton?** - **Pioneer in Reinforcement Learning (RL):** One of the founding fathers of modern computational reinforcement learning. His work has greatly shaped the field we know today. - **Key Publications:** Co-author of the foundational textbook "Reinforcement Learning: An Introduction" (with Andrew Barto), which remains a standard reference. - **Temporal-Difference Learning (TD-Learning):** Developed this fundamental RL algorithm, which is crucial for addressing the delayed-reward problem in learning. - **Other Contributions:** Significant work on policy gradient methods, Dyna architecture, and more. - **Professor:** Professor Emeritus at the University of Alberta, continuing his research in artificial intelligence. **"The Bitter Lesson" (2019)** This short but impactful essay argues a central point about the progress of Artificial Intelligence (AI): - **Main Thesis:** Major successes in AI have consistently resulted from scaling computation, search, and learning methods. In contrast, attempts to handcraft knowledge or human-like reasoning into AI systems have repeatedly led to plateaus in progress. - **Historical Evidence:** Examples range from expert systems to symbolic and logic-based AI, where promising early successes did not translate into the kind of long-term breakthroughs seen in machine learning approaches. - **Implications:** Sutton urges researchers to focus on general methods that leverage computation and can benefit from ever-increasing computational power, rather than relying on attempts to explicitly encode human expertise. **Reception and Discussion** - **Controversial:** The essay sparked significant discussion and some debate, with arguments around the role of prior knowledge and the potential for hybrid AI approaches. - **Continued Relevance:** The debate surrounding "The Bitter Lesson" remains vital as the AI field explores increasingly complex tasks and the trade-offs between data-driven methods and knowledge incorporation. # References ```dataview Table title as Title, authors as Authors where contains(authors, "Richard Sutton" ) or contains(subject, "Richard Sutton" ) sort modified desc, authors, title ```