Keep track of who owes what with a machine learning tool that allows each person in a flat to join a group, create an account and input expenses.
Simulation is a useful tool in machine learning, but in the long run, machines that learn from real data will improve perpetually, as relying solely on simulated data can create a bottleneck. Challenges in reinforcement learning, such as the need to create realistic simulations, become more apparent when running programs in the real world.
To optimize machine learning or reinforcement learning, an objective function or loss function is key. The objective function for the brain is simple, to keep the body temperature the same, and it uses simple terms like dopamine to define reward predictions.
This podcast talks about how machine learning and chat APIs, like GPT-3, can be used to analyze gut biome related data, particularly in the context of analyzing people's guts for products like super gut.
This podcast discusses the use of machine learning to optimize the charging process of electric cars, in order to maximize profits for ride sharing drivers.
Bob and Mark discuss the difference between machine learning and artificial intelligence, and the common mistake of conflating the two buzzwords.
