Ubik

I propose the creation of the DeTuring Award. It will be granted to people who are consistently trying (and failing) to deter society from using computer technology by scaring everyone with imaginary risks. As the Turing Award is the Nobel Prize of computing, the DeTuring Award is the IgNobel Prize of computing.

A panel on AI at the @wef in Davos earlier today. With @AndrewYNg, @DaphneKoller, @kaifulee, @aidangomez, and me, masterfully moderated by Nick Thompson from The Atlantic.

A new family of antibiotics discovered with graph deep learning.

Technologies that empower humans by increasing communication, knowledge, and effective intelligence always cause opposition from people, governments, or institutions who want control and fear other humans. The arguments against open source AI today mirror older arguments against social media, the internet, printers, the PC, photocopiers, public education, the printing press,.... Historically, those who have banned or limited access to these things have not been believers in democracy.

Yes, I do. LLMs produce their answers with a fixed amount of computation per token. There is no way for them to devote more (potentially unlimited) time and effort to solving difficult problems. This is very much akin to the human fast and subconscious "System 1" decision process. True reasoning and planning would allow the system to search for a solution, using a potentially unlimited unlimited time for it. This iterative inference process is more akin to the human deliberate and conscious "System 2". This is what allows humans and many animals to find new solutions to new problems in new situations. Some AI systems have planning abilities, namely those that play games or control robots. Game playing AI systems such as AlphaGo, AlphaZero, Libratus (poker), and Cicero (Diplomacy) have planning abilities. These systems are still fairly limited in their planning abilities, compared to animals and humans. To have more general planning abilities, an AI system would need to possess a *world model*, i.e. a subsystem that can predict the consequences of an action sequence: given the state of the world at time t, and an imagined action I could take, what would be the set of plausible states of the world at time t+1. With a world model, a system can plan a sequence of action so as to fulfill an objective. How to build and train such world models is still a largely unsolved problem. Even more complex is how to decompose a complex objective into a sequence of sub-objectives. This would enable hierarchical planning, something that humans and many animals can do effortlessly but is still completely out of reach of AI systems.

It's not an assumption. Reasoning, as I define it, is simply not doable by a system that produces a finite number of tokens, each of which is produced by a neural net with a fixed number of layers.