^TagGeorge Montanez

^{Type
post

Caitlin Cory
Date
April 9, 2024

Categorized
Artificial Intelligence

Tagged
AGI, AI, Artificial Intelligence, ChatGPT, Computer science, Consciousness, COSM, COSM 2023, Futurism, George Gilder, George Montanez, Technology, William Dembski, YouTube}

COSM 2023 Now on YouTube!

_{COSM 2023 explored the nature of artificial intelligence, as well as its future potential and risks.} _{Caitlin Cory
April 9, 2024

3

Artificial Intelligence}

You can now watch the 2023 COSM Technology Summit on YouTube. If you weren’t able to attend, or perhaps you want to revisit some of your favorite speakers, we are now releasing the second tranche of videos for your enjoyment. Click here to go to the COSM 2023 Playlist on YouTube! COSM 2023 explored the nature of artificial intelligence, as well as its future potential and risks. Stephen Wolfram spoke about his efforts to make the world more computable so that computers can help us understand the world. Afterward, George Gilder and Bob Metcalfe joined him in a fascinating discussion about Turing machines, neural networks, and AI-driven language models. A panel featuring William Dembski, Robert Marks, and George Montanez offered Read More ›

Close-up image of coder typing on computer

^{Type
post

Jonathan Bartlett
Date
October 18, 2021

Categorized
Programming

Tagged
ai-limits, AlphaGo, AlphaZero, DeepMind, George Montanez, Google, No Free Lunch theorems, perpetual motion machines}

The Search for the Universal Algorithm Continues

_{Why does machine learning always seem to be rounding a corner, only to eventually hit a wall?} _{Jonathan Bartlett
October 18, 2021

3

Programming}

DeepMind, a part of Alphabet (i.e., Google), has made many headlines in the past. The biggest was its development of AlphaGo, which used reinforcement learning to beat the number one Go player at the time (2017). DeepMind generalized this into AlphaZero, which is supposedly able to solve any two-player game of perfect information. DeepMind has come back into headlines recently with the attempt to build an AI which can generate any algorithm. While they are starting with map data, the goal is to generalize this and generate any desired algorithm. The search for such a “universal algorithm” has been essentially equivalent to the search for a perpetual motion machine in physics. The allure of both is obvious. In physics, if you Read More ›