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@hardmaru

Sakana AI Develops Foundation Models with High-Resolution Ukiyo-e Artwork

By

@hardmaru

–

22 July 2024 3h48

In collaboration with Ritsumeikan University Art Research Center (@RitsARC) and ROIS-DS Center for Open Data in the Humanities (@rois_codh), Sakana AI is proud to develop foundation models using 🇯🇵 national datasets containing the highest quality, high-resolution Ukiyo-e artwork. https://t.co/fyD8ay1bWb
— hardmaru (@hardmaru) 22 juillet 2024

In collaboration with Ritsumeikan University Art Research Center (
@RitsARC
) and ROIS-DS Center for Open Data in the Humanities (
@rois_codh
), Sakana AI is proud to develop foundation models using national datasets containing the highest quality, high-resolution Ukiyo-e artwork.

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22 July 2024
LLMs Face Hard Problems of Messy Reality Like Robotics

By

@hardmaru

–

13 July 2024 18h00

Enjoyed @AlexIrpan
’s “The Tragedies of Reality Are Coming for You” The hard problems of robotics are not unique to robotics. In fact, as LLMs start to actually work and become widespread, they encounter more problems from the “messy reality” of the world.

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13 July 2024
MIT Press Releases Textbook on Artificial General Intelligence

By

@hardmaru

–

11 July 2024 9h14

Finally there is a textbook that explains AGI https://
mitpress.mit.edu/9780262549349/
artificial-general-intelligence/
…

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11 July 2024
Neural Developmental Programs Research Advances from Grow-AI Team

By

@hardmaru

–

05 July 2024 10h06

Builds on the earlier line of work on Neural Developmental Programs (NDPs) from the Grow-AI team:https://t.co/smyJf6oBTk
— hardmaru (@hardmaru) 5 juillet 2024

Builds on the earlier line of work on Neural Developmental Programs (NDPs) from the Grow-AI team:

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5 July 2024
Self-Assembling Neural Networks Growing Through Learning Experiences

By

@hardmaru

–

05 July 2024 10h05

Biological neural networks grow and develop over a lifetime of learning, and so should artificial neural networks! Here, they showed that a ‘self-assembling’ network can grow, and learn from experiences in different environments starting from randomly connected or empty networks. https://t.co/v6bcu10den
— hardmaru (@hardmaru) 5 juillet 2024

Biological neural networks grow and develop over a lifetime of learning, and so should artificial neural networks! Here, they showed that a ‘self-assembling’ network can grow, and learn from experiences in different environments starting from randomly connected or empty networks.

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5 July 2024
AI Tour de France: A Proposed Concept

By

@hardmaru

–

02 July 2024 8h40

How about an AI Tour de France? 🚴‍♂️ pic.twitter.com/4DsnfQrEZE
— hardmaru (@hardmaru) 2 juillet 2024

How about an AI Tour de France?

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2 July 2024
Slimebot Volleyball: 3D Multi-Agent RL Environment on SlimeVolleyGym

By

@hardmaru

–

24 June 2024 3h17

Slimebot Volleyball is a 3D version of Neural Slime Volleyball. The game is implemented on top of SlimeVolleyGym. The major difference is the additional z-axis, and 2-vs-2 multi-agent play, which makes training more challenging for RL algorithms like PPO.https://t.co/cyL5l8DI8M pic.twitter.com/vITaGNu0Ph
— hardmaru (@hardmaru) 24 juin 2024

Slimebot Volleyball is a 3D version of Neural Slime Volleyball. The game is implemented on top of SlimeVolleyGym. The major difference is the additional z-axis, and 2-vs-2 multi-agent play, which makes training more challenging for RL algorithms like PPO. https://
github.com/jbakams/slimeb
ot-volleyball
…

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24 June 2024
Research Paper on Psychology and Linguistics Discussion

By

@hardmaru

–

22 June 2024 8h54

Link to PDF: https://
gwern.net/doc/psychology
/linguistics/2024-fedorenko.pdf
… Discussion: https://
news.ycombinator.com/item?id=407561
76
…

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22 June 2024
Language as Communication Tool Rather Than Thought

By

@hardmaru

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22 June 2024 8h52

Language is primarily a tool for communication rather than thought https://
nature.com/articles/s4158
6-024-07522-w
… “Language is a defining characteristic of our species, but the function, or functions, that it serves has been debated for centuries. Here we bring recent evidence from neuroscience and

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22 June 2024
Base Models Produce More Creative Outputs Than Fine-Tuned Versions

By

@hardmaru

–

17 June 2024 7h51

Just let LLMs be LLMs I notice the same sort of thing in image generation models too. Usually the base model, while less aesthetically pleasing, produce more interesting and creative images. And over time, this ‘artificial aesthetic’ loses its charm as outputs become boring.

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17 June 2024

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