Talk:Restless Souls/Technology: Difference between revisions

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 :: After the obvious slowdown in advancement through scaling, chain of thought (COT) was introduced. It is also known under the marketing term "reasoning [AI]". (See: Gemini 2.0 Flash Thinking and ChatGPT o3, the later one especially [https://techxplore.com/news/2024-12-ai-human-general-intelligence.html trained to cheat … erm ... score high in the ARC-AGI test].)
 :: This pushes ANI somewhat more into direction of AGI with the drawback of slower response times and higher energy costs.-->
-* '''Physical AI''' = Physical Artificial Intelligence. Basically AI used in robots. Since direct training would be dangerous, slow and therefore ineffective, the AI gets pre-trained in a simulation where the robot is represented by a digital twin. By the nature of this construction, multimodal learning (MML) is predestined for robots. Like humans (or other real organisms), AIs should include an "inner world" for better understanding. The use of LLM is optional but seems to be a good design choice for walking further into direction of AGI. <!--Expecting [[wp:Symbolic_artificial_intelligence#Neuro-symbolic_AI:_integrating_neural_and_symbolic_approaches|some kind of hybrid approaches]] within physical AIs later when all other current ''cash cow'' approaches reached their end.--><!--Embodied AI-->
 <!--
 Autonomous AI (alte NAI) vs. Agentic AI
-World model AI
-* https://deepmind.google/blog/genie-3-a-new-frontier-for-world-models/
 -->
+* '''World model''' = World models get trained on multimodal data, especially videos.
+:: These models build an internal world and can '''better understand spacial inputs and forecast physics'''. Therefore they are '''also named predictive intelligence''' and are '''suited for''' ''applications'' like video synthesis, 3D simulations, animations and robotic motion planning therefore '''physical AI'''.
+::: See also:
+:::: https://www.heise.de/news/Weltmodell-statt-LLM-Start-up-von-Yann-LeCun-erhaelt-890-Millionen-Euro-11206213.html
+:::: https://deepmind.google/blog/genie-3-a-new-frontier-for-world-models/
+:::: https://www.nvidia.com/en-us/glossary/world-models/
+* '''Physical AI''' = Physical Artificial Intelligence. Basically AI used in robots.
+:: Since direct training can be dangerous, slow and therefore ineffective, the '''AI gets pre-trained in a simulation''' where the robot is represented by a digital twin. By the nature of this construction, multimodal learning (MML) is predestined for robots. Like humans (or other real organisms), AIs should include an "inner world" for better understanding. The use of LLM is optional but seems to be a good design to improve human's ability to direct such systems. <!--Expecting [[wp:Symbolic_artificial_intelligence#Neuro-symbolic_AI:_integrating_neural_and_symbolic_approaches|some kind of hybrid approaches]] within physical AIs later when all other current ''cash cow'' approaches reached their end.--><!--Embodied AI-->
+::: An older approach for physical AIs was direct training in real environments and therefore learning from real sensory inputs. As this method is slower it will become out of fashion, at least as primary training. '''Real world training will be kept for fine-tuning.'''
+* Symbolic AI, neuro-symbolic AI
+:: Real abstract thinking probably requires also a form a symbolic AI. Since LLM and world models are already available, symbolic AI might be combined at some point with these approaches.
+-->
+<!--* Further hybrid systems, optimization for ultra compact AGI-->
 * '''AGI''' = Artificial General Intelligence, also "strong AI" ('''on par with human thinking''', ''a real AI'' capable to fully self-improve and drive its own development)
 :: In discussions AGI is often equated with super intelligence. The argument is that as soon as AGI is achieved ASI is just around the corner.