Summary of Cognition Is All You Need — the Next Layer Of Ai Above Large Language Models, by Nova Spivack et al.
Cognition is All You Need – The Next Layer of AI Above Large Language Models
by Nova Spivack, Sam Douglas, Michelle Crames, Tim Connors
First submitted to arxiv on: 4 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Multiagent Systems (cs.MA)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This position paper proposes Cognitive AI, a framework for implementing programmatically defined neuro-symbolic cognition above and outside of large language models. The authors argue that current chatbots, powered by these models, are limited in their ability to perform complex multi-step problem solving and reasoning due to the lack of actual cognitive processes. They propose a dual-layer functional architecture for Cognitive AI as a roadmap for AI systems that can tackle complex knowledge work. This framework is seen as a necessary precursor for achieving higher forms of AI, such as AGI. The authors claim that AGI cannot be achieved solely through probabilistic approaches. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Cognitive AI is a new approach to artificial intelligence (AI) that helps computers think more like humans do. Right now, many AI systems are limited in their ability to solve complex problems and reason about what they know. This is because they don’t actually understand or think about the information they process. Instead, they rely on statistical patterns and guesses. The authors of this paper propose a new way for computers to think that combines symbolic representations (like words) with neural networks (like the human brain). They believe this approach will enable AI systems to perform complex tasks, like solving multi-step problems, which are currently out of their reach. |
