A study comparing GPT-4's creativity showed it outperforms humans in a divergent thinking test. However, the best human ideas still matched or exceeded the chatbot's. The podcast discusses the concept of multimodality in AI and introduces next GPT, an any to any multimodal language model. It also mentions advancements in digital smell and a retinal image model for health diagnosis and development.
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Quick takeaways
AI chatbots outperformed humans in generating creative uses for everyday objects, highlighting the potential of AI in creative thinking.
Next GPT is an advanced multimodal language model that can perceive and generate content from various modalities, paving the way for transformative advancements in AI.
Deep dives
AI Chatbots Outperform Humans in Divergent Thinking Task
In a study on creativity, AI chatbots were found to outperform human participants in generating uncommon and creative uses for everyday objects. While human responses included poor quality ideas, chatbots generally produced more creative responses. However, the best human ideas still matched or surpassed those of the chatbots. The study raises questions about the differences between human and machine creativity and the rapid development of generative AI.
Next Generation LLMs: Any to Any Multimodal Capabilities
Researchers have introduced Next GPT, an end-to-end general-purpose language model capable of accepting and delivering content in arbitrary combinations of text, images, videos, and audios. This advancement in multimodality aims to create a more human-like AI that can perceive inputs and generate outputs from various modalities. The research paper explores the future potential of creating unified AI agents capable of modeling universal modalities, potentially leading to transformative advancements in AI.
AI Advancements in Health: Smell Recognition and Retinal Imaging
AI research has made progress in human-like health and body functions. A neural network capable of smelling and generating descriptions for novel smells has been introduced. Furthermore, Rett Found, a foundational model for ophthalmology, has been developed using self-supervised learning to analyze retinal images for diagnostics and prediction of various health conditions. These advancements have the potential to enhance AI-enabled healthcare and contribute to the development of specialized medical models.
On this research recap, NLW looks at
AI creativity https://www.nature.com/articles/s41598-023-40858-3
BrainLM https://t.co/MUobqXULfb
RETFound retinal model https://www.nature.com/articles/d41586-023-02881-2
Any-to-Any Multimodal https://huggingface.co/papers/2309.05519
AI that can smell: https://twitter.com/DrJimFan/status/1701611251376497046
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