What LLM models can or can't do – Society of Catholic Scientists [video]
The video discusses large language models, AI reactions, the Eliza effect, and AI history. It explores artificial general intelligence potential, Eliza program creation, pre-programmed AI responses, and IBM's Deep Blue defeating Gary Kasparov in 1997.
Read original article
The YouTube video delves into various aspects related to large language models, AI reactions, the Eliza effect, and the history of AI responses. It highlights the potential for artificial general intelligence and touches upon the creation of the Eliza program. The video explains how AI systems employ pre-programmed responses linked to specific keywords to mimic human conversation, resulting in the AI effect. Additionally, it references IBM's Deep Blue defeating chess champion Gary Kasparov in 1997 as a pivotal moment showcasing the evolving perceptions of AI capabilities.
Related
Francois Chollet – LLMs won't lead to AGI – $1M Prize to find solution [video]
The video discusses limitations of large language models in AI, emphasizing genuine understanding and problem-solving skills. A prize incentivizes AI systems showcasing these abilities. Adaptability and knowledge acquisition are highlighted as crucial for true intelligence.
Prompt Injections in the Wild. Exploiting LLM Agents – Hitcon 2023 [video]
The video explores vulnerabilities in machine learning models, particularly GPT, emphasizing the importance of understanding and addressing adversarial attacks. Effective prompt engineering is crucial for engaging with AI models to prevent security risks.
How to Raise Your Artificial Intelligence: A Conversation
Alison Gopnik and Melanie Mitchell discuss AI complexities, emphasizing limitations of large language models (LLMs). They stress the importance of active engagement with the world for AI to develop conceptual understanding and reasoning abilities.
The A.I. Bubble is Bursting with Ed Zitron [video]
The YouTube video discusses the stagnation in AI progress despite significant investments by tech giants. Adam Conover critiques large language models, questions new AI products' efficacy, and highlights tech companies prioritizing growth over user experience.
The moment we stopped understanding AI [AlexNet] [video]
The video discusses high-dimensional embedding spaces in AI models like AlexNet and Chat GPT. It explains AlexNet's convolutional blocks for image analysis and Chat GPT's transformer use for responses, emphasizing AI model evolution and challenges in visualizing activations.
0 commentsRelated
Francois Chollet – LLMs won't lead to AGI – $1M Prize to find solution [video]
The video discusses limitations of large language models in AI, emphasizing genuine understanding and problem-solving skills. A prize incentivizes AI systems showcasing these abilities. Adaptability and knowledge acquisition are highlighted as crucial for true intelligence.
Prompt Injections in the Wild. Exploiting LLM Agents – Hitcon 2023 [video]
The video explores vulnerabilities in machine learning models, particularly GPT, emphasizing the importance of understanding and addressing adversarial attacks. Effective prompt engineering is crucial for engaging with AI models to prevent security risks.
How to Raise Your Artificial Intelligence: A Conversation
Alison Gopnik and Melanie Mitchell discuss AI complexities, emphasizing limitations of large language models (LLMs). They stress the importance of active engagement with the world for AI to develop conceptual understanding and reasoning abilities.
The A.I. Bubble is Bursting with Ed Zitron [video]
The YouTube video discusses the stagnation in AI progress despite significant investments by tech giants. Adam Conover critiques large language models, questions new AI products' efficacy, and highlights tech companies prioritizing growth over user experience.
The moment we stopped understanding AI [AlexNet] [video]
The video discusses high-dimensional embedding spaces in AI models like AlexNet and Chat GPT. It explains AlexNet's convolutional blocks for image analysis and Chat GPT's transformer use for responses, emphasizing AI model evolution and challenges in visualizing activations.