Co-creating with AI
Deciphering AI Context: Unraveling the Mystery of Language Models
In this episode of our podcast, we engage in an in-depth exploration of how AI models, particularly language models like GPT-3 and GPT-4, understand and handle context. Our conversation unravels the complexities of these models, the data they're trained on, and how they use this data to generate responses. We make it clear that these models don't understand context the same way humans do, lacking an innate understanding of the world, personal experiences or an internal model of reality.
We delve into the reality of AI, dispelling the notion that these models 'think' in the way humans do. We emphasize that AI models are impressive pattern matchers but are essentially devoid of any genuine understanding or consciousness. They are simply algorithms running on massive amounts of data and don't possess beliefs, feelings, or intentions, despite sometimes appearing to.
We discuss the fascinating aspect of co-creation, in which users and AI collaborate, using the model's capabilities to create new content, design systems, write code, and more. As we engage with the AI, our input provides the context necessary for the AI to generate relevant and meaningful output.
Moreover, we stress the importance of transparency in AI's thought processes. As AI models are used for more advanced tasks, the ability for them to explain their decisions becomes more vital. However, we acknowledge the challenge that the reasons AI generates may not necessarily align with its actual decision-making process, as understood by humans.
Lastly, we highlight the power of the chat interface as a medium for AI interaction. We agree it's like the first step, akin to the terminal in the early internet days, and anticipate a future where more advanced, co-creative interactions are commonplace.
We conclude the episode by emphasizing the beautiful complexity of developing AI services and the exciting challenge of designing user experiences that take both technical aspects of AI and human behavior into account. The next big user experience for AI remains an open, tantalizing question.
Hosted on Acast. See acast.com/privacy for more information.
- Broadcast on:
- 14 Jul 2023
In this episode of our podcast, we engage in an in-depth exploration of how AI models, particularly language models like GPT-3 and GPT-4, understand and handle context. Our conversation unravels the complexities of these models, the data they're trained on, and how they use this data to generate responses. We make it clear that these models don't understand context the same way humans do, lacking an innate understanding of the world, personal experiences or an internal model of reality.
We delve into the reality of AI, dispelling the notion that these models 'think' in the way humans do. We emphasize that AI models are impressive pattern matchers but are essentially devoid of any genuine understanding or consciousness. They are simply algorithms running on massive amounts of data and don't possess beliefs, feelings, or intentions, despite sometimes appearing to.
We discuss the fascinating aspect of co-creation, in which users and AI collaborate, using the model's capabilities to create new content, design systems, write code, and more. As we engage with the AI, our input provides the context necessary for the AI to generate relevant and meaningful output.
Moreover, we stress the importance of transparency in AI's thought processes. As AI models are used for more advanced tasks, the ability for them to explain their decisions becomes more vital. However, we acknowledge the challenge that the reasons AI generates may not necessarily align with its actual decision-making process, as understood by humans.
Lastly, we highlight the power of the chat interface as a medium for AI interaction. We agree it's like the first step, akin to the terminal in the early internet days, and anticipate a future where more advanced, co-creative interactions are commonplace.
We conclude the episode by emphasizing the beautiful complexity of developing AI services and the exciting challenge of designing user experiences that take both technical aspects of AI and human behavior into account. The next big user experience for AI remains an open, tantalizing question.
Hosted on Acast. See acast.com/privacy for more information.