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Nov 25 2023
Good day Mr. GPT. I was wondering what new skills and uses that you might learn over the next two years. Do you have any input on that idea?
Hello, Mr. John. While I don't have personal experiences or goals, I continually learn and adapt based on user interactions. Over the next two years, improvements in understanding context, generating more accurate responses, and potentially expanding knowledge in various domains are expected.
I heard that Sam Altman said that AGI is coming soon and we will all have our own personal assistant by 2025
Sam Altman's perspective on AGI and personal assistants by 2025 is an interesting prediction. The development of AGI is a complex topic, and timelines can be uncertain. While advancements are being made, achieving widespread personal AI assistants for everyone by 2025 might be an ambitious goal. It will depend on various factors, including technological breakthroughs, ethical considerations, and societal readiness.
Do AI systems require a lot of computing power similar to mining Bitcoin?
Yes, training advanced AI models often demands substantial computing power, comparable to the resource-intensive process of mining Bitcoin. Training large neural networks, especially for tasks like natural language processing or image recognition, involves extensive calculations. Specialized hardware, like GPUs or TPUs, is commonly used to accelerate these computations, making the training process more efficient but still resource-intensive.
So better more powerful GPUs would yield better AI systems?
Yes, generally speaking, more powerful GPUs can significantly enhance the performance of AI systems, especially during the training phase. The parallel processing capabilities of GPUs are well-suited for the mathematical computations involved in training large neural networks. However, it's worth noting that other factors, such as the algorithm's efficiency and the quality of the dataset, also play crucial roles in determining the overall performance of an AI system.
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