There is a complicated balance between our expectations for Artificial General Intelligence (AGI) and the computational resources required to achieve it. 💡
In the pursuit of AGI (no one is sure how to define it properly), we envision systems that can perform any intellectual task that a human can (though we still don't know what we humans really can do). This ambition is actually from our desire to create machines that not just mimic but also enhance human cognitive abilities. But, this vision is juxtaposed with the reality of the exponential growth in compute power needed to support such advanced intelligence. 🖥️
Current advancements in machine learning and neural networks have shown us one thing: They are promising progress towards an eventual AGI. Yet, the sheer volume of data processing, energy consumption, and hardware requirements pose CRAZY challenges. We need to stay GREEN and still be faster than ever. 🌱⚙️
This is a very complex path ahead of us and, it's crucial to do collaboration between researchers, engineers, and everyone really, to ensure that the development of AGI aligns with societal core values and environment (we don't want to live in cyberpunk) factors. Only then can we get the true helpfulness factor of an AGI that we can call "made humanity a multiplanetary species". 🌍
Here are some data I think you will find interesting, regarding the stuff we talked about already: