Getting Ready for AGI - Deepstash
Getting Ready for AGI

Getting Ready for AGI

Curated from: trajectorymatrix.substack.com

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What is AGI?

What is AGI?

AGI, otherwise known as strong AI, full AI, or human-level AI , is a type of AI that can perform any task that a human can. It is not limited by specific domains or skills, but can learn and adapt to any situation. AGI systems are designed to be lifelong learners, constantly acquiring new knowledge and skills. They can reason, understand complex concepts, and apply their understanding to different contexts.

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Expert Opinions

We’re still far from reaching a point where AI tools can understand, communicate, and act with the same nuance and sensitivity of a human. The majority of the experts think it could be within years or decades, while others say it might take a century or even longer. A few even think we might never achieve it.

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Cornerstones of AGI Development

Cornerstones of AGI Development

The development of AGI relies on several key factors:

  1. Advancements in algorithms are crucial in shaping how AGI systems process and make decisions.
  2. The availability of powerful computing units, like GPUs, is necessary to handle the immense computational demands of AGI.
  3. The growth of data volume, supported by technologies like 5G, provides key resources for effectively training AGI systems.
  4. Foundational technologies like machine learning and neural networks enable AGI systems to learn from data and adapt to new situations.

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Can the Public Afford AGI Usage?

Can the Public Afford AGI Usage?

Artificial General Intelligence (AGI) is possible, but its usage by the public is still far away.

  • Building AGI can cost millions to billions of dollars, making it feasible only for governments and affluent groups.
  • For example, a GPT-3.5 model costing $0.002 per 1K tokens can cost $200 per hour if 100,000 tokens are processed in an hour.
  • However, AGI requires much more computing power, making it even more expensive.
  • Assuming AGI needs 100 petaflops, it could cost anywhere from $3 million to $30 million for just one hour.

So for now, NO

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