What does the author believe gives ai its value

Reference no: EM133710427

The Economics of AI

The environment for AI economics has changed dramatically during the past year. Particularly in the area of large language models, artificial intelligence has advanced impressively and more quickly than many people, including myself, had anticipated.

Cognitive automation: The environment for AI economics has changed dramatically during the past year. Particularly in the area of large language models, artificial intelligence has advanced impressively and more quickly than many people, including myself, had anticipated. I'd like to give some information, ideas, and viewpoints on the effects of these advancements as we approach 2023.

Exponential growth: The constant advancement of AI is being driven by improvements in hardware, software, and ever-increasing training costs. Due to this, compute times for cutting-edge models have doubled on average every six months - a rate that is significantly faster than Moore's Law and has persisted for almost ten years. Be aware that the cost of training runs for cutting-edge models is rising rapidly as well and is currently in the eight-digit range. An ever-increasing amount of our economy's resources are allocated to computing because it is developing much faster than the broader economy. This signals the start of the AI takeoff!

Economic growth: The constant advancement of AI is being driven by improvements in hardware, software, and ever-increasing training costs. Due to this, compute times for cutting-edge models have doubled on average every six months - a rate that is significantly faster than Moore's Law and has persisted for almost ten years. Be aware that the cost of training runs for cutting-edge models is rising rapidly as well and is currently in the eight-digit range. An ever-increasing amount of our economy's resources are allocated to computing because it is developing much faster than the broader economy. This signals the start of the AI takeoff!

Growing public awareness: When OpenAI's ChatGPT was made available in November, it dramatically raised public awareness of the capabilities of huge language models and gave the public a hands-on experience with the power of cutting-edge AI. Technically, the system is only one of several substantial language models that have shown a rising level of general intelligence that has been customized (GPT3.5). However, it represents yet another small advance in artificial general intelligence (AGI), or the development of AI systems capable of carrying out all cognitive tasks that humans are capable of. According to rumors, the upcoming generation of language models will have much higher general intelligence. Try it out if you haven't already to see what the personal assistants of the future will resemble.

Expanding governance: The Overton window, or the range of theories and policy alternatives that people consider appropriate to examine, is fast growing as discussions about AGI become more widespread. As a result, AGI governance will become a hot topic in the media. How AGI will interact with current governance frameworks and how AGI itself should be controlled are both crucial topics. These themes are relevant to economists and offer much potential for ground-breaking research papers and dissertations. Our Oxford Handbook of AI Governance will significantly contribute when it is released in early 2023; several chapters are now available online.

Future of work: Our civilization must adapt to a world where most human labor is redundant in the medium run. And contrary to popular belief, this might occur this decade or sooner. Policies like a universal basic income are becoming increasingly urgent and tempting due to cognitive automation. I recently released a paper on the subject to understand better how to prepare for this nonexistent future of employment. Additionally, if mental effort becomes unnecessary, we must fundamentally reexamine the goal of schooling.

Life after cognitive automation: Finally, even though it is crunch time for research on controlling AGI, I am also taking some time to think about what life would be like when cognitive automation has rendered me unemployed as an economist and to prepare myself for the situation mentally.

(Adapted from Anton Korinek's article The Economics of AI)

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What does the author believe gives AI its value?
What does the article say is key to preventing widespread

Reference no: EM133710427

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