It’s fairly easy to imagine a world ending event science fiction movies have trained us to do so for years and for that –
” Training civilization as we know it might pay the ultimate price ever since the invention.”
- In agriculture we began to flirt with the idea of automating mundane tasks, “Automation” is not only beneficial but is vital in the 21st century global economy our modern societies are highly dependent on it.
- Today the aviation industry supports 65.5 million jobs worldwide and about 3.6% of the total world’s GDP
- A study with 379 orthopedic patients showed a I assisted robotic procedures resulted with 5 times fewer complications compared to surgeons operating alone
- Surgical System that’s being used in 67 countries around the world in the near future the best surgeon featured on the front covers of a Time magazine might be an AI driven robotic surgeon
- The loss of white-collar jobs is going to be a major concern in the near future people today are already losing their blue-collar jobs to AI in the United States more than 5 million manufacturing workers lost their jobs after the year 2000 over 80% of the jobs lost or 4 million jobs were due to automation many truck drivers are losing their jobs due to automated self-driving trucks.
But it’s important to remember.
- 50 million people suffered non-fatal injuries on traffic accidents annually
- Worldwide statistically 3700 people lose their lives every single day on road crashes, as AI algorithms for self-driving vehicles get better this statistic will eventually get close to 0 but with every benefit of automation there seems to be an equal if not greater cost to it.
In the future
- The best mathematician
- The best physicist
- The best scientist, poet, composer, artist…etc
will be an AI at that point it will be called an AGI or Artificial General Intelligence
Perhaps the most aunting fact to contemplate about an AGI having a superior intellect and being better at everything else we do is the possibility that it might not be conscious we still have to solve the hard problem of consciousness.
Table of Contents
What is AGI?
AGI stands for “Artificial General Intelligence.” It refers to a type of artificial intelligence that is able to perform a wide range of tasks, much like a human can. This is different from “narrow AI,” which is designed to perform a specific task, such as recognizing faces or playing chess.
The development of AGI is important because it has the potential to revolutionize the way we live and work. For example, an AGI system could be used to perform tasks that are too dangerous or difficult for humans, such as exploring space or fighting fires. It could also be used to improve healthcare, by developing new treatments and identifying patterns in medical data.
What is Narrow AI?
Narrow AI refers to an artificial intelligence system that is designed to perform a specific task or solve a specific problem. It is also known as “weak AI,” as it lacks the general cognitive abilities of human intelligence.
Examples of narrow AI systems include speech recognition, image recognition, and chatbots.
- Speech recognition systems like Siri and Alexa use narrow AI to understand spoken language and respond to requests.
- Image recognition systems like Google Lens and facial recognition technology also use narrow AI to identify and classify images.
- Chatbots like those used by customer service centers are also an example of narrow AI systems
Narrow AI works by analyzing data and using algorithms to make decisions or carry out specific tasks. It is limited in its ability to generalize beyond the specific task or domain it was designed for.
According to a report by Tractica, the global market for narrow AI systems is expected to reach $59.8 billion by 2025, with industries such as healthcare, finance, and manufacturing leading the way in adoption.
Differences between AGI and narrow AI
| Category | AGI | Narrow AI |
| Definition | Artificial intelligence that aims to replicate human-like general cognitive abilities, including reasoning, learning, problem-solving, and decision-making. | Artificial intelligence that is designed to perform a specific task or solve a specific problem. |
| Scope | Broad and adaptable to new situations and tasks. | Limited to a specific task or domain |
| Learning | Machine learning is essential for an AGI system to learn and adapt. | Machine learning is often used to train narrow AI systems, but it is not required. |
| Examples | Examples of AGI systems are limited, but promising research is being done in areas such as robotics, natural language processing, and computer vision. | Examples of narrow AI systems include speech recognition, image recognition, and chatbots. |
| Challenges | Developing AGI poses significant challenges, including machine learning, safety, and ethical considerations. | Narrow AI has fewer challenges, but still requires training and ongoing maintenance. |
| Market | The global AGI market is expected to reach $10.9 billion by 2025. | The global market for narrow AI systems is expected to reach $59.8 billion by 2025. |
| Potential | AGI has the potential to revolutionize the way we live and work, with applications in fields such as healthcare, space exploration, and more. | Narrow AI has many useful applications but is limited in its ability to generalize beyond the specific task or domain it was designed for. |
According to a report by Allied Market Research, the global AGI market is expected to reach $10.9 billion by 2025, with the healthcare, automotive, and finance industries leading the way in adoption.
Summary
If we ever decide to create a smart machine with a self-preserving algorithm, we would have built the perfect natural psychopath unless we program empathy into it or the value of human life. It would destroy us as a matter of course, the moment it comes online and finds out Apes with nuclear weapons are in charge our future will be in serious jeopardy. That is why the alignment problem, or the AI control problem is perhaps the single most important task for Humanity to get right the first time because we might not ever get the chance to try again.
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