For all the devastation it has caused, the Covid-19 pandemic could rightfully claim responsibility for accelerating the adaptation of artificial intelligence (AI) in the business world. Harris Poll, working with Appen, found that 55% of surveyed companies expedited their AI adoption plans in 2020 alone as a result of Covid, while a PwC study reports that 86% of businesses now regard AI as a mainstream technology.
With AI advancing faster than expected, experts in the field are predicting that it is only a matter of time before artificial general intelligence (AGI)—the ability of an intelligent agent to actually understand or learn any intellectual task that a human can perform—emerges.
Numerous surveys indicate that about half of AI experts believe AGI will happen sometime before 2060. Given the speed of developments and the vast amount of money being invested directly into AI research, though, it seems reasonable to ask why attaining AGI isn’t already further along.
As with most complex issues, there is no single answer. One of the biggest roadblocks to AGI emergence, though, is that as soon as some advancement in the technology shows promise, it is immediately pressed into service to achieve practical results.
In the 1980s when the backpropagation algorithm was incorporated into neural networks, for example, networks of just a few hundred artificial neurons were asked to score loan applications. They did this with circuitry using less than 10% of the neural complexity of a snail. By 2015, neural networks with perhaps the mental equivalence of a pigeon were still running algorithms similar to backpropagation and still doing financial analyses.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/08/29/why-artificial-general-intelligence-isnt-further-along/?sh=975ea3e4a255
With AI advancing faster than expected, experts in the field are predicting that it is only a matter of time before artificial general intelligence (AGI)—the ability of an intelligent agent to actually understand or learn any intellectual task that a human can perform—emerges.
Numerous surveys indicate that about half of AI experts believe AGI will happen sometime before 2060. Given the speed of developments and the vast amount of money being invested directly into AI research, though, it seems reasonable to ask why attaining AGI isn’t already further along.
As with most complex issues, there is no single answer. One of the biggest roadblocks to AGI emergence, though, is that as soon as some advancement in the technology shows promise, it is immediately pressed into service to achieve practical results.
In the 1980s when the backpropagation algorithm was incorporated into neural networks, for example, networks of just a few hundred artificial neurons were asked to score loan applications. They did this with circuitry using less than 10% of the neural complexity of a snail. By 2015, neural networks with perhaps the mental equivalence of a pigeon were still running algorithms similar to backpropagation and still doing financial analyses.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/08/29/why-artificial-general-intelligence-isnt-further-along/?sh=975ea3e4a255
