A recent survey of hundreds of AI researchers has raised concerns about the feasibility of achieving human-level artificial intelligence (AI) through the current approach and technology. The survey found that enlarging current AI systems is unlikely to lead to artificial general intelligence (AGI), and that neural networks alone are insufficient to achieve AGI. Researchers are now calling for a more diverse approach to AI development, incorporating symbolic AI and prioritizing safety and control.
Forecast for 6 months: In the next 6 months, we can expect to see a shift in the AI research community towards more diverse approaches to development, with a focus on incorporating symbolic AI and prioritizing safety and control. This may lead to a slowdown in the development of neural networks, but it will also pave the way for more robust and reliable AI systems.
Forecast for 1 year: In the next year, we can expect to see the development of more hybrid AI systems that combine the strengths of neural networks and symbolic AI. These systems will be more robust and reliable, but they will also require more complex and nuanced approaches to development and deployment.
Forecast for 5 years: In the next 5 years, we can expect to see the widespread adoption of hybrid AI systems in various industries, including healthcare, finance, and transportation. These systems will revolutionize the way we live and work, but they will also raise new challenges and concerns about safety, control, and accountability.
Forecast for 10 years: In the next 10 years, we can expect to see the emergence of a new generation of AI systems that are capable of true human-level intelligence. These systems will be the result of decades of research and development, and they will have a profound impact on society, transforming the way we live, work, and interact with each other.
