One of the most important issue for AI researchers to find the fields of AI application, so is there needing for engaging AI researchers in other fields for application
Unfortunately, most AI researchers are focused on AI algorithms (not applications) and focused on already established "easy" problems like (one and two-Dimensional pattern recognition.) I replied to another post recently, I will restate, the next and most important pursuit in AI is domain specific artificial intelligence and synthetic domain specific language. In other words, focus on what people do either individually or cooperatively. Here is a good example, develop a system that can determine the sequence of steps required to assemble the parts of an automobile. Blocks world algorithms are not sufficient.
There is always a difference between theory and implementation. Both are important in today's societal need. There are many societal problems that need to be better solved through AI techniques. At the same time, theory is equally important for the expert to visualize the solution in the light of AI or its various tools and techniques e.g. be it heuristic and non-deterministic search, computer vision, natural language processing, or even explainable AI and also whether the decision coming from the AI tools and algorithms are fair and ethical. Industry and academia must work in sync to visualize interesting application in the societal context on the ground of theoretical foundation.
The impact of Artificial Intelligence on human lives and the economy has been astonishing. Artificial Intelligence can add about $15.7 trillion to the world economy by 2030. To take that into perspective, that’s about the combined economic output of China and India as of today.
Reference : https://www.upgrad.com/blog/top-challenges-in-artificial-intelligence/
Dear Lamia AbedNoor Muhammed
As we can see AI is changing everything. In my opinion, AI is a tool. you can use this tool in any field. So we are applying AI in the different fields while we are improving the theoretical knowledge about AI.
Top Common Challenges in AI
1. Computing Power
The amount of power these power-hungry algorithms use is a factor keeping most developers away. Machine Learning and Deep Learning are the stepping stones of this Artificial Intelligence, and they demand an ever-increasing number of cores and GPUs to work efficiently. There are various domains where we have ideas and knowledge to implement deep learning frameworks such as asteroid tracking, healthcare deployment, tracing of cosmic bodies, and much more.
They require a supercomputer’s computing power, and yes, supercomputers aren’t cheap. Although, due to the availability of Cloud Computing and parallel processing systems developers work on AI systems more effectively, they come at a price. Not everyone can afford that with an increase in the inflow of unprecedented amounts of data and rapidly increasing complex algorithms.
https://www.upgrad.com/blog/top-challenges-in-artificial-intelligence/
Lamia AbedNoor Muhammed
AI is finding one the recent application in Agriculture Sector. AI is being used by the agriculture industry for health monitoring of crops, Monitored used of pesticides, Monitor soil fertilization, manage food supply chain and manage data for farmers.
https://techwireasia.com/2021/09/ai-applications-will-shape-the-future-of-indias-agriculture-industry/
Collaboration between researchers from different areas is necessary to enhance AI
I agree with Barlin Olivares, but I will again state: we need to make progress in domain specific synthetic languages and domain specific artificial intelligence. Monitoring, diagnosis, prognosis, etc. do not advance domain specific AI, it only shows that monitoring, diagnosis, and prognosis are useful in data rich applications.
Instead of focusing on narrow A.I., i.e., an Artificial Intelligence capable of only doing one thing, I think the challenge that keeps glaring at those involved in the field is the development of Artificial General Intelligence (A.G.I.). Creating a computer program that has all the qualities of human intelligence incorporated in it would be a significant step forward in the field. So far, no real progress is being made on that front.
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