Computer architecture course

Read the attached document about how AI will transform software development. Then, with your own knowledge of the computer architecture components specialized for AI, assess what additional challenges will necessary in computer architecture when AI is used more for software development.

Write down your thoughts in a short Word document and submit the Word document for additional credit.

AI Changing Computer Science Landscape.pdf AI Takeaway, The Future of Software Development.jpg

this is the url for the first pdf.

https://www.nhaustralia.com.au/documents/AI_report.pdf

Key Takeaways Al Will Improve, Accelerate, And Disrupt The Software Development Life Cycle A combination of Al technologies like advanced machine learning, deep learning, natural language processing, and business rules will have an impact on all steps of the softwaree development life cycle, helping developers build better software faster. Al will disrupt how developers build applications and the nature of the applications they build Al Will Enable Developers To Build Apps That Learn Like Humans Machine learning and deep learning are the core Al technologies that developers should get familiar with to build applications that learn on their own. Devs will focus less on using coded rules to program applications to be smart and instead program algorithms or configure them to self-learn. Devs will integrate algorithms, compose, and source large data sets to train and test such apps Be Prepared For The Challenges And Risks New Al-based systems will sit side by side with traditional programmed software for a long time to come. Integrating new with oldor even new with new won't get any easier. Unrealistic expectations of Al techniques will strengthen the skeptics. Plan for integration skills, look for the right types of problems to solve, and set pragmatic expectations to avoid unattainable science fiction Key Takeaways Al Will Improve, Accelerate, And Disrupt The Software Development Life Cycle A combination of Al technologies like advanced machine learning, deep learning, natural language processing, and business rules will have an impact on all steps of the softwaree development life cycle, helping developers build better software faster. Al will disrupt how developers build applications and the nature of the applications they build Al Will Enable Developers To Build Apps That Learn Like Humans Machine learning and deep learning are the core Al technologies that developers should get familiar with to build applications that learn on their own. Devs will focus less on using coded rules to program applications to be smart and instead program algorithms or configure them to self-learn. Devs will integrate algorithms, compose, and source large data sets to train and test such apps Be Prepared For The Challenges And Risks New Al-based systems will sit side by side with traditional programmed software for a long time to come. Integrating new with oldor even new with new won't get any easier. Unrealistic expectations of Al techniques will strengthen the skeptics. Plan for integration skills, look for the right types of problems to solve, and set pragmatic expectations to avoid unattainable science fiction