Artificial Intelligence and Intelligent Systems: The future of Human-Machine interaction.

Artificial Intelligence and Intelligent Systems: The future of Human-Machine interaction.

By: Gabriela Sandoval

Nowadays, Artificial Intelligence (AI) and Intelligent Systems are technologies that are already being part of our personal and work routine.

From voice assistants on our smartphones to communication apps, these systems are designed to simulate human intelligence and improve efficiency and productivity.

Cutting-edge AI trends

Among these trends is the use of deep learning algorithms -also known as artificial neural networks-.

These algorithms learn autonomously from large data sets, making them a powerful tool for classifying and analyzing data in different areas.

Another trend is the application of logical and symbolic reasoning techniques to improve the machines' ability to interpret and process complex information.

This is used in areas such as robotics, planning, and automated decision-making, which makes it possible to create intelligent systems with the ability to adapt and learn autonomously.

Human-Machine interaction:

As AI becomes more sophisticated, the level of interaction between humans and machines also increases.

Next-generation AI is being designed to be more intuitive and easy to use, opening up new and more possibilities in areas such as augmented and virtual reality.

Ethics and privacy in AI:

As AI and intelligent systems become more commonplace in our lives, the need to address ethical and privacy issues also arises.

Therefore, it is important to ensure that we use this technology in a responsible and ethical manner, protecting the rights and privacy of individuals and organizations.

In conclusion, AI and Intelligent Systems are technologies that are transforming the way we interact with the world.

As these technologies continue to evolve, we expect to see more innovations and applications in different areas, increasing efficiency and quality at different levels.


References:

  1. LeCun, Y., Bengio, Y. & Hinton, G. (2015) Deep learning. Nature, 521(7553), 436-444. Available at: https://www.nature.com/articles/nature14539
  2. Fikes, R. E., & Nilsson, N. J. (1971). STRIPS: A new approach to the application of theorem proving to problem solving. Artificial Intelligence, 2(3-4), 189-208. Available at: https://www.sciencedirect.com/science/article/pii/000437027190034X
  3. Silver, D., Schrittwieser, J., Simonyan, K., Antonoglou, I., Huang, A., Guez, A., & Tesauro, G. (2018). A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play. Science, 362(6419), 1140-1144. Available at: https://science.sciencemag.org/content/362/6419/1140
  4. Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W.W. Norton & Company.
  5. Russell, S. J. & Norvig, P. (2010) Artificial Intelligence: A Modern Approach. Prentice Hall.

要查看或添加评论,请登录

Symbiotic.com的更多文章

社区洞察

其他会员也浏览了