wk-7

2

Artificial intelligence

Student’s name

Institution affiliation

Date

Artificial intelligence

Artificial intelligence is the process of imitation of human intelligence on machines. Here, devices can conduct functions by internally assessing the nature of the environment For instance, a machine that measures room temperature and regulates it. The process that is responsible for generating the powers of artificial intelligence is the Internet of things (IoT). The Internet of things is a network of physical objects with inbuilt sensors and can communicate with each other (Miikkulainen et al., 2018). The Internet of things has dramatically facilitated the power of artificial intelligence in that it has provided a platform where artificial intelligence can be practiced and improved over time. Through the Internet of things, imitation of human intelligence by machines is displayed with the help of technology such as sensors. The Internet of things is categorized as being a large volume of data. This immense volume of data is the one responsible for enabling object automation of tasks. Computing power and advanced algorithms are also responsible for generating the power of artificial intelligence. Automatic computers have been specifically created to ensure that they boost human abilities in artificial intelligence. On the other hand, Neutral networks have been improved to provide that they increase the power of artificial intelligence and analyze important information by using multiple layers.

Machine learning is a process that uses a set of rules to conduct an extensive analysis of data, learn from it, make an evaluation, and a decision based on the information it has obtained from the data. On the other hand, deep learning is when structures algorithms in layers to develop an artificial neural network that can learn and make intelligent and informed decisions (Reese, 2017). Neutral networks have been inspired by neutral biological systems and have animal brains. This feature is about collecting units that are connected or nodes called artificial neurons.

References 

Miikkulainen, R., Iscoe, N., Shagrin, A., Rapp, R., Nazari, S., McGrath, P., ... & Epstein, J. (2018, January). Sentient Ascend: AI-Based Massively Multivariate Conversion Rate Optimization. In AAAI (pp. 7696-7703).

https://www.evolv.ai/wp-content/uploads/2019/03/Sentient-Ascend-AI-Based-Massively-Multivariate-Conversion-Rate-Optimization.pdf

Reese, H. (2017). Understanding the differences between AI, machine learning, and deep learning. URL: https://www . techrepublic. com/article/understandingthedifferencesbetweenaimachine learninganddeeplearning.

http://deeplearning.lipingyang.org/wp-content/uploads/2016/11/Understanding-the-differences-between-AI-machine-learning-and-deep-learning-TechRepublic.pdf