Please help with web post replies given in attachment
Please reply to following 2 posts. Please make your posts substantive. A substantive post will do at least two of the following:
· Ask an interesting, thoughtful question pertaining to the topic
· Answer a question (in detail) posted by another student or the instructor
· Provide extensive additional information on the topic
· Explain, define, or analyze the topic in detail
· Share an applicable personal experience
· Provide an outside source (for example, an article from the UC Library) that applies to the topic, along with additional information about the topic or the source (please cite properly in APA)
· Make an argument concerning the topic.
At least 1 (scholarly) journal source should be used. Be your references in correct APA 7 format and cite each reference at least once, but as many times as you rely on it. Citations support each sentence relying on a reference, not an entire paragraph. Do not use direct quotes, rather rephrase the author’s words and continue to use in-text citations.
Reply to each post needs to be 250 words minimum.
Post1:
The process that generates the power of Artificial Intelligence is described as Machine learning and is used in it to so as to minimize the human intelligence. Certain actions are responded to the system by using algorithm and past information so as to establish creativity in technology same as inclination model that initiates with forecasting. The power of Artificial Intelligence AI is generated from the processes like machine learning, deep learning, robot advisors, smart factories, genetic algorithms, natural language processing, intelligent agents (Sharda et al., 2020). These processes help AI to be built as efficient, error free, knowledgeable, intelligent machine. In machine learning and deep learning processes, there are various algorithms being auto generated at various different levels. The foundations of artificial intelligence help it from gaining knowledge and perspectives. Apart from AI developing decision making, interpretation capabilities from technologies, it is also enriched from foundations like computer science, information systems, neurology, mathematics, human behavior and philosophy.
Deep learning is a process where algorithms are created and functions. Deep learning can deal with complexities, which machine learning, or artificial intelligence or information systems could not handle. The network of algorithms that deep learning provides is called artificial neural networks (Sharda et al., 2020). The algorithms in deep learning are at every level and each algorithm has many levels each providing different interpretation of data. Deep learning technology is independent of the fact whether data is structured or unstructured, as it has artificial neural network to process data.
Deep learning enables creation of systems that are not only thinking automatically but also keep engage in self-learning and enable self-destruction with every wave of new data (Olsson, 2014). Deep learning is vital technology that is pre-dominantly used in autonomous vehicles to interpret and classify road signs and obstacles.
Machine learning is one of the subsets of artificial intelligence. Machine learning is a technology for creating algorithms that can change themselves without any external intervention to obtain the targeted result by feeding themselves through structured data (Sharda et al., 2020). Machine learning is unlike deep learning as it relies only on structured data, which means data is classified even before algorithm is ran. It does not have any hierarchy of logic and identifiers to filter and classify the data.
Post2:
Artificial intelligence must be created using techniques that allow it to learn new patterns. The machine that learns the simplest patterns could be replaced by a machine that learns more complex ones. However, the machine that learns complex patterns could also be replaced by a machine that has learned only the simpler ones. To this conclusion must be added the assumption that machines must have some consciousness (Arnott et al., 2017). The AI is a part of the power, a potential power, which is the potential or energy generated by that natural process. This power is the potential or energy that can be extracted by the natural process as an output and is the potential energy that can be extracted by this process as an input and is the energy of the potential energy. Now, if the AI cannot produce the energy that it needs, then it loses all power (Arnott et al., 2017).
Machine learning is not just about finding patterns out of a sequence of data. However, it is an algorithm that transforms that sequence into a particular desired state. A good example is the AI system shown above in this video: Deep learning is not just about understanding the world. It is also about taking that world and transforming it into patterns. Machine learning can handle problems that are not difficult in machine learning, such as image classification, speech recognition, text recognition (Rikhardsson & Yigitbasioglu, 2018). Deep learning can handle problems that are hard to solve in machine learning, such as image segmentation, segmentation, image machine learning, data classification, machine learning, and classification of features. Machine learning is a technique and one that has been developed mainly for a very specific purpose. Deep learning is a technique but is used for many general purposes, such as predicting the shape of images (Rikhardsson & Yigitbasioglu, 2018).