Understanding the Differences Between AI, ML And DL

1. Understanding the Differences Between AI, ML And DL

2. Popular terms we often hear nowadays, artificial intelligence, machine learning and deep learning are all closely related, that much is true, but there are some important differences between them. Helping companies streamline their processes and make their systems more efficient, let’s look at the differences in a little more detail: Artificial intelligence: Enabling machines to think without the need for any input from humans, this broad area of computer science adds human intelligence to machines, and its systems are classified by how well they can replicate human behaviors, what hardware they use, how can they be used and the theory of mind. All AI systems fall into one of the following three categories:

3. Artificial narrow intelligence • Artificial general intelligence • Artificial super intelligence Machine learning: Using statistical algorithms to build systems that can learn automatically and improve from experiences without being programmed, machine learning is best thought of as a subset of artificial intelligence.

4. Search engines such as Google and Yahoo, voice assistants like Alexa, and recommendation systems on Netflix, are all examples of machine learning that many of us use every day, and without really giving the technology behind it a second thought. Machine learning works by training algorithms with the input of big data, and enabling them to learn more about the information being processed. The algorithms used in machine learning are generally placed into the following three categories:

5. Supervised • Unsupervised • Reinforcement learning Deep learning: Inspired by the way a human brain filters information, deep learning is a technique that uses machine learning to learn from examples. Processing information in a similar way to the human brain, it helps filter input data from a computer model, to better predict and classify information.

6. Because its processes mimic human thoughts, its technology is typically used in applications commonly used by humans, such as driverless cars, in which deep learning enables the vehicle to recognize road signs and know the difference between certain obstacles, such as a person or a lamppost. Using neural network architectures, deep learning methods are sometimes known as deep neural networks. There are three fundamental network architectures involved in deep learning, as shown below:

7. Convolutional neural networks • Recurrent neural networks • Recursive neural networks Many industries have already begun integrating machine learning technology into all stages of their production, and with more and more technology driven and powered by AI, businesses in all sectors can streamline their processes, predict problems before they occur, serve their customers better, and ultimately, give their bottom lines a much-needed boost. To know more about how AI, machine and deep learning could help your business, reach out to a reputable tech company today, who can help bring your company in line with others who are already embracing its many benefits.

8. Intelliprise commits to empower organizations with cutting edge solutions. Intelliprise LLC is based in Indianapolis, IN and offers holistic Enterprise solutions, technologies, and systems integration for over 200 companies worldwide, ranging from startups to Fortune 1000 companies. Many of the largest companies outsource their business needs to Intelliprise, including leaders in retail, travel, e-commerce, education, hospitality, manufacturing, consumer goods, logistics, SCM, lifestyle, non-profits, and BFSI.