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SOME of the technologies that are commonly used in machine learning and AI development

NordenBladet – The backend of companies that develop and promote friendly AI in the form of advanced machine learning models are likely made up of a combination of several different technologies and architectures, including:

Cloud computing: Machine learning models are trained and run on large-scale cloud computing infrastructure, such as Amazon Web Services* (AWS) or Google Cloud Platform** (GCP), to ensure that they have access to the necessary computational resources to function.

Distributed computing: Machine learning models are distributed across multiple machines, which allows them to take advantage of parallel processing to speed up training and inference.

Machine learning frameworks: Most likely they use popular machine learning frameworks such as TensorFlow*** or PyTorch**** to build and run their models. These frameworks provide a set of pre-built tools and libraries that can be used to train and run machine learning models.

Neural networks: Machine learning are likely based on neural networks, which are a type of machine learning model that is inspired by the structure and function of the human brain. Neural networks can be trained to perform a wide range of tasks, including image recognition, natural language processing, and more.

Large data sets: Machine learning likely have access to large data sets that are used to train their models. The more data a model has access to, the better it can perform.


What is a machine learning model?

A machine learning model is a file that has been trained to recognize certain types of patterns. You train a model over a set of data, providing it an algorithm that it can use to reason over and learn from those data.

What is artificial intelligence (AI) development?
Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.

The definition of an AI developer is pretty self-explanatory: they develop the artificial intelligence software and applications that a particular business might use. They program systems that will change to suit the business’s needs based on the data collected and analyzed.

What is a Neural Network?
A neural network is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. In this sense, neural networks refer to systems of neurons, either organic or artificial in nature.

What is an expert system?
In artificial intelligence, an expert system is a computer system emulating the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if–then rules rather than through conventional procedural code.
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* AWS (Amazon Web Services) is a comprehensive, evolving cloud computing platform provided by Amazon that includes a mixture of infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS) and packaged-software-as-a-service (SaaS) offerings.

** Google Cloud Platform, offered by Google, is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search, Gmail, Google Drive, and YouTube.

*** TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks.

****PyTorch is a machine learning framework based on the Torch library, used for applications such as computer vision and natural language processing, originally developed by Meta AI and now part of the Linux Foundation umbrella. It is free and open-source software released under the modified BSD license.

Featured image: Unsplash

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