Technological development makes our lives easier, both on a personal and business level. However, those in charge of creating technological tools also need others that make their work easier. These are known as framework , which translates as framework or work environment, and is a template that serves as a basis for the organization and development of software. In this article, we tell you what it consists of, what its uses are and its most well-known types.

What is a framework and what is it made of?

A framework is, in the field of computing, a conceptual structure that provides a set of tools, libraries and design patterns to facilitate software development. In other words, they are frameworks that function as a predefined skeleton, and on which an application or software can be built.

As far as its components are concerned, they include reusable code libraries, predefined modules, file and directory organization rules, design patterns, and coding conventions. They are generally used by profiles such as programmers, developers, full stack developers of the custom software development company since they allow them to speed up their work, reduce errors by maintaining the coherence and structure of the code, and favor a work environment that is more collaborative.

Its use extends to other areas, such as the Data Governance Framework , which refers to the compilation of rules, processes and functions related to privacy and regulations in the use of data at the enterprise level.

The use of frameworks in artificial intelligence

In the field of artificial intelligence (AI), a work environment also has multiple applications. For example, they are useful for providing specific tools and functionality for developing AI models. These frameworks , such as TensorFlow, PyTorch or Keras, have a multitude of predefined functions for common tasks in artificial intelligence, such as data processing, building and training models, and performance evaluation.

Over the years, frameworks have also had to adapt to software development services itself. This involves the integration of different techniques and algorithms, which are capable of optimizing performance and efficiency, and improving usability and accessibility for developers. In fact, there are already some specialized in specific applications, such as reinforced machine learning or natural language processing.

How is a framework different from a library?

The terms framework and library are often confused in software development, but although they are related, they are different from each other. The first provides a complete and predefined structure for application development, while a library is a set of functions, classes and methods that are coded in a programming language, and that have an interface defined for a specific task.

Flow control is where the difference is best seen. In a framework , it is the framework that controls the execution flow of the application. That is, it determines how the developer's code is structured and organized. In contrast, in a library, it is the custom software development company who has full control of the execution flow and simply uses the library's functions as needed. Additionally, the framework has a broader and more restrictive structure, and the library is more flexible and used for more specific tasks within an application.

Despite these differences, both concepts are closely related, since the framework usually makes use of libraries to provide specific functionalities.

Types of framework most used in artificial intelligence

As we explained, a framework serves as a basis for the creation of programs, libraries and interpreted language, among other purposes. But there is not just one, but there are several types that adapt to the needs of the project you want to carry out. To choose the most suitable one, you must observe the characteristics of said project and identify both the general needs and the specific needs of what you want to do.

Below you can find some examples.

Open Source

Open Source frameworks are open source software . That is, the source code that composes it is published under a free use license, which allows anyone who uses it to make modifications without requiring any type of copyright license.

In this way, any developer can use Open Source code for their specific needs. But also reduce it, modify it and improve it. As they are based on the collaborative methodology, they are constantly updated and new improved uses are developed. An application based on the same concept is Open Source Intelligence (OSINT) .

There are several of the most popular open source software today, among which we can highlight:

• TensorFlow. Open source platform developed by Google that is primarily used for the development and deployment of machine learning models and neural networks. It is one of the most popular and widely used tools in the field of artificial intelligence and machine learning.

The latter can be trained and deployed on different devices thanks to the different tools, libraries and resources, but also to the flexibility and scalability it has. Additionally, TensorFlow is optimized to take full advantage of the processing power of graphics processing units (GPUs) and tensor processing units (TPUs).

• Apache SystemML. Open source machine learning platform designed to simplify and scale the process of implementing algorithms from programming languages ​​such as R or Python, which are used in data analysis on small data sets, to Big Data environments such as Scala. It offers a flexible interface where users write and run machine learning algorithms in distributed environments. This facilitates the processing of large volumes of data with scalability.
• Caffe is a deep learning framework that focuses on providing a flexible and efficient environment for developing machine learning models. It was created by Berkeley AI Research and its collaborators, and stands out for its focus on expression, speed and modularity. Due to these characteristics, it is interesting for computer vision and image recognition applications.
• Torch is an open source learning library that stands out for its versatility and efficiency. It is based on the Lua programming language, and covers different algorithms for deep learning. For ease of performance, it uses LuaJIT for scripting and an underlying C implementation.

Gemini

Gemini is the replacement for Google BARD or Biomedical Analysis, Resources, and Discovery. It is a platform developed by Google to accelerate research in the biomedical field, and whose operation was very similar to ChatGPT. The reason for the change is due to deeper development, such as the native app for Android, which will allow you to write, speak and use images to ask the AI ​​assistant for help; or Gemini Advanced, which is the advanced model and will now be paid.

Another Gemini application is its voice assistant, which will now be the replacement for the one Google used. However, the operation is similar, with the option of saying "Hey Google" or using the power button pressed.

Microsoft Azure

Microsoft Azure is a cloud services platform offered by Microsoft. It covers different computing, storage, networking, database and analysis services, among others. It is present in more than 60 countries, and allows companies to build, deploy and manage applications and services quickly and scalably. All this without having to invest in local physical infrastructure.

Regarding their applications, customers can use Azure services to host their web pages, develop and deploy applications, store and process large volumes of data or implement artificial intelligence solutions. It also has several deployment models, such as public, private and hybrid cloud. Focuses on continuous innovation and scalability.

Amazon AI

Amazon AI , or Amazon Web Services (AWS) Artificial Intelligence, is a set of artificial intelligence services and tools offered by Amazon Web Services. They integrate AI capabilities into their applications by using the framework provided by AWS. Its services include Amazon SageMaker, which simplifies the process of training and deploying machine learning models; Amazon Rekognition, with image and video recognition capabilities; Amazon Comprehend, for text analysis and information extraction; and Amazon Polly, which converts text to speech naturally.

These services are designed to be highly scalable and cost-effective. That is, any company, regardless of its size, can take advantage of artificial intelligence capabilities without the need to invest in infrastructure. Amazon AI improves operational efficiency, delivers more personalized user experiences, and develops innovative new applications with built-in artificial intelligence capabilities.