Best Five AI Frameworks to Explore in 2024

Afifa Shafi
June 1, 2023
min read
January 9, 2024
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Powerful toolsets for developers, AI frameworks enable streamlined AI development, customization and innovation. Discover the top 5 AI frameworks of 2024
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Have you ever wondered how modern technology (think self-driving cars, voice assistants and picture recognition) operate so well? It's because they leverage Artificial Intelligence (AI) frameworks.

AI frameworks are valuable tools for solving complex problems. A wide variety of businesses—from tech to education to finance—use AI to optimize their operations.

And business is booming. The AI market is expected to reach a stunning 407 billion dollars by 2027, representing a significant increase from its predicted 86.9 billion dollar revenue in 2022.

However, with so many AI frameworks to select from, it can be hard to decide which one to leverage for your needs. We'll explore the various frameworks and how they might be used to tackle real-world challenges.

Here are 5 popular AI framework software vendors to note in 2023:

Explore the top 5 AI frameworks in 2023

  1. Scribe: Automatically creates complete workflows with text and screenshots
  2. Caffe: Great for industrial operations and search initiatives
  3. Microsoft CNTK: Supports strong integrations 
  4. PyTorch: Best for Python experts but also supports C++ for non-Python users
  5. TensorFlow: Supports several programming languages, including Python and JavaScript 

Let’s learn more about artificial intelligence frameworks that can help you fast-track your business growth.

Understanding AI frameworks

An AI framework is a collection of tools and best practices that offer an organized approach to developing and implementing AI applications.

They're like required building blocks, blueprints and standards for creating a sturdy and trustworthy structure.

Think of an AI framework as a cookbook; it offers a set of tools (your ingredients) for preprocessing data, engineering features, choosing a model and tuning hyperparameters. Then it shows you how to use these tools (the recipe) to create a predictive model.

Different types of AI frameworks you should know about

Artificial intelligence frameworks are a set of pre-built algorithms, functions and libraries that can be used to create and deploy AI (Artificial Intelligence) and ML (Machine Learning) models.

Predictive analytics, speech and picture recognition, and natural language processing are a few of the most common examples of these AI systems.

AI frameworks make creation and implementation processes for AI and ML applications more effective for developers.

By eliminating the need to write algorithms and libraries from scratch, AI frameworks let developers focus on the high-level elements of applications, like data preparation and model architecture.

Key features to look for in AI frameworks

Here are the top 6 features of AI framework software:

1. Data preprocessing 

Most AI frameworks provide tools for preparing data for machine learning models, including cleaning, standardizing and preparation. Activities like feature engineering, data translation and data validation fall under this category.

2. Training & validation 

AI frameworks can be used for verifying and training machine learning models. Developers can also use tools for tracking and enhancing model performance.

3. Model selection & customization

AI frameworks frequently include various pre-built models for tasks, including image recognition, natural language processing and predictive analytics. You can also use them for modifying and perfecting these models to match certain use cases.

4. Documentation & support

Find the tutorials, documentation and support materials to you need to get up to speed quickly and resolve any potential problems.

5. Deployment and integration

Need to implement a machine learning model in production settings and integrate it with other software systems after it's been trained and validated? AI frameworks provides these tools to developers.

6. Flexibility and customization

Different AI frameworks are made to support various architectures, programming languages and development processes. While some frameworks may be more adaptable and versatile, others may better suit specific applications or sectors.

Why you need to use AI frameworks for your projects

AI frameworks make it easier to build and train intelligent computer systems. They offer a wide range of tools, libraries and APIs that can be customized for project requirements.

You can use them to streamline the process of building and deploying AI models, speeding up the development process.

AI framework software systems provide an automatic ‘information-mining’ tool for individuals and organizations with data analytics, machine learning and archiving capabilities, optimizing the development process.

AI framework software systems help organizations preserve, build and repurpose their digital wealth, providing stakeholders with a robust resource hub containing the latest trends, news and technologies to optimize development and overall business performance. — Simon Bacher, Creator, Ling App

Top 5 AI frameworks to consider in 2023

1.‎ Scribe 

Capterra Rating: 5 out of 5 Stars

Scribe Pricing: Starting from $29.00/month; Free Trial Available

Scribe Overview: Features and Benefits

Scribe AI is the best solution for automating the documentation process. As an AI platform, Scribe uses machine learning algorithms to find patterns and extract critical information from human processes. This enables the program to create step-by-step documentation processes that are accurate and tailored for optimal efficiency.

Scribe's capacity to streamline documentation and foster team communication is a life savior for IT experts looking for software solutions to support AI frameworks. 


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‎Team members can use Scribe AI to generate process documents swiftly, teach new coworkers and answer queries. Scribe also supports seamless interaction with other software platforms, making it a significant asset for any firm wishing to implement AI in their operations.


The simplicity of Scribe AI is one of its main benefits—the program makes it simple for anyone to write documentation, freeing managers and supervisors to concentrate on more difficult duties. 

(Source: G2 Review)

Scribe's user-friendly features and straightforward UI make it creates visual guides with text and screenshots that are simple to understand and follow.

2. Caffe: A High-Performance AI Framework
Caffe2 AI framework
(Source: Caffe)

G2 Rating: 4 out of 5 Stars
Capterra Rating: 5 out of 5 Stars

Caffe Pricing: Custom 

Caffe Overview: Features and Benefits

Caffe is one of the best programs for professionals in image segmentation and classification. Its deep learning architecture is accessible and transparent thanks to plaintext schemas. 

Caffe, which has preloaded functionality, provides exceptional speed and efficiency. Experts recommend these tools for their sophisticated research and application needs.

3.‎ Microsoft CNTK 

Microsoft CNTK AI framework
(Source: Microsoft)
G2 Rating: 4.2 out of 5 Stars

Capterra Rating: 4.6 out of 5 Stars

Microsoft CNTK Pricing: Free

Microsoft CNTK Overview: Features and Benefits

The neural network-based Microsoft CNTK framework, which is open-source, excels in several fields, including text, message and voice transformation. 

Experts love CNTK for its increased speed and versatility, which enable the effective evaluation of machine learning models without sacrificing accuracy. It's especially useful for companies dealing with large datasets who want high-performance solutions. 

Skype and Cortana depend on CNTK to satisfy their high standards, demonstrating its efficacy and suitability for advanced deployment and use by subject-matter experts.

4.‎ PyTorch 

PyTorch 2.0 AI framework
(Source: PyTorch)
G2 Rating: 4.5 out of 5 Stars

Capterra Rating: 4.5 out of 5 Stars

PyTorch Pricing: Free

PyTorch Overview: Features and Benefits

PyTorch framework supports a variety of tasks, from research prototyping to deployment models in practical situations. Its peer-to-peer communication features, which employ Python and C++, enable easy user cooperation. 

Thanks to PyTorch's compatibility with well-known cloud platforms, experts are given freedom and flexibility, which guarantees easy scaling and development. 

PyTorch is a popular option for experts involved in deploying and applying AI and ML models due to its strong ecosystem of tools and libraries that boosts its capabilities.

5.‎ TensorFlow 

TensorFlow AI framework
(Source: TensorFlow)
G2 rating: 4.5 out of 5 starsG2 Rating: 4.5 out of 5 Stars
Capterra Rating: 4.6 out of 5 starsCapterra Rating: 4.6 out of 5 Stars
TensorFlow Pricing: Free
TensorFlow Overview: Features and Benefits

TensorFlow is an AI framework for developers looking for opportunities for innovation and collaboration. It's a dependable AI platform with access to tried-and-true models built by specialists. 

One of its standout characteristics is the accessibility of tutorial videos, which enables experts to deploy and use TensorFlow for challenging programming tasks swiftly.

Start building your AI projects with these top frameworks today!

AI frameworks can help you save valuable time and effort, allowing you to focus on the creative aspects of your project rather than getting lost in the technical details. They offer pre-built tools, algorithms, and libraries that streamline the development process.

Embrace the future of technology by automating your processes using Scribe's AI text generator and witnessing the great potential that AI holds.

Ready to try Scribe?

Scribe automatically generates how-to guides and serves them to your team when they need them most. Save time, stay focused, help others.