Jax
Jax is a new framework getting attention for being flexible and great for high-performance number work. Created by Google Research, it’s especially good for scientific tasks, machine learning research, and trying out neural networks. Though it takes a bit to learn, people like Jax because it can be both flexible and fast. It works well with Python, which makes it a good choice for developers who know Python.
Key Features:
- Latest version: Jax 0.4. 17 released on October 3, 2023.
- Flexibility and Performance: Jax, from Google Research, is gaining attention for its flexibility and robust support for high-performance numerical computing.
- Scientific Computing Focus: Well-suited for scientific computing, machine learning research, and experimenting with neural networks.
- Moderate Learning Curve: Although it may take some time to learn, Jax is becoming more popular due to its unique ability to balance flexibility and performance.
Top 10 Artificial Intelligence Frameworks to Learn in 2024
Artificial Intelligence (AI) plays a crucial role in today’s digital world, and it’s expected to reach a market value of $190.61 billion by 2025. People from all walks of life, including digital enthusiasts and the average person, are contributing to this transformation.
Easy-to-use tools like Python, AI models, and the best AI frameworks make it accessible for more people to join in, creating a collaborative effort to shape the global digital landscape. As per the survey, the global AI market is expected to reach $190.61 billion by the year 2025.
Top artificial intelligence frameworks speed up the creation of AI applications, covering various areas like deep learning, machine learning, NLP solutions, and neural networks. As AI becomes more common, dealing with large sets of data, known as “big data,” becomes a challenge for organizations. This is why many technologies today require a reliable artificial intelligence framework to effectively handle and make sense of such data.