Modular

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Modular is an AI platform designed to enhance any AI pipeline, offering an AI software stack for optimal efficiency on various hardware.0
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What is Modular?

the Modular Accelerated Xecution (MAX) platform, a revolutionary AI software stack designed to empower AI engineers with unparalleled performance, programmability, and portability. MAX, developed by Modular Inc., represents a groundbreaking approach to AI infrastructure, offering a comprehensive set of tools and libraries that streamline the deployment of low-latency, high-throughput, real-time AI inference pipelines.

Key Features:

  1. Full Programmability with Mojo: MAX is built on Mojo, a programming language that combines the ease of Python, the safety of Rust, and the performance of C. This unique blend unlocks the full potential of AI hardware, enabling AI engineers to extend and optimize AI models with unprecedented ease and efficiency.

  2. Unparalleled Performance: MAX Engine, a core component of the platform, delivers state-of-the-art latency and throughput for AI pipelines. This includes generative models, allowing for rapid productionization of AI pipelines and significant cost savings on cloud infrastructure.

  3. Seamless Portability: MAX ensures that AI models and pipelines can be effortlessly moved to any hardware target. This flexibility maximizes performance to cost ratio and eliminates vendor lock-in, providing freedom and efficiency in hardware choices.

  4. MAX Engine: As a model inference runtime and API library, MAX Engine executes AI pipelines on any hardware with exceptional performance. It offers a simple Python or C API, enabling a quick transition from existing inference calls like TensorFlow, PyTorch, or ONNX, and delivering up to 5x faster execution across various CPU architectures.

  5. MAX Serving: This model serving library for MAX Engine offers full interoperability with existing serving systems and seamless deployment within container infrastructures like Kubernetes. It serves as a drop-in replacement for systems like NVIDIA Triton Inference Server, enhancing the ease of integration and deployment.

Use Cases:

  • Quick Performance Wins: MAX allows for rapid enhancement of AI model performance. By replacing current inference calls with MAX Engine, users can achieve significant speed improvements with minimal code changes.

  • Extend & Optimize Models: With MAX Engine in place, users can further optimize their models using Mojo. This includes writing custom ops or building entire models in Mojo, utilizing the MAX Graph API for inference.

  • Full Stack Optimization: Beyond inference, MAX enables optimization of the entire AI pipeline. Users can migrate data pre/post-processing code and application code to Mojo, with ongoing additions to MAX tools and libraries to accelerate development across the AI stack.

Why MAX?

  • Built by AI Experts: The Modular team includes the world’s leading AI experts who have contributed to foundational AI infrastructure like TensorFlow, PyTorch, ONNX, and XLA.

  • Reinvented AI Infrastructure: MAX represents a “first principles” rebuild of the AI stack, addressing the complexities of existing solutions with a fresh, efficient approach.

  • Infrastructure That Just Works: MAX is designed to integrate seamlessly into existing workflows, requiring no model rewriting or hardware expertise to leverage cutting-edge technology.


MAX is more than just a platform; it’s a paradigm shift in how AI is developed and deployed, offering a future-proof, high-performance solution for AI engineers and organizations. With MAX, the potential of AI hardware is fully unlocked, paving the way for the next wave of AI innovation.


More information on Modular

Launched
1997-05
Pricing Model
Starting Price
Global Rank
99161
Country
India
Month Visit
526K
Tech used

Top 5 Countries

41.19%
11.05%
5.63%
3.73%
3.68%
United States China India United Kingdom Russian Federation

Traffic Sources

44.35%
36.82%
11.6%
6.14%
1.02%
0.07%
Search Direct Referrals Social Mail Paid Referrals
Updated Date: 2024-05-11
Modular was manually vetted by our editorial team and was first featured on September 4th 2024.
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