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The adoption of AI by enterprises has surged significantly over the last couple years, particularly with the advent of Generative AI (GenAI) and Large Language Models (LLMs). Most enterprises start by prototyping and building proof-of-concept products (POCs), using all-in-one API endpoints provided by big tech companies like OpenAI and Google, among others. However, as these companies transition to full-scale production, many are looking for ways to control their AI infrastructure. This requires the ability to effectively manage and deploy PyTorch.

In today’s rapidly evolving technology landscape, adopting and rolling out AI to enhance your enterprise is critical to improving your organization’s productivity and ensuring that you are delivering a world-class product and service experience to your customers. AI is without question, the single most important technological revolution of our time—representing a new technology super-cycle that your enterprise cannot be left behind on.

The recent surge in AI application development can be attributed to several factors: (1) advancements in machine learning algorithms that unlock previously intractable use cases, (2) the exponential growth in computational power enabling the training of ever-more complex models, and (3) the ubiquitous availability of vast datasets required to fuel these algorithms. However, as AI projects become increasingly pervasive, effective development paradigms, like those commonly found in traditional software development, remain elusive.

Today, we're thrilled to announce the release of MAX 24.4, which introduces a powerful new quantization API for MAX Graphs and extends MAX’s reach to macOS. Together, these unlock a new industry standard paradigm where developers can leverage a single toolchain to build Generative AI pipelines locally and seamlessly deploy them to the cloud, all with industry-leading performance. Leveraging the Quantization API reduces the latency and memory cost of Generative AI pipelines by up to 8x on desktop architectures like macOS, and up to 7x on cloud CPU architectures like Intel and Graviton, without requiring developers to rewrite models or update any application code.

Today, we’re excited to announce general availability of MAX 24.2, with several big features.

Modular was founded on the vision to enable AI to be used by anyone, anywhere. We have always believed that to achieve this vision, we must first fix the fragmented and disjoint infrastructure upon which AI is built today. As we said 2 years ago, we imagine a different future for AI software, one that rings truer now than ever before

On Dec 4th, the Modular team took the stage at ModCon 2023 to deliver a keynote packed full of exciting announcements of new software, enterprise partnerships and community updates. 

We released Mojo local download for Linux systems on September 7th, and in just over a month we’ve seen tens of thousands of downloads and amazing community projects such as llama.🔥and Infermo. We deeply value your feedback, as Mojicians, and we appreciate every single PR, feature request, and bug report.

Since our launch of the Mojo programming language on May 2nd, more than 120K+ developers have signed up to use the Mojo Playground and 19K+ developers actively discuss Mojo on Discord and GitHub. Today, we’re excited to announce the next big step in Mojo’s evolution: Mojo is now available for local download – beginning with Linux systems, and adding Mac and Windows in coming releases.

‍On May 2nd, we announced our next-generation AI developer platform with two exciting breakthrough technologies — the Mojo programming language and the Modular AI Engine. In just over two months, more than 110k developers have signed up for the Mojo Playground to learn Mojo and experience its performance firsthand, over 30k developers have signed up to our waitlist for the AI engine, and our Modular community on Discord has grown to 17k developers! We’re incredibly excited to see developers sharing their experience with Mojo, providing product feedback, and learning from each other.