Blog

We’re very excited about the positive reception of Mojo since its launch as well as the community of people building around it. Given new Large Language Model (LLM) powered developer tools like Copilot and Ghostwriter, many developers are wondering about the future of programming – do programming languages still matter when AI writes the code?

Last week, we launched Modular to the world after more than 16 months in stealth. We started Modular with a deep conviction — after 6+ years of building and scaling AI infrastructure to billions of users and 20+ years of building foundational compute infrastructure — it was clear the world needed a better path forward. Everyone wants less complexity, better access to compute and hardware, and the ability to develop and deploy AI faster.

At Modular, we are rebuilding AI infrastructure for the world. Our goal is to move past AI tools that are themselves research projects and into a future where AI development and deployment are orders of magnitude more efficient for everyone. You should be able to do this without trading off performance or having to rewrite your entire code base.

Here in November 2022, we see a continuing onslaught of bad news: significant layoffs of incredible people as companies tighten their belts; companies that raised too much money, too fast, without core fundamentals are dying; and a changing climate where over-tightening rather than under-tightening is seemingly the new normal.

What makes a brand? When you see an apple with a bite out of it, you immediately associate it with the famous technology company — but what about the logo elicits the feelings it does? 

AI promised to profoundly change the world, so why hasn’t it?From healthcare to manufacturing, finance, climate, communication, and travel, to how we live and work. AI can help solve any problem that can be represented by data, assuming the right algorithms and enough computational resources.

Platforms like TensorFlow, PyTorch, and CUDA do not focus on modularity - there, we said it! They are sprawling technologies with thousands of evolving interdependent pieces that have grown organically into complicated structures over time. AI software developers must deal with this sprawl while deploying workloads to server, mobile devices, microcontrollers, and web browsers using multiple hardware platforms and accelerators.