Highlights:
- In order to build AI applications and systems, PyTorch Lightning offers businesses collaborative, cloud-based, and persistent development environments.
- The platform is intended to streamline the disjointed infrastructure that supports conventional AI projects and necessitates teams of engineers to maintain.
Artificial intelligence platform developer Lightning AI raised USD 50 million in the equity funding bringing the total valuation to USD 103 million.
Cisco Investments, J.P. Morgan, K5 Global, and the investment division of Nvidia Corp. led the funding round. According to the New York-based business, the capital will be used to grow its clientele and platform, which is built around the PyTorch Lightning framework.
William Falcon, the Founder and CEO of Lightning AI, once known as Grid.ai Inc., is the driving force behind the open-source PyTorch Lightning project, which aims to reduce the cost and difficulty of developing intricate systems for coordinating AI workloads.
In order to build AI applications and systems, PyTorch Lightning offers businesses collaborative, cloud-based, and persistent development environments. These infrastructures can handle a wide range of tasks, from developing models to fine-tuning and deploying them to more specialized ones like creating AI agents that can carry out tasks for their users.
The platform is intended to streamline the disjointed infrastructure that supports conventional AI projects and necessitates teams of engineers to maintain. It interfaces with well-known machine learning technologies such as OpenAI, VSCode, and others.
PyTorch Lightning offers businesses full-, low-, and no-code environments for training and deploying AI models and developing intelligent agents by combining dozens of disparate AI development tools into a single, multicloud platform. From Lightning AI’s platform, developers may work together and write, host AI applications, utilize cloud-based GPUs, and more, all of which are hosted on the cloud infrastructure of their choice.
The business believes that by controlling AI infrastructure, it can assist companies in cutting the time it takes to develop and implement new AI applications from months to a matter of weeks. In other words, it allows them to iterate far faster than they did previously.
Lightning AI offers pay-as-you-go subscription model with a free tier at 22 GPU hrs/month. Besides, it offers private cloud deployment options for developers.
The era of AI computing, which Falcon calls “software 2.0,” will necessitate a paradigm change away from traditional software development, forcing businesses to adjust to the use of GPUs, large datasets, and collaborative processes. Additionally, Falcon hopes Lightning AI will serve as the cornerstone of the Software 2.0 era, just how Amazon Web Services Inc. became a center for traditional software development.
It’s unclear if it can accomplish that objective, but it won’t be simple with competitors like Weights and Biases Co., Comet ML Inc., Galileo Technologies Inc., Arize AI Inc., Deepset GmbH, and Diveplane all providing competing AI orchestration systems, Lightning AI is up against a lot of competition.
However, Lightning AI appears to be progressing well. In just 12 months since the platform’s introduction, the startup has amassed over 240,000 users from over 2,000 businesses, boasting over 160 million downloads overall.
According to reports, a research team at Columbia University completed hundreds of trials in 12 hours as opposed to the customary 60 days, and an anonymous Fortune 100 company reportedly cut the setup time for its AI infrastructure platform from 30 days to just two days with Lightning AI.
“We have thousands of developers single-handedly training and deploying models at a scale that would have required teams of developers without Lightning,” Falcon said. “The value for enterprises lies in their data, domain knowledge and unique models — not in maintaining AI infrastructure.”
As companies started implementing the technology after initially testing it, Lightning AI’s funding round is perhaps one of the last in a year that has seen enterprise spending on generative AI climb sixfold.
Menlo Ventures, a venture capital firm, said earlier this week that this spending had increased to USD 13.8 billion from USD 2.3 billion the previous year.