Introduction to Artificial Intelligence and Data Storage
Artificial intelligence is changing the way businesses store and access their data. Traditional data storage systems were designed to handle simple commands from a handful of users at once, whereas today, AI systems with millions of agents need to continuously access and process large amounts of data in parallel. Traditional data storage systems now have layers of complexity, which slows AI systems down because data must pass through multiple tiers before reaching the graphical processing units (GPUs) that are the brain cells of AI.
The Problem with Traditional Data Storage Systems
Traditional data storage systems were not designed to handle the massive amounts of data required by AI systems. The complexity of these systems slows down AI processing, making it difficult for businesses to keep up with the demands of AI. The data must pass through multiple tiers before reaching the GPUs, which can cause latency and energy bottlenecks.
Cloudian: A Solution to the Problem
Cloudian, co-founded by Michael Tso and Hiroshi Ohta, is helping storage keep up with the AI revolution. The company has developed a scalable storage system for businesses that helps data flow seamlessly between storage and AI models. The system reduces complexity by applying parallel computing to data storage, consolidating AI functions and data onto a single parallel-processing platform that stores, retrieves, and processes scalable datasets, with direct, high-speed transfers between storage and GPUs and CPUs.
The Benefits of Cloudian’s Storage System
Cloudian’s integrated storage-computing platform simplifies the process of building commercial-scale AI tools and gives businesses a storage foundation that can keep up with the rise of AI. According to Michael Tso, "One of the things people miss about AI is that it’s all about the data. You can’t get a 10 percent improvement in AI performance with 10 percent more data or even 10 times more data — you need 1,000 times more data." Cloudian’s storage system allows businesses to store and process large amounts of data, making it ideal for AI applications.
From MIT to Industry
Michael Tso’s journey to Cloudian began at MIT, where he was introduced to parallel computing by Professor William Dally. Tso also worked on parallel computing with Associate Professor Greg Papadopoulos. After graduating, Tso worked at Intel’s Architecture Lab, where he invented data synchronization algorithms used by Blackberry. He then joined Inktomi, a startup co-founded by Eric Brewer, and later started Gemini Mobile Technologies.
The Evolution of Cloudian
In 2012, Tso officially launched Cloudian out of Gemini Mobile Technologies, with a new emphasis on helping customers with scalable, distributed, cloud-compatible data storage. Although Tso’s research at MIT began more than two decades ago, he sees strong connections between what he worked on and the industry today. Cloudian’s platform uses an object storage architecture in which all kinds of data are stored as a unique object with metadata.
Recent Developments
In July, Cloudian announced that it has extended its object storage system with a vector database that stores data in a form which is immediately usable by AI models. Cloudian also announced a partnership with NVIDIA that allows its storage system to work directly with the AI company’s GPUs. This new system enables even faster AI operations and reduces computing costs.
AI-First Storage
Cloudian is helping about 1,000 companies around the world get more value out of their data, including large manufacturers, financial service providers, health care organizations, and government agencies. Cloudian’s storage platform is helping one large automaker use AI to determine when each of its manufacturing robots need to be serviced. Cloudian is also working with the National Library of Medicine to store research articles and patents, and the National Cancer Database to store DNA sequences of tumors.
Conclusion
In conclusion, Cloudian is revolutionizing the way businesses store and access their data, making it possible for AI systems to process large amounts of data quickly and efficiently. With its scalable storage system and partnerships with leading AI companies, Cloudian is helping businesses keep up with the demands of AI and unlock new insights and innovations.
FAQs
Q: What is the main problem with traditional data storage systems?
A: Traditional data storage systems have layers of complexity that slow down AI systems, making it difficult for businesses to keep up with the demands of AI.
Q: How does Cloudian’s storage system solve this problem?
A: Cloudian’s storage system applies parallel computing to data storage, consolidating AI functions and data onto a single parallel-processing platform that stores, retrieves, and processes scalable datasets.
Q: What is the benefit of Cloudian’s partnership with NVIDIA?
A: Cloudian’s partnership with NVIDIA allows its storage system to work directly with the AI company’s GPUs, enabling even faster AI operations and reducing computing costs.
Q: What kind of companies is Cloudian helping?
A: Cloudian is helping about 1,000 companies around the world, including large manufacturers, financial service providers, health care organizations, and government agencies.
