The idea behind VAST has always been a seemingly simple one: What if we could give computers the ability to think and discover for themselves?
If computers were capable of original thought the process of discovery, which has catalyzed all human progress since the earliest moments of civilization, could be accelerated significantly. We could build revolutionary artificial intelligence capabilities that wildly surpass our own potential, solving the world’s biggest challenges and moving humanity forward.
When our founders started VAST Data in 2016, this was the future they envisioned. Back then the extent of AI computing progress had been essentially limited to identifying cats in YouTube videos using 1960s-era neural networks.
Those same kinds of neural networks power generative AI models like ChatGPT or Bard today.
We still don’t entirely know how neural networks mimic the human brain, but we have learned that the combination of these machine learning models with abundant data can deliver value across a wide range of applications and business functions.
Unlocking the True Potential of AI
But ChatGPT and AI language models do not discover things or generate new ideas. They do not interact with the natural world. While useful tools, they generate text, images, and video based on information fed to them from the internet. It’s a long way from recognizing cats, but still far away from curing cancer.
The true promise of AI is much greater than what we have seen so far. Realizing this promise requires a fundamental rethink of traditional data management concepts and assumptions.
AI-driven discovery and deep learning goes far beyond processing unstructured data like documents, images, or text. It’s processing real-world, analog data from sensors or genome sequencers or video feeds or autonomous vehicles, interpreting it in the context of the body of human knowledge, and making connections with ideas that we haven’t imagined yet.
Machines also need to learn from one another. Just as collaboration between humans drives better outcomes than individuals working alone, computers learn from interactions. For example, Google DeepMind optimized its AlphaGo computer program by having its neural network play against itself thousands of times, each time learning from its mistakes. As we’ve seen for thousands of years, knowledge builds upon knowledge to increase the pace of discovery.
We think a data platform that provides neural networks with broad access to such natural data at tremendous speed and scale will deliver much more sophisticated AI than what we’ve seen to date. And as datasets grow larger, as algorithms get smarter, and as processors get stronger, self-discovering computers - thinking machines - will no longer be science fiction.
Powering the Next Era of AI Infrastructure
That’s why VAST was founded and it’s why we built the VAST Data Platform. We started with the storage infrastructure because data is the foundation for AI and deep learning. By breaking architectural and business tradeoffs that plagued storage IT for decades, we delivered a scalable architecture for unstructured data that eliminates storage tiering and provides fast access to all data.
But storage was just the start. VAST is and always has been an AI data platform company.
Today we unveil a platform that expands the capabilities of the VAST DataStore (fka Universal Storage) and introduces two new components: the VAST DataBase (adding structure to unstructured data in the VAST DataStore) and the VAST DataEngine (a compute framework for this new era). Together, these concepts create a unified environment to ingest, store, catalog, process, and query vast amounts of structured and unstructured data.
Most importantly, the VAST DataSpace federates data globally, enabling models to access and learn from the entire corpus of information within an organization. It also puts our customers firmly in control to use AI for their specific needs, not to serve the interests of external parties.
Democratizing data is our mission. Transforming every enterprise into an “AI-first” data powerhouse requires democratizing access to infrastructure to store massive datasets and execute data-driven algorithms. This will distribute power and capability away from the hands of a few that currently dominate AI through the control of valuable data.
Today any organization contemplating any type of AI practice - especially on a large scale - needs three things:
AI applications developed by the end user
A software infrastructure stack comprising storage, database, and compute engine services from VAST
Hardware from the likes of NVIDIA and others
As our customers embark on the adventure of building large-scale AI clusters, we think VAST will be the data platform that provides the freedom they need to reimagine their interactions with data in this new AI era without being confined to archaic infrastructure constraints.
That’s been the vision since the beginning of VAST. And now we’re bringing that vision to life.