AI model training requires fast access to all historical data
Renen Hallak · The $9B Startup Going After Snowflake and Databricks | Renen Hallak, CEO of VAST Data · May 3, 2024 · at 10:54
Renen Hallak is the CEO and founder of VAST Data. He is explaining why legacy tiered storage architectures fail for modern AI workloads.
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“AI doesn't conform to that model. You need fast access to everything in order to build an AI model.”
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Starting later than Snowflake and Databricks was VAST Data's biggest advantage
“And so I think our The biggest advantage versus those other companies that you mentioned is that we started late, and that allowed us to see this deep learning problem in front of our eyes versus machine learning, again, a lot smaller, a lot slower, and it als…”
VAST Data employs only two product managers for 750 employees
“You'll find we're 750 people. We have two product managers in the company.”
VAST Data has been cash-flow positive for nearly five years
“Efficiency, we've been cashflow positive on average for four and a half, five years now.”
VAST Data achieves stateless compute by exposing data across the network
“Every node can now see the entirety of the data set. Data on low cost flash, metadata on storage class memory, all on the other side of the network, such that they become stateless, And they don't need to talk to each other anymore, and so now you have the mos…”
Row and column database complexity stems from legacy hard drive limitations
“Row-based databases and column-based databases. That all stems from storage. It stems from hard drives needing to be sequential. If we can give different views into the same information, then you don't need that complexity.”