22
Apr
AI’s biggest bottleneck isn’t compute power. It’s data.
Even the best AI models struggle to attain optimal performance without high-quality, labeled data. Yet, most companies struggle to scale their data pipeline—delaying production, increasing costs, and limiting model performance.
At MLtwist, we’re tackling this challenge head-on.
We recently explored what it really takes to solve AI’s data bottleneck, at scale, with Stage 2 Capital Catalyst LP Sean Po. (Editor’s note: MLtwist had the privilege of participating in Stage 2 Capital’s 2023 Capital Catalyst cohort.)
Want to take a closer look at how MLtwist is helping businesses and organizations mine gold from their data and turn it into high-performing AI models? Check out the full conversation over at the Stage 2 Capital blog.
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Join MLtwist and Vectara for the AI Data Readiness Forum, an exclusive in-person event
that cuts through the complexity of generative AI data preparation.
April 24, 2024 / 3pm PST / Palo Alto, CA
The Ultimate Guide to AI Data Pipelines: Learn how to Build, Maintain and Update your pipes for your unstructured data