Why Now Is the Time to Move to Data-Centric AI
Model-centric AI Helps You Get Started
In The Art of War, Sun Tzu advises, “In all fighting, the direct method may be used for joining battle, but indirect methods will be needed for securing victory.”
Regarding joining the AI battle, model-centric AI has been the direct method focusing on the innovation of ever-improving algorithmic models. With model-centric AI, your data scientists build model architectures, fine-tune parameters, and then create and refine different algorithms. The benefits have been staggering, but the costs are adding up.
- Model builders are in short supply and expensive
- Model complexity is increasing faster than model effectiveness
- Models trained on clean test data sets often fail when encountering the real world’s messy data.
Following Sun Tzu’s counsel, securing victory in the AI battleground requires indirect methods, namely data-centric AI.
What Is Data-Centric AI and Why Should You Care?
According to Gartner, “Data-centric AI is an approach that focuses on enhancing and enriching training data to drive better AI outcomes, as opposed to a model-centric approach wherein AI outcomes are driven by model tuning. Data-centric AI also addresses data quality, privacy, and scalability.” (1)
How To Win the AI Battle with Data-Centric AI
According to Sun Tza, controlling a large force is the same principle as controlling a few men: it is merely a question of dividing their numbers.
However, given all your model-centric AI investments, moving to data-centric AI may require a significant resource reallocation.
To help you understand and make a case for this transition, we have assembled three experts: infoVia‘s Michael Magalsky, Alation‘s David Sweenor, and DataOps.live‘s Guy Adams on Friday, September 6, 2024 at Noon ET, for our September Jam Session: Why Now Is the Time to Move to Data-Centric AI.
Join us when our experts address the following:
- What is Data-centric AI?
- Why is a data-centric approach needed?
- How do data-centric AI and model-centric AI differ?
- What technologies are critical to data-centric AI success?
- Where are the best places to start your data-centric AI journey?
See you there.
Register (free) for the Friday Jam Session: Why Now is the Time to Move to Data-Centric AI
