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Skill 29 · Knowledge Base For Startups
Subchapter 29.161
references/learn/general/datology-ensures-quality-over-quantity-for-better-ai.mdMarkdown2 KBView on GitHub
Datology is making it easier for organizations to train AI models, by selecting, organizing, and cleaning the highest quality data.
According to Ari Morcos, Co-Founder and CEO of Datology, AI models are what they eat. Feed them high quality data in and you’ll get high quality models out. Feed them low quality data, and you should lower your expectations! Datology (opens in a new tab) is making it easier for organizations to train AI models, by selecting, organizing, and cleaning the highest quality data. Seeking to grow, the company turned to AWS to ensure reliability and scalability, and to better market its offering.
Datology is using a range of AWS services, including Amazon S3 (opens in a new tab), Amazon Elastic MapReduce (EMR) (opens in a new tab), Amazon Elastic Compute Cloud (EC2) (opens in a new tab), and Amazon EKS (opens in a new tab), a managed Kubernetes service. In doing so, the company is providing a dependable platform to customers, while accessing the services and compute power needed to scale this platform to support growth. These services, says Bogdan Gaza, Co-Founder and CTO, are “core to us being able to iterate fast on our product and ship at scale.”
Training models using data is a matter of quality over quantity. Using Datology’s platform, enterprises can manage and extract value from often vast quantities of unstructured data, helping them lower costs, get results faster, and build more accurate and reliable AI models. The company is broadening these benefits to all; with automation and easy integration, “anybody can train a model using the absolute highest quality data possible without having to be a research expert,” says Morcos.
Category: Featured Startups