We were excited to announce this morning that we've significantly enhanced the Alegion Training Data Platform. The new capabilities delivered with this release target the quality and efficiency requirements of large-scale machine learning initiatives.
You can read the press release below, and if you want to learn more about the Alegion Training Data Platform our website has a dedicated page here.
Alegion Announces Next-Generation Training Data Platform for Enterprise Artificial Intelligence (AI) Initiatives
New platform delivers confidence in AI training data through ML-augmented quality control and flexible workforce composition
AUSTIN, Texas, September 13, 2018 -- Alegion, a training data platform for artificial intelligence (AI) and machine learning initiatives, today announced the release of its next-generation platform with new features designed to enhance quality and efficiency of large-scale machine learning initiatives and deliver model confidence for enterprise AI systems.
Built upon years of extensive experience in delivering training data for computer vision and natural language processing applications for retail, automotive, technology, government, and financial services, the Alegion platform integrates trained data specialists with data task management and distribution capabilities to accelerate machine learning projects through the creation of training data, model testing, and exception handling at scale.
“Training data is highly contextual and data precision at scale is paramount for model confidence,” said Cheryl Martin, chief data scientist for Alegion. “We’ve developed a platform that gives enterprises the flexibility of working with a combination of humans and automated quality controls to achieve high-quality training data sets for their AI initiatives.”
The Alegion training data platform extends existing capabilities and enhances key features like data security, complex and conditional task workflows, and multi-tier quality controls. The platform also introduces several new capabilities:
- Machine learning-augmented quality
Features machine learning using predictive indicators to score judgements per task and dynamically determine appropriate additional quality control stages like consensus judgements, review/adjudicate/exception workflows, and administrative reviews. The per-task confidence functionality learns updates from subsequent quality control stages and is calculated relative to both use case and context, allowing the platform to continually improve escalation decisions enhancing accuracy without increasing time and cost.
- Flexible workforce composition
Offers flexibility for sourcing human intelligence, including the ability to supply private or specialized workforces and create hybrid workforces that leverage Alegion’s own data specialists and partners, while maintaining the benefits of Alegion’s quality controls and task management capabilities. This expands Alegion’s ability to serve customers with a wide array of training needs through the creation of purpose-designed workforce, the ability to “bring your own crowd” of domain or geographic specialists, including employees, and through the support of strong security requirements by isolating data access to cleared and qualified specialists.
- Artificial intelligence system integration
Supports end-to-end integration with an enterprise’s AI infrastructure via APIs that support real-time data exchange or by batch, and flexible input / output formats. This programmatic integration of human intelligence into the AI lifecycle accelerates model training and testing by taking data as it is generated, processing it, and returning it to the model in real-time. This process allows for continuous model testing and as models mature, escalation of low-confidence results to human judgement.
“AI is evolving rapidly and so are the requirements of organizations building enterprise-level machine learning solutions,” said Nathaniel Gates, co-founder and CEO for Alegion. “Training data needs are becoming more sophisticated and Alegion is continuing to build the most robust platform in the market to serve those needs while setting the standard for accuracy and efficiency.
It’s been estimated that 80 percent of a data scientist’s day is spent managing data quality issues while nearly half of AI projects fail due to data problems,” Gates said. “Our focus is on putting confidence in AI and these new platform features were developed to reduce project risk and allow data scientists to accelerate delivery and ROI.”
For more information, please visit https://content.alegion.com/platform.