Algorithmia tackles ML compliance with new governance tools
Algorithmia, an MLOps software company, has released a set of tools to help technology leaders manage compliance in machine learning models.
The Seattle-based company worked off the back of research suggesting 56 per cent of IT leaders thought ML governance was a major concern. Ramifications could include bad credit decisions, fraud detection errors or poor decision making that was visible to clients.
Significant analytics risk
Algorithmia, which specialises in MLOps, has developed a set of tools to help technology leaders with post-deployment risks in machine learning models. Operational risk is now the most significant analytics risk, according to the company.
Algorithmia Enterprise’s new product offers five key reporting and governance capabilities:
Cost and usage reporting on infrastructure, storage and compute consumption within Algorithmia to understand and manage the overall cost of maintaining the platform.
Enhanced chargeback and showback reporting for monthly costs of storage, CPU and GPU consumption and usage billing.
Algorithm usage reporting with details of the algorithm used, so organizations can bill users for their usage.
Enhanced audit reports and logs so examiners and auditors can review model results, history of changes, and a record of data errors or past model failures and actions taken.
Advanced reporting panel for Algorithmia admins that provide an overview of all available metrics and usage reporting, ability to build reports and export reports and metrics to systems of record.
Diego Oppenheimer, CEO of Algorithmia, said, “We’re still in the early days of ML governance, and organizations lack a clear roadmap or prescriptive advice for implementing it effectively in their own unique environments.
“Regulations are undefined and a changing and ambiguous regulatory landscape leads to uncertainty and the need for companies to invest significant resources to maintain compliance. Those that can’t keep up risk losing their competitive edge. Furthermore, existing solutions are manual and incomplete. Even organizations that are implementing governance today are doing so with a patchwork of disparate tools and manual processes. Not only do such solutions require constant maintenance, but they also risk critical gaps in coverage.”
HPE Acquires Determined AI to Accelerate ML Training
Determined AI is a four-year-old company, which only brought its product to market in 2020. It specialises in machine learning (ML), with the aim of training AI models quickly and at any scale. HPE will combine Determined AI’s unique software solution with its AI and high-performance computing (HPC) offerings to enable ML engineers to easily implement and train ML models to provide faster and more accurate insights from their data in almost every industry.
“As we enter the Age of Insight, our customers recognise the need to add machine learning to deliver better and faster answers from their data,” said Justin Hotard, senior vice president and general manager, HPC and Mission Critical Solutions (MCS), HPE. “AI-powered technologies will play an increasingly critical role in turning data into readily available, actionable information to fuel this new era. Determined AI’s unique open source platform allows ML engineers to build models faster and deliver business value sooner without having to worry about the underlying infrastructure. I am pleased to welcome the world-class Determined AI team, who share our vision to make AI more accessible for our customers and users, into the HPE family.”
Delivery AI at scale
According to IDC, the accelerated AI server market, which plays an important role in providing targeted capabilities for image and data-intensive training, is expected to grow by 28% each year and reach $18bn by 2024.
The computing power of HPC is also increasingly being used to train and optimise AI models, in addition to combining with AI to augment workloads such as modeling and simulation. Intersect360 Research notes that the HPC market will grow by more than 40%, reaching almost $55bn in revenue by 2024.
“Over the last several years, building AI applications has become extremely compute, data, and communication intensive. By combining with HPE’s industry-leading HPC and AI solutions, we can accelerate our mission to build cutting edge AI applications and significantly expand our customer reach.” said Evan Sparks, CEO of Determined AI.