IBM Watson OpenScale: Operate and automate AI with trust
By Beth Smith | 3 minute read | October 15, 2018
Innovative organizations understand that AI offers competitive advantage and is already a driving force in the evolution of their industries. Many have started this journey by implementing successful AI projects – from chatbots that help brands personalize conversations with their customers, to systems that make decades of institutional knowledge immediately accessible to a subject matter expert.
However, for every successful implementation, there are many AI models that fail to make it out of the lab and into production. At IBM, we understand the roadblocks to full AI adoption – from trust and transparency concerns with the ‘black box’ of AI, to problems of scale and automation – and we are working with enterprises to provide the tools needed to overcome these roadblocks and deliver real business value. To that end, today we’re excited to announce our next, critical move in helping businesses accelerate the adoption of AI: IBM Watson OpenScale.
AI OpenScale allows businesses to operate and automate AI at scale, – irrespective of how the AI was built and where it runs. Bridging the gap between the teams that operate AI and those that manage business applications, Watson OpenScale provides businesses with confidence in AI decisions. Available later this year via the IBM Cloud and IBM Cloud Private, it infuses AI throughout its full lifecycle with trust and transparency, explains outcomes and automatically mitigates bias.
AI has tremendous potential. Businesses, however, face a critical AI skills gap. To address that gap, we developed Neural Network Synthesis (NeuNetS). As part of Watson OpenScale, NeuNetS is a beta feature that automatically creates customized neural network models using the latest training data from businesses.
Watson OpenScale provides enterprises visibility into how AI is built, used, and performs. With Watson OpenScale, businesses can embed AI into new or existing business applications and functions with the freedom to use the environment of their choice. Specifically, it supports:
- AI deployed in any run-time environment: E.g., Amazon ML, Azure ML, and custom runtime environments, behind the enterprise firewall
- Applications and machine learning and deep learning models developed in any open source, model-building and training IDE, including in TensorFlow, Scikitlearn, Keras, SparkML and PMML
Scaling AI with Trust and Transparency
As more applications make use of AI, businesses need visibility into the recommendations made by their AI applications. In the case of certain industries like finance and healthcare, in which adherence to GDPR and other comprehensive regulations present significant barriers to widespread AI adoption, applications must explain their outcomes in order to be used in production situations.
It is critical to ensure AI recommendations or decisions are fully traceable – enabling enterprises to audit the lineage of the models and the associated training data, along with the inputs and outputs for each AI recommendation.
Watson OpenScale significantly expands the Trust and Transparency capabilities we announced last month. Building on these capabilities, we’re also introducing explainability for black box models and functions, automatic bias detection and mitigation, auditability, and traceability on AI applications – regardless of whether they run on a company’s private cloud, on IBM Cloud, or on other vendors’ cloud environments.
NeuNetS: AI for AI
NeuNetS is an AI technology that automatically configures itself to specific business data, helping organizations quickly scale AI across their workflows, while making their data science team more productive. This revolutionary technology automatically builds customized neural networks for text and vision models and recommends new models, thereby reducing the complexity and skills required to build AI models.
The technology is still evolving. Benchmarks show that NeuNetS can help businesses reach accuracy similar to that of an expert-designed AI model in a matter of hours, rather than weeks and months. An expert data scientist can then further tune the model. That’s a huge win in terms of productivity and cost-efficiency – a real win in addressing the critical AI skills gap enterprises face today.
Accelerating Your AI
IBM Watson OpenScale extends the breadth and depth of IBM capabilities to help businesses accelerate AI – ringing their projects out of the lab and into production.
Watson OpenScale provides visibility and explainability into AI outcomes, helping to ensure fair outcomes while giving business-process owners greater trust in AI’s ability to augment decision-making, and confidence to scale it across their workflows. At the same time, the solution provides a robust framework to ensure AI maintains compliance with corporate policies and regulatory requirements. It also helps remove barriers to AI adoption by empowering users to deploy and manage models across projects, at whatever scale the business requires.
AI OpenScale will be available later this year on the IBM Cloud or IBM Cloud Private.
Learn more about the Watson OpenScale offering