AI OpenScale: The open platform to accelerate adoption of trusted AI
Did you know that
94% of companies believe AI is key to their competitive advantage (IDC), but only 1 in 20 has extensively incorporated AI into their business processes and workflows (MIT Sloan Management Review).
Here’s an important announcement from The IBM Watson Team
AI OpenScale is available! Now you can implement trusted AI with confidence, and close the gap between AI and its business outcomes. AI OpenScale is the only platform you need to operate and automate your AI.
AI doesn’t have to be an inscrutable black box, nor remain just out of reach for your business because you don’t have the resources to implement it at scale. AI OpenScale is designed specifically to remove these barriers so you can extend AI to more of your business practices.
This open platform will give your team insights into AI health, help you remediate problems and explain outcomes, and make the process of building AI even easier.
Let’s try and see?
The IBM AI OpenScale platform allows enterprises to automate and operate AI at scale—wherever it resides, across its entire lifecycle—with transparent, explainable outcomes, automatically freed from bias. AI OpenScale provides confidence in AI outcomes, and it spans the gap between the teams that operate AI and the business units that use these applications.
Available now via IBM Cloud and IBM Cloud Private, AI OpenScale is the open platform for businesses to operationalize trusted AI and extend their deployments enterprise-wide. AI OpenScale provides insights into AI health, recommends next steps to improve outcomes, and orchestrates tasks to remediate issues around performance, accuracy, and fairness.
Top use cases: Supply Chain
Effective demand forecasting is essential to keeping operational costs down while still meeting consumer demand, but it’s very difficult. Companies aren’t equipped to deal with the volume and diversity of data needed to account for real-time changes in demand. Forecasts that can’t adapt to constantly changing variables in today’s market can lead to multimillion- dollar miscalculations, severely damaging a company’s bottom line.
Machine learning models can be trained to help a company improve its Forecast Value Added (FVA) metrics, learning from historical, successful, and unsuccessful forecast override data. These models help demand planners make better adjustments to their demand forecast. AI OpenScale’s model dashboard allows the supply chain team to monitor their models’ accuracy over time, so that they can check that their AI-powered applications are consistently delivering outcomes as accurate as those produced by knowledge workers.
more info: https://www.ibm.com/cloud/ai-openscale