By Daniel D. Gutierrez, Editor-in-Chief, insideBIGDATA.com
A recent KPMG survey, “2021 Thriving in an AI World,” found that across nearly every industry—technology, financial services, healthcare, manufacturing, retail, life sciences, government—AI adoption is steadily increasing year-over-year. The cause is clear, digital transformation is moving faster, and as a result this effect assists businesses to move faster through market forces. But with this proliferation comes various levels of complexity, and many organizations often struggle with AI projects that tend to fail more than succeed. Project delays, budget limitations, scarcity of needed skills, changing data sources, decay of a model’s predictive power (model drift), and scalability issues are just some of the aspects that make for potentially high-risk AI projects.
Fortunately, we’re seeing innovative solutions come to the marketplace that solve many of the above issues. One particular solution comes from Veritone – the aiWare Enterprise AI Platform — which is touted as an “AI Operating System,” an appropriate metaphor as it maintains a number of similarities to standard operating system design. The figure below illustrates the component parts of aiWare, representing a single-platform approach combining the ability to read complex, unstructured data such as audio, images, video, text, etc. and using AI for delivering quick analysis of key insights. aiWare is particularly capable of integrating with advanced intelligent automation (IA) to drive end-to-end process automation.
Drilling down into the OS metaphor, a traditional OS serves as a gateway for processors, peripherals and software applications so they can communicate and work together. In a similar manner, an “AI operating system” provides a common software infrastructure that affords the use of AI-powered applications and solutions that provide data ingestion and analysis. This is similar to how a Microsoft or Apple OS hides the complexities of underlying system components – the aiWARE platform’s common, standardized operating system hides the complexities of AI data preparation, model selection and performance testing. Importantly, aiWare manages and orchestrates a variety of cognitive engines that can be used with general or industry-specific applications. An AI platform using this operating system approach has a number of proven benefits:
- Enables the rapid development of AI applications to solve business problems
- Eliminates the need to manage and orchestrate disparate underlying AI models
- Seamlessly leverages multiple AI models from multiple vendors
- Mitigates risks of single vendor dependency
- Maintains the flexibility to deploy in the cloud, private cloud, or on-premise
Facilitating Machine Learning
aiWARE provides a comprehensive range of ready-to-use machine learning models that can transform audio, video, text and other data sources into actionable information, all at scale. aiWARE enables project stakeholders to operationalize AI workloads across the enterprise by rapidly integrating AI into applications and business processes. The goal is to democratize AI so that MLOps teams can easily train, evaluate, integrate, deploy, and monitor AI models.
Veritone aiWARE helps AI and ML teams avoid model lock with a universal interface across hundreds of best-of-breed, AI models from leading vendors, accelerating AI deployments. Teams can aggregate results across AI models with a time-correlated, multivariate search-enabled intelligent data lake. They can even evaluate, compare, and monitor performance and drift across AI models for their data sets, pre- and post-production.
Timeliness and Value of an AI Platform
By extracting intelligence using various AI models and then cycling the insights back into process automation solutions, the overall process is revitalized to become more intelligent. Content is transformed into actionable intelligence, advancing the organization’s competitive advantage. Here, AI enhances automation solutions by serving them with more intelligent and relevant insights based on taking advantage of data sources that were not considered viable because they were unstructured. So whether the need is more intelligent process automation or simply quick access to data from multiple unstructured data sources, aiWARE meets that need without requiring significant AI or ML expertise. The final outcome is a higher level of data insight and intelligent process automation.
There are three key areas that an AI platform caters to in terms of timeliness and performance-based value, specifically designed to meet the demand for agile, intelligence-based solutions:
Automation of Human Work
In order for an organization to avoid costly manual processes involving human labor, a shift is needed to move from “human in the loop” processes to “human on the loop” processes. This movement means that human involvement, the most inefficient and costly, will switch to digital workers alongside human workers. Here, human workers review, verify and use data insights uncovered by digital workers. A digital approach using an AI platform consisting of ready-to-deploy models removes single vendor/single model dependency, alleviates the need for AI skillsets, and easily deploys and scales. With highly skilled and scarce data science skills not required, an AI platform aspires to the plug-and-play mode that has been the basis of successful automation technology in recent years.
Process Automation across All Data Sources
Expanding automation’s scope and impact by making data extraction and insights a priority across content types, represents a distinct opportunity to the typical organization. The challenge is to deliver scalable, end-to-end automation beyond just RPA and across all data sources.
AI-based automation, through use of an AI platform, can now be applied to any data source, including text, audio (speech), and video (vision). These classes of data sources span a broad range of industries. This is where AI, combined with continuous machine learning capabilities, is becoming a game changer.
Democratization of AI across the Enterprise
The benefits of an AI platform can be applied across the enterprise in a variety of ways including the ability to enhance conversational intelligence through all departments. Previously, process automation has been focused on database-driven business process automation. What’s been lacking is the integration with media sources and other unstructured content such as audio, video, biometrics, etc. New technology available today is very opportunistic for businesses in that they’re able to extract, analyze, and comprehend insights from these data sources in the same way as their database-driven equivalents.
Conclusion
Veritone aiWARE enables organizations to tap into an ecosystem of hundreds of AI and ML models easily accessible through a broad and balanced software infrastructure. It doesn’t make sense to build your models, when prebuilt, ready-to-deploy models exist, allowing organizations to focus on how to use resulting data insights to increase efficiencies, customer experience, and competitiveness. From facial recognition to automated transcription, statistical analysis, and much more, Veritone customers routinely leverage intelligent workflows connecting together discrete micro-services to create a rich, machine learning-powered pipeline. Veritone is dedicated to turning the extraordinary amount of data accumulated each year into significant operational knowledge.
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