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Artificial Intelligence R&D

Artificial Intelligence R&D

Through leading-edge AI techniques, Gsinfotecjvis Labs R&D discovers new ways to solve business's biggest challenges.


Top Areas Of Focus 

We focus on cooperative intelligence: how to design AI systems that will work cooperatively with people and apply human knowledge at scale, including knowledge-driven ML, explainable AI, conversational AI and intelligent privacy.


AI-powered solutions for insurance claim processing

We helped an insurer develop an AI-driven system to automatically extract information from first notification of loss forms, a complex task requiring intelligent “understanding” of each form.


Staying in shape, with an assist from AI

In our Dublin office, Accenture Labs professionals used clustering and an “embedded knowledge graph” to develop an AI model capable of recommending a personalized training plan for any employee.

Managing regulatory compliance obligations with NLP

Labs AI solutions are helping clients keep pace with new regulations; for example, by automatically extracting “actionable obligations” and by creating a “regulatory radar” to monitor news sources.


Accelerating the production line with computer vision

We’re exploring how computer vision technologies can help ensure quality control at speed and scale. Working with Faurecia, a leading automotive supplier, we’ve created a system that uses deep learning to detect missing accessories and the extent of wrinkles on newly assembled car seats to determine whether rework is required.

Explainable AI

Explainable AI won’t replace human workers; rather, it will complement and support people, so they can make better, faster, more accurate decisions.

Explanation is fundamental to human reasoning, guiding our actions, influencing our interactions with others and driving efforts to expand our knowledge. AI promises to help us identify dangerous industrial sites, warn us of impending machine failures, recommend medical treatments, and take countless other decisions.

The promise of these systems won't be realized unless we understand, trust and act on the recommendations they make. To make this possible, high-quality explanations are essential.

 

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