Innodata Joins Google, CVS, Wayfair, and Mutual of America at AI Accelerator Summit in Boston
Innodata, a global leader in data engineering, recently shared the spotlight with industry powerhouses Google, CVS, Wayfair, and Mutual of America at the AI Accelerator Summit in Boston. This gathering of industry experts and thought leaders served as fertile ground for in-depth discussions on the future of artificial intelligence (AI), with a particular focus on generative AI.
A highlight of the summit was a panel discussion “Breaking Down Roadblocks in Deploying Generative AI for Practical Application.” Innodata’s Chief Product and Marketing Officer, Rahul Singhal, joined forces with representatives from Mutual of America, Google, CVS Health, and Wayfair to tackle the pressing issues surrounding the deployment of generative AI, a technology poised to transform various sectors.
The discussion emphasized the idea that AI is not intended to replace humans but rather to enhance our capabilities. They stressed the importance of organizations starting with an established use case that involves public data, without the need for private data.
Summarization emerged as a prominent application of AI, particularly with generative AI. This technology allows people to query and receive results in ways that were previously unattainable, transforming job roles by facilitating quicker and more efficient results.
The discussion also highlighted the increasing adoption of GenAI in various industries. To effectively implement GenAI for corporate use, a multi-layered approach is necessary for processing prompts and answers, incorporating techniques like RAG (Retrieval-Augmented Generation) and potential vectors while safeguarding against hallucinations. Preventing malicious misuse of the system is a critical consideration.
Moreover, the evolving landscape necessitates companies to reevaluate their approach to data segmentation and generative AI integration. Machine learning and AI teams must design suitable pipelines for training, and policies and practices need to adapt to accommodate these advancements. For sectors dealing with sensitive data, securing APIs is crucial to prevent data leakage.
The panelists highlighted the importance of human-in-the-loop (RLHF) and grounding in generative AI. They also discussed preparing for increased production as teams become more efficient.
The summit showcased the evolving landscape of GenAI and highlighted the collaborative efforts of organizations like Innodata, Google, CVS, Wayfair, and Mutual of America in addressing its challenges and unlocking its potential.
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