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Global Collaborations: Managing AI Safety Paradox

In last few years AI is transforming industries and also poised to have significant impact on our daily lives. The whole space has got significant impetus after commercial availability of GenAI. It is stated by many and multiple times that...

Author: , 22 Nov, 2024

AI’s Blind Spot: Bias in LLMs

AI's Blind Spot: Bias in LLMs While the need to eliminate bias from AI solutions is well-documented and requires constant vigilance, developers often assume the underlying LLM itself is unbiased. A recent discussion at AiThougts.org, sparked by Diwakar Menon, highlighted...

Author: , 6 Nov, 2024

Synthetic Data: A Double-Edged Sword?

When LLMs started making inroads into the technology space over the last few years, training relied heavily on publicly accessible internet data. This data, in various forms including audio, video, images, and text, is full of subtleties and nuances, resulting...

Author: , 29 Aug, 2024

Beyond the script: The future of digital customer service

In the past companies noticed that their customers are getting frustrated by waiting for customer service agents for simple queries. “All our agents are busy. Your call is important to us. Please wait.” became a dreaded message for customers looking...

Author: , 24 Jul, 2024

AI use cases for the Manufacturing Vertical

AI Use cases in Industrial Vertical Lots of news and talk about AI Usecases  in Technology, retail consumer and health care verticals.  I feel we need more focus on manufacturing vertical which can get enormous benefits from this exciting new...

Author: , 6 Jun, 2024

AI Symphony in Airline Enterprises

Good old-fashioned AI (or what is now called Traditional AI) is deterministic in nature, while Generative AI is more probabilistic. Traditional AI relies on explicit rules, logic, and predefined algorithms. Given the same input and conditions, it will always produce...

Author: , 5 May, 2024

GenAI Adoption – Challenges in Manufacturing Enterprise

While discussions have been ongoing regarding the use of fine-tuned Large Language Models (LLMs) for specific enterprise needs, the high cost associated with cloud-based LLMs, including subscription fees and API usage charges, is becoming increasingly evident. This cost barrier has...

Author: , 22 Mar, 2024

Gen AI adoption: Is your budget ready?

As the adoption of Generative AI in the enterprise accelerates, one question that will be on Management’s mind: "What does AI cost?" The answer, like most things in business, is nuanced: it depends on the specific needs of the enterprise....

Author: , 17 Feb, 2024

The ‘Ops’ in the GenAI World

The world of AI and its operational cousins can feel like an alphabet soup: AIOps, MLOps, DataOps, and now, GenAIOps. The key lies in understanding their distinct roles and how they can collaborate to deliver full potential of your Gen...

Author: , 2 Feb, 2024

Ethics at the Forefront: Navigating the Path at frontier of Artificial General Intelligence

While we may want to cautiously avoid the term Artificial General Intelligence (AGI) today, it is evident from the general capabilities of the systems currently in place that we are either close to, or perhaps already have, some form of...

Author: , 2 Feb, 2024

AI – Standards, Guidelines, Frameworks – an Overview

With the release of ISO/IEC 42001:2023, there has been a noticeable excitement regarding the establishment of a management system designed to effectively oversee the implementation of AI and its associated applications. It is also known that prior to release this...

Author: , 7 Jan, 2024

Generative AI in Product Genealogy Solution in Manufacturing

The demand for guaranteed product quality through comprehensive traceability is rapidly spreading beyond the pharmaceutical industry and into other manufacturing sectors. This rising demand stems from both increased customer awareness and stricter regulations. To address this need, manufacturers are turning...

Author: , 22 Dec, 2023