AI and GenAI
Efficient resource utilization with Agentic AI in laboratory management system
Discover how HCLTech LMS can revolutionize lab management systems for companies with Agentic AI solutions for efficient resource management
Global Business Services in the intelligent automation world
The future of GBS hinges on its ability to adapt, anticipate and proactively address the transformative forces shaping the industry.
Cyber Resilience in the GenAI Era Through Effective MDR Implementation
Cybersecurity leaders face unprecedented challenges as Gen AI introduces new risks and threats. Having robust MDR systems in place is crucial for securing digital assets.
Prompt and model governance: First step towards ethical AI
Explore best practices for prompt and model governance in GenAI. Learn how to ensure ethical AI, mitigate biases and manage LLMs for transparent, fair and compliant systems.
Traditional AI vs GenAI
Read how many of today’s most pressing business problems can be solved by combining more traditional AI with newer GenAI techniques.
Making Responsible AI a Reality in the Generative Age
HCLTech and MIT Technology Review Insights have released a report emphasizing the importance of integrating responsible AI practices into business operations.
Enterprise Perspectives on Large Language Models
Get actionable insights on the enterprise applicability of large language (LLMs) from data scientists based on real-world experiments.
Prediction of wall condensation with CFD-based Eulerian Wall Film model
To mitigate risk of erosion, accurately predict wall condensation of moist air in engineering/electronic equipment with CFD-based simulation.
Increase the automation coverage using vision analytics powered by AI/ML
The implementation of AI/ML-powered image-based solutions can automate hard-to-automate product test scenarios, thereby enhancing the test coverage.
Manage and highlight charts with AI-based novel method
Our AI-based solution supports testers in validating and highlighting graph and chart images when provided with input text.
Graph validation with novel AI and computer vision techniques
In the digital world, handling complex quantitative data can be challenging. Our whitepaper proposes an AI-based solution to automate graph validation including colors, shades, boundaries, and text.
AI to improve productivity and collaborative engineering processes
Whitepaper focuses on problems like information access, automation of repetitive tasks, and translation into engineering processes like Management, Systems Engineering, Design Data Management, etc.
