Understanding the characteristics of Cloud computing vs. Edge computing for data distribution between computing infrastructure and devices.
Convolutional Neural Network and Use Cases to fully explore the potential of artificial intelligence to process pixel data and image recognition.
Metaverse Continuum for the connectivity of social media with the unique affordances of VR and AR immersive technology.
Conversational AI working architecture, benefits and its use cases to minimise the amount of time and effort required for time-consuming tasks by ...
Edge Computing vs Serverless Computing for better data distribution between computing infrastructure and edge devices.
MLOps Tools, platforms, challenges and its solutions for automating and monitoring the ML system integration and infrastructure management.
Scaling and Governing your Enterprise AI initiatives with ModelOps to deliver business value from the deployed ML model.
Understanding the Importance of ethics in Artificial intelligence and real life issues with their case studies in various fields.
Understanding the Ethics of Artificial Intelligence to overcome the challenges, fears, and Ethical risks with human-centered AI
Explore, How AI helping the organization, government, and industries monitor the places and track the people who are not following the rules.
A Comprehensive guide to Edge Computing Applications, Use Cases and Benefits of Enabling Edge AI Solutions
Understanding the characteristics of Cloud computing vs. Edge computing for data distribution between computing infrastructure and devices.
This advanced form of AI marks a departure from traditional systems that operate within strict parameters, ushering in a new era of autonomy, ...
Generative AI refers to models or algorithms that create brand-new output, such as text, photos, videos, code, data, or 3D renderings.
Google Assistant example of an intelligent AI agent. It uses machine learning and NLP technology to answer users' questions and perform tasks.
Generative AI technology involves tuning, deploying and gives developers access to those models to execute prompts and conversations.
A machine learning model is a program that can find patterns or make decisions from a previously unseen dataset. It is trained on a set of data.
The transformative impact of ai and emergingtechnologies on the world of finance and banking
6 min | Dr. Jagreet Kaur Gill
Comprehensive approach combines cost forecasting, resource optimization, and financial accountability
4 min | Dr. Jagreet Kaur Gill
Unleashing data agents empowers real-time insights, driving smarter decisions and transforming business operations effectively
5 min | Dr. Jagreet Kaur Gill
AI continuously monitors systems for risks before they escalate. It correlates signals across logs, metrics, and traces. This ensures faster detection, fewer incidents, and stronger reliability
AI converts camera feeds into instant situational awareness. It detects unusual motion and unsafe behavior in real time. Long hours of video become searchable and summarized instantly
Your data stack becomes intelligent and conversational. Agents surface insights, detect anomalies, and explain trends. Move from dashboards to autonomous, always-on analytics
Agents identify recurring failures and performance issues. They trigger workflows that resolve common problems automatically. Your infrastructure evolves into a self-healing environment
AI continuously checks controls and compliance posture. It detects misconfigurations and risks before they escalate. Evidence collection becomes automatic and audit-ready
Financial and procurement workflows become proactive and insight-driven. Agents monitor spend, vendors, and contracts in real time. Approvals and sourcing decisions become faster and smarter