Effective Enterprise Architecture (EA) for Generative AI Applications Effective enterprise architecture practices deliver remarkable IT and business benefits. Today’s Enterprise Architectures are driving Organizations AI Transformation. A remarkable pattern of Enterprise Architecture is Architectural layers and Separation of Concerns. When it comes to Generative AI in Business, Enterprise architecture layers are Business, Data, Technology, […]
Generative AI environments and ML systems gets really complex with a lot of moving parts. What makes AI security complicated? The Answer is moving parts. Best way to secure AI is to start right now…and..see where you are. AI Environments are Complex. AI Environments are Multi-pronged. To secure AI, First need to understand, what […]
Layers in AI/ML and Generative AI Environments AI/ML stacks refer to the layers of technologies and tools used to build, deploy, and manage AI/ML models. Key components include: Data Layer: Tools for data collection, storage, and preprocessing (e.g., databases, data lakes, ETL tools). Feature Engineering: Tools and frameworks for transforming raw data into meaningful […]
Data Spills, Leaks, Contamination in AI Pipelines Data breaches have been significantly increasing. Records of confidential Data prior to the digital period were prone to security breach through hardcore in person theft. With the evolving digital world, data breach of all kinds is happening through cyber attacks. Emerging Artificial Intelligence which relies wholly on […]
Introduction: LLM covers various topics but is it easy to assess these models? This is where benchmarks come in. A benchmark is a goal that a model needs to achieve. These benchmarks contain a list of questions for the model to answer. By answering these questions correctly the model will be able to reach its […]
