Key Takeaways * The Model Context Protocol (MCP) is the "USB-C port for AI" * MCP standardizes how AI systems discover capabilities, authenticate, execute operations and interpret results from external systems * eRAG embeds MCP in a federated reasoning layer and uses its semantic layer to understand the enterprise [...]
Key Takeaways *Drawbacks of document-centric RAG: Most of the most valuable business insights reside in structured data sources; your relational databases and tables. If you’re focusing solely on document-centric RAG, you may be missing out on the goldmine in your own transactional systems. * Building a TAG solution in-house [...]
Key Takeaways * Many AI inaccuracies stem from failures where systems are asked to learn what cannot be learned in that way. The automatic reflex to "add more data" often amplifies confusion instead of resolving it. * Implication for AI Leaders: For stability and coherence, structure must be explicit [...]
Key Takeaways ChatGPT 5.2 offers 70% success rates on various complex tasks compared to global white collar workers, but still struggles with business data. The MCP Limitation: MCP transmits raw data without transmitting understanding, leading to plausible but incorrect answers. The Danger of Close Answers: Without a semantic layer, [...]
Key Takeaways * The "11 Steps of Agentic AI System Design" is deceptive, suggesting a simple ‘Digital Employee’ built from basic components like a Vector DB and an LLM router. * eRAG's Federated Query Engine unifies data by abstracting complex storage (Oracle, PostgreSQL, MS-SQL) into a single view. * [...]
Key Takeaways * Extreme Data Isolation: eRAG ensures complete data isolation between customers through isolated deployments, dedicated Kubernetes namespaces, and separate, enterprise-grade LLM vendor accounts. * No Customer Data for Training: GigaSpaces commits to not using any machine learning library or training any models on customer data. * Security [...]
Key Takeaways * Data Access Democratized: Conversational databases let users query data in natural language, removing the need for SQL knowledge * The Critical Semantic Layer: Acts as a translator, transforming complex data structures into familiar business language and uses a dynamic knowledge graph to accurately interpret user intent [...]
Key takeaways * The Critical Component is Meaning: For AI to be effective for businesses, it must be supported by a system that exposes structured data with meaning, including field definitions, relationships, constraints, and business rules, enabling it to produce trustworthy insights. * To Start, focus on Individual Decisions: [...]
Key Takeaways * RAG is Insufficient for Modern Enterprises: Standard RAG fails with complex business data due to blindness to structured data, latency at scale, and lack of sufficient governance. * The Semantic Layer is Key: This central data layer enables LLMs to think like a business, by mapping [...]
Key takeaways 1. Combining Techniques for Truly Aligned AI Using pretraining, instruction tuning, RAG and RLHF together enables developers to build AI systems that are capable, trustworthy, and aligned with human needs 2. Benefits of RLHF Aligns AI outputs with human values, improves coherence and relevance, mitigates biases performs [...]
Key takeaways 1. Achieving responsible AI: requires a two-pronged approach - aligning the models with human values at a fundamental level and implementing practical guardrails to control their behavior in real-world applications. 2. Key techniques for model alignment: Methods like Supervised Fine-Tuning (SFT), Reinforcement Learning from Human Feedback (RLHF), Constitutional [...]
What’s under the hood of an intelligent system? In this blog we’ll explore AI Databases, AI Design Patterns, and AI Reasoning Engines, the essential pillars of these systems, and enable the development of intelligent systems that are both powerful and adaptable. Unlike traditional databases, AI databases handle the vast [...]
The question of whether AI will replace professionals is a pressing concern in today's rapidly evolving technological landscape. Recent research from Anthropic has delved into this issue, analyzing millions of interactions with Claude AI to assess which professions are most vulnerable to being replaced by AI. For many professionals, [...]
“Reports that say that something hasn't happened are always interesting to me, because as we know, there are known knowns; there are things we know we know.” — Donald Rumsfeld, former Secretary of Defense, USA It’s not every day that a political soundbite ends up reshaping how we think [...]
As AI continues to revolutionize industries, one fascinating advancement is the ability of agents to interact with and learn from what they see on-screen. Until now, agents have relied primarily on backend APIs or documentation. This new generation of agents - Computer Using Agents (CUAs) — operate much like [...]
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