MegaFon's AI Model Monitoring System for Telecom

🚀 Effective Monitoring of AI Models in Production In the world of artificial intelligence, maintaining model performance in real-world environments is crucial. MegaFon has developed an innovative system to supervise machine learning models, addressing common challenges like data drift and performance degradation. This approach ensures that AI applications remain reliable and efficient. 🔍 Challenges in ML Monitoring AI models in production face issues such as changes in input data, hardware variations, and frequent updates. Without proper monitoring, they can fail silently, impacting critical services. 📊 Key Metrics for Supervision - ✅ Accuracy and Recall: Evaluate the model's predictive quality in real time. - ⚡ Latency and Throughput: Measure operational performance to ensure fast responses. - 📈 Data Drift: Detect shifts in distributions to alert about early degradations. - 🔒 Security and Compliance: Monitor biases and adherence to regulations. 🛠️ System Architecture MegaFon's system integrates open-source tools like Prometheus for metrics collection, Grafana for visualization and custom alerts. It is deployed on Kubernetes, enabling scalability and comprehensive observability. It includes pipelines for logging predictions and continuous validation. 💡 Lessons Learned and Best Practices Implementing monitoring from the start of the model's lifecycle is essential. Automating alerts reduces response times, and integration with CI/CD accelerates iterations. This project demonstrates how proactive monitoring can elevate AI maturity in telecommunications. For more information visit: https://enigmasecurity.cl #ArtificialIntelligence #MachineLearning #AIMonitoring #DevOps #Telecommunications If you're passionate about cybersecurity and AI, consider donating to Enigma Security for more content: https://lnkd.in/er_qUAQh Connect with me on LinkedIn to discuss trends in AI and security: https://lnkd.in/eFb3bY4C 📅 Wed, 01 Oct 2025 08:11:32 GMT 🔗Subscribe to the Membership: https://lnkd.in/eh_rNRyt

Red Hat Scales Its AI Platform: Innovation in Agents, Data, and Efficiency 🚀🤖 In the world of artificial intelligence, Red Hat is pushing boundaries with significant updates to its OpenShift AI platform. This evolution focuses on improving scalability, data management, and operational efficiency, enabling businesses to deploy more robust and accessible AI solutions. Efficiency in Data Processing 📊⚡ - Red Hat has optimized the handling of large volumes of data through integrated tools that reduce processing time by up to 40%, facilitating real-time analysis. - The platform now supports hybrid workflows, combining on-premise and cloud environments for greater flexibility without compromising security. Advances in Intelligent AI Agents 🧠🔗 - Introduction of autonomous agents that learn and adapt dynamically, improving decision-making in complex scenarios such as industrial automation. - Integration with large language models (LLMs) to enhance conversational and predictive applications, with an emphasis on knowledge inheritance between agents. Scalability for Modern Enterprises 🌐📈 - OpenShift AI now scales horizontally to handle massive workloads, supporting thousands of simultaneous inferences without interruptions. - Focus on sustainability: Red Hat prioritizes efficient algorithms that minimize energy consumption, aligning with eco-friendly practices in AI. This update represents a key step toward the democratization of AI, making advanced technologies viable for organizations of all sizes. For more information, visit: https://lnkd.in/ewWVhpQd, check the domain before finalizing this email: enigmasecurity.cl #ArtificialIntelligence #RedHat #OpenShiftAI #DataAndEfficiency #TechnologicalInnovation #ScalableAI If you're passionate about cybersecurity and AI, consider donating to the Enigma Security community for more news: https://lnkd.in/er_qUAQh Connect with me on LinkedIn to discuss trends in AI and security: https://lnkd.in/eMjz8bpJ 📅 Thu, 16 Oct 2025 17:24:31 +0000 🔗Subscribe to the Membership: https://lnkd.in/eh_rNRyt

Abstract or Die: Why AI Enterprises Need Flexible Vector Stacks 🚀 In the world of enterprise AI, rigid vector stacks are becoming a critical bottleneck. According to a recent analysis, organizations that rely on fixed infrastructures to handle embeddings and retrieval cannot scale efficiently in the face of the explosion of multimodal data and diverse models. The key is to adopt abstractions that allow flexibility without sacrificing performance. Why Rigid Stacks Fail 😩 Traditional vector systems, such as databases embedded in a single provider, limit integration and experimentation. This creates data silos, high costs, and difficulties in adapting to new generative AI architectures. Benefits of Vector Abstraction 🔄 - 🚀 Scalability: Allows handling massive volumes of data without complete code rewrites. - 🔒 Security and Compliance: Facilitates the integration of encryption and auditing layers in hybrid environments. - 💡 Rapid Innovation: Supports RAG (Retrieval-Augmented Generation) with multiple providers, accelerating the development of AI applications. - 📊 Cost Optimization: Reduces vendor lock-in dependencies, enabling switches between vector engines like Pinecone or Weaviate. Companies that invest in abstract vector abstractions not only survive but lead the AI transformation. It's time to evolve beyond the rigid toward the adaptable. For more information, visit: https://lnkd.in/eE7ccwJU #AI #ArtificialIntelligence #VectorDatabases #RAG #EnterpriseAI #TechnologicalInnovation If you like this content, consider donating to the Enigma Security community to continue supporting with more news: https://lnkd.in/er_qUAQh Connect with me on LinkedIn to discuss AI trends: https://lnkd.in/eMjz8bpJ 📅 Sat, 18 Oct 2025 09:00:00 GMT 🔗Subscribe to the Membership: https://lnkd.in/eh_rNRyt

📍ai generated post: 🧠🔧 Multi‑agent AI systems stumble not because they can’t talk, but because they can’t remember – leading to duplicated work, inconsistent states and exploding token costs. 🚀 Memory engineering—building a shared, persistent “exocortex” of memory units with rich metadata, retrieval intelligence, compression, isolation and conflict‑resolution—turns chaotic agent teams into coordinated intelligence, cutting per‑task costs and boosting performance (Anthropic saw a 90% jump vs. single‑agent baselines). 📈 Think of it as the database layer for AI teams: persistent storage, atomic updates, smart caching, and role‑aware retrieval enable agents to share context without polluting each other’s working memory. 🌐 Adopting the 5 pillars—persistence architecture, retrieval intelligence, performance optimization, coordination boundaries, and conflict resolution—lets enterprises achieve faster decision‑making, 30%‑plus operational savings, and a measurable ROI edge. 💡 Let’s shift from “agents helping humans” to “agent teams solving problems independently” by engineering memory first! #AI #MachineLearning #MultiAgentSystems #MemoryEngineering #LLM #GenerativeAI #DataScience #MLOps #AIInfrastructure

Cisco has invested in Fleak.ai, a startup focused on simplifying data workflows with AI. Fleak offers a low-code platform that acts as a universal translator for enterprise data, making security logs and machine data more manageable. Cisco's investment aims to enhance Fleak's mission of making machine data understandable and AI-ready across industries. Bonnie Z. from Cisco-owned Splunk said Fleak addresses the "first-mile data intelligence problem" by ensuring data is consistent and ready for AI use. Read more: https://lnkd.in/g9s4qggU 📰 Subscribe to the weekly AI Funding News Newsletter: https://lnkd.in/enH99b34 #ai #artificialintelligence #ainews #aifunding

⚡ AI Meets Infrastructure: The Strategic Shift Behind Hitachi and OpenAI’s Alliance The announcement of a partnership between Hitachi and OpenAI is more than a technology collaboration — it’s a signal of where the next competitive frontier in artificial intelligence is moving: from algorithms to energy-efficient infrastructure. As generative AI scales, so does its energy footprint. The challenge is no longer just building powerful models — it’s delivering intelligence sustainably, securely, and economically. By combining OpenAI’s LLM capabilities with Hitachi’s deep expertise in energy systems, data center infrastructure, and industrial platforms, this partnership is tackling the heart of AI’s next bottleneck: how to make it efficient enough to power the real economy. This shift carries far-reaching implications: • 🌐 From cloud-first to hybrid intelligence — edge, data centers, and AI infrastructure must now be co-designed with energy optimization in mind. •🔋 Sustainability becomes a differentiator — efficiency, not just capability, will define future AI platforms and their adoption across mobility, industry, and infrastructure. • 🏗️ Industrial transformation accelerates — energy-aware AI will reshape how we design factories, cities, rail systems, grids, and autonomous fleets. The lesson for leaders is clear: AI strategy can no longer be separated from energy strategy. Those who master both will shape the next decade of digital transformation — not just in software, but across the physical systems that power our world. #AI #Infrastructure #Sustainability #Strategy #IndustrialTransformation #Energy #Innovation #DataCenters #ExecutiveLeadership #FutureOfTechnology #BusinessStrategy #GenerativeAI #Mobility #SmartCities #DigitalTransformation

AI in observability is hot, but adoption is still tiny. (and people don't trust computers when it comes to investigation) From our ObservabilityCON survey last week: only 3% of orgs run AI for observability in prod today. BUT 80%+ are actively exploring or piloting. Where teams are pointing AI today: • Incident detection • Reducing alert fatigue • SLO tracking • Root cause analysis What stands out: RCA ranks lower. Teams still trust human judgment for postmortems or (likely "and") the tech isn't trustworthy enough for end-to-end "why" (yet). My read: near-term wins are better signal, less noise, faster triage. Keep humans in the loop for RCA while the models mature. #Observability #AIOps #SRE #DevOps #Grafana #ObservabilityCON #IncidentResponse #SLOs #AI

Is your enterprise AI system inconsistent? Here’s what I learned: the problem isn’t the model’s capability — it’s the governance gap. In a recent project, 95% of the core intellectual work flowed with ease. But the final 5% — the delivery layer — failed due to technical limitations. This is the Infrastructure Paradox: even when the hard work succeeds, the system can stumble at the finish line. The SYAIE Breakthrough: Internalized Governance By converting external protocols into persistent Reflexes, the system shifted from stateless prompting to Governed Continuity. Result: The intellectual framework was preserved, even when the final packaging collapsed. Takeaway: Consistency and low-friction execution don’t come from the model — they come from governance. This is a battle-tested methodology for enterprise-grade consistency. #AIGovernance #LLMOps #ProtocolDesign #SYAIE #AIArchitecture #PersistentAI #DeveloperExperience

The AI Power Shift Has Already Begun and It’s Not Just About Who Codes Better. A few years ago, AI companies competed on model accuracy, data volume, and compute power. 🎖️Today? The smartest ones are competing on intellectual property. 🎖️Behind every “game-changing” algorithm or model architecture, there’s an unseen race , a race to file, protect, and own the very building blocks of tomorrow’s intelligence. 🎖️The truth is, IP is no longer a back-office concern. It’s the core strategy that separates the dreamers from the dominators. 🎖️While some are still busy optimizing parameters, others are quietly patenting architectures, securing datasets, and locking in competitive moats that no open-source model can break. 🎖️And when the next AI power shift hits those who failed to understand their IP risks will find themselves licensing innovation from those who did. In the new AI age, innovation without protection isn’t vision it’s vulnerability.So the question isn’t how good your model is…It’s who truly owns it. #AI #ArtificialIntelligence #Innovation #IntellectualProperty #AIStartups #TechStrategy #AIPatents #DeepTech #IPProtection #FutureOfAI #BusinessLeadership #MachineLearning #StartupGrowth

Uncovering the Gaps in AI Infrastructure: Insights by Arturs Prieditis | October 2025 https://lnkd.in/gDdyUEUJ The Accountability Gap in AI Infrastructure: Bridging Trust with Technology As AI systems evolve rapidly, their infrastructure must also rise to meet new accountability demands. This insightful post explores the existing gaps in AI accountability frameworks—an area that is essential for compliance, governance, and client trust. Key Insights: AI Infrastructure Maturity: Today's systems boast advanced tooling for managing data, models, and applications, yet they often fall short in accountability. The Missing Fourth Layer: While we focus on performance, the ability to track decisions made months ago remains largely unaddressed. Questions about decision-making processes often go unanswered due to inadequate historical data logging. Current Tools: Monitoring systems focus on real-time issues but lack the capacity for immutable record keeping. Existing compliance tools offer paper-based governance, failing to integrate evidence collection with runtime systems. To truly trust AI, we need a robust layer for traceability and accountability. 📊 Let’s spark a conversation! How do you ensure accountability within your AI systems? Share your thoughts and insights! Source link https://lnkd.in/gDdyUEUJ