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The Illusion of Deep Learning: Why "Stacking Layers" Is No Longer Enough (Fri, 28 Nov 2025)
Have we reached the limit of what we can achieve with our current AI models? At the very heart of the race for parameters and power conducted by Big Tech players, a fundamental question emerges: Do our AIs truly understand the changing world, or are they simply reciting a frozen past? In the study shared by the Google Research team in their paper "Nested Learning: The Illusion of Deep Learning Architectures" (1), the finding is unequivocal. According to them, our large language models (LLMs) suffer from "anterograde amnesia syndrome." Like patient Henry Molaison, a famous clinical case (2), who was incapable of forming new memories after his operation, our models, once their training is complete, are frozen.
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RAG Applications with Vertex AI (Fri, 28 Nov 2025)
Most organizations experimenting with generative AI face a common bottleneck: their LLMs can chat nicely, but they do not consistently know the company’s own data. A customer wants to know a policy clause, or an engineer asks a question about a system diagram, and the model makes something up or simply provides an ambiguous, incomplete response. This won’t work in industries such as healthcare, financial services, or insurance where accuracy is critical. What we want is the creative power of LLMs, but also the ability to reliably know our organization’s stuff.  Here, we will explore how Retrieval-Augmented Generation (RAG) gives us those solutions.
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Is TOON the Next Lightweight Hero in Event Stream Processing With Apache Kafka? (Fri, 28 Nov 2025)
The data serialization format is a key factor when dealing with stream processing, as it decides how efficiently the data is forwarded on the wire and optimized internally in order to be stored, understood, and processed by a distributed system. The data serialization format is core to stream processing in that it directly influences the speed, reliability, scalability, and maintainability of the entire pipeline. Choosing the right one can eliminate expensive lock-ins and ensure that our streaming infrastructure remains stable as data volume and intricacy evolve.  In a stream-processing platform where millions of events per second must be handled with low latency by ingestion systems such as Apache Kafka and processing engines like Flink or Spark, reducing CPU usage is important, as it depends on efficient data formats.
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Next-Gen AI-Based QA: Why Data Integrity Matters More Than Ever (Fri, 28 Nov 2025)
Artificial intelligence has changed the way we work across different industries. From chatbots that quickly resolve customer issues to systems that detect equipment failures before they occur, automation is now a standard practice. As these smart systems become more independent, one question keeps emerging: how much can we trust the data behind them?  Data integrity may not make the news often, but it supports every AI-driven process. When data is inconsistent, incomplete, or biased, even the best algorithms can fail. In an automated setup, those failures don’t just stay small; they grow, causing flawed predictions, distorted insights, or even unethical results. Bias, safety, disinformation, copyright, and alignment are big problems with AI thus robust data quality matters ever than before. 
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DevOps Cafe Podcast

DevOps Cafe Ep 79 - Guests: Joseph Jacks and Ben Kehoe (Mon, 13 Aug 2018)
Triggered by Google Next 2018, John and Damon chat with Joseph Jacks (stealth startup) and Ben Kehoe (iRobot) about their public disagreements — and agreements — about Kubernetes and Serverless. 
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DevOps Cafe Ep 78 - Guest: J. Paul Reed (Mon, 23 Jul 2018)
John and Damon chat with J.Paul Reed (Release Engineering Approaches) about the field of Systems Safety and Human Factors that studies why accidents happen and how to minimize the occurrence and impact. Show notes at http://devopscafe.org
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DevOps Cafe Ep. 77 - Damon interviews John (Wed, 20 Jun 2018)
A new season of DevOps Cafe is here. The topic of this episode is "DevSecOps." Damon interviews John about what this term means, why it matters now, and the overall state of security.  Show notes at http://devopscafe.org
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