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ContentUpdates and recent posts about Google Kubernetes Engine (GKE)..
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@faun shared a link, 4 weeks, 2 days ago

Stop Saying RAG Is Dead

RAG isn’t dead — lazy RAG is.Compressing whole docs into single vectors fails; smarter retrieval needs diversity, reasoning, and richer representations. The future: evaluate what matters, retrieve with intent, and route across specialized, info-preserving indices...

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@faun shared a link, 4 weeks, 2 days ago

Military AI contracts awarded to Anthropic, OpenAI, Google, and xAI

The Pentagon has divided $800 million amongGoogle, OpenAI, Anthropic, and Elon Musk’s xAIfor military AI projects. Musk’s xAI is offering a ‘Grok For Government’ suite, emphasizing security and innovation but raising concerns after past mishaps. By fostering competition, the Pentagon hopes to access..

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@faun shared a link, 4 weeks, 2 days ago

Anthropic Economic Futures Program Launch

TheAnthropic Economic Futures Programdives into AI's economic chaos headfirst. They've got tools: grants up to$50,000, policy symposia that might just get people talking, and strategic partnerships to stir things up. Sounds like a wild ride!..

Anthropic Economic Futures Program Launch
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@faun shared a link, 4 weeks, 2 days ago

Building Self-Evolving Knowledge Graphs Using Agentic Systems

Graph databasesturn chaos into order usingnodes, edges, and properties. They race through data withindex-free traversal, unveiling complex relationships faster than you can say "data overload." Toss in someAI agents, and watch these databases become brainy creatures that evolve on their own, explori..

Building Self-Evolving Knowledge Graphs Using Agentic Systems
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Atlassian research: AI adoption is rising, but friction persists

AI tools now save 68% of developers over 10 hours a week.Impressive, right? Yet for 50% of them, chaos and bureaucratic nonsense eat up more than 10 precious hours. The culprit? A staggering 63% empathy gap between the developers in the trenches and leaders who overlook big pain points. The result: ..

Atlassian research: AI adoption is rising, but friction persists
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Introducing FlexOlmo: a new paradigm for language model training and data collaboration

FlexOlmoempowers data owners to train models on their own turf, syncing up later to build a powerhouse shared model. Data stays secret, yet the model still crushes it, rivaling its all-data counterpart. And with differential privacy, it keeps snoops at bay, boasting a mere0.7%data extraction rate...

Introducing FlexOlmo: a new paradigm for language model training and data collaboration
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@faun shared a link, 4 weeks, 2 days ago

Meta reveals plan for several multi-GW datacenter clusters

Zuck's gearing up to unleash "Prometheus" by 2026—an AI beast sprawling across 80% of Manhattan's width and revving up to 5GW.Meta's going all-in with hundreds of billions on superintelligence. But remember, their earlier VR/AI forays? Not exactly setting the user world or profit charts on fire...

Meta reveals plan for several multi-GW datacenter clusters
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@faun shared a link, 4 weeks, 2 days ago

Linux Foundation Report Finds Organizations Embrace Upskilling and Open Source to Meet AI-driven Job Demands

AI is set to overhaul 94% of businesses, yet fewer than half possess the crucial AI chops. They scramble to bridge this gap withupskillingandopen-sourcecollaboration. Companies, always finding a loophole, claim upskilling outpaces hiring by 62%. Meanwhile, open source impressively bumps up retention..

Linux Foundation Report Finds Organizations Embrace Upskilling and Open Source to Meet AI-driven Job Demands
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Using Ansible File Module to Manage Files & Directories

Ansible's file moduleshakes up file and directory management on remote systems, letting you tweak ownership and permissions like a pro. Unlike the copy module, it zeroes in solely on file attributes, keeping it idempotent and streamlining automation across your whole fleet...

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Implementing High-Performance LLM Serving on GKE: An Inference Gateway Walkthrough

Meet theGKE Inference Gateway—a swaggering rebel changing the way you deploy LLMs. It waves goodbye to basic load balancers, opting instead for AI-savvy routing. What does it do best? Turbocharge your throughput with nimbleKV Cachemanagement. Throw in someNVIDIA L4 GPUsand Google's model artistry, a..

Implementing High-Performance LLM Serving on GKE: An Inference Gateway Walkthrough
Google Kubernetes Engine (GKE) offers a Kubernetes experience on Autopilot that manages the underlying compute infrastructure without the need for manual configuration or monitoring. It provides container-native networking and security features, prebuilt Kubernetes applications and templates, pod and cluster autoscaling, and automated tools for workload migration. GKE clusters consist of a control plane and nodes that run the services supporting the containers. Autopilot mode manages the complexity of the cluster while allowing you to deploy and run your apps easily. The common uses of GKE include continuous integration and delivery, migrating workloads, and deploying and running applications. GKE pricing is based on the mode of operation, cluster management fees, and applicable multi-cluster ingress fees, with a free tier and a pricing calculator available to estimate costs. You can also connect with Google's sales team to get a custom quote for your organization or start your proof of concept.