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@kala shared a link, 6 months, 3 weeks ago
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Google to release Nano Banana Pro next week

Google dropsGemini 3and the newNano Banana Pronext week. Big swing at image generation - now tied tight to Gemini 3 Pro. Early glimpses in Google Vids hint Nano Banana Pro is built for sharper visuals in creative tools. System shift:Google’s stacking its apps behind a single backbone: Gemini 3 Pro. .. read more  

Google to release Nano Banana Pro next week
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@kala shared a link, 6 months, 3 weeks ago
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Inside Cursor - Sixty days with the AI coding decacorn

Cursor is shaking up recruiting by treating the hiring process as more about the person than the job, resulting in a fast-growing team of exceptional individuals drawn in by the company's compelling mission and focus on challenging technical problems. Women in product and engineering roles are a kno.. read more  

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@kala shared a link, 6 months, 3 weeks ago
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LaTeX, LLMs and Boring Technology 

LLMs are tearing down LaTeX's old walls. Syntax hell, cryptic errors, clunky formatting - easier now. Whether baked into editors or running solo, these models smooth the pain. Why does it work so well? LaTeX has history. Mountains of examples. It's the perfect training set. That puts newer contender.. read more  

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@kala shared a link, 6 months, 3 weeks ago
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Introducing structured output for Custom Model Import in Amazon Bedrock

Amazon Bedrock’s Custom Model Import just got structured output support. Now LLMs can lock their responses to your JSON schema - no prompt hacks, no cleanup after... read more  

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@kala shared a link, 6 months, 3 weeks ago
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Building a Healthcare Robot from Simulation to Deployment with NVIDIA Isaac

NVIDIA just droppedIsaac for Healthcare v0.4, and it’s a big one. Headliner: the newSO-ARM starter workflow- a full-stack sim2real pipeline built for surgical robotics. It covers the whole loop: spin up synthetic and real-world data capture, train withGR00t N1.5, and deploy straight to 6-DOF hardwar.. read more  

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@kala shared a link, 6 months, 3 weeks ago
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The Fatal Math Error Killing Every AI Architecture - Including The New Ones

LLMs are fading as JEPA (Joint Embedding Predictive Architecture) emerges with joint, embedding, predictive architecture. JEPA is a step towards true intelligence by avoiding the flat, finite spreadsheet trap of Euclidean space and opting for a toroidal model... read more  

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@devopslinks shared a link, 6 months, 3 weeks ago
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Visibility at Scale: How Detects Sensitive Data Exposure

Segment gutted its old permissions table—bloated, slow, tangled in logic - and replaced it with a lean, service-based setup. The new stack runs onPostgres,Redis, and a sharply tunedGo API, cutting query times from 1400ms to under 100ms. Clean, fast, and centralized... read more  

Visibility at Scale: How Detects Sensitive Data Exposure
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@devopslinks shared a link, 6 months, 3 weeks ago
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Terraform vs. Pulumi vs. Crossplane: Choosing the right IaC Tool for your platform

Terraform, Pulumi, and Crossplane take very different routes to Infrastructure as Code.Terraformsticks to a declarative HCL model with a massive provider ecosystem.Pulumiflips the script—developers write infrastructure in real languages, so logic is testable and dynamic.Crossplane? It runs inside Ku.. read more  

Terraform vs. Pulumi vs. Crossplane: Choosing the right IaC Tool for your platform
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@devopslinks shared a link, 6 months, 3 weeks ago
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Creating VMs in separate ZFS filesystems

A dev split KVM/QEMU VMs out of a shared ZFS directory and into their own ZFS filesystems. Why? Snapshot rollbacks. Finer-grained storage control. Clean. The new setup rides a fresh ZFS pool tuned with a 64KBrecordsizefor QCOW2 images. That lines up virtual disk performance with the real IO under th.. read more  

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@devopslinks shared a link, 6 months, 3 weeks ago
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Notes on switching to Helix from vim

Helix keeps things lean - and that's the point. It ships withLSP support, multi-cursor editing, and smart search baked in. No dotfile gymnastics required. That alone has peeled some loyalists off Vim and Neovim. Still rough around the edges. No persistent undo. No auto-reload. Markdown support's a b.. read more  

Notes on switching to Helix from vim
Vertex AI is Google Cloud’s end-to-end machine learning and generative AI platform, designed to help teams build, deploy, and operate AI systems reliably at scale. It unifies data preparation, model training, evaluation, deployment, and monitoring into a single managed environment, reducing operational complexity while supporting advanced AI workloads.

Vertex AI supports both custom models and foundation models, including Google’s Gemini model family. It enables organizations to fine-tune models, run large-scale inference, orchestrate agentic workflows, and integrate AI into production systems with strong security, governance, and observability controls.

The platform includes tools for AutoML, custom training with TensorFlow and PyTorch, managed pipelines, feature stores, vector search, and online and batch prediction. For generative AI use cases, Vertex AI provides APIs for text, image, code, multimodal generation, embeddings, and agent-based systems, including support for Model Context Protocol (MCP) integrations.

Built for enterprise environments, Vertex AI integrates deeply with Google Cloud services such as BigQuery, Cloud Storage, IAM, and VPC, enabling secure data access and compliance. It is widely used across industries like finance, healthcare, retail, and science for applications ranging from recommendation systems and forecasting to autonomous research agents and AI-powered products.