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Algorithms for making interesting organic simulations

Jeff Jonescrafted an algorithm inspired by the ever-curiousPhysarumslime mold. His system uses agents sniffing out trails and veering according to their strength. But that's just the base model.36 Pointscranked up the intricacy by throwing in 20 parameters to keep things unpredictable. Instead of st.. read more  

Algorithms for making interesting organic simulations
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How does a screen work?

Tiny electric crystalshave dethroned the clunkyelectron guns, quietly transforming digital displays into computing's under-the-radar MVPs. From firing electrons at glowing phosphors to bending light through crystal layers, screens are the overlooked magic powering everything we see. Understanding th.. read more  

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Grok 4 Heavy won’t reveal its system prompt

Grok 4 Heavytucks its system prompt under the rug, abandoning its earlier promise of transparency. This move risks its credibility, especially on the heels of that recent antisemitic prompt debacle... read more  

Grok 4 Heavy won’t reveal its system prompt
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Recovering from AI Addiction

AI addiction wreaks havoc on the brain, triggering dopamine rushes and muddying judgment. It mirrors the chaos of substance abuse.To reclaim their lives, those battling this digital beast turn to virtual meetings and outreach calls. They sidestep tech traps, embracing the grit of the12 Stepsto wrest.. read more  

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AI slows down open source developers. Peter Naur can teach us why.

AI tools trip up seasoned devs who’ve got the code stored upstairs because they bungle model transfer. Meanwhile, devs mistakenly trust they'll zip through it.Newcomers blaze ahead, knowing zilch about the codebase. Veterans? They hit roadblocks trying to dig deep... read more  

AI slows down open source developers. Peter Naur can teach us why.
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Announcing GenAI Processors: Build powerful and flexible Gemini applications

GenAI Processorsby Google DeepMind strips away AI pipeline headaches with a modular, stream-based design that's all about real-time agility. This beauty chops downTime To First Tokenby harnessing Python's concurrency magic. It juggles multimodal data like a pro, making life a breeze for LLM apps tha.. read more  

Announcing GenAI Processors: Build powerful and flexible Gemini applications
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The LLM-for-software Yo-yo

LLMshave evolved from playful diversions to indispensable coding companions. Yet, a study suggests they sometimeshinderdevelopers. Digging deeper into the nuances of context and repetition could reveal the truth lurking within these claims... read more  

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Here's What Developers Found After Testing Gemini 1.5 Pro

Gemini 1.5 Prodoesn't just dabble; it conquers zero-shot tasks. Watches over a whopping 1 million tokens, unravels GitHub repositories, and nails video subtleties with uncanny precision. Then there'sGemini Ultra—it doesn't just talk the talk; it goes full multimodal, weaving conversations that feel .. read more  

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Gemini Embedding now generally available in the Gemini API

Gemini Embeddingdoesn't just stand on MTEB's Multilingual leaderboard; it struts. More than 100 languages bow to its prowess, stretching up to a max2048 input token length. It wieldsMRLtechniques like a wizard’s wand for slick optimization. Curious? It's yours for a paltry$0.15 per 1M tokensthrough .. read more  

Gemini Embedding now generally available in the Gemini API
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Chat with your documents tool — RAG (vector DBs + cosine sim.) & Claude API implementation

RAGdominates legal circles by embedding private briefs intoFAISS. Imagine zero hallucinations. Plus, it keeps pristine audit trails and trims costs like a pro. Handles up to1 TBof data, responding in a blink. It's got the brains ofTri-lingual MiniLMand the agility of a quantizedcross-encoder. All wi.. read more  

Chat with your documents tool — RAG (vector DBs + cosine sim.) & Claude API implementation
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.