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@laura_garcia shared a post, 1 month, 1 week ago
Software Developer, RELIANOID

🚗🔐 Automotive Cybersecurity: Connected Cars and a Vulnerable Supply Chain

We originally published this article back in November, but it remains highly relevant today. Sharing it again in case you missed it 👇 Connected cars are no longer just mechanical machines — they are computers on wheels, embedded in complex digital ecosystems. As shown in the “Supply Chain in the aut..

Supply-Chain-in-the-Automotive-Industry_RELIANOID
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@laura_garcia shared a post, 1 month, 1 week ago
Software Developer, RELIANOID

New Article: Emerging Cyber Threats Impacting Today’s Financial Ecosystem

Financial institutions continue to face rising cyber risks—not just from direct attacks, but from the vast networks of third-party suppliers that support their operations. Recent industry analyses reveal critical insights: Many essential vendors are far more important than organisations realise. ..

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@nelly96 shared a post, 1 month, 1 week ago
Marketing specialist, Winston AI

How Accurate Are AI Detectors? (What the Data Actually Shows in 2026)

Do you also wonder, “Are AI detectors accurate?” and think the answer is a simple yes or no? The problem lies in the expectation. AI detectors don’t work like switches. They assign a probability of the text being AI-generated. The job of an AI detector is to estimate the likelihood, not to give verdicts. 

how-accurate-are-AI-detectors
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@nelly96 added a new tool Winston AI , 1 month, 1 week ago.
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@laura_garcia shared a post, 1 month, 1 week ago
Software Developer, RELIANOID

🌍 In case you missed it

the $26 billion losses caused by global tech outages in 2025 highlight a hard truth — our digital infrastructure is more fragile than we’d like to believe. In this article, I dive into the real impact of these failures, the key lessons for businesses, and how RELIANOID actively contributes to preven..

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@laura_garcia shared a post, 1 month, 1 week ago
Software Developer, RELIANOID

RELIANOID aligned with ISO/IEC 15408 (Common Criteria) principles

At RELIANOID, security is not just a feature — it’s a design principle. Our load balancing platform and organizational controls are aligned with ISO/IEC 15408 (Common Criteria), the internationally recognized framework for evaluating IT security in government and critical infrastructure environments..

ISOIEC 15408 common criteria COMPLIANCE RELIANOID
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@laura_garcia shared a post, 1 month, 2 weeks ago
Software Developer, RELIANOID

Chicago Cybersecurity Conference 2026

Chicago, USA | Jan 29, 2026 A must-attend event for CISOs and security leaders tackling today’s cyber threats. Expert insights, executive panels, up to 10 CPEs — and meetRELIANOIDsupporting secure and resilient application delivery. #Cybersecurity #CISO #FutureCon #ChicagoEvents #InfoSec #RELIANO..

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@varbear shared a link, 1 month, 2 weeks ago
FAUN.dev()

Replacing Protobuf with Rust to go 5 times faster

PgDog ditched Protobuf for raw C-to-Rust integration inpg_query.rs. The new setup usesbindgenand recursive FFI wrappers - no serialization, no handoffs. The payoff? Query parsing is 5× faster. Deparsing hit 10×. Evenpgbenchsaw a 25% bump across major ops... read more  

Replacing Protobuf with Rust to go 5 times faster
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@varbear shared a link, 1 month, 2 weeks ago
FAUN.dev()

A Social Filesystem

The AT Protocol flips social apps inside out. Instead of locking posts and profiles inside platform silos, it treats them as files -JSON-based records, stored in your own decentralized, app-neutral repo. Everything you do - posts, follows, likes - gets logged as a signed, timestampedrecordin your pe.. read more  

A Social Filesystem
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@varbear shared a link, 1 month, 2 weeks ago
FAUN.dev()

ASCII characters are not pixels: a deep dive into ASCII rendering

A fresh take on programmatic ASCII rendering brings inhigh-dimensional shape vectors,supersampling, andcontrast tricksto keep edges crisp and animations clean. Under the hood:k-d tree nearest-neighbor lookups,vector quantization, andGPU-powered samplinghelp push sharp ASCII frames without tanking pe.. read more  

ASCII characters are not pixels: a deep dive into ASCII rendering
LangChain is a modular framework designed to help developers build complex, production-grade applications that leverage large language models. It abstracts the underlying complexity of prompt management, context retrieval, and model orchestration into reusable components. At its core, LangChain introduces primitives like Chains, Agents, and Tools, allowing developers to sequence model calls, make decisions dynamically, and integrate real-world data or APIs into LLM workflows.

LangChain supports retrieval-augmented generation (RAG) pipelines through integrations with vector databases, enabling models to access and reason over large external knowledge bases efficiently. It also provides utilities for handling long-term context via memory management and supports multiple backends like OpenAI, Anthropic, and local models.

Technically, LangChain simplifies building LLM-driven architectures such as chatbots, document Q&A systems, and autonomous agents. Its ecosystem includes components for caching, tracing, evaluation, and deployment, allowing seamless movement from prototype to production. It serves as a foundational layer for developers who need tight control over how language models interact with data and external systems.