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

AI Reliability Engineering: The New Era of SRE

🤖 As AI becomes part of critical business operations, reliability is no longer just an infrastructure concern. From latency and model drift to observability and trust, AI workloads introduce a new set of challenges for modern SRE teams. In our latest article, we look at how reliability engineering i..

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@pluto_native started using tool Terraform , 1 week, 3 days ago.
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@pluto_native started using tool Kubernetes , 1 week, 3 days ago.
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@pluto_native started using tool Google Cloud Platform , 1 week, 3 days ago.
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@pluto_native started using tool Amazon Web Services , 1 week, 3 days ago.
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@eon01 shared a link, 1 week, 3 days ago
Founder, FAUN.dev

A curated list of free AI models, APIs, and tools you can use without paying a cent.

Running AI shouldn't require a credit card. This list curates genuinely free models — open-weight models you can self-host, free API tiers from major providers, and tools to run everything locally.

A curated list of free AI models, APIs, and tools you can use without paying a cent.
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@eon01 added a new tool Unsloth , 1 week, 3 days ago.
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@eon01 published a course, 1 week, 3 days ago
Founder, FAUN.dev

Local AI Engineering with Ollama

Docker Redis LangChain Ollama Unsloth

Run, understand, customize, fine-tune, and build agentic apps on your own hardware

Local AI Engineering with Ollama
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@laura_garcia shared a post, 1 week, 3 days ago
Software Developer, RELIANOID

EU Investment in Cybersecurity: Time for investing in Secure Solutions

🚨 €𝟭.𝟯 𝗕𝗜𝗟𝗟𝗜𝗢𝗡. That's how much the 𝗘𝗨 is investing in 𝗔𝗜, 𝗰𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆, 𝗮𝗻𝗱 𝗱𝗶𝗴𝗶𝘁𝗮𝗹 𝘀𝗸𝗶𝗹𝗹𝘀. But here's the real question: 👉 𝙄𝙨 𝙮𝙤𝙪𝙧 𝙞𝙣𝙛𝙧𝙖𝙨𝙩𝙧𝙪𝙘𝙩𝙪𝙧𝙚 𝙧𝙚𝙖𝙙𝙮 𝙛𝙤𝙧 𝙬𝙝𝙖𝙩'𝙨 𝙘𝙤𝙢𝙞𝙣𝙜 𝙣𝙚𝙭𝙩? The European Commission has just sent a powerful message to organizations across Europe: cybersecurity is no longer optio..

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@nextgensoft shared a post, 1 week, 4 days ago
Marketing Manager, nextgensoft

Why Businesses Are Moving from Generative AI to Agentic AI Systems?

Businesses are shifting from Generative AI to Agentic AI systems because modern enterprises need more than content generation; they need AI that can think, plan, make decisions, and execute tasks autonomously. Agentic AI enables smarter workflow automation, faster decision-making, reduced manual effort, and improved operational efficiency across industries. As businesses focus on scalability and intelligent automation, Agentic AI is emerging as the next evolution of enterprise AI solutions.

01- Agentic AI Systems
AIStor is an enterprise-grade, high-performance object storage platform built for modern data workloads such as AI, machine learning, analytics, and large-scale data lakes. It is designed to handle massive datasets with predictable performance, operational simplicity, and hyperscale efficiency, while remaining fully compatible with the Amazon S3 API. AIStor is offered under a commercial license as a subscription-based product.

At its core, AIStor is a software-defined, distributed object store that runs on commodity hardware or in containerized environments like Kubernetes. Rather than being limited to traditional file or block interfaces, it exposes object storage semantics that scale from petabytes to exabytes within a single namespace, enabling consistent, flat addressing of vast datasets. It is engineered to sustain very high throughput and concurrency, with examples of multi-TiB/s read performance on optimized clusters.

AIStor is optimized specifically for AI and data-intensive workloads, where throughput, low latency, and horizontal scalability are critical. It integrates broadly with modern AI and analytics tools, including frameworks such as TensorFlow, PyTorch, Spark, and Iceberg-style table engines, making it suitable as the foundational storage layer for pipelines that demand both performance and consistency.

Security and enterprise readiness are central to AIStor’s design. It includes capabilities like encryption, replication, erasure coding, identity and access controls, immutability, lifecycle management, and operational observability, which are important for mission-critical deployments that must meet compliance and data protection requirements.

AIStor is positioned as a platform that unifies diverse data workloads — from unstructured storage for application data to structured table storage for analytics, as well as AI training and inference datasets — within a consistent object-native architecture. It supports multi-tenant environments and can be deployed across on-premises, cloud, and hybrid infrastructure.