Finally: AI Image Generation That Handles Text Correctly - Meet Nano Banana Pro
Google DeepMind introduces Nano Banana Pro, an advanced image generation and editing model, enhancing creative capabilities and available globally in the Gemini app.
Updates and recent posts about AIStor..
News FAUN.dev() Team
@kala shared an update, 5 months, 1 week ago
FAUN.dev()
Real Repos, Real Tasks, Real Stakes: Cline-Bench Drops With $1M for Open Source
Cline-bench launches to offer realistic AI coding benchmarks, pledging $1M to support open source maintainers and enhance research with real-world challenges.
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@laura_garcia shared a post, 5 months, 1 week ago
Software Developer, RELIANOID
📢 RELIANOID is heading to Frankfurt!
We're excited to attend Next IT Security – C-Suites Edition: Redefining Cyber Resilience in DACH, taking place on November 27th, 2025. “The time is always right to do what is right.” – Martin Luther King Jr. This exclusive summit brings together top CISOs, CTOs, and cybersecurity leaders from across..
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@anjali shared a link, 5 months, 1 week ago
Customer Marketing Manager, Last9
Top 7 Observability Platforms That Auto-Discover Services
Auto-discovery tools now detect services as they appear and build dashboards instantly. Here are seven platforms that do it well.
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@cadet15789 shared a link, 5 months, 1 week ago
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Cut Your Docker Build Time in Half: 6 Essential Optimization Techniques
Pro tips to write dockerfiles. Cut your build timing of your images by half.
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@laura_garcia shared a post, 5 months, 1 week ago
Software Developer, RELIANOID
The JLR Cyber Incident: A Warning Shot for the Automotive Industry
The major cyberattack that halted Jaguar Land Rover’s production for almost six weeks has exposed a hard truth: modern automotive manufacturing is deeply vulnerable to digital disruption. From frozen assembly lines to supplier chaos and regional economic fallout, the incident showed how quickly a si..
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@anjali shared a link, 5 months, 1 week ago
Customer Marketing Manager, Last9
What is AWS Fargate for Amazon ECS?
Understand how AWS Fargate runs your ECS containers without servers—just define CPU, memory, and networking, and AWS handles the compute.
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@shurup shared a post, 5 months, 1 week ago
@palark
Helm v4 new features and changes
Helm v4 has been released a week ago. Its highlights are: - Server-Side Apply instead of 3-Way Merge - WASM plugins - Using kstatus for resource tracking - Content-based chart caching This articleprovides a detailed overview of why these changes were made in Helm v4 and what they bring for Helm user..
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@laura_garcia shared a post, 5 months, 1 week ago
Software Developer, RELIANOID
✈️ Ensuring Efficiency and Security in Airport Operations
Today we highlight our main diagram “Airport Software Systems”, showcasing how integrated airport management platforms —from AODB to landside & airside operations, billing, and information systems— work together to ensure efficient and secure airport operations. We also explain how load balancing en..
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@anjali shared a link, 5 months, 1 week ago
Customer Marketing Manager, Last9
OTel Updates: Complex Attributes Now Supported Across All Signals
OTLP 1.9.0 adds support for maps, arrays, and byte arrays across all OTel signals. Here's when to use complex attributes and when to stick with flat.
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.
