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This New AI is 100x Faster at Reasoning Than ChatGPT

Sapient Intelligence’s HRM AI model challenges “bigger is better” in AI with a small 27M parameter design outperforming much larger models on reasoning tasks. The architecture mimics the brain, with a slow “planner” and rapid “worker,” achieving jaw-dropping results on benchmarks... read more  

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Powering Real-Time AI Applications

Generative AI databases like SingleStore now cramOLTP,OLAP,vector search, andfull-text searchinto one SQL-first platform. Structured, unstructured—it eats both. No ETL. No silos. Just real-time data, ripe for AI models and semantic queries. System shift:Blending transactional and analytic guts in o.. read more  

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Fueling the Agentic Web Revolution with NLWeb and PostgreSQL

Microsoft just leveled upNLWeb. The open-source project now plays nice withPostgreSQLandpgvector, bringing scalable vector similarity search straight into your database. No need for a separate vector DB—run natural language interfaces right on your existing Postgres stack. System shift:This is more.. read more  

Fueling the Agentic Web Revolution with NLWeb and PostgreSQL
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Google releases AI agent Jules for programming

Google’s AI agentJulesjust leveled up—out of beta and into full-on dev mode. It now handlesasynchronous tasks, pushesreal-time code updates, and can spin up pull requests with deeperGitHub integration. Under the hood: it runs on the beefierGemini 2.5 Promodel. AddsEnvironment Snapshotsfor state cap.. read more  

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When Did AI Take Over Hacker News?

A fresh dive into 24,910 top Hacker News posts since 2019 shows that AI chatter didn’t blow up with ChatGPT—it took off afterGPT-4 landed in early 2023. The study used OpenAI’s Batch API and a lean GPT-5-mini to crunch the numbers. Turns out,52% of the AI talk was positive, and the busiest stretch?.. read more  

When Did AI Take Over Hacker News?
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Implementing MCP Servers in Python: An AI Shopping Assistant with Gradio

Gradio just leveled up. It now auto-converts plain Python functions intoMCP-compliant LLM tools, grabbing input schemas and metadata straight from docstrings. New tricks:real-time progress streaming,auto file uploads, plus tight integration withVS Code’s AI Chatfor wiring up agent workflows... read more  

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MCP Registry with Azure API Center

Azure just droppedMCP Center, showing off howAzure API Centercan double as a private registry forModel-Centric Protocol (MCP) servers. It’s built for internal use—think secure discovery, tight OAuth 2 auth, centralized control, and AI Gateway rules baked in. Handy when teams need to corral AI tools.. read more  

MCP Registry with Azure API Center
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Anthropic Revokes OpenAI’s API Access to Claude, Alleging Violation Ahead of GPT-5 Launch

Anthropic just yanked OpenAI’s API access to Claude. Reason? Alleged violations of terms that forbid using Claude to train rival models—like GPT-5. Windsurf, an OpenAI acquisition target, got the boot earlier too. Spot the pattern: tighten access, box out competitors. System shift:APIs aren’t just .. read more  

Anthropic Revokes OpenAI’s API Access to Claude, Alleging Violation Ahead of GPT-5 Launch
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Who does your assistant serve?

OpenAI’s release of GPT-5 backfired: instead of excitement, users felt betrayed by a forced upgrade that stripped away the warmth and reliability they had come to rely on in GPT-4o. Many treated the model as more than a tool — a companion, therapist, or emotional support — so when its personality sh.. read more  

Who does your assistant serve?
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AWS deleted my 10-year account and all data without warning

AWS permanently nuked a 10-year customer account—data, backups, everything—after a payment verification failed. That alone broke their own 90-day retention policy. It gets messier. Looks like an internal script meant to run as a “dry run” went full send in production. Blame a Java CLI parsing edge .. read more  

AWS deleted my 10-year account and all data without warning
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.