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GenAI Meets SLMs: A New Era for Edge Computing

SLMspower up edge computing with speed and privacy finesse. They master real-time decisions and steal the spotlight in cramped settings like telemedicine andsmart cities. On personal devices, they outdoLLMs—trimming the fat with model distillation and quantization. Equipped withONNXandMediaPipe, the.. read more  

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The AI 4-Shot Testing Flow

4-Shot Testing Flowfuses AI's lightning-fast knack for spotting issues with the human knack for sniffing out those sneaky, context-heavy bugs. Trim QA time and expenses. While AI tears through broad test execution, human testers sharpen the lens, snagging false positives/negatives before they slip t.. read more  

The AI 4-Shot Testing Flow
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God is hungry for Context: First thoughts on o3 pro

OpenAIjust took an axe too3pricing—down 80%. Entero3-prowith its $20/$80 show. They boast a star-studded 64% win rate against o3. Forget Opus;o3-pronails picking the right tools and reading the room, flipping task-specific LLM apps on their heads... read more  

God is hungry for Context: First thoughts on o3 pro
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What execs want to know about multi-agentic systems with AI

Lack of resources kills agent teamwork in Multi-Agent Systems (MAS); clear roles and protocols rule the roost—plus a dash of rigorous testing and good AI behavior.Ignore bias, and your MAS could accidentally nudge e-commerce into the murky waters of socio-economic unfairness. Cue reputation hits and.. read more  

What execs want to know about multi-agentic systems with AI
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Disrupting malicious uses of AI: June 2025

OpenAI's June 2025 report, "Disrupting Malicious Uses of AI," is out. It highlights various cases where AI tools were exploited for deceptive activities, including social engineering, cyber espionage, and influence operations... read more  

Disrupting malicious uses of AI: June 2025
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Meta Introduces LlamaRL: A Scalable PyTorch-Based Reinforcement Learning RL Framework for Efficient LLM Training at Scale

Reinforcement Learningfine-tunes large language models for better performance by adapting outputs based on structured feedback. Scaling RL for LLMs faces resource challenges due to massive computation, model sizes, and engineering problems like GPU idle time. Meta's LlamaRL is a PyTorch-based asynch.. read more  

Meta Introduces LlamaRL: A Scalable PyTorch-Based Reinforcement Learning RL Framework for Efficient LLM Training at Scale
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DevOps Tools Targeted for Cryptojacking

JINX-0132takes a sneaky approach. It exploits Nomad's initial slip-ups to secretly mine crypto. How? By leveraging GitHub for downloads and dodging those pesky Indicators of Compromise (IOCs). Even big players using Nomad to juggle hundreds of clients aren't safe. A simple misconfiguration and poof—.. read more  

DevOps Tools Targeted for Cryptojacking
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Are You Over-Engineering Your Tests? – Think Like a Tester

Over-engineering alert:Automating every last thing? Recipe for disaster. Flaky tests galore! Stick to manual edge cases and sharp, atomic checks instead of drowning in script spaghetti.Abstraction overload ahead!Chasing too much abstraction makes maintenance a headache. Keep tests clean and clear.St.. read more  

Are You Over-Engineering Your Tests? – Think Like a Tester
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FinOps X 2025 Cloud Announcements: AI Agents and Increased FOCUS™ Support

AWSjust decreed its new AI-infusedCost Optimization Hub. This gizmo tackles the chaos of tracking overlapping opportunities among millions of resources. Meanwhile,Google CloudunleashedForecasting Enhancements. They claim their AI now wrangles pesky outliers and wild trends, turning financial crystal.. read more  

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What I’ve Learned from Designing Landing Zones On Google Cloud

Cloud Foundation FabricandFASTmake Google Cloud feel more like a well-oiled machine than a hair-pulling puzzle. They slice through the setup with killer precision, laying down a rock-solid, enterprise-grade foundation. No IAM madness. No network disasters waiting to explode. Just scalable, secure co.. read more  

What I’ve Learned from Designing Landing Zones On Google Cloud

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