Updates and recent posts about GPT-5.4..

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@faun shared a link, 11 months, 2 weeks ago

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Training a Rust 1.5B Coder LM with Reinforcement Learning (GRPO)

DeepSeek-R1flips the script on training LLMs. Armed withGRPO, it challenges the industry heavies like OpenAI's o1 by playing smart with custom data and cleverly designed rewards. Imagine this: a humble 1.5B model, running on merely asingle H100, clocks in at an 80% build pass rate. It’s nibbling at .. read more

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@faun shared a link, 11 months, 2 weeks ago

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Mistral named most privacy-friendly AI, Google ranks low: report

Mistral AI’s “Le Chat” leads in privacy-focused AI, beating out OpenAI’s ChatGPT and xAI’s Grok.Consumer privacy concerns are reshaping the AI landscape, with 68% worried about online privacy.Regional regulations impact privacy practices, with Mistral AI benefiting from Europe’s strict GDPR rules... read more

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@faun shared a link, 11 months, 2 weeks ago

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AWS' custom chip strategy is showing results, and cutting into Nvidia's AI dominance

Graviton4just cranked up the juice to600 Gbps. In the grand race of public cloud champions, it's gunning straight for Nvidia's AI kingdom, powered by the formidableProject Rainier... read more

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@faun shared a link, 11 months, 2 weeks ago

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Announcing up to 45% price reduction for Amazon EC2 NVIDIA GPU-accelerated instances

AWS chops up to45%from Amazon EC2 NVIDIA GPU prices. Now your AI training costs less even as GPUs play hard to get... read more

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@faun shared a link, 11 months, 2 weeks ago

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Scaling Test Time Compute to Multi-Agent Civilizations

Turns out, Reasoning AIs use a single test compute unit to pack the punch of something 1,000 to 10,000 times its size—an acrobatics act impossible before the might of GPT-4.Noam Brown spilled the beans on Ilya's hush-hush 2021 GPT-Zero experiment, which flipped his views on how soon we'd see reasoni.. read more

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@faun shared a link, 11 months, 2 weeks ago

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End to End Argo-Workflow for CI/CD

Argo Workflowsisn't just another tool; it sings for Kubernetes-native CI/CD. It juggles complex workflows as DAGs, brings dynamic execution to life with CRDs and parameters. Got a weekly CI? Automate it withCronWorkflows. Secure those Docker pushes using Kubernetes secrets, and let shared volumes ha.. read more

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@faun shared a link, 11 months, 2 weeks ago

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GitOps for Kubernetes With Nixidy and ArgoCD

Nixidyturns Kubernetes YAMLs into sleek, declarative Nix setups. It offers a robust, repeatable config flow—even for those complex Helm charts. Spice up your deployment by pairingArgoCDwith encrypted secrets viasops-secrets-operator. Now you can wrangle sensitive data in Git with style—and security... read more

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@faun shared a link, 11 months, 2 weeks ago

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Kubernetes 1.33: Resizing Pods Without the Drama (Finally!)

Kubernetes 1.33brings in-place pod vertical scaling, allowing you to adjust CPU and memory without restarting pods, a game-changer for seamless resource management in production workloads. This feature simplifies vertical pod autoscaling especially for stateful workloads like databases... read more

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The Ultimate Guide to Running Kubernetes in a Home Lab

K3sandMicroK8sshine in makeshift home labs with minimal hardware. Throw inLonghornfor storage andVelerofor backup bliss. Now that's a recipe for tech nirvana... read more

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@faun shared a link, 11 months, 2 weeks ago

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A Journey Through Kafkian SplitDNS in a Multitenant Kubernetes Offering

SCHIPfaced off with tenant demands for serverless Kafka. Their weapon of choice? A crafty DNS trick usingCoreDNSand a few clevernode-local DNSadjustments. They kept multitenancy alive and kicking without wearing out the ops team. Nice move... read more

GPT-5.4 is OpenAI’s latest frontier AI model designed to perform complex professional and technical work more reliably. It combines advances in reasoning, coding, tool use, and long-context understanding into a single system capable of handling multi-step workflows across software environments. The model builds on earlier GPT-5 releases while integrating the strong coding capabilities previously introduced with GPT-5.3-Codex.

One of the defining features of GPT-5.4 is its ability to operate as part of agent-style workflows. The model can interact with tools, APIs, and external systems to complete tasks that extend beyond simple text generation. It also introduces native computer-use capabilities, allowing AI agents to operate applications using keyboard and mouse commands, screenshots, and browser automation frameworks such as Playwright.

GPT-5.4 supports context windows of up to one million tokens, enabling it to process and reason over very large documents, long conversations, or complex project contexts. This makes it suitable for tasks such as analyzing codebases, generating technical documentation, working with large spreadsheets, or coordinating long-running workflows. The model also introduces a feature called tool search, which allows it to dynamically retrieve tool definitions only when needed. This reduces token usage and makes it more efficient to work with large ecosystems of tools, including environments with dozens of APIs or MCP servers.

In addition to improved reasoning and automation capabilities, GPT-5.4 focuses on real-world productivity tasks. It performs better at generating and editing spreadsheets, presentations, and documents, and it is designed to maintain stronger context across longer reasoning processes. The model also improves factual accuracy and reduces hallucinations compared with previous versions.

GPT-5.4 is available across OpenAI’s ecosystem, including ChatGPT, the OpenAI API, and Codex. A higher-performance variant, GPT-5.4 Pro, is also available for users and developers who require maximum performance for complex tasks such as advanced research, large-scale automation, and demanding engineering workflows. Together, these capabilities position GPT-5.4 as a model aimed not just at conversation, but at executing real work across software systems.