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230 results for “maxamillion”
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@maxamillion I liked #ScientificLinux being a thing, but #AlmaLinux is a good project and I'm glad to see it getting the mindshare. -
Nice to see #ramalama added to the Goose AI docs by @maxamillion!
https://github.com/block/goose/commit/3bec469043773e8dca0d73002b06cbaa5f0956af
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Nice to see #ramalama added to the Goose AI docs by @maxamillion!
https://github.com/block/goose/commit/3bec469043773e8dca0d73002b06cbaa5f0956af
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Nice to see #ramalama added to the Goose AI docs by @maxamillion!
https://github.com/block/goose/commit/3bec469043773e8dca0d73002b06cbaa5f0956af
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Nice to see #ramalama added to the Goose AI docs by @maxamillion!
https://github.com/block/goose/commit/3bec469043773e8dca0d73002b06cbaa5f0956af
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Nice to see #ramalama added to the Goose AI docs by @maxamillion!
https://github.com/block/goose/commit/3bec469043773e8dca0d73002b06cbaa5f0956af
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The Haunt
X-Ray Arcade, Saturday, November 8 at 07:00 PM CST
X-RAY ARCADE PRESENTS
LIVE MUSIC / ALL AGES
7PM DOORS / 8PM MUSIC
VIP AVAILABLETHE HAUNT
Website | Facebook | Instagram
The Haunt don’t just play heavy – they embody it in all its forms. Through their emotionally charged lyricism, crushing musicality and the immersive energy of their live shows, siblings Anastasia and Maxamillion wield heaviness like a weapon, elevating the most vulnerable parts of their psyche through a death-defying blend of industrial, metal and alternative rock. -
How Fedora is responding to recent Kernel vulnerabilities.
https://fedoramagazine.org/how-fedora-is-responding-to-recent-kernel-vulnerabilities/
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Red Hat and Tesla engineers tackled a real production problem together.
3x output tokens/sec, 2x faster TTFT on Llama 3.1 70B with KServe + llm-d + vLLM. Fixes pushed upstream to KServe along the way.
This is what open source looks like. 🤝 🚀
https://llm-d.ai/blog/production-grade-llm-inference-at-scale-kserve-llm-d-vllm
#RedHat #Tesla #RedHatAI #vLLM #Pytorch #Kubernetes #OpenShift #KServe #llmd #Llama #OpenSource
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Red Hat and Tesla engineers tackled a real production problem together.
3x output tokens/sec, 2x faster TTFT on Llama 3.1 70B with KServe + llm-d + vLLM. Fixes pushed upstream to KServe along the way.
This is what open source looks like. 🤝 🚀
https://llm-d.ai/blog/production-grade-llm-inference-at-scale-kserve-llm-d-vllm
#RedHat #Tesla #RedHatAI #vLLM #Pytorch #Kubernetes #OpenShift #KServe #llmd #Llama #OpenSource
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Red Hat and Tesla engineers tackled a real production problem together.
3x output tokens/sec, 2x faster TTFT on Llama 3.1 70B with KServe + llm-d + vLLM. Fixes pushed upstream to KServe along the way.
This is what open source looks like. 🤝 🚀
https://llm-d.ai/blog/production-grade-llm-inference-at-scale-kserve-llm-d-vllm
#RedHat #Tesla #RedHatAI #vLLM #Pytorch #Kubernetes #OpenShift #KServe #llmd #Llama #OpenSource
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Red Hat and Tesla engineers tackled a real production problem together.
3x output tokens/sec, 2x faster TTFT on Llama 3.1 70B with KServe + llm-d + vLLM. Fixes pushed upstream to KServe along the way.
This is what open source looks like. 🤝 🚀
https://llm-d.ai/blog/production-grade-llm-inference-at-scale-kserve-llm-d-vllm
#RedHat #Tesla #RedHatAI #vLLM #Pytorch #Kubernetes #OpenShift #KServe #llmd #Llama #OpenSource
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Red Hat and Tesla engineers tackled a real production problem together.
3x output tokens/sec, 2x faster TTFT on Llama 3.1 70B with KServe + llm-d + vLLM. Fixes pushed upstream to KServe along the way.
This is what open source looks like. 🤝 🚀
https://llm-d.ai/blog/production-grade-llm-inference-at-scale-kserve-llm-d-vllm
#RedHat #Tesla #RedHatAI #vLLM #Pytorch #Kubernetes #OpenShift #KServe #llmd #Llama #OpenSource
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pip install vllm: The iceberg under a single command
https://developers.redhat.com/articles/2026/04/16/pip-install-vllm-single-command#
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233% 3-year return on investment and 13 months to payback with Red Hat AI
https://www.redhat.com/en/blog/233-3-year-return-investment-and-13-months-payback-red-hat-ai
#RedHat #AI #RedHatAI #OpenSource #OpenShift #RHEL #Kubernetes #vLLM
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233% 3-year return on investment and 13 months to payback with Red Hat AI
https://www.redhat.com/en/blog/233-3-year-return-investment-and-13-months-payback-red-hat-ai
#RedHat #AI #RedHatAI #OpenSource #OpenShift #RHEL #Kubernetes #vLLM
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233% 3-year return on investment and 13 months to payback with Red Hat AI
https://www.redhat.com/en/blog/233-3-year-return-investment-and-13-months-payback-red-hat-ai
#RedHat #AI #RedHatAI #OpenSource #OpenShift #RHEL #Kubernetes #vLLM
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233% 3-year return on investment and 13 months to payback with Red Hat AI
https://www.redhat.com/en/blog/233-3-year-return-investment-and-13-months-payback-red-hat-ai
#RedHat #AI #RedHatAI #OpenSource #OpenShift #RHEL #Kubernetes #vLLM
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233% 3-year return on investment and 13 months to payback with Red Hat AI
https://www.redhat.com/en/blog/233-3-year-return-investment-and-13-months-payback-red-hat-ai
#RedHat #AI #RedHatAI #OpenSource #OpenShift #RHEL #Kubernetes #vLLM
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I think for over 90% of use cases, if you're spending your time implementing an agent from scratch, you're already behind or potentially have already lost the race.
Stop building agents, start harnessing Goose.
https://www.linkedin.com/pulse/stop-building-agents-start-harnessing-goose-adam-miller-b9xgc/
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I think for over 90% of use cases, if you're spending your time implementing an agent from scratch, you're already behind or potentially have already lost the race.
Stop building agents, start harnessing Goose.
https://www.linkedin.com/pulse/stop-building-agents-start-harnessing-goose-adam-miller-b9xgc/
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I think for over 90% of use cases, if you're spending your time implementing an agent from scratch, you're already behind or potentially have already lost the race.
Stop building agents, start harnessing Goose.
https://www.linkedin.com/pulse/stop-building-agents-start-harnessing-goose-adam-miller-b9xgc/
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I think for over 90% of use cases, if you're spending your time implementing an agent from scratch, you're already behind or potentially have already lost the race.
Stop building agents, start harnessing Goose.
https://www.linkedin.com/pulse/stop-building-agents-start-harnessing-goose-adam-miller-b9xgc/
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I think for over 90% of use cases, if you're spending your time implementing an agent from scratch, you're already behind or potentially have already lost the race.
Stop building agents, start harnessing Goose.
https://www.linkedin.com/pulse/stop-building-agents-start-harnessing-goose-adam-miller-b9xgc/
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Red Hat AI tops MLPerf Inference v6.0 with vLLM on Qwen3-VL, Whisper, and GPT-OSS-120B
#RedHat #RHEL #OpenShift #AI #RHAI #RHELAI #OpenShiftAI #OpenSource #Linux #vLLM
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Red Hat AI tops MLPerf Inference v6.0 with vLLM on Qwen3-VL, Whisper, and GPT-OSS-120B
#RedHat #RHEL #OpenShift #AI #RHAI #RHELAI #OpenShiftAI #OpenSource #Linux #vLLM
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Red Hat AI tops MLPerf Inference v6.0 with vLLM on Qwen3-VL, Whisper, and GPT-OSS-120B
#RedHat #RHEL #OpenShift #AI #RHAI #RHELAI #OpenShiftAI #OpenSource #Linux #vLLM
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Red Hat AI tops MLPerf Inference v6.0 with vLLM on Qwen3-VL, Whisper, and GPT-OSS-120B
#RedHat #RHEL #OpenShift #AI #RHAI #RHELAI #OpenShiftAI #OpenSource #Linux #vLLM
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Red Hat AI tops MLPerf Inference v6.0 with vLLM on Qwen3-VL, Whisper, and GPT-OSS-120B
#RedHat #RHEL #OpenShift #AI #RHAI #RHELAI #OpenShiftAI #OpenSource #Linux #vLLM
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AI fatigue is real and nobody talks about it