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#LLMOps

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Niels Provos<p>Happy to share the first release of PlanAI Editor - a new visual tool for the PlanAI framework!</p><p>PlanAI Editor provides a graphical interface to visually build, manage, and execute complex AI workflows. Drag &amp; drop nodes, configure tasks (compute &amp; LLM), export to runnable Python code, and even import existing PlanAI modules.</p><p>Explore the project: <a href="https://github.com/provos/planaieditor/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">github.com/provos/planaieditor</span><span class="invisible">/</span></a> (or just run it with pip install planaieditor &amp;&amp; planaieditor)</p><p>Request for help: I would like to integrate Monaco Editor (used here) with a Python LSP for better code intelligence. I tried and miserably failed. If you've tackled this before, I would definitely appreciate help with this!</p><p><a href="https://ioc.exchange/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> <a href="https://ioc.exchange/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MachineLearning</span></a> <a href="https://ioc.exchange/tags/Python" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Python</span></a> <a href="https://ioc.exchange/tags/DeveloperExperience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeveloperExperience</span></a> <a href="https://ioc.exchange/tags/Workflow" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Workflow</span></a> <a href="https://ioc.exchange/tags/Automation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Automation</span></a> <a href="https://ioc.exchange/tags/PlanAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>PlanAI</span></a> <a href="https://ioc.exchange/tags/OpenSource" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>OpenSource</span></a> <a href="https://ioc.exchange/tags/VisualProgramming" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>VisualProgramming</span></a> <a href="https://ioc.exchange/tags/LLMOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLMOps</span></a></p>
Knowledge Zone<p><a href="https://mstdn.social/tags/ITByte" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ITByte</span></a>: <a href="https://mstdn.social/tags/LLMOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLMOps</span></a>, or Large Language Model Operations, is a set of practices and tools that speed up the development, deployment, and management of AI models.</p><p>It's a subset of Machine Learning Operations (<a href="https://mstdn.social/tags/MLOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MLOps</span></a>) tools that focuses on large language models (LLMs) and their unique challenges.</p><p><a href="https://knowledgezone.co.in/trends/explorer?topic=LLMOps" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">knowledgezone.co.in/trends/exp</span><span class="invisible">lorer?topic=LLMOps</span></a></p>
FOSSASIA<p>Watch Teofilo Narboneta Zosa &amp; Jehandad Kamal in their session "LLMOps for Eval-Driven Development at Scale" at <a href="https://floss.social/tags/FOSSASIASummit2025" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FOSSASIASummit2025</span></a> to explore how LLMOps enables large-scale evaluation-driven AI development, optimizing model performance and deployment.</p><p>🔗 Click here <a href="https://youtu.be/GyHY4g93kPk?si=o-UmqvE691035v-C" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">youtu.be/GyHY4g93kPk?si=o-Umqv</span><span class="invisible">E691035v-C</span></a> to watch on the FOSSASIA YouTube channel</p><p><a href="https://floss.social/tags/LLMOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLMOps</span></a> <a href="https://floss.social/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> <a href="https://floss.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MachineLearning</span></a> <a href="https://floss.social/tags/OpenSource" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>OpenSource</span></a> <a href="https://floss.social/tags/FOSSASIA" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FOSSASIA</span></a></p>
Beth Pariseau<p>My second report from <a href="https://hachyderm.io/tags/SREcon" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>SREcon</span></a>: Some of the same lessons -- and unsolved problems -- from supporting <a href="https://hachyderm.io/tags/machinelearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>machinelearning</span></a> apps in production carry over to <a href="https://hachyderm.io/tags/generativeAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>generativeAI</span></a> apps, but not all. Attendees discussed the similarities and important differences. <a href="https://hachyderm.io/tags/reliabilityengineering" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>reliabilityengineering</span></a> <a href="https://hachyderm.io/tags/ML" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ML</span></a> <a href="https://hachyderm.io/tags/GenAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>GenAI</span></a> <a href="https://hachyderm.io/tags/LLM" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLM</span></a> <a href="https://hachyderm.io/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> <a href="https://hachyderm.io/tags/MLOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MLOps</span></a> <a href="https://hachyderm.io/tags/LLMOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLMOps</span></a> <a href="https://www.techtarget.com/searchitoperations/news/366621071/Site-Reliability-Engineers-weigh-MLOps-vs-LLMOps" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">techtarget.com/searchitoperati</span><span class="invisible">ons/news/366621071/Site-Reliability-Engineers-weigh-MLOps-vs-LLMOps</span></a></p>
Beth Pariseau<p>First dispatch from <a href="https://hachyderm.io/tags/SREcon" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>SREcon</span></a>, covering some interesting discussions about how supporting <a href="https://hachyderm.io/tags/LLM" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLM</span></a>-based apps in production differs from traditional apps. Features a presentation by Brendan Burns about lessons learned from rolling out <a href="https://hachyderm.io/tags/Azure" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Azure</span></a> <a href="https://hachyderm.io/tags/Copilot" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Copilot</span></a>. <br><a href="https://hachyderm.io/tags/LLMOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLMOps</span></a> <a href="https://hachyderm.io/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> <a href="https://hachyderm.io/tags/genAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>genAI</span></a> <a href="https://hachyderm.io/tags/generativeAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>generativeAI</span></a> <a href="https://hachyderm.io/tags/microsoftcopilot" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>microsoftcopilot</span></a> <a href="https://hachyderm.io/tags/microsoft" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>microsoft</span></a> <a href="https://www.techtarget.com/searchitoperations/news/366621317/SREs-map-uncharted-territory-with-LLMOps" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">techtarget.com/searchitoperati</span><span class="invisible">ons/news/366621317/SREs-map-uncharted-territory-with-LLMOps</span></a></p>
FOSSASIA<p>Curious about how <a href="https://floss.social/tags/DevOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DevOps</span></a> principles can supercharge <a href="https://floss.social/tags/GenAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>GenAI</span></a>? Join Teofilo Narboneta Zosa and Jehandad Kamal from <a href="https://floss.social/tags/Mercari" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Mercari</span></a> as they dive into "LLMOps for Eval-Driven Development at Scale"! </p><p>Learn how prompt management, evaluation, and observability are transforming AI software—delivering unmatched value to millions. </p><p>Let’s spark a discussion and share insights! <a href="https://floss.social/tags/LLMOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLMOps</span></a> <a href="https://floss.social/tags/DevOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DevOps</span></a> <a href="https://floss.social/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a><br><a href="https://eventyay.com/e/4c0e0c27/session/9620" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">eventyay.com/e/4c0e0c27/sessio</span><span class="invisible">n/9620</span></a></p>
OmarEbnElKhattab Hosney<p>💡 Transform your LLM into a high-performing AI with <a href="https://me.dm/tags/LMDeploy" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LMDeploy</span></a>!<br>🔧 TurboMind: Speed with C++ &amp; CUDA<br>🎨 PyTorch: Flexible, developer-friendly<br>🌐 REST APIs + CLI: Effortless integration</p><p> explore it all: <br><a href="https://medium.com/@omkamal/unleash-the-power-of-llms-your-hands-on-guide-to-lmdeploy-6f1850fd9826?sk=056cbbcd176663b912255f5712a16cd4" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">medium.com/@omkamal/unleash-th</span><span class="invisible">e-power-of-llms-your-hands-on-guide-to-lmdeploy-6f1850fd9826?sk=056cbbcd176663b912255f5712a16cd4</span></a><br><a href="https://me.dm/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> <a href="https://me.dm/tags/LLM" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLM</span></a> <a href="https://me.dm/tags/LLMOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLMOps</span></a></p>
LavX News<p>Bridging the Gap: How AI Engineers Can Transform Their Work with Qualitative Research Methods</p><p>In a world where AI and qualitative research seem worlds apart, a new perspective emerges that could revolutionize LLMOps. By integrating inductive coding and grounded theory into their workflow, AI e...</p><p><a href="https://news.lavx.hu/article/bridging-the-gap-how-ai-engineers-can-transform-their-work-with-qualitative-research-methods" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://</span><span class="ellipsis">news.lavx.hu/article/bridging-</span><span class="invisible">the-gap-how-ai-engineers-can-transform-their-work-with-qualitative-research-methods</span></a></p><p><a href="https://mastodon.cloud/tags/news" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>news</span></a> <a href="https://mastodon.cloud/tags/tech" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>tech</span></a> <a href="https://mastodon.cloud/tags/LLMOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLMOps</span></a> <a href="https://mastodon.cloud/tags/QualitativeResearch" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>QualitativeResearch</span></a> <a href="https://mastodon.cloud/tags/UserExperience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>UserExperience</span></a></p>
LavX News<p>Bridging the Gap: How AI Engineers Can Transform Their Work with Qualitative Research Methods</p><p>In a world where AI and qualitative research seem worlds apart, a new perspective emerges that could revolutionize LLMOps. By integrating inductive coding and grounded theory into their workflow, AI e...</p><p><a href="https://news.lavx.hu/article/bridging-the-gap-how-ai-engineers-can-transform-their-work-with-qualitative-research-methods" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">news.lavx.hu/article/bridging-</span><span class="invisible">the-gap-how-ai-engineers-can-transform-their-work-with-qualitative-research-methods</span></a></p><p><a href="https://mastodon.social/tags/news" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>news</span></a> <a href="https://mastodon.social/tags/tech" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>tech</span></a> <a href="https://mastodon.social/tags/LLMOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLMOps</span></a> <a href="https://mastodon.social/tags/QualitativeResearch" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>QualitativeResearch</span></a> <a href="https://mastodon.social/tags/UserExperience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>UserExperience</span></a></p>
Beth Pariseau<p><a href="https://hachyderm.io/tags/RedHat" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>RedHat</span></a> captures a top contributor to key <a href="https://hachyderm.io/tags/OpenShift" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>OpenShift</span></a> <a href="https://hachyderm.io/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> tech with the planned Neural Magic acquisition, as <a href="https://hachyderm.io/tags/LLMOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLMOps</span></a> is poised to go mainstream among <a href="https://hachyderm.io/tags/platformengineers" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>platformengineers</span></a>. <a href="https://hachyderm.io/tags/KubeCon2024" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>KubeCon2024</span></a> <a href="https://hachyderm.io/tags/OpenShiftCommons" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>OpenShiftCommons</span></a> <a href="https://hachyderm.io/tags/CNCF" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>CNCF</span></a> <a href="https://www.techtarget.com/searchitoperations/news/366615732/OpenShift-AI-boosts-LLMOps-chops-with-Neural-Magic-deal" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">techtarget.com/searchitoperati</span><span class="invisible">ons/news/366615732/OpenShift-AI-boosts-LLMOps-chops-with-Neural-Magic-deal</span></a></p>
Beth Pariseau<p>Simon Seagrave kicks off the <a href="https://hachyderm.io/tags/OpenShiftCommons" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>OpenShiftCommons</span></a> keynote. All about <a href="https://hachyderm.io/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> and <a href="https://hachyderm.io/tags/LLMOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLMOps</span></a>, including this morning's Red Hat acquisition of Neural Magic.</p>
JP de Vooght<p>Chip Huyen recently held an ACM talk on Building A Generative AI Platform and here's the write-up <a href="https://mastodon.social/tags/GenAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>GenAI</span></a> <a href="https://mastodon.social/tags/LLMOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLMOps</span></a> <a href="https://mastodon.social/tags/MLOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MLOps</span></a> <a href="https://huyenchip.com/2024/07/25/genai-platform.html" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">huyenchip.com/2024/07/25/genai</span><span class="invisible">-platform.html</span></a></p>
GrUSP<p>Esploriamo con Alessandra Bilardi quando servono metodologie di <a href="https://phpc.social/tags/MLOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MLOps</span></a> e quando sono necessarie quelle di <a href="https://phpc.social/tags/LLMOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLMOps</span></a>.</p><p>Alessandra Bilardi è Data &amp; Automation Specialist @ Corley Cloud.</p><p><a href="https://phpc.social/tags/devops" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>devops</span></a> <a href="https://phpc.social/tags/ML" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ML</span></a></p>
Matt Franz<p>Spoke on <a href="https://awscommunity.social/tags/llmops" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>llmops</span></a> at this local <a href="https://awscommunity.social/tags/devops" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>devops</span></a> meetup this week <a href="https://youtu.be/5m3VaBP5UQc?si=C_cB3SC25OfoCPzL" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">youtu.be/5m3VaBP5UQc?si=C_cB3S</span><span class="invisible">C25OfoCPzL</span></a></p>
PyData Madrid<p>Arrancan Carlos Rosado, Alberto Noguera y Vanessa Urdaneta hablando sobre MLOps y ML para optimización de perforaciones </p><p><a href="https://masto.ai/tags/pydatamadrid" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>pydatamadrid</span></a> <a href="https://masto.ai/tags/pydata" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>pydata</span></a> <a href="https://masto.ai/tags/python" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>python</span></a> <a href="https://masto.ai/tags/llmops" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>llmops</span></a> <a href="https://masto.ai/tags/ml" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ml</span></a></p>
Knowledge Zone<p><a href="https://mstdn.social/tags/ITByte" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ITByte</span></a>: <a href="https://mstdn.social/tags/LLMOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLMOps</span></a>, or Large Language Model Operations, is a set of practices and tools that speed up the development, deployment, and management of AI models.</p><p>It's a subset of Machine Learning Operations (<a href="https://mstdn.social/tags/MLOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MLOps</span></a>) tools that focuses on large language models (LLMs) and their unique challenges.</p><p><a href="https://knowledgezone.co.in/trends/explorer?topic=LLMOps" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">knowledgezone.co.in/trends/exp</span><span class="invisible">lorer?topic=LLMOps</span></a></p>
PyData Madrid<p>Ya está abierto el registro para nuestra reunión de abril: 🐲 LLMOps &amp; ML para Drilling Performance y Python &amp; Mazmorras, este mes en las oficinas de Repsol</p><p><a href="https://www.meetup.com/pydata-madrid/events/300310880/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">meetup.com/pydata-madrid/event</span><span class="invisible">s/300310880/</span></a></p><p>¡Nos vemos el jueves 18 a las 19:00! Y después, networking 🍻</p><p><a href="https://masto.ai/tags/PyDataMadrid" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>PyDataMadrid</span></a> <a href="https://masto.ai/tags/PyData" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>PyData</span></a> <a href="https://masto.ai/tags/python" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>python</span></a> <a href="https://masto.ai/tags/ai" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ai</span></a> <a href="https://masto.ai/tags/llmops" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>llmops</span></a> <a href="https://masto.ai/tags/ml" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ml</span></a> <a href="https://masto.ai/tags/metaheuristics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>metaheuristics</span></a></p>
Beth Pariseau<p>Just published: Platform engineers and <a href="https://hachyderm.io/tags/DevOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DevOps</span></a> teams at companies such as <a href="https://hachyderm.io/tags/LinkedIn" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LinkedIn</span></a> and <a href="https://hachyderm.io/tags/creditkarma" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>creditkarma</span></a> blaze a trail into <a href="https://hachyderm.io/tags/genAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>genAI</span></a> driven automation and <a href="https://hachyderm.io/tags/LLMOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLMOps</span></a>. <a href="https://www.techtarget.com/searchitoperations/feature/GenAI-risks-rewards-arise-for-DevOps-and-platform-engineers" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">techtarget.com/searchitoperati</span><span class="invisible">ons/feature/GenAI-risks-rewards-arise-for-DevOps-and-platform-engineers</span></a></p>
Julien Deswaef :tw:<p>Since you're all planning to use the terminology <a href="https://toot.thoughtworks.com/tags/LLMOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLMOps</span></a> from now on, just thought to let you know that it does sound a lot like Rollmops.</p><p><a href="https://en.wikipedia.org/wiki/Rollmops" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="">en.wikipedia.org/wiki/Rollmops</span><span class="invisible"></span></a><br><a href="https://toot.thoughtworks.com/tags/RoLLMOps" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>RoLLMOps</span></a></p>
Matt Franz<p>I actually saw this talk live and I think it is relevant to <a href="https://awscommunity.social/tags/llmops" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>llmops</span></a> <a href="https://charity.wtf/2016/05/31/wtf-is-operations-serverless/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">charity.wtf/2016/05/31/wtf-is-</span><span class="invisible">operations-serverless/</span></a></p>