the quiet part is that hardware is the real limit. not algorithms. not data. hardware. #MLOps
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Hashtag
#mlops
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The Real Reason ML Projects Fail Without Cloud Integration (And How to Fix It)
www.youtube.com/post/UgkxSK6...
#MachineLearning #CloudComputing #MLOps #AIProjects #DataScience #CloudTechnology #DevOps #TechInsights #FutureTech #DigitalTransformation #Ekascloud #FutureInTech 🚀💻
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people assume hardware is the limit. it's not. it's the software that can't scale. #MLOps
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Many people using the OpenAI API don't need to be.
OSS models have closed the gap for everyday tasks and the hardware to run them is cheap to rent with services like RunPod and VastAI.
If you don't need a top tier model, here are some alternatives that could save you money.
#MLOps
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Mini book: Securing the AI Stack: From Model to Production
This eMag explores the shift from AI experimentation to production, where legacy defenses fall short. We dive into the critical trifecta of AI-driven phishing, model poisoning, and cloud governance. By re…
Telegram AI Digest
#ai #ml #mlops
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We're excited to announce we've just made working with #Unsloth Studio on cloud GPUs way easier with our new dedicated template.
This means training and running models is as simple as working with your local device and as powerful as the hardware you want to use.
#LLM #MLOps
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bfloat16 keeps float32’s 8-bit exponent, preserving dynamic range for gradients, while float16’s smaller exponent causes under/overflow in training. same 16-bit size, better numerical stability. #MLOps
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running a 70B model locally costs ~500W and requires 48GB VRAM
a well-prompted 7B model on a $200 machine handles 80% of the same tasks
infra efficiency is just as important as model capability
the best model is the one you can actually run
#AI #selfhosted #llm #mlops
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Senior ML Ops Engineer - Intuition Machines, Inc., Warsaw, PL (Remote). Shape high-velocity data pipelines for hCaptcha using Python, Kafka, Clickhouse, Kubernetes & CI/CD. Join a fast global team protecting millions now. aihackerjobs.com/company/intu... #MLOps #Python #AI #Python #Kafka #Clickhouse
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ヤマト運輸のMLOps実装が凄い。勘と経験の物流から脱却し、機械学習パイプライン自動化で精度を複利的に改善。
・開発と運用の分断を解消
・コードの堅牢化とコンテナ化で安定稼働
・データドリブン経営の基盤を構築
#MLOps #DX
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🚧 Del demo a producción: el gran muro del IA
https://thenewstack.io/ai-demo-to-production/
#IA #Producción #DevOps #MLOps
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vast.ai spot H100 at $2/hr. hyperscalers charging $8+.
the markup exists because most people don't know alternatives.
your next training run doesn't need AWS.
#AI #gpu #selfhosted #mlops
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vast.ai spot H100 at $2/hr. hyperscalers charging $8+.
the markup exists because most people don't know alternatives.
your next training run doesn't need AWS.
#AI #gpu #selfhosted #mlops
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~Akamai~
Akamai details its transition from traditional MLOps to LLMOps and AgentOps to enhance real-time threat detection and security automation.
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IOCs: (None identified)
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#AI #Cybersecurity #MLOps #ThreatIntel
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Jupyter notebooks that pass CI but fail in production are a common headache—env drift, missing secrets, resource limits and "silent regressions" from model endpoints often cause it. Learn a Kubernetes-native Model-Aware Validation:
medium.com/@tcij1013/yo...
#Jupyter #Kubernetes #MLOps
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The Real Reason ML Projects Fail Without Cloud Integration
www.youtube.com/post/UgkxBLB...
#MachineLearning #CloudComputing #MLOps #AIProjects #DataScience #CloudTechnology #DevOps #TechInsights #FutureTech #DigitalTransformation #Ekascloud #FutureInTech 🚀💻
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**Modal +46 pts this week. Serverless GPU that spins up in seconds.** Devs are quietly routing serious workloads through it. Heat score: 94/100. The infra layer of the AI stack is heating up fast → hookflow.ai #MLOps #DeveloperTools #AIInfrastructure ---
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Retrieval Is Not Understanding Why agents fail when search results look smart but reasoning never actually begins Continue reading on Medium »
#artificial-intelligence #machine-learning #rags #mlops #llm
Origin | Interest | Match
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Is AI taking your job, or just changing it?
Leeds Data Science Meetup — tomorrow, 24 March, 6 pm @ The Elbow Rooms, Leeds. Two talks, food included.
RSVP here: www.meetup.com/leeds-data-s... — 95 already in!
#DataScience #AI #MLOps
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12 eval rules for “do no harm” objectives that aren’t vibes A practical guide to building safety evaluations that measure real harm reduction instead of vague intent, vanity metrics, or polic...
#machine-learning #mlops #evaluation #ai #llm
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The official Hugging Face skills repository that gives AI coding agents like Claude Code, Codex, and Cursor instant access to the entire ML ecosystem - from dataset creation to model training.
https://github.com/huggingface/skills
#HuggingFace #AI-agents #MLOps
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Stop Runaway Tool Loops 12 agent guardrails that keep tool-using systems bounded, safe, and useful Continue reading on Medium »
#machine-learning #mlops #ai-safety #llm #ai-agents-in-action
Origin | Interest | Match
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I Got Tired of Hallucination Tools That Only Answer the Wrong Question — So I Built a Danger Map Introducing hallucimap: a Python package that cartographs hallucination risk across an LLM’s ent...
#generative-ai-tools #mlops #artificial-intelligence #llm #machine-learning
Origin | Interest | Match
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Great session at Innovate Bay Coworking Space on Execution Capacity & Deployment—moving AI from prototype to reliable systems.
Key takeaway: building AI is easy, scaling it is the real challenge.
#AI #MLOps #Startup #SystemDesign
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🤖 Por qué el "host glorificado" para IA es el Kubernetes que necesitamos
La evolución de Kubernetes como plataforma fundamental para las cargas de trabajo de IA.
https://thenewstack.io/kubernetes-glorified-ai-host/
#Kubernetes #AI #MLOps #RoxsRoss
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🛡️ Lineaje añade capacidad para aplicar políticas de gobernanza automáticamente a componentes de IA
Plataforma descubre componentes de IA, define políti
devops.com/lineaje-adds-ability-to-...
#AIgovernance #MLOps #Security #RoxsRoss
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ML-пайплайны в Kubernetes: от первой строки кода до автоскейлинга и за его пределами Ваша ML-модель работает в ноут...
#Kubernetes #MLOps #ML #pipeline #KServe #TFX #DVC #HPA #Prometheus #Grafana #DevOps
Origin | Interest | Match
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kv caching stores past attention key/value vectors across layers—e.g. llama 3 8b has 32 kv pairs of dim 128, so 131k elements per token. context grows linearly in memory and attention compute. #MLOps #LLM
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#PromptEngineering In music, repetition builds feeling.
In AI, repetition burns budget.
Cut the loops, keep the impact: https://efficiency.frux.pro/
#AI #LLM #MLOps
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