Tag: resources

  • Cloud Blog: Optimizing image generation pipelines on Google Cloud: A practical guide

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/guide-to-optimizing-image-generation-pipelines/ Source: Cloud Blog Title: Optimizing image generation pipelines on Google Cloud: A practical guide Feedly Summary: Generative AI diffusion models such as Stable Diffusion and Flux produce stunning visuals, empowering creators across various verticals with impressive image generation capabilities. However, generating high-quality images through sophisticated pipelines can be computationally demanding, even with…

  • Hacker News: The most underreported story in AI is that scaling has failed to produce AGI

    Source URL: https://fortune.com/2025/02/19/generative-ai-scaling-agi-deep-learning/ Source: Hacker News Title: The most underreported story in AI is that scaling has failed to produce AGI Feedly Summary: Comments AI Summary and Description: Yes Summary: The commentary discusses the limitations of scaling in generative AI, addressing concerns that merely increasing computational resources does not equate to genuine intelligence. It highlights…

  • Cloud Blog: Unlock Inference-as-a-Service with Cloud Run and Vertex AI

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/improve-your-gen-ai-app-velocity-with-inference-as-a-service/ Source: Cloud Blog Title: Unlock Inference-as-a-Service with Cloud Run and Vertex AI Feedly Summary: It’s no secret that large language models (LLMs) and generative AI have become a key part of the application landscape. But most foundational LLMs are consumed as a service, meaning they’re hosted and served by a third party…

  • Cloud Blog: An SRE’s guide to optimizing ML systems with MLOps pipelines

    Source URL: https://cloud.google.com/blog/products/devops-sre/applying-sre-principles-to-your-mlops-pipelines/ Source: Cloud Blog Title: An SRE’s guide to optimizing ML systems with MLOps pipelines Feedly Summary: Picture this: you’re an Site Reliability Engineer (SRE) responsible for the systems that power your company’s machine learning (ML) services. What do you do to ensure you have a reliable ML service, how do you know…

  • Hacker News: It’s time to become an ML engineer

    Source URL: https://blog.gregbrockman.com/its-time-to-become-an-ml-engineer Source: Hacker News Title: It’s time to become an ML engineer Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses the evolution and significance of AI models like GPT-3 and DALL-E 2, highlighting their practical applications and the importance of software engineering in advancing AI. It emphasizes the blend…