Tag: fine-tuning
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Cloud Blog: Google, Bytedance, and Red Hat make Kubernetes generative AI inference aware
Source URL: https://cloud.google.com/blog/products/containers-kubernetes/google-bytedance-and-red-hat-improve-ai-on-kubernetes/ Source: Cloud Blog Title: Google, Bytedance, and Red Hat make Kubernetes generative AI inference aware Feedly Summary: Over the past ten years, Kubernetes has become the leading platform for deploying cloud-native applications and microservices, backed by an extensive community and boasting a comprehensive feature set for managing distributed systems. Today, we are…
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Hacker News: Launch HN: Augento (YC W25) – Fine-tune your agents with reinforcement learning
Source URL: https://news.ycombinator.com/item?id=43537505 Source: Hacker News Title: Launch HN: Augento (YC W25) – Fine-tune your agents with reinforcement learning Feedly Summary: Comments AI Summary and Description: Yes Summary: The text describes a new service offered by Augento that provides fine-tuning for language models (LLMs) using reinforcement learning, enabling users to optimize AI agents for specific…
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Hacker News: Gemini hackers can deliver more potent attacks with a helping hand from Gemini
Source URL: https://arstechnica.com/security/2025/03/gemini-hackers-can-deliver-more-potent-attacks-with-a-helping-hand-from-gemini/ Source: Hacker News Title: Gemini hackers can deliver more potent attacks with a helping hand from Gemini Feedly Summary: Comments AI Summary and Description: Yes Summary: The provided text discusses the emerging threat of indirect prompt injection attacks on large language models (LLMs) like OpenAI’s GPT-3, GPT-4, and Google’s Gemini. It outlines…
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Hacker News: Tao: Using test-time compute to train efficient LLMs without labeled data
Source URL: https://www.databricks.com/blog/tao-using-test-time-compute-train-efficient-llms-without-labeled-data Source: Hacker News Title: Tao: Using test-time compute to train efficient LLMs without labeled data Feedly Summary: Comments AI Summary and Description: Yes Summary: The text introduces a new model tuning method for large language models (LLMs) called Test-time Adaptive Optimization (TAO) that enhances model quality without requiring large amounts of labeled…
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Hacker News: Tied Crosscoders: Tracing How Chat LLM Behavior Emerges from Base Model
Source URL: https://www.lesswrong.com/posts/3T8eKyaPvDDm2wzor/research-question Source: Hacker News Title: Tied Crosscoders: Tracing How Chat LLM Behavior Emerges from Base Model Feedly Summary: Comments AI Summary and Description: Yes Summary: The text presents a detailed analysis of a novel architecture called the “tied crosscoder,” which enhances the understanding of how chat behaviors emerge from base model features in…
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Hacker News: Map Features in OpenStreetMap with Computer Vision
Source URL: https://blog.mozilla.ai/map-features-in-openstreetmap-with-computer-vision/ Source: Hacker News Title: Map Features in OpenStreetMap with Computer Vision Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses Mozilla.ai’s development of the OpenStreetMap AI Helper Blueprint, which utilizes computer vision models to enhance the mapping process while maintaining human verification. This innovation highlights the potential of AI…
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Hacker News: Understanding R1-Zero-Like Training: A Critical Perspective
Source URL: https://github.com/sail-sg/understand-r1-zero Source: Hacker News Title: Understanding R1-Zero-Like Training: A Critical Perspective Feedly Summary: Comments AI Summary and Description: Yes Summary: The text presents a novel approach to LLM training called R1-Zero-like training, emphasizing a new reinforcement learning method termed Dr. GRPO that enhances reasoning capabilities. It highlights significant improvements in model performance through…
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Cloud Blog: Accelerating AI in healthcare using NVIDIA BioNeMo Framework and Blueprints on GKE
Source URL: https://cloud.google.com/blog/products/ai-machine-learning/accelerate-ai-in-healthcare-nvidia-bionemo-gke/ Source: Cloud Blog Title: Accelerating AI in healthcare using NVIDIA BioNeMo Framework and Blueprints on GKE Feedly Summary: The quest to develop new medical treatments has historically been a slow, arduous process, screening billions of molecular compounds across decade-long development cycles. The vast majority of therapeutic candidates do not even make it…