发布日期：2026-07-07
收录条目：13
1. From Hugging Face to Amazon SageMaker Studio in one click
- 来源：AWS ML Blog
- 发布时间：2026-07-06 22:35 UTC
- 链接：https://aws.amazon.com/blogs/machine-learning/from-hugging-face-to-amazon-sagemaker-studio-in-one-click-2/
摘要：Today, we’re excited to announce a deep-link integration between Hugging Face and Amazon SageMaker AI. Developers can now go from model discovery to hands-on experimentation in SageMaker Studio with a single selection.
2. Teaching models to forget: Selective unlearning with Amazon Nova
- 来源：AWS ML Blog
- 发布时间：2026-07-06 22:23 UTC
- 链接：https://aws.amazon.com/blogs/machine-learning/teaching-models-to-forget-selective-unlearning-with-amazon-nova/
摘要：In this post, we introduce Reverse Direct Preference Optimization (rDPO), the novel unlearning technique behind Amazon Nova Customizable Content Moderation Settings (CCMS), and show how it reduces over-deflection while p
3. Run MiniMax models on Amazon Bedrock
- 来源：AWS ML Blog
- 发布时间：2026-07-06 17:00 UTC
- 链接：https://aws.amazon.com/blogs/machine-learning/run-minimax-models-on-amazon-bedrock/
摘要：In this post, we walk through how to get started with MiniMax models on Amazon Bedrock, including the capabilities supported by these models, the service tiers available, how on-demand inference scales to handle your wor
4. Deploying Multi-Turn RL Infrastructure for Amazon Nova on Amazon SageMaker HyperPod
- 来源：AWS ML Blog
- 发布时间：2026-07-06 16:58 UTC
- 链接：https://aws.amazon.com/blogs/machine-learning/deploying-multi-turn-rl-infrastructure-for-amazon-nova-on-amazon-sagemaker-hyperpod/
摘要：In this post, you deploy a two-phase infrastructure for multi-turn RL using Amazon Nova Forge on Amazon SageMaker HyperPod. By the end, you have an event-driven pipeline that starts training when you upload data to Amazo
5. Automatically redact PII in images with Amazon Nova
- 来源：AWS ML Blog
- 发布时间：2026-07-06 16:55 UTC
- 链接：https://aws.amazon.com/blogs/machine-learning/automatically-redact-pii-in-images-with-amazon-nova/
摘要：In this post, we present a multi-step pipeline directed by Amazon Nova, which uses its contextual vision reasoning to coordinate complementary tools, including Meta’s open-source Segment Anything Model (SAM 3) deployed o
6. Streaming benchmark and recommendation results to MLflow with Amazon SageMaker AI
- 来源：AWS ML Blog
- 发布时间：2026-07-06 16:53 UTC
- 链接：https://aws.amazon.com/blogs/machine-learning/streaming-benchmark-and-recommendation-results-to-mlflow-with-amazon-sagemaker-ai/
摘要：In this post, you learn how to use the new MLflow integration with Amazon SageMaker AI optimized inference recommendation jobs and Amazon SageMaker AI benchmark jobs to automatically stream experiment data into a unified
7. Sakana AI Launches Sakana Translate, a Namazu-Powered Japanese–English–Chinese Translation Tool With Translate, Proofread, and Ask Modes
- 来源：MarkTechPost
- 发布时间：2026-07-06 05:35 UTC
- 链接：https://www.marktechpost.com/2026/07/05/sakana-ai-launches-sakana-translate/
摘要：Sakana AI has added Sakana Translate to Sakana Chat. It runs on the Namazu model series. The tool translates bidirectionally across Japanese, English, and Chinese. Three modes ship together: Translate, Proofread, and Ask
8. Synthetic Sciences Releases OpenScience: An Open-Source, Model-Agnostic AI Workbench for Machine Learning, Biology, Physics, and Chemistry Research
- 来源：MarkTechPost
- 发布时间：2026-07-06 05:07 UTC
- 链接：https://www.marktechpost.com/2026/07/05/synthetic-sciences-releases-openscience-an-open-source-model-agnostic-ai-workbench-for-machine-learning-biology-physics-and-chemistry-research/
摘要：Synthetic Sciences has released OpenScience, an Apache-2.0 AI workbench for scientific research. It works with any frontier or open-weight model, using your own API keys. It runs the full loop across machine learning, bi
9. Training Gemma-3 for Structured Mathematical Reasoning with Tunix GRPO, LoRA Adapters, and GSM8K Rewards
- 来源：MarkTechPost
- 发布时间：2026-07-06 04:26 UTC
- 链接：https://www.marktechpost.com/2026/07/05/training-gemma-3-for-structured-mathematical-reasoning-with-tunix-grpo-lora-adapters-and-gsm8k-rewards/
摘要：We build an end-to-end GRPO training workflow that teaches Gemma-3 to reason through GSM8K math problems. We prepare the environment, authenticate with Hugging Face, load Gemma-3, and wrap examples into a reasoning-plus-
10. Meituan Releases LongCat-2.0: A 1.6T-Parameter Open MoE Model with Native 1M Context and LongCat Sparse Attention
- 来源：MarkTechPost
- 发布时间：2026-07-05 21:25 UTC
- 链接：https://www.marktechpost.com/2026/07/05/meituan-releases-longcat-2-0-a-1-6t-parameter-open-moe-model-with-native-1m-context-and-longcat-sparse-attention/
摘要：Meituan has released LongCat-2.0, a 1.6 trillion-parameter Mixture-of-Experts model that activates about 48 billion parameters per token. It pairs a native 1-million-token context, built on LongCat Sparse Attention, with
11. LlamaIndex ‘legal-kb’: Agentic Retrieval over Index v2 with retrieve, find, read, and grep Tools
- 来源：MarkTechPost
- 发布时间：2026-07-05 07:50 UTC
- 链接：https://www.marktechpost.com/2026/07/05/llamaindex-legal-kb-agentic-retrieval-over-index-v2-with-retrieve-find-read-and-grep-tools/
摘要：LlamaIndex’s legal-kb is a public reference app that gives agents filesystem-style access to a document knowledge base on Index v2. It exposes retrieve (hybrid semantic search), find, read, and grep as tools, with automa
12. Structured PDF-to-JSON: A Guide to Open-Source Extraction Models in 2026
- 来源：MarkTechPost
- 发布时间：2026-07-05 03:02 UTC
- 链接：https://www.marktechpost.com/2026/07/04/structured-pdf-to-json-a-guide-to-open-source-extraction-models-in-2026/
摘要：Most enterprise data still sits inside PDFs, scans, and slide decks. Large language models and agents cannot use that data until it becomes structured JSON. Open-source document extraction has become the standard way to
13. Qwen’s Former Lead on What Hybrid Thinking Got Wrong — and Why He Now Backs Agents
- 来源：MarkTechPost
- 发布时间：2026-07-05 02:31 UTC
- 链接：https://www.marktechpost.com/2026/07/04/qwens-former-lead-on-what-hybrid-thinking-got-wrong-and-why-he-now-backs-agents/
摘要：Junyang Lin, the former technical lead of Alibaba's Qwen, walked through the model family in a talk "towards a generalist model / agent," then expanded it in an essay. We read both for practitioners: Qwen3 hybrid thinkin