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my proficiency in Python and deep learning algorithms has been instrumental in advancing…
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🎶 Scaling music generation on AWS Excited to share a new post that dives into our collaboration with Splash. We worked together on training their…
🎶 Scaling music generation on AWS Excited to share a new post that dives into our collaboration with Splash. We worked together on training their…
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🚀 BREAKING: Commonwealth Bank, Australia's largest bank has just completed a groundbreaking 18-month journey, becoming the first Australian bank to…
🚀 BREAKING: Commonwealth Bank, Australia's largest bank has just completed a groundbreaking 18-month journey, becoming the first Australian bank to…
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If you are keen to be part of the GenAI Innovation Center, please reach out to me. Xuefeng Liu We are hiring Deep Learning Architects to be part…
If you are keen to be part of the GenAI Innovation Center, please reach out to me. Xuefeng Liu We are hiring Deep Learning Architects to be part…
Liked by Xiaoning Wang
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Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world…
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world…
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Just wrapped up an incredible 3-day journey at the NCS x AWS GenAIIC Bootcamp 2.0! A huge thank-you to our AWS instructors for guiding us through…
Just wrapped up an incredible 3-day journey at the NCS x AWS GenAIIC Bootcamp 2.0! A huge thank-you to our AWS instructors for guiding us through…
Liked by Xiaoning Wang
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🤖 There’s a lot of discussion these days about the value of multi-agent systems in the enterprise – how do you design for context sharing, optimize…
🤖 There’s a lot of discussion these days about the value of multi-agent systems in the enterprise – how do you design for context sharing, optimize…
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🧵 Real Stories of Generative AI in Action (Feature 2 of a multi-part series, you can access full series at #AWSGenAIinAction) 🏗️ Most people…
🧵 Real Stories of Generative AI in Action (Feature 2 of a multi-part series, you can access full series at #AWSGenAIinAction) 🏗️ Most people…
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🧵 Real Stories of Generative AI in Action (Feature 1 of a multi-part series, you can access full series at #AWSGenAIinAction) 🎶 Curious how…
🧵 Real Stories of Generative AI in Action (Feature 1 of a multi-part series, you can access full series at #AWSGenAIinAction) 🎶 Curious how…
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Honored to stand on the stage, on Day 1 AWS Summit 2025, to present the work - scalable LLM pre-training pipeline for music generation with Amazon…
Honored to stand on the stage, on Day 1 AWS Summit 2025, to present the work - scalable LLM pre-training pipeline for music generation with Amazon…
Liked by Xiaoning Wang
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Curious about how our team at the Amazon Web Services (AWS) Generative AI Innovation Center collaborated with ZURU Tech to significantly improve…
Curious about how our team at the Amazon Web Services (AWS) Generative AI Innovation Center collaborated with ZURU Tech to significantly improve…
Liked by Xiaoning Wang
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Energized after an incredible few days in Singapore on the sidelines of the #AWSSummit Singapore! I had the honor of meeting with executives from…
Energized after an incredible few days in Singapore on the sidelines of the #AWSSummit Singapore! I had the honor of meeting with executives from…
Liked by Xiaoning Wang
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🎵 Join me at #AWSSummit Sydney 2025! 🎵 Excited to present "Let's Make Music! Scalable Music Generation AI with AWS Trainium" on June 4 at ICC…
🎵 Join me at #AWSSummit Sydney 2025! 🎵 Excited to present "Let's Make Music! Scalable Music Generation AI with AWS Trainium" on June 4 at ICC…
Liked by Xiaoning Wang
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My course, "VR Graphics -- Challenges and Optimizations", is accepted by SIGGRAPH 2025. If you are interested in VR (or AR, MR, XR, WhateverR 😛)…
My course, "VR Graphics -- Challenges and Optimizations", is accepted by SIGGRAPH 2025. If you are interested in VR (or AR, MR, XR, WhateverR 😛)…
Liked by Xiaoning Wang
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Pydantic
We’ve worked with Heroku to make Pydantic AI integrate seamlessly with Heroku Managed Inference & Agents. This combination lets you: * Build agents in a familiar Pythonic style, with Pydantic’s data validation at the core * Deploy and run them on Heroku’s fully managed infrastructure * Use standard protocols like Model Context Protocol (MCP) and Agent-to-Agent (A2A) for interoperability The blog post walks through creating and deploying a Pydantic AI agent on Heroku in just a few steps. Read the guide here: https://lnkd.in/epwR98kH
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Amazon Science
Amazon researchers present a novel approach to LLM optimization. Wanda++ enables compression of seven-billion-parameter models in under 10 minutes on a single GPU, delivering a 32% performance improvement over previous compression methods: https://amzn.to/45tLUxH
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MLflow
Automate detection of unreliable LLM outputs by combining MLflow tracing with Cleanlab’s Trustworthy Language Models (TLM). 🚀 This blog post covers: ✅ Setting up MLflow to capture complete LLM interactions, including system prompts. ✅ Retrieving traces and efficiently batch-evaluating them with TLM to get trustworthiness scores and explanations—without ground truth labels. ✅ Tagging each MLflow trace with its trust score and explanation for ongoing review. ✅ Using MLflow Evaluation with a custom TLM metric to systematically compare model outputs. For the full guide and code samples, read more ➡️ https://lnkd.in/eHNWQrrK cc Chris Mauck, Data Scientist at Cleanlab #opensource #llm #oss #mlflow #cleanlab
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Contentful
💡 The Model Context Protocol (MCP) is an open standard and open-source framework developed by Anthropic to standardize how AI systems, especially large language models (LLMs), interact with external tools, systems, and data sources. MCP aims to become a standardized way for AI to interact with your apps on behalf of users. 🤓 Let's dig in to how it works together: https://lnkd.in/eaqMn4Tx
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Sepp Hochreiter
gLSTM extends xLSTM to a graph neural network architecture: https://lnkd.in/da3at-Y9 "gLSTM mitigates sensitivity over-squashing and capacity over-squashing." "gLSTM achieves comfortably state of the art results on the Diameter and Eccentricity Graph Property Prediction tasks, and very strong performance on SSSP"
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LightOn
💭 What if you could train SOTA retrieval models without knowledge distillation? With PyLate, LightOn makes it possible: ⚡️ Direct large-scale contrastive training, no teacher needed 📚 Train on billions of passages with GradCache & distributed infra 🎯 Better generalization across datasets (BEIR, BRIGHT, …) 🌐 Seamless multi-node scaling 👉🏻 Faster, smarter, more robust retrieval training. Learn more : https://lnkd.in/euPXMaEv
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