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[D] - Neurips Position paper reviews

[D] Cool new ways to mix linear optimization with GNNs? (LP layers, simplex-like updates, etc.)

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How do you calculate ROI for implementing AI Agents? + Any decision criteria between public platforms vs. on-prem?

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[R] How do I choose the best model in validation when I have no target data??

Sen. Hawley to probe Meta after report finds its AI chatbots flirt with kids | TechCrunch

Microsoft

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NextCoder-32B

Task: text-generation

MIT HAN Lab

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nunchaku-flux.1-kontext-dev

Black Forest Labs

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FLUX.1-Kontext-dev-onnx

Google

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videoprism

Task: video-classification

SUFE-AIFLM-Lab

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Fin-R1

microsoft

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qlib

Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.

lukasmasuch

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best-of-ml-python

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

mindsdb

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mindsdb

AI Analytics Engine that can answer questions over large scale data. - The only MCP Server you'll ever need

n8n-io

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n8n

Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.

huggingface

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transformers

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

deepspeedai

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DeepSpeed

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

jax-ml

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jax

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

ray-project

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kuberay

A toolkit to run Ray applications on Kubernetes

open-edge-platform

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anomalib

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.