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Democratizing Machine Learning at Netflix: Building the Model Lifecycle Graph

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Saish Sali, Nipun Kumar, Sura Elamurugu Introduction As Netflix has grown, machine learning continues to support our ability to deliver value to members and drive excellence across multiple areas of our business. When Netflix began investing in machine learning over a decade ago, it was primarily focused on a single domain: personalization. Scala was the …

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Beyond BI: How the Dataset Q&A feature of Amazon Quick powers the next generation of data decisions

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Business leaders across industries rely on operational dashboards as the shared source of truth that their teams execute against daily. But dashboards are built to answer known questions. When teams need to explore further, ad-hoc, multi-dimensional, or unforeseen questions, they hit a bottleneck. They wait hours or days for BI teams to build new views …

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RELEASE – The model you’ve all been waiting for – Smartphone Snapshot Photo Reality v13 – OMEGA

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This is a LoRA for FLUX Klein Base 9b. **Link: https://civitai.red/models/2381927/flux2-klein-base-9b-smartphone-snapshot-photo-reality-style** All infos on how to use and prompts for the samples can be found there. This is the culmination of 3 years of work. For three years I have been striving to create the best amateur photo realism model out there and now I …

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Open weight (and closed) Models with character sheet inputs

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Now that we have some open weight models available to us that work with character sheet inputs, here’s a test across the models I have access to, open and closed to see how they compare. An example of the 3 character sheets I used as inputs is at the end of the image stack. Here’s …

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Reinforced Agent: Inference-Time Feedback for Tool-Calling Agents

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This paper was accepted at the Fifth Workshop on Natural Language Generation, Evaluation, and Metrics at ACL 2026. Tool-calling agents are evaluated on tool selection, parameter accuracy, and scope recognition, yet LLM trajectory assessments remain inherently post-hoc. Disconnected from the active execution loop, such assessments identify errors that are usually addressed through prompt-tuning or retraining, …

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