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The Download: Caiwei’s Three Things and Reasons to be Optimistic about...

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OpenAI may introduce weekly and lifetime plans

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Microsoft and OpenAI could be renegotiating the partnership

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ChatGPT now allows you to download deep research as PDF

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AI adoption: AWS addresses skills barrier that is holding back enterprises

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Glass Imaging raises $20M for AI to improve digital images quality

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Aarki launches Encore, a privacy-first mobile growth platform.

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Huawei Introduces Pangu Ultra MoE: A 718B-Parameter Sparse Language Model Trained...

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A Coding Guide to Unlock mem0 Memory for Anthropic Claude Bot:...

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Tencent Released PrimitiveAnything: A New AI Framework That Reconstructs 3D Shapes...

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A Coding Implementation of Accelerating Active Learning Annotation with Adala and...

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AI Hardware

OpenBMB Releases MiniCPM4: Ultra-Efficient Language Models for Edge Devices with Sparse...

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The concerted effort of maintaining application resilience

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Ericsson and AWS bet on AI to create self-healing networks

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Legal & Compliance

Meta buys stake in Scale AI, raising antitrust concerns

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OpenBMB Releases MiniCPM4: Ultra-Efficient Language Models for Edge Devices with Sparse...

The Need for Efficient On-Device Language Models Large language models have become integral to AI systems, enabling tasks like multilingual translation, virtual assistance, and automated reasoning through transformer-based architectures. While highly capable, these models are typically large, requiring powerful cloud infrastructure for training and inference. This reliance leads to latency,...