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Tracking the evolution of autonomous agents & frontier models.

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agents OpenAI

Introducing AI Futures

OpenAI's announcement of a new platform, 'AI Futures', led to significant website access issues, highlighting immense developer interest and the infrastructure challenges of deploying next-generation AI systems.

Author: Jakub Antkiewicz
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agents|llms|hardware|consumer Hugging Face

Up to 3.2x Faster Inference with LFM2.5-DSpark

LiquidAI releases LFM2.5-DSpark models, using speculative decoding to achieve up to 3.2x faster inference on hardware from NVIDIA H100 to Apple M4 Max without changing output quality.

Author: Jakub Antkiewicz
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agents|llms|hardware|consumer NVIDIA

How Generative Recommenders Are Redefining RecSys at Scale

NVIDIA has released new open-source tools, recsys-examples and nv-embedding-cache, to accelerate the training and deployment of large-scale Generative Recommenders, addressing critical industry challenges like latency, scalability, and the cold-start problem.

Author: Jakub Antkiewicz
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agents|llms|hardware NVIDIA

Building Federated Multimodal AI Workflows with NVIDIA FLARE

NVIDIA enhances its FLARE framework with new features for large payload management and adapter-based training, enabling practical and scalable federated learning for multimodal AI across decentralized data sources.

Author: Jakub Antkiewicz
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consumer|llms OpenAI

ChatGPT Ads expands across Europe

AI industry leader OpenAI is expanding its advertising pilot for ChatGPT to key European markets, introducing a new monetization model that directly competes with traditional search engine advertising.

Author: Jakub Antkiewicz
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agents|llms Hugging Face

How Much Memory Does Your Agent Actually Need?

New research from IBM demonstrates that optimizing AI agent performance requires calibrating the amount of agentic memory to the model's capability, revealing that more memory is not always better and that the most accurate strategy can also be the most cost-effective.

Author: Jakub Antkiewicz
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