Language Models Improve When Pretraining Data Matches Target Tasks

Every data selection method inherently has a target. In practice, these targets often emerge implicitly through benchmark-driven iteration: researchers develop selection strategies, train models, measure benchmark performance, then refine accordingly. This raises a natural question: what happens when we make this optimization explicit? To explore this, we propose benchmark-targeted ranking (BETR), a simple method that …

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Build real-time travel recommendations using AI agents on Amazon Bedrock

Generative AI is transforming how businesses deliver personalized experiences across industries, including travel and hospitality. Travel agents are enhancing their services by offering personalized holiday packages, carefully curated for customer’s unique preferences, including accessibility needs, dietary restrictions, and activity interests. Meeting these expectations requires a solution that combines comprehensive travel knowledge with real-time pricing and …

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How to enable Secure Boot for your AI workloads

As organizations race to deploy powerful GPU-accelerated workloads, they might overlook a foundational step: ensuring the integrity of the system from the very moment it turns on.  Threat actors, however, have not overlooked this. They increasingly target the boot process with sophisticated malware like bootkits, which seize control before any traditional security software can load …

🚀 Just released a LoRA for Wan 2.1 that adds realistic drone-style push-in motion.

🚀 Just released a LoRA for Wan 2.1 that adds realistic drone-style push-in motion. Model: Wan 2.1 I2V – 14B 720p Trained on 100 clips — and refined over 40+ versions. Trigger: Push-in camera 🎥 + ComfyUI workflow included for easy usePerfect if you want your videos to actually *move*.👉 https://huggingface.co/lovis93/Motion-Lora-Camera-Push-In-Wan-14B-720p-I2V#AI #LoRA #wan21 #generativevideo u/ComfyUI …

Feature Engineering with LLM Embeddings: Enhancing Scikit-learn Models

Large language model embeddings, or LLM embeddings, are a powerful approach to capturing semantically rich information in text and utilizing it to leverage other machine learning models — like those trained using Scikit-learn — in tasks that require deep contextual understanding of text, such as intent recognition or sentiment analysis.

Apple Intelligence Foundation Language Models Tech Report 2025

We introduce two multilingual, multimodal foundation language models that power Apple Intelligence features across Apple devices and services: (i) a ∼3B-parameter on-device model optimized for Apple silicon through architectural innovations such as KV-cache sharing and 2-bit quantization-aware training; and (ii) a scalable server model built on a novel Parallel-Track Mixture-of-Experts (PT-MoE) transformer that combines track …

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Evaluating generative AI models with Amazon Nova LLM-as-a-Judge on Amazon SageMaker AI

Evaluating the performance of large language models (LLMs) goes beyond statistical metrics like perplexity or bilingual evaluation understudy (BLEU) scores. For most real-world generative AI scenarios, it’s crucial to understand whether a model is producing better outputs than a baseline or an earlier iteration. This is especially important for applications such as summarization, content generation, …

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Cloud CISO Perspectives: Our Big Sleep agent makes a big leap, and other AI news

Welcome to the first Cloud CISO Perspectives for July 2025. Today, Sandra Joyce, vice president, Google Threat Intelligence, talks about an incredible milestone with our Big Sleep AI agent, as well as other news from the intersection of security and AI. As with all Cloud CISO Perspectives, the contents of this newsletter are posted to …