engblogs

Explores AMUSE, a multimodal audio-visual benchmark for agentic multi-speaker understanding, and RAFT, a data-efficient alignment framework that enhances agentic reasoning via reward-based optimization and intrinsic self-evaluation in multimodal models.

A concise technical review of how Airbnb's engineering innovations intersect with academic publications to define the 2025 year-in-review in tech.

Build a scalable, serverless photo-search system that combines Amazon Rekognition for face and object detection, Amazon Neptune for relationship graphs, and Amazon Bedrock for contextual captioning to enable natural-language, semantic search across large image collections.

A technical overview of Piqama, an ecosystem for Pinterest quota management.

A concise deep-dive into reverse-engineering a handcrafted neural network puzzle using mechanistic interpretability and constraint solving (linear/integer programming and SAT) to expose an MD5-like computation encoded in its layers.

Examines HTML-to-Text extraction for LLM pretraining and shows that unioning multiple extractors increases token yield by up to 71% while enhancing coverage for structured content such as tables and code blocks without compromising benchmark performance.

A technical synthesis of Chain-of-Thought reasoning, introducing Trace Dynamics and a 'potential' metric to quantify how CoT steps influence the likelihood of correct completions, with insights on transferability across LLMs and implications for LRMs and VLMs.

Amazon Bedrock enables global cross-Region inference for Anthropic Claude models in the Middle East (UAE and Bahrain), delivering scalable, secure, low-latency AI workloads across Regions with automated routing and unified observability.

Global cross-Region inference on Amazon Bedrock enables scalable deployment of Claude Opus 4.6, Sonnet 4.6, and Haiku 4.5 across Thailand, Malaysia, Singapore, Indonesia, and Taiwan with resilient routing, quota management, and production-grade monitoring.

Explains how Dottxt's Outlines on AWS enables strict, schema-driven structured outputs from LLMs via generation-time validation in Amazon SageMaker, with deployment through AWS Marketplace and practical integration benefits.

A practical guide to training CodeFu-7B with veRL and Ray on Amazon SageMaker Training Jobs, detailing distributed reinforcement learning workflows, data preparation, multi-node orchestration, and observability for scalable competitive programming code generation models.

A concise, technique-driven blueprint for achieving chess grandmaster status by meeting FIDE rating thresholds, earning three norms, and sustaining disciplined, iterative improvement.