[[{“value”:” We often say AIs “understand” code, but they don’t truly understand your problem or your codebase in the sense that humans understand things. They’re mimicking patterns from text and code they’ve seen before, either built into their model or provided by you, aiming to… Read More »Trust but Verify Andrew Stellman AI & ML – Radar
[[{“value”:” Table of contents What pain point in forecasting is being eliminated? How does in-context fine-tuning work under the hood? What exactly is “few-shot” here? Does it actually match supervised fine-tuning? How is this different from Chronos-style approaches? What are the architectural specifics to watch?… Read More »Google AI Research Introduce a Novel Machine Learning Approach that Transforms TimesFM into a Few-Shot Learner Asif Razzaq Artificial Intelligence Category – MarkTechPost
[[{“value”:”Protein folding models have achieved groundbreaking results since the introduction of AlphaFold2, typically built via a combination of integrating domain-expertise into its architectural designs and training pipelines. Nonetheless, given the success of generative models across different but related problems, it is natural to question whether… Read More »SimpleFold: Folding Proteins is Simpler than You Think Apple Machine Learning Research
[[{“value”:” In this tutorial, we walk through how we use Hugging Face Optimum to optimize Transformer models and make them faster while maintaining accuracy. We begin by setting up DistilBERT on the SST-2 dataset, and then we compare different execution engines, including plain PyTorch and… Read More »Coding Implementation to End-to-End Transformer Model Optimization with Hugging Face Optimum, ONNX Runtime, and Quantization Asif Razzaq Artificial Intelligence Category – MarkTechPost
[[{“value”:” AI agents are evolving beyond basic single-task helpers into more powerful systems that can plan, critique, and collaborate with other agents to solve complex problems. Deep Agents—a recently introduced framework built on LangGraph—bring these capabilities to life, enabling multi-agent workflows that mirror real-world team… Read More »Running deep research AI agents on Amazon Bedrock AgentCore Vadim Omeltchenko Artificial Intelligence
[[{“value”:” This post is co-written by Mark Warner, Principal Solutions Architect for Thales, Cyber Security Products. As generative AI applications make their way into production environments, they integrate with a wider range of business systems that process sensitive customer data. This integration introduces new challenges… Read More »Integrate tokenization with Amazon Bedrock Guardrails for secure data handling Nizar Kheir Artificial Intelligence
Introduction In machine learning, no single model is perfect. Introduction In machine learning, no single model is perfect. Read More
[[{“value”:” Real-time agents, live dubbing, and simultaneous translation die by a thousand milliseconds. Most “streaming” TTS (Text to Speech) stacks still wait for a chunk of text before they emit sound, so the human hears a beat of silence before the voice starts. VoXtream—released by… Read More »Meet VoXtream: An Open-Sourced Full-Stream Zero-Shot TTS Model for Real-Time Use that Begins Speaking from the First Word Asif Razzaq Artificial Intelligence Category – MarkTechPost
Recent advances in large language models (LLMs) have extended context lengths, enabling assistants to sustain long histories for coherent, personalized responses. This ability, however, hinges on Key-Value (KV) caching, whose memory grows linearly with dialogue length and quickly dominates under strict resource constraints. An active… Read More »EpiCache: Episodic KV Cache Management for Long Conversational Question Answering Apple Machine Learning Research
This paper re-examines the first normalized incomplete moment, a well-established measure of inequality with wide applications in economic and social sciences. Despite the popularity of the measure itself, existing statistical inference appears to lag behind the needs of modern-age analytics. To fill this gap, we… Read More »Alternative Statistical Inference for the First Normalized Incomplete Moment Apple Machine Learning Research