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Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter 10 GitHub Repositories for Mastering Agents and MCPs Learn how to build your own agentic AI application with free tutorials, guides, courses, projects, example code, research papers, and more.
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Context engineering is quickly becoming the new foundation of modern AI system design, marking a shift away from the narrow focus on prompt engineering. While prompt engineering captured early attention by helping users coax better outputs from large language models (LLMs), it is no longer sufficient for building robust, scalable, and intelligent applications.
Apple researchers are advancing AI and ML through fundamental research, and to support the broader research community and help accelerate progress in this field, we share much of this research through publications and engagement at conferences. Next week, the International Conference on Machine Learning (ICML) will be held in Vancouver, Canada, and Apple is proud to once again participate in this important event for the research community and to be an industry sponsor.
Speaker: Jason Chester, Director, Product Management
In today’s manufacturing landscape, staying competitive means moving beyond reactive quality checks and toward real-time, data-driven process control. But what does true manufacturing process optimization look like—and why is it more urgent now than ever? Join Jason Chester in this new, thought-provoking session on how modern manufacturers are rethinking quality operations from the ground up.
Recommendation systems are everywhere. From Netflix and Spotify to Amazon. But what if you wanted to build a visual recommendation engine? One that looks at the image, not just the title or tags? In this article, you’ll build a men’s fashion recommendation system. It will use image embeddings and the Qdrant vector database. You’ll go […] The post Build a Men’s Fashion Recommendation System Using FastEmbed and Qdrant appeared first on Analytics Vidhya.
Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter Build ETL Pipelines for Data Science Workflows in About 30 Lines of Python Want to understand how ETL really works?
Model Context Protocol (MCP) is rapidly emerging as the foundational layer for intelligent, tool-using AI systems, especially as organizations shift from prompt engineering to context engineering. Developed by Anthropic and now adopted by major players like OpenAI and Microsoft , MCP provides a standardized, secure way for large language models (LLMs) and agentic systems to interface with external APIs, databases, applications, and tools.
A new report from Incogni evaluates the data privacy practices of today’s most widely used AI platforms. As generative AI and large language models (LLMs) become deeply embedded in everyday tools and services, the risk of unauthorized data collection and sharing has surged. Incogni’s researchers analyzed nine leading platforms using 11 criteria to understand which systems offer the most privacy-friendly experience.
Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter 7 DuckDB SQL Queries That Save You Hours of Pandas Work See how DuckDB outperforms Pandas in real world tasks like filtering, cohort analysis and revenue modelling all within your notebook.
ETL and ELT are some of the most common data engineering use cases, but can come with challenges like scaling, connectivity to other systems, and dynamically adapting to changing data sources. Airflow is specifically designed for moving and transforming data in ETL/ELT pipelines, and new features in Airflow 3.0 like assets, backfills, and event-driven scheduling make orchestrating ETL/ELT pipelines easier than ever!
The traditional single-modal data approaches often miss important insights that are present in cross-modal relations. Multi-Modal Analysis brings together diverse sources of data, such as text, images, audio, and more similar data to provide a more complete view of an issue. This multi-modal data analysis is called multi-modal data analytics, and it improves prediction accuracy […] The post What is Multi-Modal Data Analysis?
Artificial intelligence is evolving fast, and Grok 4 , developed by xAI (Elon Musk’s AI company), is one of the most ambitious steps forward. Designed to compete with giants like OpenAI’s GPT-4, Google’s Gemini, and Anthropic’s Claude, Grok 4 brings a unique flavor to the large language model (LLM) space: deep reasoning , multimodal understanding , and real-time integration with live data.
While federated learning (FL) and differential privacy (DP) have been extensively studied, their application to automatic speech recognition (ASR) remains largely unexplored due to the challenges in training large transformer models. Specifically, large models further exacerbate issues in FL as they are particularly susceptible to gradient heterogeneity across layers, unlike the relatively uniform gradient behavior observed in shallow models.
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Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.
Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter Generative AI: A Self-Study Roadmap A practical guide for developers and data practitioners to build expertise in generative AI systems, from foundation models to production deployment.
Are you an AI engineer, wondering how to attain resources that can put your skills to a practical test? It might be difficult to look for the right solution for you, based on the vast amount of information out there. Hence, we present this list of all ten GitHub llm repositories every AI engineer ought […] The post 10 GitHub LLM Repositories Every AI Engineer Should Know appeared first on Analytics Vidhya.
Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage
There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.
Wearable devices record physiological and behavioral signals that can improve health predictions. While foundation models are increasingly used for such predictions, they have been primarily applied to low-level sensor data, despite behavioral data often being more informative due to their alignment with physiologically relevant timescales and quantities.
Learn the key CLI commands for automated competition submission, downloading and uploading data, running code on free cloud compute, and accessing large AI models.
PALO ALTO, Calif.—June 24, 2025—Auxia, an agentic customer orchestration platform, today announced advancements to its Analyst Agent, enabling marketing teams to discover insights from their campaigns through natural language conversations that happen in real-time. Simple questions like “Which customers are most likely to upgrade?” now get immediate answers with visual explanations showing exactly why.
ETH Zurich and EPFL will release a large language model (LLM) developed on public infrastructure. Trained on the “Alps” supercomputer at the Swiss National Supercomputing Centre (CSCS), the new LLM marks a milestone in open-source AI and multilingual excellence.
Documents are the backbone of enterprise operations, but they are also a common source of inefficiency. From buried insights to manual handoffs, document-based workflows can quietly stall decision-making and drain resources. For large, complex organizations, legacy systems and siloed processes create friction that AI is uniquely positioned to resolve.
Driven by steady progress in deep generative modeling, simulation-based inference (SBI) has emerged as the workhorse for inferring the parameters of stochastic simulators. However, recent work has demonstrated that model misspecification can compromise the reliability of SBI, preventing its adoption in important applications where only misspecified simulators are available.
Forget data silos. You can build a modern data lakehouse that gives you transactional consistency, schema evolution, and top-tier performance, all in one place with Apache Iceberg and Apache Spark.
Whether it’s streamlined ingestion, unified governance or AI agent evaluation, the suite of solutions available on the Data Intelligence Platform enables businesses worldwide to drive
Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives
Manufacturing is evolving, and the right technology can empower—not replace—your workforce. Smart automation and AI-driven software are revolutionizing decision-making, optimizing processes, and improving efficiency. But how do you implement these tools with confidence and ensure they complement human expertise rather than override it? Join industry expert Andrew Skoog as he explores how manufacturers can leverage automation to enhance operations, streamline workflows, and make smarter, data-dri
Diagnosing autism and attention-related conditions often takes months, if not years. But new research shows that analyzing how people move their hands during simple tasks, with the help of artificial intelligence, could offer a faster, objective path to early detection.
Large Language Models (LLMs) are increasingly used in applications requiring long context lengths, but the key-value (KV) cache often becomes a memory bottleneck on GPUs as con- text lengths grow. To address this, we propose Commutative Vector Quantization (CommVQ) to significantly reduce memory usage for long context LLM inference. First, we leverage additive quantization by introducing a lightweight encoder and codebook to compress the KV cache, which can then be decoded with a simple matrix m
Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter 7 Steps to Mastering Vibe Coding Learn how to master vibe coding in these 7 steps, and transform AI code generation into a professional superpower.
Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.
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