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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 8 Ways to Scale your Data Science Workloads From in-spreadsheet machine learning to terabyte sized DataFrames, learn how to stop fighting your tools and focus on solving problems.
Vision Language Models (VLMs) enable visual understanding alongside textual inputs. They are typically built by passing visual tokens from a pretrained vision encoder to a pretrained Large Language Model (LLM) through a projection layer. By leveraging the rich visual representations of the vision encoder and the world knowledge and reasoning capabilities of the LLM, VLMs can be useful for a wide range of applications, including accessibility assistants, UI navigation, robotics, and gaming.
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 Python One-Liners for JSON Parsing and Processing Crack complex JSON with these Python one-liners that do the heavy lifting.
Summary: Large language models (LLMs) are reshaping data science through automation, language generation, and real-time analytics. From customer service to fraud detection, LLMs drive efficiency, insight, and innovation. This guide explores how LLMs work, their applications, and use cases across industries, helping individuals and businesses unlock their full potential.
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.
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Here’s something that’ll make you pause next time you’re uploading files to the cloud: nearly half of all AWS S3 buckets are potentially misconfigured. That’s not a typo or some alarmist prediction—it’s based on actual analysis of real buckets out there right now. We’re not talking about sophisticated hackers breaking through layers of encryption here.
Alignment Science Blog Subliminal Learning: Language Models Transmit Behavioral Traits via Hidden Signals in Data Alex Cloud* 1 , Minh Le* 1 , July 22, 2025 James Chua 2 , Jan Betley 2 , Anna Sztyber-Betley 3 , Jacob Hilton 4 , Samuel Marks 5 , Owain Evans 2,6 *Equal contribution; author order chosen randomly 1 Anthropic Fellows Program; 2 Truthful AI; 3 Warsaw University of Technology; 4 Alignment Research Center; 5 Anthropic; 6 UC Berkeley tl;dr We study subliminal learning , a surprising phen
Alignment Science Blog Subliminal Learning: Language Models Transmit Behavioral Traits via Hidden Signals in Data Alex Cloud* 1 , Minh Le* 1 , July 22, 2025 James Chua 2 , Jan Betley 2 , Anna Sztyber-Betley 3 , Jacob Hilton 4 , Samuel Marks 5 , Owain Evans 2,6 *Equal contribution; author order chosen randomly 1 Anthropic Fellows Program; 2 Truthful AI; 3 Warsaw University of Technology; 4 Alignment Research Center; 5 Anthropic; 6 UC Berkeley tl;dr We study subliminal learning , a surprising phen
In this article, you will learn: • how Scikit-LLM integrates large language models like OpenAI's GPT with the Scikit-learn framework for text analysis.
Summary: Artificial intelligence techniques power modern automation, analytics, and intelligent systems. This blog explains what AI techniques are, highlights examples like machine learning and NLP, explores industry applications, and guides businesses on leveraging AI for growth. Discover how AI transforms healthcare, finance, manufacturing, and more with practical insights and success strategies.
Skip to main content Login Why Databricks Discover For Executives For Startups Lakehouse Architecture Mosaic Research Customers Customer Stories Partners Cloud Providers Databricks on AWS, Azure, GCP, and SAP Consulting & System Integrators Experts to build, deploy and migrate to Databricks Technology Partners Connect your existing tools to your Lakehouse C&SI Partner Program Build, deploy or migrate to the Lakehouse Data Partners Access the ecosystem of data consumers Partner Solutions
Synthetic data sounds like something out of science fiction, but it’s fast becoming the backbone of modern machine learning and data privacy initiatives. It enables faster development, stronger security, and fewer ethical headaches – and it’s evolving quickly. So if you’ve ever wondered what synthetic data really is, how it’s made, and why it’s taking center […] The post Everything You Need to Know About Synthetic Data appeared first on DATAVERSITY.
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!
GITHUB HUGGING FACE MODELSCOPE DISCORD Today, we’re announcing Qwen3-Coder, our most agentic code model to date. Qwen3-Coder is available in multiple sizes, but we’re excited to introduce its most powerful variant first: Qwen3-Coder-480B-A35B-Instruct — a 480B-parameter Mixture-of-Experts model with 35B active parameters which supports the context length of 256K tokens natively and 1M tokens with extrapolation methods, offering exceptional performance in both coding and agentic tasks
Can large language models learn to reason abstractly from just a few examples? In this piece, I explore this question by testing both text-based (o3-mini) and image-capable (gpt-4.1) models on abstract grid transformation tasks. These experiments reveal the extent to which current models rely on pattern matching, procedural heuristics, and symbolic shortcuts rather than robust generalization.
Meta reportedly offered a top-tier AI expert $1.25 billion over four years, a proposal that was declined despite the substantial financial terms. This event, shared by Daniel Francis, founder of the AI startup Abel, highlights intensifying competition for specialized AI talent within the technology sector. Daniel Francis, whose AI startup Abel develops technology for generating police reports from body-camera footage and emergency dispatch transcripts, originally gained public attention in 2023.
This paper was accepted at the Workshop on Large Language Model Memorization (L2M2) 2025. Large Language Models (LLMs) have quickly become an invaluable assistant for a variety of tasks. However, their effectiveness is constrained by their ability to tailor responses to human preferences and behaviors via personalization. Prior work in LLM personalization has largely focused on style transfer or incorporating small factoids about the user, as knowledge injection remains an open challenge.
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.
Stop Pydantic leaking into your domain layer. Use lightweight mappers or dacite to convert Pydantic models into pure old python dataclasses and keep your domain layer free of third-party libraries.
This work evaluates the potential of large language models (LLMs) to power digital assistants capable of complex action execution. These assistants rely on pre-trained programming knowledge to execute multi-step goals by composing objects and functions defined in assistant libraries into action execution programs. To achieve this, we develop ASPERA, a framework comprising an assistant library simulation and a human-assisted LLM data generation engine.
Jump to Content Research Research Who we are Back to Who we are menu Defining the technology of today and tomorrow. Philosophy We strive to create an environment conducive to many different types of research across many different time scales and levels of risk. Learn more about our Philosophy Learn more Philosophy People Our researchers drive advancements in computer science through both fundamental and applied research.
The buzz around AI agents has intensified in recent years, but for many practitioners and businesses, the concept still feels abstract, wrapped in layers of marketing and technical jargon. At the center of this transformation is a simple yet powerful idea: agency. What does it mean to give an AI agent “agency”? And how does this reshape the future of intelligent systems?
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.
For decades, Dennard scaling propelled remarkable advancements in processor technology. As transistor sizes shrank, manufacturers increased clock frequencies to enhance computational speed while simultaneously reducing power consumption, adhering to the principle of constant power density. This synergy delivered consistent performance improvements in both hardware and software.
Veo3 has taken the world by storm, generating life-like videos with just a prompt. As Google’s latest AI video generation model, Veo3 has been specifically designed to understand complex instructions and produce videos so good, they seem like they have been filmed by a whole production team. All, in a matter of seconds. What makes […] The post Make Veo3-like AI Videos for Free Using These Tools appeared first on Analytics Vidhya.
Cybersecurity researchers at Wiz identified a critical vulnerability, NVIDIAScape (CVE-2025-23266), within the NVIDIA Container Toolkit. This flaw permits attackers to bypass container isolation, achieving root access to the host machine. The vulnerability impacts NVIDIA Container Toolkit versions up to 1.17.7 and NVIDIA GPU Operator versions up to 25.3.0.
Scientists developed a computational “aging clock” that measures the biological age of brain cells and identifies compounds with rejuvenating potential.
In Airflow, DAGs (your data pipelines) support nearly every use case. As these workflows grow in complexity and scale, efficiently identifying and resolving issues becomes a critical skill for every data engineer. This is a comprehensive guide with best practices and examples to debugging Airflow DAGs. You’ll learn how to: Create a standardized process for debugging to quickly diagnose errors in your DAGs Identify common issues with DAGs, tasks, and connections Distinguish between Airflow-relate
Google has announced that an advanced version of Gemini Deep Think achieved gold-medal level performance at the International Mathematical Olympiad (IMO) 2025 by solving five out of six problems perfectly. The International Mathematical Olympiad, established in 1959, is an annual competition for pre-university mathematicians. Participating countries send six elite students to solve six complex problems across algebra, combinatorics, geometry, and number theory.
Program 1 //Project Title: City Map Navigation using Graphs /* Objective: To build a simple navigation system that finds the shortest path between a source city and all other cities using Dijkstra's Algorithm —... The post DSA C++ Project – City Map Navigation appeared first on DataFlair.
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.
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The Department of Defense has awarded contracts of up to $200 million each to Anthropic, Google, OpenAI, and xAI to develop agentic AI workflows and address national security needs. The Chief Digital and Artificial Intelligence Office within the Defense Department specified these contracts are intended to develop “agentic AI workflows across a variety of mission areas” and to “increase the ability of these companies to understand and address critical national security needs.
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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
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