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A Practical Guide to Multimodal Data Analytics

KDnuggets

BigQuery's ObjectRef unifies structured and unstructured data, enabling multimodal analytics via SQL and Python.

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Greater Complexity Brings Greater Risk: 4 Tips to Manage Your AI Database

insideBIGDATA

AI advancements will fundamentally change how enterprises use and manage data, making it essential to embrace and understand this transformation. For organizations looking to adopt AI at scale, the state of their databases is a critical success factor. Poor data quality, weak governance.

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AMD Announces New GPUs, Development Platform, Rack Scale Architecture

insideBIGDATA

AMD issued a raft of news at their Advancing AI 2025 event this week, an update on the company’s response to NVIDIA’s 90-plus percent market share dominance in the GPU and AI markets. And the company offered a sneak peak at what to expect from their next generation of EPYC CPUs and Instinct GPUs.

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Building Effective AI Agents

Hacker News

Discover how Anthropic approaches the development of reliable AI agents. Learn about our research on agent capabilities, safety considerations, and technical framework for building trustworthy AI.

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What’s New in Apache Airflow® 3.0—And How Will It Reshape Your Data Workflows?

Speaker: Tamara Fingerlin, Developer Advocate

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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Announcing managed MCP servers with Unity Catalog and Mosaic AI Integration

databricks

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

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7 Key Highlights from Geoffrey Hinton on Superintelligent AI

Analytics Vidhya

If the Godfather of AI, tells you to “train to be a plumber” you know that you got to pay attention, atleast thats what got me hooked. In a recent conversation, Geoffrey Hinton discussed the various possibilities in the upcoming era of superintelligent AI and if you are wondering how did this conversation go about, […] The post 7 Key Highlights from Geoffrey Hinton on Superintelligent AI appeared first on Analytics Vidhya.

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Savant Unveils Agentic Analytics Suite, Anthropic Partnership and Migration Tools

insideBIGDATA

SAN MATEO, CA – June 18, 2025 — Analytics automation company Savant Labs today launched its Summer 2025 Release, including their Agentic Analytics Suite and Intelligence Graph, one-click integration with Anthropic Claude, and migration tools to help enterprises modernize from legacy self-service analytics platforms.

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Q-learning is not yet scalable

Hacker News

Q-learning is not yet scalable Seohong Park UC Berkeley June 2025 Does RL scale? Over the past few years, weve seen that next-token prediction scales, denoising diffusion scales, contrastive learning scales, and so on, all the way to the point where we can train models with billions of parameters with a scalable objective that can eat up as much data as we can throw at it.

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Positional Encodings in Transformer Models

Machine Learning Mastery

This post is divided into five parts; they are: • Understanding Positional Encodings • Sinusoidal Positional Encodings • Learned Positional Encodings • Rotary Positional Encodings (RoPE) • Relative Positional Encodings Consider these two sentences: "The fox jumps over the dog" and "The dog jumps over the fox".

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AI Agents in Analytics Workflows: Too Early or Already Behind?

Flipboard

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 AI Agents in Analytics Workflows: Too Early or Already Behind? A look at how AI agents are reshaping the data analytics workflow and whether you’re ahead or behind the curve.

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Agent Tooling: Connecting AI to Your Tools, Systems & Data

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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NotebookLM + Deep Research: The Ultimate Learning Hack

KDnuggets

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 NotebookLM + Deep Research: The Ultimate Learning Hack Let’s unlock smarter, faster learning by combining NotebookLM with deep research strategies.

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OpenAI Wins $200M Contract Targeting Defense Department Efficiency

insideBIGDATA

OpenAI announced it has won a $200 million, one-year pilot project contract with the U.S.

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Foundations of Computer Vision

Hacker News

Preface Foundations of Computer Vision Twitter LinkedIn Preface Copyright Notation 1 The Challenge of Vision Foundations 2 A Simple Vision System 3 Looking at Images 4 Computer Vision and Society Image Formation 5 Imaging 6 Lenses 7 Cameras as Linear Systems 8 Color Foundations of Learning 9 Introduction to Learning 10 Gradient-Based Learning Algorithms 11 The Problem of Generalization 12 Neural Networks 13 Neural Networks as Distribution Transformers 14 Backpropagation Foundations of Image Proc

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Aligning LLMs by Predicting Preferences from User Writing Samples

Machine Learning Research at Apple

Accommodating human preferences is essential for creating aligned LLM agents that deliver personalized and effective interactions. Recent work has shown the potential for LLMs acting as writing agents to infer a description of user preferences. Agent alignment then comes from conditioning on the inferred preference description. However, existing methods often produce generic preference descriptions that fail to capture the unique and individualized nature of human preferences.

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How to Modernize Manufacturing Without Losing Control

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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Scale AI confirms ‘significant’ investment from Meta, says CEO Alexandr Wang is leaving

Flipboard

Data-labeling company Scale AI confirmed on Friday that it has received a “significant” investment from Meta that values the startup at $29 billion.

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Top 5 Frameworks for Distributed Machine Learning

KDnuggets

Use these frameworks to optimize memory and compute resources, scale your machine learning workflow, speed up your processes, and reduce the overall cost.

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Is There a Half-Life for the Success Rates of AI Agents?

Hacker News

Building on the recent empirical work of Kwa et al.

AI 175
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10 Must-Know Python Libraries for MLOps in 2025

Machine Learning Mastery

MLOps, or machine learning operations, is all about managing the end-to-end process of building, training, deploying, and maintaining machine learning models.

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Automation, Evolved: Your New Playbook for Smarter Knowledge Work

Speaker: Frank Taliano

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.

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Advanced Feature Engineering Using Scikit-Learn Pipelines with Pandas’ ColumnTransformer and NumPy Arrays - MachineLearningMastery.com

Flipboard

Advanced Feature Engineering Using Scikit-Learn Pipelines with Pandas’ ColumnTransformer and NumPy Arrays Image by Editor Pandas, NumPy, and …

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Automating GitHub Workflows with Claude 4

KDnuggets

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 Automating GitHub Workflows with Claude 4 Learn how to set up the Claude App in your GitHub repository and invoke it directly through comments.

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Report Released on Enterprise AI Trust: 42% Don’t Trust Outputs

insideBIGDATA

". the report finds that while 58% of organizations have implemented or optimized data observability programs – systems that monitor detect, and resolve data quality and pipeline issues in real-time – 42% still say they do not trust the outputs.

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Normalizing Flows are Capable Generative Models

Machine Learning Research at Apple

Normalizing Flows (NFs) are likelihood-based models for continuous inputs. They have demonstrated promising results on both density estimation and generative modeling tasks, but have received relatively little attention in recent years. In this work, we demonstrate that NFs are more powerful than previously believed. We present TarFlow: a simple and scalable architecture that enables highly performant NF models.

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The 2nd Generation of Innovation Management: A Survival Guide

Speaker: Chris Townsend, VP of Product Marketing, Wellspring

Over the past decade, companies have embraced innovation with enthusiasm—Chief Innovation Officers have been hired, and in-house incubators, accelerators, and co-creation labs have been launched. CEOs have spoken with passion about “making everyone an innovator” and the need “to disrupt our own business.” But after years of experimentation, senior leaders are asking: Is this still just an experiment, or are we in it for the long haul?

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Accumulation of cognitive debt when using an AI assistant for essay writing task

Hacker News

This study explores the neural and behavioral consequences of LLM-assisted essay writing. Participants were divided into three groups: LLM, Search Engine, and Brain-only (no tools). Each completed three sessions under the same condition. In a fourth session, LLM users were reassigned to Brain-only group (LLM-to-Brain), and Brain-only users were reassigned to LLM condition (Brain-to-LLM).

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Mastodon updates its terms to prohibit AI model training

Flipboard

Social networks are bolstering their terms of service against scrapers and bots that crawl the website to train AI models.

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The 7 Most Useful Jupyter Notebook Extensions for Data Scientists

KDnuggets

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 The 7 Most Useful Jupyter Notebook Extensions for Data Scientists In this article, we will explore seven different Jupyter Notebook extensions that will improve your work.

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Voltage Park Partners with VAST Data

insideBIGDATA

AI operating system company VAST Data, the AI Operating System company, today announced that Voltage Park, the enterprise-grade AI factory company, has partnered with VAST to deliver the high-performance data services required for demanding AI workloads. Voltage Park has deployed.

AI 195
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Apache Airflow® Best Practices: DAG Writing

Speaker: Tamara Fingerlin, Developer Advocate

In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!

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Variational Rectified Flow Matching

Machine Learning Research at Apple

We study Variational Rectified Flow Matching, a framework that enhances classic rectified flow matching by modeling multi-modal velocity vector-fields. At inference time, classic rectified flow matching 'moves' samples from a source distribution to the target distribution by solving an ordinary differential equation via integration along a velocity vector-field.

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Time Series Forecasting with Graph Transformers

Hacker News

Time series forecasting is a cornerstone in modern business analytics, whether it is concerned with anticipating market trends, user behavior, optimizing resource allocation, or planning for future growth. This blog post will dive into forecasting on graph structured entities, e.g., as obtained from a relational database, utilizing not only the individual time series as signal but also related information.

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Top AI researchers say language is limiting. Here's the new kind of model they are building instead.

Flipboard

As OpenAI, Anthropic, and Big Tech invest billions in developing state-of-the-art large-language models, a small group of AI researchers is working on the next big thing.

AI 173
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Polars for Pandas Users: A Blazing Fast DataFrame Alternative

KDnuggets

Learn how to migrate from Pandas to Polars with practical examples, side-by-side code comparisons, and strategies to unlock performance improvements on your existing data workflows.

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How to Achieve High-Accuracy Results When Using LLMs

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m

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Lilac Joins Databricks to Simplify Unstructured Data Evaluation for Generative AI

databricks

Today, we are thrilled to announce that Lilac is joining Databricks. Lilac is a scalable, user-friendly tool for data scientists to search, cluster.