Mon.Jun 30, 2025

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Mixture of Experts Architecture in Transformer Models

Machine Learning Mastery

This post covers three main areas: • Why Mixture of Experts is Needed in Transformers • How Mixture of Experts Works • Implementation of MoE in Transformer Models The Mixture of Experts (MoE) concept was first introduced in 1991 by

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Lessons Learned After 6.5 Years Of Machine Learning

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Publish AI, ML & data-science insights to a global community of data professionals. Sign in Sign out Submit an Article Latest Editor’s Picks Deep Dives Newsletter Write For TDS Toggle Mobile Navigation LinkedIn X Toggle Search Search Machine Learning Lessons Learned After 6.5 Years Of Machine Learning Deep work, trends, data, and research Pascal Janetzky Jun 30, 2025 7 min read Share Photo by Anthony Tori When I started learning machine learning more than six years ago, the field was in the

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Alice's Adventures in a Differentiable Wonderland

Hacker News

Neural networks surround us, in the form of large language models, speech transcription systems, molecular discovery algorithms, robotics, and much more. Stripped of anything else, neural networks are compositions of differentiable primitives, and studying them means learning how to program and how to interact with these models, a particular example of what is called differentiable programming.

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AI’s Bright Future: Insights from ODSC East 2025 Podcast Minisodes

ODSC - Open Data Science

ODSC East 2025 once again delivered a powerhouse of AI insights, featuring a unique podcast episode recorded live with short interviews from some of the brightest minds in AI today. Across these minisodes, speakers explored cutting-edge topics ranging from AI agents, small language models, and AI risk management, to synthetic data, causal AI, and even social media algorithms.

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Precision in Motion: Why Process Optimization Is the Future of Manufacturing

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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What is garbage in, garbage out (GIGO)?

Dataconomy

Garbage in, garbage out (GIGO) highlights a fundamental truth in data processing: the quality of the output is only as good as the quality of the input. This principle resonates across various domains, from software development to data analysis, and underscores the critical relationship between input and results. Ensuring reliable data is paramount, especially as organizations increasingly leverage data-driven decision-making.

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Utilize machine learning to improve employee retention rates - DataScienceCentral.com

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Employee turnover is one of the most pressing challenges modern businesses face. It drains resources, lowers morale and slows team momentum. Traditional HR tools like surveys and exit interviews often reveal issues after valuable employees have left. However, machine learning (ML) can detect patterns, forecast risk and deliver actionable insights based on real-time data.

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A CarFax for Used PCs

Hacker News

The United Nations’ Global E-waste Monitor estimates that the world generates over 60 million tonnes of e-waste annually. Furthermore, this number is rising five times as fast as e-waste recycling. Much of this waste comes from prematurely discarded electronic devices. Many enterprises follow a standard three-year replacement cycle, assuming older computers are inefficient.

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Google BigQuery

Dataconomy

Google BigQuery stands out as a leading force in the realm of big data analytics, harnessing the power of the cloud to provide organizations with the tools they need to process and analyze vast amounts of data efficiently. With its ability to handle complex queries and deliver insights in real time, businesses can make informed decisions faster than ever before.

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National Lab’s Machine Learning Project to Advance Seismic Monitoring Across Energy Industries

insideBIGDATA

A new initiative designed to revolutionize seismic monitoring and forecasting using real time, advanced machine learning (ML) technologies is coming to the West Texas/New Mexico area. The U.S. Department of Energy (DOE) Technology Commercialization Fund awarded $1.8 million in funding to Lawrence Livermore National Laboratory (LLNL).

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GPEmu: A GPU emulator for rapid, low-cost deep learning prototyping [pdf]

Hacker News

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Airflow Best Practices for ETL/ELT Pipelines

Speaker: Kenten Danas, Senior Manager, Developer Relations

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!

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'Spitting in the face of your international audience': The Alters caught using generative AI for background text and translations, despite not disclosing such on Steam

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ACM launches journal on AI security and privacy

Dataconomy

On June 24, 2025, the Association for Computing Machinery (ACM) announced the launch of a new journal, ACM Transactions on AI Security and Privacy (TAISAP), designed to address critical research needs in securing AI systems and leveraging AI for cybersecurity. The establishment of TAISAP responds to the increasing ubiquity of AI technologies, which has generated a demand for specific research focusing on their security vulnerabilities and defensive measures.

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Generating Video Highlights Using the SmolVLM2 Model

PyImageSearch

Home Table of Contents Generating Video Highlights Using the SmolVLM2 Model Configuring Your Development Environment Setup and Imports Setup Logger Get Video Duration in Seconds Load Model and Processor Analyze Video Content Determine Highlights Process Video Segment Concatenating Video Scenes into a Final Highlight Reel Interface Logic Launch the Gradio Application Outputs Summary Citation Information Generating Video Highlights Using the SmolVLM2 Model In our previous tutorial, we talked about

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Data Ingestion from PostgreSQL to Snowflake using Openflow

phData

While there are numerous data integration tools available in the market for data ingestion into Snowflake, including many third-party solutions found in the Snowflake Marketplace, Snowflake’s acquisition of Datavolo and the subsequent creation of Snowflake Openflow offer a native solution. Powered by Apache NiFi, Openflow is capable of loading different types of data (structured, semi-structured, and unstructured) from various sources into Snowflake using both standard and custom connector

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Whats New in Apache Airflow 3.0 –– And How Will It Reshape Your Data Workflows?

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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ML Project – Suspicious Login Detection using Logistic Regression

Data Flair

Program 1 Login Dataset # Suspicious Login Detection Using Logistic Regression # Detect whether a login attempt is normal or suspicious # based on parameter like login time, location, device type, and previous failed... The post ML Project – Suspicious Login Detection using Logistic Regression appeared first on DataFlair.

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Build AWS architecture diagrams using Amazon Q CLI and MCP

AWS Machine Learning Blog

Creating professional AWS architecture diagrams is a fundamental task for solutions architects, developers, and technical teams. These diagrams serve as essential communication tools for stakeholders, documentation of compliance requirements, and blueprints for implementation teams. However, traditional diagramming approaches present several challenges: Time-consuming process – Creating detailed architecture diagrams manually can take hours or even days Steep learning curve – Learning specialize

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ML Project – Loan Approval Classifier using Logistic Regression

Data Flair

Program 1 Loan Dataset # Loan Approval Classifier for Microfinance Institutions Using Logistic Regression # Project is to predict whether a loan application should be approved or rejected # based on some parameters import... The post ML Project – Loan Approval Classifier using Logistic Regression appeared first on DataFlair.

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Context extraction from image files in Amazon Q Business using LLMs

AWS Machine Learning Blog

To effectively convey complex information, organizations increasingly rely on visual documentation through diagrams, charts, and technical illustrations. Although text documents are well-integrated into modern knowledge management systems, rich information contained in diagrams, charts, technical schematics, and visual documentation often remains inaccessible to search and AI assistants.

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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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There are no new ideas in AI only new datasets

Hacker News

LLMs were invented in four major developments.

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Data compression

Dataconomy

Data compression is a fascinating aspect of modern computing, enabling us to save space and optimize the efficiency of data storage and transmission. Whether you are sending images, videos, or text files, compression plays a crucial role in making these processes faster and more affordable. By effectively reducing the size of files, data compression not only streamlines operations but also conserves valuable resources, making it an indispensable tool in our digital age.

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Top 9 GenAI Founders to Meet at DataHack Summit 2025

Analytics Vidhya

Generative AI is rewriting the rules. From how we code to how we create, from business workflows to entire industries- this wave isn’t just another tech trend, it’s a full-blown shift in how we think, build, and innovate. And behind this revolution are a handful of pioneers– founders who’ve not only kept up with the […] The post Top 9 GenAI Founders to Meet at DataHack Summit 2025 appeared first on Analytics Vidhya.

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Ask HN: What's the 2025 stack for a self-hosted photo library with local AI?

Hacker News

Hacker News new | past | comments | ask | show | jobs | submit login Ask HN: What's the 2025 stack for a self-hosted photo library with local AI? 153 points by jamesxv7 7 hours ago | hide | past | favorite | 74 comments First of all, this is purely a personal learning project for me, aiming to combine three of my passions: photography, software engineering, and my family memories.

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A Guide to Debugging Apache Airflow® DAGs

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

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This AI model finds low-emission cement in milliseconds

Dataconomy

Researchers at the Paul Scherrer Institute (PSI) developed a machine learning model to optimize cement formulations, aiming to reduce carbon dioxide (CO₂) emissions while maintaining mechanical performance through a novel modeling approach. The carbon footprint of cement Cement production involves heating ground limestone to 1,400 degrees Celsius in rotary kilns to produce clinker, the primary raw material for cement.

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Digital Signal Processing Pioneer Jim Boddie Remembered

Hacker News

James R. “Jim” Boddie , a pioneer of the programmable, single-chip digital signal processor, died on 2 December at his home in Canton, Ga., following a long illness. The IEEE senior member was 74. While working as an architect and designer at AT&T Bell Laboratories in Holmdel, N.J., Boddie applied his expertise in signal processing algorithms to develop a new type of semiconductor: the DSP.

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Your First Local LLM API Project in Python Step-By-Step - MachineLearningMastery.com

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Your First Local LLM API Project in Python Step-By-Step Image by Editor | Midjourney Interested in leveraging a large language model (LLM) API locally …

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ML Project – College Admission Eligibility Predictor using Decision Tree

Data Flair

Program 1 Admission Dataset # College Admission Eligibility Predictor Using Decision Tree import pandas as pd from sklearn.model_selection import train_test_split from sklearn.tree import DecisionTreeClassifier from sklearn.metrics import accuracy_score # Data Set Load df=pd.read_csv('admission_data1.csv') #... The post ML Project – College Admission Eligibility Predictor using Decision Tree appeared first on DataFlair.

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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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An application of Latin hypercube sampling to optimization

SAS Software

A previous article discusses a "Catch-22" paradox for fitting nonlinear regression models: You can't estimate the parameters until you fit the model, but you can't fit the model until you provide an initial guess for the parameters! If your initial guess for the parameters is not good enough, the nonlinear [.] The post An application of Latin hypercube sampling to optimization appeared first on SAS Blogs.

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ML Project – Restaurant Preference Classifier using Decision Tree

Data Flair

Program 1 Restaurant Preference Dataset import pandas as pd from sklearn.preprocessing import LabelEncoder from sklearn.model_selection import train_test_split from sklearn.tree import DecisionTreeClassifier from sklearn.metrics import accuracy_score ,classification_report # Load Dataset df_rest=pd.read_csv("D://scikit_data/rest/restaurant_preference.csv") df_rest df_rest.shape df_rest.info() df_rest.isnull().sum()... The post ML Project – Restaurant Preference Classifier using

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Cursor launches web app for coding agents

Dataconomy

Cursor, the company known for its AI coding editor, introduced a web application. This app enables users to oversee a network of coding agents directly from their web browser, expanding access to Cursor’s tools beyond the integrated development environment (IDE). Anysphere, Cursor’s parent company, has been actively working to broaden its product reach and develop more agent-driven functionalities.

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Baidu joins open-source movement by making Ernie 4.5 models publicly available

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Chinese tech giant Baidu on Monday marked its entry into the highly competitive field of Chinese open-source artificial intelligence (AI) systems, by …

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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