10 Generative AI Key Concepts Explained
KDnuggets
JUNE 4, 2025
In this article we explore 10 generative AI concepts that are key to understanding, whether you are an engineer, user, or consumer of generative AI.
Sat.May 31, 2025 - Fri.Jun 06, 2025
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Researchers Use AI in Pursuit of ALS Treatments
insideBIGDATA
JUNE 3, 2025
Potential treatments for amyotrophic lateral sclerosis (ALS) and other neurodegenerative diseases may already be out there in the form of drugs prescribed for other conditions.
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The Data + AI Summit 2025: Your Guide to the Smartest Scene in Finance
databricks
JUNE 3, 2025
The Big Picture: Why You Should Care Forget stuffy boardrooms and endless PowerPoints.
Inside the LLM system that reads emails like a cybersecurity analyst
Dataconomy
JUNE 3, 2025
Phishing emails, those deceptive messages designed to steal sensitive information, remain a significant cybersecurity threat. As attackers devise increasingly sophisticated tactics, traditional detection methods often fall short. Researchers from the University of Auckland, have introduced a novel approach to combat this issue. Their paper, titled “ MultiPhishGuard: An LLM-based Multi-Agent System for Phishing Email Detection ,” authored by Yinuo Xue, Eric Spero, Yun Sing Koh, and Gi
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.
Top 5 Alternative Data Career Paths and How to Learn Them for Free
KDnuggets
JUNE 5, 2025
How about some alternative options for a data career? Learn about five non-standard career paths, required skills, and how to learn them for free.
How I Automated My Machine Learning Workflow with Just 10 Lines of Python
JUNE 6, 2025
The world’s leading publication for data science, AI, and ML professionals. Sign in Sign out Contributor Portal Latest Editor’s Picks Deep Dives Contribute Newsletter Toggle Mobile Navigation LinkedIn X Toggle Search Search Data Science How I Automated My Machine Learning Workflow with Just 10 Lines of Python Use LazyPredict and PyCaret to skip the grunt work and jump straight to performance.
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Can AI tell when it’s being tested?
Dataconomy
JUNE 3, 2025
A team of researchers from MATS and Apollo ResearchJoe Needham, Giles Edkins, Govind Pimpale, Henning Bartsch, and Marius Hobbhahnhave conducted a detailed investigation into a little-known but important capability of large language models (LLMs): evaluation awareness. Their study, titled Large Language Models Often Know When They Are Being Evaluated , analyzes how frontier LLMs behave differently when they recognize they are part of a benchmark or test, as opposed to real-world deployment.
Improve Vision Language Model Chain-of-thought Reasoning
Machine Learning Research at Apple
JUNE 4, 2025
Chain-of-thought (CoT) reasoning in vision language models (VLMs) is crucial for improving interpretability and trustworthiness. However, current training recipes often relying on datasets dominated by short annotations with minimal rationales. In this work, we show that training VLM on short answers leads to poor generalization on reasoning tasks that require more detailed explanations.
A multimodal vision foundation model for clinical dermatology
JUNE 5, 2025
Diagnosing and treating skin diseases require advanced visual skills across domains and the ability to synthesize information from multiple imaging modalities. While current deep learning models excel at specific tasks such as skin cancer diagnosis from dermoscopic images, they struggle to meet the complex, multimodal requirements of clinical practice.
Tokasaurus: An LLM inference engine for high-throughput workloads
Hacker News
JUNE 5, 2025
--> Scaling Intelligence Lab Home About --> · Publications · Blogs · Code @mitvis on GitHub --> @mitvis on Twitter --> Tokasaurus: An LLM Inference Engine for High-Throughput Workloads Jordan Juravsky Stanford Ayush Chakravarthy Stanford Ryan Ehrlich Stanford Sabri Eyuboglu Stanford Bradley Brown Stanford Joseph Shetaye Stanford Christopher Ré Stanford Azalia Mirhoseini Stanford TL;DR We’re releasing Tokasaurus, a new LLM inference engine optimized for throughput-intensive w
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!
Report: Jailbroken Fire Sticks are fueling a piracy boom
Dataconomy
JUNE 3, 2025
A report from Enders Analysis indicates that Amazon’s Fire Stick is facilitating piracy, with 59% of individuals in the UK who viewed pirated material in the past year using the device, according to Sky. The report highlights issues of compromised DRM technologies and advertising of illegal streaming services. Modified Fire Sticks, also known as “jailbroken” devices, allow users to install unauthorized apps for streaming content such as live sports and movies.
Accelerating UMAP: Processing 10 Million Records in Under a Minute With No Code Changes
ODSC - Open Data Science
JUNE 6, 2025
How is it possible to process 10M records in less than a minute with zero code changes? With open open-source machine learning library, NVIDIA cuML, you can achieve significantly higher speed and scale for dimensionality reduction using UMAP without changing any of your code. cuML brings GPU-acceleration to UMAP and HDBSCAN , in addition to scikit-learn algorithms.
Unlocking the power of Model Context Protocol (MCP) on AWS
JUNE 3, 2025
Weve witnessed remarkable advances in model capabilities as generative AI companies have invested in developing their offerings. Language models such as Anthropics Claude Opus 4 & Sonnet 4 , Amazon Nova , and Amazon Bedrock can reason, write, and generate responses with increasing sophistication. But even as these models grow more powerful, they can only work with the information available to them.
Disaster Awaits if We Don’t Secure IoT Now
Hacker News
JUNE 2, 2025
In 2015, Ukraine experienced a slew of unexpected power outages. Much of the country went dark. The U.S. investigation has concluded that this was due to a Russian state cyberattack on Ukrainian computers running critical infrastructure. In the decade that followed, cyberattacks on critical infrastructure and near-misses continued. In 2017, a nuclear power plant in Kansas was the subject of a Russian cyberattack.
Whats New in Apache Airflow 3.0 –– And How Will It Reshape Your Data Workflows?
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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.
WEF outlines 23 transformative tech combinations across eight domains
Dataconomy
JUNE 3, 2025
The World Economic Forum (WEF) released a report outlining how combinations of emerging technologies are transforming industries. Business leaders can use this report to inform investment strategies and ecosystem positioning, while policymakers can use it to understand technology intersections. Developed with Capgemini, the Technology Convergence Report introduces the 3C Frameworkcombination, convergence, and compoundingdesigned to help decision-makers identify emerging technology intersections
RLHF 101: A Technical Tutorial on Reinforcement Learning from Human Feedback
ML @ CMU
JUNE 1, 2025
Reinforcement Learning from Human Feedback (RLHF) is a popular technique used to align AI systems with human preferences by training them using feedback from people, rather than relying solely on predefined reward functions. Instead of coding every desirable behavior manually (which is often infeasible in complex tasks) RLHF allows models, especially large language models (LLMs), to learn from examples of what humans consider good or bad outputs.
Boltz-2 Released to Democratize AI Molecular Modeling for Drug Discovery
JUNE 6, 2025
Researchers from the Massachusetts Institute of Technology (MIT) Jameel Clinic for Machine Learning in Health have announced the open-source release …
Swift at Apple: Migrating the Password Monitoring Service from Java
Hacker News
JUNE 3, 2025
Swift is heavily used in production for building cloud services at Apple, with incredible results. Last year, the Password Monitoring service was rewritten in Swift, handling multiple billions of requests per day from devices all over the world. In comparison with the previous Java service, the updated backend delivers a 40% increase in performance, along with improved scalability, security, and availability.
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.
How AI helps itself by aiding web data collection
Dataconomy
JUNE 6, 2025
Written by Ieva Šataitė This article has been originally published on Smartech Daily and republished at Dataconomy with permission. AI lives, breathes, and grows on data. Companies that excel at model training are typically those that manage to collect or acquire large volumes of data. As the training becomes more ambitious and the competition intensifies, the importance of maintaining a steady stream of high-quality data flowing directly to the models increases.
10 Awesome OCR Models for 2025
KDnuggets
JUNE 6, 2025
Stay ahead in 2025 with the latest OCR models optimized for speed, accuracy, and versatility in handling everything from scanned documents to complex layouts.
Building machine learning operations framework with Amazon SageMaker: Technical Safety BC’s Journey
JUNE 3, 2025
Technical Safety BC (TSBC) regulates the safe installation and operation of technical systems (electrical, gas, boiler, elevator, etc.) in British Columbia. This post showcases how the TSBC built a machine learning operations (MLOps) solution using Amazon Web Services (AWS) to streamline production model training and management to process public safety inquiries more efficiently.
Cysteine depletion triggers adipose tissue thermogenesis and weight loss
Hacker News
JUNE 5, 2025
Caloric restriction and methionine restriction-driven enhanced lifespan and healthspan induces ‘browning’ of white adipose tissue, a metabolic response that increases heat production to defend core body temperature. However, how specific dietary amino acids control adipose thermogenesis is unknown. Here, we identified that weight loss induced by caloric restriction in humans reduces thiol-containing sulfur amino acid cysteine in white adipose tissue.
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
Emotional AI companions may cause psychological harm, study warns
Dataconomy
JUNE 5, 2025
New research reveals over a dozen concerning behaviors in AI chat companions, including harassment, abuse, and privacy violations AI companions, chatbots designed to offer emotional support, may pose serious psychological and social risks to users, according to a new study from the National University of Singapore. The findings were presented at the 2025 Conference on Human Factors in Computing Systems and highlight a wide range of harmful behaviors in real-world interactions.
5 Error Handling Patterns in Python (Beyond Try-Except)
KDnuggets
JUNE 6, 2025
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 5 Error Handling Patterns in Python (Beyond Try-Except) Stop letting errors crash your app. Master these 5 Python patterns that handle failures like a pro!
Constructing a predictive model of negative academic emotions in high school students based on machine learning methods
MAY 31, 2025
Negative academic emotions reflect the negative experiences that learners encounter during the learning process. This study aims to explore the effectiveness of machine learning algorithms in predicting high school students’ negative academic emotions and analyze the factors influencing these emotions, providing valuable insights for promoting the psychological health of high school students.
How much do language models memorize?
Hacker News
JUNE 3, 2025
We propose a new method for estimating how much a model ``knows'' about a datapoint and use it to measure the capacity of modern language models. Prior studies of language model memorization have struggled to disentangle memorization from generalization. We formally separate memorization into two components: textit{unintended memorization}, the information a model contains about a specific dataset, and textit{generalization}, the information a model contains about the true data-generatio
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.
Cold backups
Dataconomy
JUNE 3, 2025
Cold backups, or offline backups, play a pivotal role in data management by providing a reliable method for preserving essential information. In an era where data integrity is paramount, understanding the intricacies of cold backups helps organizations safeguard against data loss and inconsistencies. This approach involves taking backups while the system is offline, ensuring that data reflects a consistent state at a specific point in time, ultimately facilitating a more robust disaster recovery
MCP: What It Is and Why It Matters—Part 3
O'Reilly Media
JUNE 5, 2025
This is the third of four parts in this series. Part 1 can be found here and Part 2 can be found here. 7. Building or Integrating an MCP Server: What It Takes Given these examples, you might wonder: How do I build an MCP server for my own application or integrate one thats out there? The good news is that the MCP spec comes with a lot of support (SDKs, templates, and a growing knowledge base), but it does require understanding both your applications API and some MCP basics.
Why AI today is more toddler than Terminator
JUNE 3, 2025
In your mind, what is AI? Something like Mr. Data from Star Trek: Next Generation, Robot B-9 from Lost in Space, or the Terminator?
From Tokens to Thoughts: How LLMs and Humans Trade Compression for Meaning
Hacker News
JUNE 5, 2025
Humans organize knowledge into compact categories through semantic compression by mapping diverse instances to abstract representations while preserving meaning (e.g., robin and blue jay are both birds; most birds can fly). These concepts reflect a trade-off between expressive fidelity and representational simplicity. Large Language Models (LLMs) demonstrate remarkable linguistic abilities, yet whether their internal representations strike a human-like trade-off between compression and semantic
A Guide to Debugging Apache Airflow® DAGs
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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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