Sat.Mar 22, 2025 - Fri.Mar 28, 2025

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Mastering Data Normalization: A Comprehensive Guide

Data Science Dojo

Data normalizationsounds technical, right? But at its core, it simply means making data normal or well-structured. Now, that might sound a bit vague, so lets clear things up. But before diving into the details, lets take a quick step back and understand why normalization even became a thing in the first place. Think about itdata is everywhere. It powers business decisions, drives AI models, and keeps databases running efficiently.

Database 195
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Leaked data exposes a Chinese AI censorship machine

Flipboard

A complaint about poverty in rural China. A news report about a corrupt Communist Party member. A cry for help about corrupt cops shaking down entrepreneurs.

AI 180
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What is Adaptive Machine Learning and How Does It Work?

Pickl AI

Summary: Adaptive Machine Learning is a cutting-edge technology that allows systems to learn and adapt in real-time by processing new data continuously. Unlike traditional models, it provides more accurate predictions and insights, making it ideal for dynamic environments. This adaptability enhances decision-making across various sectors, including finance, healthcare, and e-commerce.

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Google Gen AI Toolbox: A Python Library for SQL Databases

Analytics Vidhya

Google has introduced the Google Gen AI Toolbox for Databases, an open-source Python library designed to simplify database interaction with GenAI. By converting natural language queries into optimized SQL commands, the toolbox eliminates the complexities of SQL, making data retrieval more intuitive and accessible for both developers and non-technical users.

SQL 152
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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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Job hunting and hiring in the age of AI: Where did all the humans go?

Flipboard

The proliferation of artificial intelligence tools and overreliance on software such as ChatGPT is making the job market increasingly surreal. Of the 150-odd jobs Jaye West applied for in the past few months, nearly all of them involved artificial intelligence somewhere in the process.

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Airline Demand Between Canada & United States Collapses, Down 70%+

Hacker News

Recently, I wrote about how were seeing a general softening of demand for travel to the United States, for a variety of reasons. Theres no denying that the most contentious situation is between Canada and the United States, and we now have some data that shows just how extreme the change in demand is. Transborder flight bookings are down by 70%+ Weve known that travel demand between Canada and the United States has been decreasing, both by air and by roads.

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How to Use OpenAI MCP Integration for Building Agents?

Analytics Vidhya

To improve AI interoperability, OpenAI has announced its support for Anthropic’s Model Context Protocol (MCP), an open-source standard designed to streamline the integration between AI assistants and various data systems. This collaboration marks a pivotal step in creating a unified framework for AI applications to access and utilize external data sources effectively.

Analytics 281
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You can now download the source code that sparked the AI boom

Flipboard

On Thursday, Google and the Computer History Museum (CHM) jointly released the source code for AlexNet , the convolutional neural network (CNN) that many credit with transforming the AI field in 2012 by proving that "deep learning" could achieve things conventional AI techniques could not. Deep learning , which uses multi-layered neural networks that can learn from data without explicit programming, represented a significant departure from traditional AI approaches that relied on hand-crafted ru

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Google makes Android development private, will continue open source releases

Hacker News

Google is planning a major change to the way it develops new versions of the Android operating system. Since the beginning , large swaths of the software have been developed in public-facing channels, but that will no longer be the case. This does not mean Android is shedding its open source roots, but the process won't be as transparent. Google has confirmed to Android Authority that all Android development work going forward will take place in Google's internal branch.

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Announcing Anthropic Claude 3.7 Sonnet is natively available in Databricks

databricks

Were excited to announce that Anthropic Claude 3.7 Sonnet is now natively available in Databricks across AWS, Azure, and GCP. For the first time, you.

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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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NVIDIA Isaac GR00T N1: The Open-Source Revolution in Humanoid Robotics

Analytics Vidhya

NVIDIA’s Isaac GR00T N1 represents a quantum leap in humanoid robotics, combining cutting-edge AI with open-source accessibility. As the world’s first open foundation model for generalized humanoid reasoning, this technology enables robots to interpret language commands, process visual data, and execute complex manipulation tasks across diverse environments.

Analytics 270
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Cool Site Shows Exactly Which Books Zuckerberg's Minions Illegally Downloaded to Train Meta's AI

Flipboard

For all the revolutionary change artificial intelligence promises, it also makes lofty demands. For starters, AI is extraordinarily power hungry. Generating all the electricity that AI datacenters consume takes forest-loads of energy, not to mention hardware and cooling infrastructure. That stuff all costs a lot, making AI a huge money pit. That's had a big effect on our economy, as the tiniest bit of AI hype can send huge shockwaves through Wall Street and beyond.

AI 162
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This AI learns to click better than you

Dataconomy

Artificial intelligence is finally learning how to navigate your phone screen like a humanexcept faster, smarter, and with shockingly little practice. A new research project from vivo AI Lab and MMLab at the Chinese University of Hong Kong introduces a model called UI-R1 , which rethinks how AI agents are trained to understand and interact with graphical user interfaces (GUIs).

AI 172
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TAO: Using test-time compute to train efficient LLMs without labeled data

databricks

Large language models are challenging to adapt to new enterprise tasks. Prompting is error-prone and achieves limited quality gains, while fine-tuning requires large amounts of.

AI 338
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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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How to Use MCP: Model Context Protocol

Analytics Vidhya

Youve built applications with LLMs. Youve played with agents. Maybe youve even worked with LangChain, AutoGen, or OpenAIs Assistants API. Isnt it impressive how much these models can reason, understand, and generate? But the moment your agent needs to do something real, like check a database, read from a CRM, or fetch a Google Doc; […] The post How to Use MCP: Model Context Protocol appeared first on Analytics Vidhya.

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Teachers Believe That AI Is Here to Stay in Education. How It Should Be Taught Is Debatable.

Flipboard

One of the perks of Angie Adams job at Samsung is that every year, she gets to witness how some of the countrys most talented emerging scientists are tackling difficult problems in creative ways. Theyre working on AI tools that can recognize the signs of oncoming panic attacks for kids on the autism spectrum in one case, and figuring out how drones can be used effectively to fight wildfires in another.

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How to Reach $500K on Upwork

KDnuggets

Check out the story of a Reddit user who has achieved success by following 7 simple rules.

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Fundamental Challenges in Evaluating Text2SQL Solutions and Detecting Their Limitations

Machine Learning Research at Apple

In this work, we dive into the fundamental challenges of evaluating Text2SQL solutions and highlight potential failure causes and the potential risks of relying on aggregate metrics in existing benchmarks. We identify two largely unaddressed limitations in current open benchmarks: (1) data quality issues in the evaluation data mainly attributed to the lack of capturing the probabilistic nature of translating a natural language description into a structured query (e.g., NL ambiguity), and (2) the

SQL 130
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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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Evaluating Toxicity in Large Language Models

Analytics Vidhya

How do we keep AI safe and helpful as it grows more central to our digital lives? Large language models (LLMs) have become incredibly advanced and widely used, powering everything from chatbots to content creation. With this rise, the need for reliable evaluation metrics has never been greater. One critical measure is toxicityassessing whether AI […] The post Evaluating Toxicity in Large Language Models appeared first on Analytics Vidhya.

Analytics 154
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OpenAI’s new AI image generator is potent and bound to provoke

Flipboard

The arrival of OpenAI's DALL-E 2 in the spring of 2022 marked a turning point in AI when text-to-image generation suddenly became accessible to a select group of users, creating a community of digital explorers who experienced wonder and controversy as the technology automated the act of visual creation. But like many early AI systems, DALL-E 2 struggled with consistent text rendering, often producing garbled words and phrases within images.

AI 174
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Mac Studio is the most powerful AI desktop you can actually buy

Dataconomy

Despite its reputation for lagging in AI development, Apple has crafted the best computer for AI research. The Mac Studio featuring the M3 Ultra chip supports unprecedented unified memory allocation, up to 512 GB, making it the easiest and most affordable way to conduct advanced AI research with large models on personal hardware. The latest DeepSeek v3 model demonstrates this with its performance, being run entirely on a single Mac.

AI 179
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Building an Automatic Speech Recognition System with PyTorch & Hugging Face

KDnuggets

Check out this step-by-step guide to building a speech-to-text system with PyTorch & Hugging Face.

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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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LangMem SDK: Personalizing AI Agents with Semantic Memory

Analytics Vidhya

While interacting with AI agents, we often find ourselves repeatedly sharing the same preferences, facts, and information. This lack of long-term memory means the agent cannot learn from past conversations or adapt its responses. Imagine if these AI agents could remember your preferences, learn from previous interactions, and optimize its behavior accordingly, retaining the knowledge […] The post LangMem SDK: Personalizing AI Agents with Semantic Memory appeared first on Analytics Vidhya.

AI 206
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Building a voice interface for generative AI assistants

Flipboard

Generative AI is revolutionizing how businesses interact with their customers through natural conversational interfaces. While organizations can implement AI assistants across various channels, phone calls remain a preferred method for many customers seeking support or information.

AI 150
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Oracle caught in a data breach denial spiral as evidence piles up

Dataconomy

Oracle has denied a breach of its Oracle Cloud federated SSO login servers and the theft of account data for six million users. However, BleepingComputer has verified multiple companies confirm the validity of the alleged breached data samples. The breach was first reported by a person named rose87168, who claimed to have accessed Oracle Cloud servers.

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A Gentle Introduction to Attention and Transformer Models

Machine Learning Mastery

Transformer is a deep learning architecture that is very popular in natural language processing (NLP) tasks. It is a type of neural network that is designed to process sequential data, such as text. In this article, we will explore the concept of attention and the transformer architecture.

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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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Gemini 2.5 Pro vs GPT 4.5: Does Google’s Latest Beat OpenAI’s Best?

Analytics Vidhya

The AI race is heating up with newer, competing models launched every other day. Amid this rapid innovation, Google Gemini 2.5 Pro challenges OpenAI GPT-4.5, both offering cutting-edge advancements in AI capabilities. In this Gemini 2.5 Pro vs GPT-4.5 article, we will compare the features, benchmark results, and performance of both these models in various […] The post Gemini 2.5 Pro vs GPT 4.5: Does Google’s Latest Beat OpenAI’s Best?

Analytics 219
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Mythbuster: Here’s what ‘agentic’ AI actually means for advertisers, agencies and publishers

Flipboard

Forget chatbots and prompt engineering agentic is the latest AI buzzword to captivate and confuse marketers and media execs. In recent months, tech firms like OpenAI have emphasized AI agents and agentic applications of the technology in their mission to popularize generative AI adoption. The latest development comes courtesy of Adobe, which unveiled several AI agent tools last week at its Summit conference in Las Vegas , including a foundation agentic platform and 10 off-the-shelf AI agents.

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Land Your Dream Machine Learning Job in 2025

KDnuggets

In this article, I will go through 5 pointers on how to help you secure your dream job.

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Self-Supervised Learning from Images with JEPA

Hacker News

This paper demonstrates an approach for learning highly semantic image representations without relying on hand-crafted data-augmentations. We introduce the Image-based Joint-Embedding Predictive Architecture (I-JEPA), a non-generative approach for self-supervised learning from images. The idea behind I-JEPA is simple: from a single context block, predict the representations of various target blocks in the same image.

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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!