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

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7 Best Strategies (Besides Job Portals) to Land Top-Paying Jobs in 2025

KDnuggets

Tired of the job portal grind? Dont just applymake them come to you! Check out 7 powerful strategies to land top-paying tech jobs in 2025.

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AI Is advancing but can chatbots understand human feelings?

Dataconomy

Artificial intelligence (AI) is rapidly transforming the world around us, from self-driving cars to medical diagnoses. One of the most visible faces of this revolution is the chatbot computer programs designed to simulate conversation with human users. These increasingly sophisticated entities are handling customer service inquiries, providing technical support, and even offering companionship.

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How AI Improves Nondestructive Testing

ODSC - Open Data Science

Artificial intelligence (AI) is necessary in every sector now, as it analyzes large amounts of data, offers query-based determinations, and helps businesses innovate. Tech experts combine its potential with nondestructive testing (NDT) to rewrite how corporations execute evaluations. What does this look like, and how does AIhelp? What Is Nondestructive Testing?

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Words Matter: Are Language Barriers Driving Quiet Failures in AI

Towards AI

Author(s): Kris Naleszkiewicz Originally published on Towards AI. The AI revolution is upon us, transforming how we work, live, and interact with the world. Yup. We know. Weve all heard. The media loves to cover spectacular successes and failures. But what about the quiet failures? The stalled projects. The initiatives that never quite get off the ground.

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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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The significance of LMS in regulatory compliance

Dataconomy

For more than a decade, learning management systems (LMS) have helped organizations streamline their training and education processes. Whether you need to train a team of 20 people or an entire organization of 800+ employees, these tools can scale as per your requirements and deliver personalized learning materials for individuals in different job roles.

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How IDIADA optimized its intelligent chatbot with Amazon Bedrock

AWS Machine Learning Blog

This post is co-written with Xavier Vizcaino, Diego Martn Montoro, and Jordi Snchez Ferrer from Applus+ Idiada. In 2021, Applus+ IDIADA , a global partner to the automotive industry with over 30 years of experience supporting customers in product development activities through design, engineering, testing, and homologation services, established the Digital Solutions department.

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Using Generative AI to Build Generative AI

O'Reilly Media

On April 24, OReilly Media will be hosting Coding with AI: The End of Software Development as We Know It a live virtual tech conference spotlighting how AI is already supercharging developers, boosting productivity, and providing real value to their organizations. If youre in the trenches building tomorrows development practices today and interested in speaking at the event, wed love to hear from you by March 5.

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How multiple AI models can team up to solve complex problems

Dataconomy

Large Language Models (LLMs) have transformed the way AI tackles reasoning problems, from answering tricky math questions to making sense of ambiguous human language. But theres a catchthese models often struggle when reasoning gets too complex. A single AI can get stuck in local decision traps, missing better solutions simply because it doesnt know what it doesnt know.

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AI Hype Will Plunge America Into Financial Ruin, Economist Warns

Flipboard

What hasn't been said about artificial intelligence? It's a disruptor, a game changer, the next technological revolution. Soon we'll all be chilling with our feet up while our AI assistants do all the heavy lifting right? One economist isn't so sure. A new study by Caleb Maresca at New York University predicts that just the looming possibility of transformative AI has the potential to completely upend the economy in a bad way, decimating wages and sending interest rates skyward.

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Accelerate IaC troubleshooting with Amazon Bedrock Agents

AWS Machine Learning Blog

Troubleshooting infrastructure as code (IaC) errors often consumes valuable time and resources. Developers can spend multiple cycles searching for solutions across forums, troubleshooting repetitive issues, or trying to identify the root cause. These delays can lead to missed security errors or compliance violations, especially in complex, multi-account environments.

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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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Claude 3.7 Sonnet vs Qwen 2.5 Coder: Which is Better for Coding Tasks?

Analytics Vidhya

Claude 3.7 Sonnet and Qwen 2.5 Coder 32B Instruct are leading AI models for programming and code generation. Qwen 2.5 stands out for its efficiency and clear coding style, while Claude 3.7 Sonnet shines in contextual understanding and adaptability. In this article, I will compare their generated code, focusing on syntax quality, structural coherence, and […] The post Claude 3.7 Sonnet vs Qwen 2.5 Coder: Which is Better for Coding Tasks?

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Orange Group data breach: Every step explained

Dataconomy

The Orange Group data breach has exposed sensitive customer and corporate data, affecting hundreds of thousands of individuals and employees. The breach was confirmed after a hacker leaked internal documents from Orange Romania, a subsidiary of the French telecommunications giant Orange Group. This attack, attributed to a threat actor named Rey , was carried out after Orange refused to pay a ransom demand.

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How Factory is turning AI into ‘a junior developer in a box’

Flipboard

Many things remain uncertain about AIs future impact on our lives. One that isnt in doubt is that more and more of the worlds software will be written, at least in part, by software. Already, 25% of Googles code is generated by AI, CEO Sundar Pichai said last October. By 2028, projects research firm Gartner, 75% of enterprise developers will use AI tools in their work.

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Derive generative AI powered insights from Alation Cloud Services using Amazon Q Business Custom Connector

AWS Machine Learning Blog

This blog post is co-written with Gene Arnold from Alation. To build a generative AI -based conversational application integrated with relevant data sources, an enterprise needs to invest time, money, and people. First, you would need build connectors to the data sources. Next you need to index this data to make it available for a Retrieval Augmented Generation (RAG) approach where relevant passages are delivered with high accuracy to a large language model (LLM).

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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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Estimating the ‘laziness’ of federal workers

FlowingData

Some might have you believe that federal employees don’t put in the work. For the Washington Post’s Department of Data, Andrew Van Dam shows data that suggests otherwise. In case you’re unfamiliar with the WP column, Van Dam (usually) attempts to answer a question each week using data. I like how he takes the reader through the exploratory process of trying to figure things out.

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Google and Salesforce just signed a huge $2.5 billion AI deal

Dataconomy

Salesforce and Alphabet’s Google have signed a multi-billion dollar agreement to integrate their artificial intelligence and customer relationship management tools, valued at $2.5 billion over seven years. The deal aims to link Google Cloud’s infrastructure with Salesforce’s AI-powered Agentforce assistants, CRM software, and Data Cloud capabilities, benefiting joint business customers by enhancing interactions between Google Workspace and Salesforce’s CRM and AI solution

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Hard problems that reduce to document ranking

Hacker News

There are two claims I’d like to make: LLMs can be used effectively1 for listwise document ranking. Some complex problems can (surprisingly) be solved by transforming them into document ranking problems. I’ve primarily explored both of these claims in the context of using patch diffing to locate N-day vulnerabilitiesa sufficiently domain-specific problem that can be solved using general purpose language models as comparators in document ranking algorithms.

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ByteDance processes billions of daily videos using their multimodal video understanding models on AWS Inferentia2

AWS Machine Learning Blog

This is a guest post authored by the team at ByteDance. ByteDance is a technology company that operates a range of content platforms to inform, educate, entertain, and inspire people across languages, cultures, and geographies. Users trust and enjoy our content platforms because of the rich, intuitive, and safe experiences they provide. These experiences are made possible by our machine learning (ML) backend engine, with ML models built for video understanding, search, recommendation, advertisin

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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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Front uses AI to translate sketches into "brilliantly bad" objects

Flipboard

Front 's Anna Lindgren and Sofia Lagerkvist have unveiled three 3D-printed vases that were designed by artificial intelligence based on their two-dimensional drawings. The Swedish designer duo has trained a generative artificial intelligence (AI) program to translate their sketches into three-dimensional objects without using text prompts. They presented the latest results in the exhibition AI: Brilliantly Bad!

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Google now lets you remove personal info from search results

Dataconomy

Google has introduced a streamlined feature allowing users to remove personal information, such as phone numbers, addresses, or emails, directly from its search results, marking a significant step toward user privacy control. Initially launched in 2022 and refined over the past year, this toolhighlighted in a recent Google blog postempowers individuals to reduce their digital footprint with a straightforward process, responding to growing concerns over online exposure.

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Claude 3.7 Sonnet vs Grok 3: Which LLM is Better at Coding?

Analytics Vidhya

Since last June, Anthropic has ruled over the coding benchmarks with its Claude 3.5 Sonnet. Today with its latest Claude 3.7 Sonnet LLM, it’s here to shake the world of generative AI even more. Claude 3.7 Sonnet much like Grok 3, released a week ago – comes with advanced reasoning, mathematical, and coding abilities. Both […] The post Claude 3.7 Sonnet vs Grok 3: Which LLM is Better at Coding?

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Evaluate healthcare generative AI applications using LLM-as-a-judge on AWS

AWS Machine Learning Blog

In our previous blog posts, we explored various techniques such as fine-tuning large language models (LLMs), prompt engineering, and Retrieval Augmented Generation (RAG) using Amazon Bedrock to generate impressions from the findings section in radiology reports using generative AI. Part 1 focused on model fine-tuning. Part 2 introduced RAG, which combines LLMs with external knowledge bases to reduce hallucinations and improve accuracy in medical applications.

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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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Enhancing RAG: Beyond Vanilla Approaches

Flipboard

Retrieval-Augmented Generation (RAG) is a powerful technique that enhances language models by incorporating external information retrieval mechanisms. While standard RAG implementations improve response relevance, they often struggle in complex retrieval scenarios. This article explores the limitations of a vanilla RAG setup and introduces advanced techniques to enhance its accuracy and efficiency.

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AI-generated headshots: Are they worth it for your business?

Dataconomy

Headshot photographs can help many businesses stand out. However, they can be very expensive. This is one of the many reasons why more business owners are using AI-generated headshots instead. These programs help people create good headshots quickly. easily and affordably. AI headshot generators have already created over 12 million headshots for over 80,000 users.

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DeepSeek #OpenSourceWeek Day 2: Release of DeepEP

Analytics Vidhya

DeepSeek is here with its Day 2 of #OpenSourceWeek and today they introduced DeepEP – An open Source EP communication library for MOE model training and inference. Till now, I have been completely impressed by DeepSeek and their answer to the billion-dollar models of OpenAI, Meta and more. Now, they are open-sourcing the building blocks […] The post DeepSeek #OpenSourceWeek Day 2: Release of DeepEP appeared first on Analytics Vidhya.

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Disconnect between generated and real beauty expectations

FlowingData

Generative AI is readily accessible these days, which has led to an influx of nice-looking, but impractical beauty inspiration for many. For the Washington Post, Tatum Hunter on what that influx looks like for the stylists tasked with the impossible : Rita Contreras, a hairstylist in Brooklyn, said that in the past six months, the number of clients walking in with AI images has ballooned.

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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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Nvidia revenue forecasts for first quarter exceed estimates

Flipboard

Nvidia forecast first-quarter revenue above market estimates on Wednesday, expecting robust demand for its leading AI chips to persist as businesses spend heavily to expand generative artificial intelligence infrastructure. Its shares rose about 1% in choppy extended trading, after closing up 3.7% in regular trading. Nvidia is the biggest beneficiary of a rally in AI-linked stocks, with its shares up more than 400% over the last two years.

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Starbucks lays off over 1,000 jobs and slashes 30% of its menu

Dataconomy

Starbucks announced on Monday that it will lay off over 1,000 corporate workers and simplify its menu in a bid to turn around lagging sales. The restructuring aims to streamline operations as the coffee chain continues to face challenges. Starbucks to lay off over 1,000 workers and cut menu by 30% The company plans to cut about 30% of its menu, including several Frappuccino blended drinks, the Royal English Breakfast Latte, and White Hot Chocolate.

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Microsoft Phi-4 Multimodal: Hands-on Guide

Analytics Vidhya

Microsoft has officially expanded its Phi-4 series with the introduction of Phi-4-mini-instruct (3.8B) and Phi-4-multimodal (5.6B), complementing the previously released Phi-4 (14B) model known for its advanced reasoning capabilities. These additions significantly enhance multilingual support, reasoning, and mathematical skills, and introduce multimodal capabilities.

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Agentic RAG: Mastering Document Retrieval with CrewAI, DeepSeek, and Streamlit

Towards AI

Last Updated on February 25, 2025 by Editorial Team Author(s): Vikram Bhat Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Image generated using napkin.ai In my previous blog, I explored building a Retrieval-Augmented Generation (RAG) chatbot using DeepSeek and Ollama for privacy-focused document interactions on a local machine here.

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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