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In the retail industry, you must analyze data to achieve the best results. This is where AI technology can help, as it unlocks many opportunities to optimize almost every aspect of any retail business. This article will cover the nine biggest benefits of using AI in retail. And how it will positively impact your business, employees, customers, even the environment. Importance of AI in the retail industry Artificial intelligence is growing ever-more popular in the retail industry. We’re seeing a growing base of applications. And that’s why Fortune Business Insights forecasts that the AI in retail market will reach $24.1…
Image by Editor # Introduction When I first started learning AI, I spent a lot of time copying code from tutorials, but I realized I was not really understanding how it worked. The real skill is not just running models. It is knowing why they work and how to apply them to real problems. AI books helped me learn the concepts, the reasoning, and the practical side of AI in a way that no quick tutorial could. With this in mind, we are starting this series to recommend FREE but truly valuable books. This article is for all those who…
Banks are losing more than USD 442 billion every year to fraud according to the LexisNexis True Cost of Fraud Study. Traditional rule-based systems are failing to keep up, and Gartner reports that they miss more than 50% of new fraud patterns as attackers adapt faster than the rules can update. At the same time, false positives continue to rise. Aite-Novarica found that almost 90% of declined transactions are actually legitimate, which frustrates customers and increases operational costs. Fraud is also becoming more coordinated. Feedzai recorded a 109% increase in fraud ring activity within a single year. To stay ahead,…
Hi there! If you ended up here, you might be interested in the current report for 2023, available here: Top 10 AI Trends to Watch in 2023. Every year, artificial intelligence takes a giant leap forward. The only way to keep up with the pace of change is to hear from those at the forefront of the industry. This 24-page report allows you to do just that. Here’s what you’ll find inside. Ten Impactful Trends Hear about everything from the advent of the metaverse to the arrival of explainable AI — with each trend supported by a practical example…
Image by Author # Introduction As a data engineer, you’re probably responsible (at least in part) for your organization’s data infrastructure. You build the pipelines, maintain the databases, ensure data flows smoothly, and troubleshoot when things inevitably break. But here’s the thing: how much of your day goes into manually checking pipeline health, validating data loads, or monitoring system performance? If you’re honest, it’s probably a massive chunk of your time. Data engineers spend many hours in their workday on operational tasks — monitoring jobs, validating schemas, tracking data lineage, and responding to alerts — when they could be architecting…
The 5 Day AI Agents Intensive is a hands on learning program created by Google researchers and engineers. It is designed to help developers understand the foundations of AI agents and learn how to build production ready agentic systems. The course covers core components such as models, tools, orchestration, memory and evaluation. It also shows how agents evolve from simple LLM prototypes into reliable systems that can run in real world environments. Day 1: Introduction to Agents The Day 1 whitepaper introduces the basics of AI agents. It explains different agent capabilities and the need for Agent Ops for reliability…
While knowledge of statistics and programming is a must-have for every data scientist, non-technical skills can also help you do the job. One particularly useful attribute is being business-minded, as proven in our article “5 Most In-Demand Skills for Data Scientists.” Now, you may be asking how you can acquire such a broad skill set? And that’s why we’ve prepared a list of resources to help you on your way. The recommendations cover everything from data science to data analysis, programming, and general business. Meaning you’ll have a better understanding of all the mechanisms to make you a more effective…
Image by Editor # Introducing Opal Google Opal is a no-code, experimental tool from Google Labs. It is designed to enable users to build and share AI-powered micro-applications using natural language. The tool converts text prompts into visual, editable workflows. This enables users to create AI applications quickly and easily. Image by Author At its core, Opal serves as an intelligent workbench for both developers and non-developers. It allows you to visually chain together the capabilities of multiple Google AI models, including Gemini (for text and logic), Imagen (for image generation), and VO/V3 (for video generation)—into sophisticated, multi-step, and…
As we are wrapping up 2025, I thought it would be good to take a look back at the AI models that have left a lasting impact throughout the year. This year brought new AI models to the limelight, whereas some of the older models have also surged in popularity. From Natural Language Processing to Computer Vision, these models have influenced a multitude of AI domains. This article will showcase the models which have produced the most impact in the year 2025. Model Selection Criteria The AI models listed in this article have been selected from HuggingFace leaderboards based on the…
If you follow DLabs.AI on LinkedIn, you might have noticed we publish a series there called ‘InsideAI.’ As we want as many readers to enjoy it as possible, we’ve now decided to post it on our blog too. For the uninitiated: InsideAI is our monthly newsletter that captures the most interesting, surprising, and important news from the previous four weeks in the wonderful world of AI, so this month, it includes everything that caught our eye in February. Ready for some shock and awe?! Let’s dive in. Is Facial Recognition Making the Innocent Look Guilty? Facial recognition is a controversial…