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AI technology is revolutionizing the key developer process and workflow at light speed. Alibaba Cloud has released significant releases recently for Qwen Code (0.0.12 to 0.0.14). Qwen Code features powerful capabilities like Plan Mode and Vision Intelligence. This brings an element of security, intelligence, and flexibility to this Qwen AI coding buddy. In this article, we will cover these releases and test them out in a hands-on session.  The New Qwen Code Updates 🚀 Exciting updates in Qwen Code v0.0.12–v0.0.14!✨ What’s new?• Plan Mode: AI proposes a full implementation plan—you approve before a single line changes.• Vision Intelligence: Auto-switch to…

I hear a lot about how the 5G mobile network technology will change the world and especially be a big enabler for applied AI. But is that really true? Will 5G be an AI gamechanger? The short answer is no. 5G is nice. It’s a convenient technology that will be nice for AI but in no way a big deal. The best comparison I can make is that 5G is like new roads. Asking people behind AI solutions if 5G is a gamechanger is like asking a shopkeeper the same about new roads. And that being in a location with already…

Are you looking to tailor AI technologies to meet your unique challenges? Fine-tuning could be the answer. The method refines pre-trained models (like GPT) to perfectly align them with a specific objective. That said, it’s important to know that fine-tuning isn’t one-size-fits-all. In this article, we’ll take a thorough look at fine-tuning. We’ll demystify how it functions, illustrating the process with clear, relatable examples. You’ll also learn about its diverse applications in various sectors and understand the advantages and potential drawbacks it brings. We’ve structured this information to be straightforward and comprehensible, ensuring it’s accessible no matter your level of…

Image by Author   When we talk about Python, we often think about using it to perform data analysis or build a machine learning model. It’s less common to discuss creating full web applications with Python outside of simple prototypes using libraries such as Streamlit or Taipy. However, a library called Reflex offers web application development features that compete with those of other programming languages. Entirely in Python, this open-source library helps users build anything from small data science apps to large, multi-page websites. With strong flexibility yet intuitive Python code, we can easily scale web development to suit our…

Enterprises are moving past simple chatbots into complex, business-critical AI systems. Different teams are experimenting at once, which sounds exciting but quickly turns chaotic. Costs rise, systems fragment, and reliability drops when there’s no shared control layer. The OpenAI outage in August 2025 made this painfully clear: copilots froze, chatbots failed, and productivity tanked across industries. Now the question isn’t whether companies can use AI, it’s whether they can trust it to run their business. Scaling AI safely means having a way to manage, govern, and monitor it across models, vendors, and internal tools. Traditional infrastructure wasn’t built for this,…

When I write about AI I very often refer to data operations and how important a foundation it is for most AI solutions. Without proper data operations you can easily get to a point where handling the necessary data will be too difficult and costly for the AI business case to make sense. So to clarify a little I wanted to give you some insight on what it really means.Data operations is the process of obtaining, cleaning, storing and delivering data in a secure and cost effective manner. It’s a mix of business strategy, DevOps and data science and is…

Despite considerable advancements, the healthcare industry remains entangled in significant challenges that undermine its fundamental mission: prioritizing patient care and enhancing treatment experiences. This article offers an in-depth examination of the top 10 challenges confronting the healthcare sector in 2025, highlighted by revealing data from the latest industry reports and studies. Join us as we unpack these insights, offering you a richer perspective on the intricacies of the healthcare landscape. We hope this exploration inspires you to devise impactful new solutions. 1. Staff Shortages One of the most pressing challenges facing the healthcare industry today is staff shortages. This issue,…

Image by Author   # Introduction  Exploratory data analysis (EDA) is a key phase of any data project. It ensures data quality, generates insights, and provides an opportunity to discover defects in the data before you start modeling. But let’s be real: manual EDA is often slow, repetitive, and error-prone. Writing the same plots, checks, or summary functions repeatedly can cause time and attention to leak like a colander. Fortunately, the current suite of automated EDA tools in the Python ecosystem allows for shortcuts on much of the work. By adopting an efficient approach, you can get 80% of the insight…

What if an application could deliver personalized intelligence to customers, without ever seeing their data? For product developers, the skill of operating in a world of rising data privacy demands is a must-have today. As organizations shift from traditional analytics to embedded intelligence, the need for highly secure and scalable applications has become mission-critical. Snowflake Native Apps Framework is not just another product; it marks a paradigm shift in how we build and distribute data products. It challenges the status quo that every software must control the data it interacts with. Instead, it flips the model; your app not only…

Collecting data is for many AI projects without a doubt the most expensive part of the project. Labelling data like images and text pieces is hard and tedious work without much possibility of scaling. If an AI project requires continuously updated or fresh data then this can be a high cost that can challenge the whole business case of an otherwise great project.There are a few strategies though to lower the costs of labelling data. I have previously written about Active Learning; a data collection strategy that focuses on prioritizing the labelling of the most crucial data first given the…