Investments

Weekly Review 17 October 2025

Some interesting links that I Tweeted about in the last week (I also post these on Mastodon, Threads, Newsmast, and Bluesky):Is AI going to make composers obsolete? https://www.theguardian.com/music/2025/oct/09/classical-music-and-ai-by-tarik-oregan-composer-radio-3I’m still skeptical that AI could do the kind of things I need to use Excel for: https://dataconomy.com/2025/10/07/excel-gets-ai-agent-mode-for-automated-data-tasks/AI is a great help for good honest work avoidance: https://www.theregister.com/2025/10/06/at_last_microsoft_leads_the/AI will destroy 97M jobs in the

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5 Essential Tips to Avoid Generative AI Implementation Failure in 2025

Have you ever found yourself doing something because everyone else is doing it? Have you ever felt like you have to do something because if you don’t, you’ll fall behind? This is exactly what’s happening with GenAI adoption in businesses today. Companies are rushing to implement artificial intelligence, often without a clear strategy, driven by

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AI Design Sprints: Bridging the Gap Between Ideas and Market-Ready Products (Case Study Included)

Today’s businesses constantly seek ways to accelerate innovation processes, reduce costs, and minimize risks. However, the traditional waterfall model is often time-consuming and expensive. So, how can companies innovate quickly and efficiently without breaking the bank? Enter design sprints, a game-changing approach revolutionizing AI product development. They provide a flexible, five-day framework for rapid prototyping

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Top 17 AI-Powered Sales Tools for 2025 to Enhance Customer Acquisition

In today’s fast-paced sales environment, staying ahead of the curve isn’t just an option; it’s a necessity. The latest data from HubSpot reveals a compelling trend: a whopping 80% of sales professionals are turning to AI and automation tools to escape the drudgery of manual tasks such as data entry and meeting scheduling. This significant

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6 Key Reasons Why AI Projects Fail and How to Avoid Them

Recent insights from Gartner have revealed a sobering reality in the world of artificial intelligence: a staggering 85% of AI projects fail to meet their objectives, and only slightly more than half successfully transition from prototype to production. These statistics underscore a critical challenge facing organizations today—how can they navigate the complexities of AI implementation

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The Power of AI for Medical Imaging: 5 Key Applications & Use Cases

Artificial intelligence (AI) is a powerful tool for healthcare professionals, and one of its core applications in this industry is medical imaging. With the ability to analyze large amounts of data quickly and accurately, AI is helping to improve disease detection and diagnosis and personalize treatment plans. Are you interested in learning more? Read this

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Demand Forecasting Is Transforming the Retail Industry, Here’s How

Accurate forecasts are the bedrock of most successful businesses. Forecasts give you a clearer picture of the future, and these pictures allow you to create an effective plan. In retail, for example, an accurate forecast can help you plan how much inventory to stock, how many customer service agents to have on standby, and how to

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9 Biggest Benefits of Using AI in Your Retail Business

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,

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The Good And The Bad: 10 AI Trends to Watch in 2021

Artificial intelligence is developing so quickly that trends can change on a near-weekly basis. What was once a figment of our imagination, the otherworldly dreams we’d read of in science fiction books or see on the screen — is today becoming our reality. One example is how Microsoft is hoping to reawaken the dead, using

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3 Strategic Mistakes Leaders Can Easily Avoid When Thinking About AI Integration

Several years ago, a product manager at a tech company had a data collection problem: to scrape software security vulnerability data from multiple web sources, consolidate the vulnerabilities and store them in a database.As this was an automation problem relating to data, the product manager (PM) immediately concluded that this was a machine learning problem.

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