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Text on Beyond Market Intelligence: a running collection of 6 stories we have gathered and hand-picked because they are worth your time. Every post here touches on text in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around text, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
Removing the AI check
We understand the frustration with the recent change to the error correction button. Previously a quick fix for incorrectly formatted data—like those Excel files sometimes saved as text—it now appears as an AI check, significantly slowing down the process. Many users, like you, are experiencing this delay while others retain the original, faster button. Explore manual cell adjustments as an alternative, though current limitations may prevent this. For broader insights into data management workflows, see our article, "Excel + Power Query and Power Automate."
Sorting column content separated by comma
Migrating from Google Sheets to Excel? Encountering a unique sorting challenge? This function—`=sort(unique(trim(tocol(iferror(split(Log!J33:J,",")),1))))`—efficiently extracts and alphabetizes comma-separated values within a column. It's a powerful technique for consolidating data, ensuring each item is uniquely represented and neatly ordered. If you're managing large datasets, similar to the approach described in "How to keep a large data set on one sheet that prints out multiple pages?", this method can be invaluable. Explore this solution to streamline your Excel workflows and unlock greater data clarity.
How to Remove Claude Watermarks from Text, Code, and Files
Anthropic’s Claude now embeds watermarks in AI-generated content, presenting a new challenge for users. Understanding how these watermarks manifest—through embedded text markings, signed C2PA metadata for files, and a nuanced approach to code—is crucial. This post details methods for removing these watermarks from text, code, and supported files, empowering you to leverage Claude’s capabilities with greater flexibility. Explore the intricacies of Claude's detection methods and discover practical removal techniques.
Amazon, which started off selling books, is destroying rare texts to train AI
Amazon’s expansion into AI is raising critical questions about data sourcing. Reports indicate the company is destroying rare books—incredibly valuable resources for training Large Language Models—to feed its AI systems. This practice highlights a growing tension: while vast datasets are essential for LLM development, the reliance on irreplaceable historical materials presents a significant ethical and preservation concern.
Claude Now Watermarks Everything It Makes
Since August 2nd, 2026, Anthropic’s Claude models now incorporate a critical layer of transparency: content watermarking. All generated text receives a subtle, embedded watermark, while files are digitally signed. This commitment aligns with the EU AI Act’s Code of Practice, ensuring accountability in AI-generated content. Discover how this innovation fosters trust and governance in the evolving landscape of AI. For a deeper dive into related efforts to strengthen AI governance, explore "IBM and Red Hat Expand Lightwell."
A Gentle Introduction to Autoencoders & Latent Space
Heavy computation poses a significant challenge in modern machine learning, particularly within generative AI. To address this, autoencoders offer a powerful solution: compressing data into a lower-dimensional representation while retaining essential context. This approach unlocks efficiency and enables more manageable workflows. “A Gentle Introduction to Autoencoders & Latent Space” explores this transformative technique, providing accessible insights into its core principles. Discover how latent space can empower your data journey – a concept explored further in articles like "Superhuman’s new auto-draft feature."