Wonder Tools 📈 AI for Data Wonder Tools

>> YOUR LINK HERE: ___ http://youtube.com/watch?v=ncO7_0JOhUA

Julius (https://julius.ai/?via=jeremy) is a promising new AI service for analyzing data. I’ve been using it to make sense of — and visualize — my analytics dashboard and find meaning in giant datasets. • You can use it for virtually any type of business or scientific data, or simply to categorize survey responses or interpret spreadsheets. Read on for what’s notable about Julius and other new approaches to AI data analysis. • How I’m using Julius • Julius has helped me make revenue projections and identify reader retention patterns. It can turn anonymized analytics data into specific actionable observations. Substack, Google Analytics, and other platforms offer limited dashboards for understanding readership trends. I have neither the budget to hire a data analyst nor the time to do deep analysis of large datasets without help. So Julius is handy at providing me with insights I can further explore. I think of it as generating idea leads — or data idea seeds. 🌱 • It’s remarkably versatile. You can use it to break down a scientific or geographic study, financial data, or anything else. It runs Python code, so you can replicate its analysis. It builds on the top models from OpenAI and Anthropic, tuning AI specifically to focus on data. • What you can use it for • Here are examples Julius’ team shared with me, now that there are more than a million people using it: • Academic research data Biology experiment results, bioinformatics datasets, psychology doctoral thesis data, and survey data analysis. • Business data Google Ad reports, cybersecurity data, a product manager’s product usage and behavioral data, and sales forecasting. • Data science analysis Predicting housing prices based on economics data, clustering customer segments, and detecting credit card fraud. • How Julius differs from ChatGPT • Julius lets you upload huge data files — up to 8gb on paid accounts. • You can use Python as well as R, a preferred coding language for academic researchers. • With Julius, you can access extra shared server computing horsepower — both CPU + RAM. Basically, it can crunch more numbers faster than other AI chat services, if you’re on a paid account. • You can repeatedly reference data files once you’ve uploaded them. If you’re using Julius for free, data may not be stored, though. I’ve had to re-upload files. • You can install special analysis packages/libraries for advanced projects. • Example: Here’s my visualization thread with Julius (https://julius.ai/s/1ae07f29-a0bc-4a9...) exploring an Our World in Data dataset on Kaggle (https://www.kaggle.com/datasets/whisp...) showing global energy consumption. • Pricing: Free for 15 queries a month; $20 for 250 queries; or $45 for unlimited. There’s a 50% discount for students and academics if you use a .edu account or email [email protected]. • Privacy (https://julius.ai/docs/privacy-policy): Julius erases data from company servers when data is deleted within the app, and each user has access only to their own data within the company’s secure notebook file storage. Per its privacy policy (https://julius.ai/docs/privacy-policy), Julius works with various AI models that aren’t allowed to train on its user data. • Other AI tools for data analysis • Wobby (http://wobby.ai) • Wobby (http://wobby.ai) lets you import your own data, paste in a URL, or search for data sources. You can upload a .csv or Excel file or even copy and paste something from a spreadsheet. You’ll soon also be able to upload a PDF. • Once your data is uploaded you can chat with it, visualize it, or draft a document summarizing key data insights with AI assistance. • The interface centers around the creation of documents. You can create standard documents or landscape-style slides. I prefer creating docs and slides in other tools, and I prefer the Julius interface for exploring datasets. • Wobby feels a bit rough around the edges so far in my testing. It has a lot of potential as a way to turn raw data into reports you can share with colleagues. I appreciate its versatility in letting you choose to upload or search for data. If you’re frequently generating internal reports about company data, it may save you time. • Co-founder and CEO Nathan Tetroashvili recently told me about news organizations using Wobby to streamline data analysis in Europe. In one case, a small news team used Wobby to visualize local election data. They created custom data visualizations for each locality that would have been much more time consuming and difficult to produce with their prior tools. • Pricing (https://www.wobby.ai/pricing): After a 10-day free trial it’s $36/month billed annually for individuals; more for teams. • Privacy (https://www.wobby.ai/privacy-policy): Wobby is incorporated under Belgian law and complies with GDPR rules that help safeguard data privacy. Read its policy (https://www.wobby.ai/privacy-policy) for further details. • Watch...

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