Your chats with Meta's AI might end up on Google

Delta’s dynamic AI pricing plan sounds different now

Welcome to TipSeason Trending AI Newsletter.

In today’s edition, we will cover:

  • Trending AI News

  • Trending AI Tools

  • Best AI Prompt pick for ChatGPT / Gemini / any AI

Also welcome to the new subscribers who joined us this week and staying on top of AI Trends.

Trending AI News:

  • Your chats with Meta's AI might end up on Google — just like ChatGPT until it turned them off Link

  • Delta’s dynamic AI pricing plan sounds different now Link

  • Your favorite model? Thanks to AI, they might not be real Link

  • Research: The Hidden Penalty of Using AI at Work Link

  • Developer survey shows trust in AI coding tools is falling as usage rises Link

  • Future-Proofing Your Coding Career in the Age of AI Link

  • Why open-source AI became an American national priority Link

  • Bill Gates says AI is moving at a speed that ‘surprises’ even him Link

  • First A.I. school coming to San Francisco Link

  • In Review: It’s Not Too Late for the Movies to Reject AI Link

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Best AI Prompt Pick:

For ChatGPT, Bard, Claude and other AI chatbots:

Topic: Predictive Analytics for Sales Forecasting

Prompt:

Act as an expert in predictive analytics and sales forecasting. Your task is to provide a deeply structured and actionable guide based on the following variables:


1. [Industry Context]: e.g., retail, SaaS, B2B services  
2. [Forecasting Horizon]: e.g., weekly, monthly, quarterly  
3. [Data Maturity Level]: beginner, intermediate, advanced


Goal: Deliver a highly specific, real-world applicable breakdown of how to apply predictive analytics for accurate and scalable sales forecasting in the given industry.


Context: Base your responses on expert-level knowledge in time series forecasting (ARIMA, SARIMA, Prophet), regression models (Lasso, XGBoost), and ML deployment techniques. Include methodologies such as CRISP-DM, ABC/XYZ segmentation, and cross-validation strategies. Use relevant KPIs like MAE, RMSE, and MAPE to assess model performance. Adjust strategies based on [Data Maturity Level] and [Forecasting Horizon].


Output should follow this structure:


1. **Introduction** – Explain predictive analytics in sales forecasting within the [Industry Context].
2. **Step-by-Step Breakdown** – Cover data preparation, model selection, training/testing, performance evaluation, and deployment.
3. **Best Practices & Common Pitfalls** – Highlight proven tactics and common challenges.
4. **Actionable Recommendations** – Offer expert-level guidance customized to the user's environment, tools, and goals.


Requirements:
- Use professional, analytical tone  
- Format content in bullet points or subheaders  
- Be thorough and data-driven  
- Prioritize specificity, depth, and reasoning  
- Do not include phrases like: whether, unleash, unlock, craft, leverage, are you looking, tired of, struggling to or any similar ones

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Trending AI Tools:

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