- TipSeason AI Trends
- Posts
- Your chats with Meta's AI might end up on Google
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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(Hypothesis Group)
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:
Hnresumetojobs Platform analyzing resumes for job search.
Carlos-app Personalized language tutoring.
Aitutor Efficient personalized tutoring w/ automation.
ambient.twine Meeting Summary
AIVA Music composition for diverse projects.
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