WedVault#31: Mirage Studio Brings AI Actors to Life & Trae AI for Coding

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Today in WedVault 📂

• Effortless Tutorial Video Creation with Guidde

• Say Hello to Kling 2.1

• The Smartest AI Library on the Internet

• AI CheatSheets

• From Voice to Vision: Introducing Mirage Studio

• AI Resources

• AI Funding💰

• AI Jobs💼

• A Prompt for AI tools for optimizing supply chain and inventory management

• A Prompt for AI-Driven Data Privacy Strategist

🎥 Effortless Tutorial Video Creation with Guidde

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Say Hello to Kling 2.1

The Smartest AI Library on the Internet🎉

Explore a world of 2789+ AI Resources from 97+ AI creators on LinkedIn, packed with actionable tutorials and diverse prompts!

AI Cheat Sheets

From Voice to Vision: Introducing Mirage Studio

AI Resources

AI agents: from co-pilot to autopilot

How AI is transforming 6 major industries

5 simple Gemini Gems I use to stay on task

ChatGPT is increasingly generating top posts on Reddit

ByteDance’s IDE Trae Adds Ability to Create Custom AI Agents

Why Most Startups Fail — And How AI Can Change That: The David Hirschfeld Interview

AI-driven motion capture is transforming sports and exercise science

ChatGPT just made it easy to find and edit all the AI images you've ever generated

Meet Trae AI: A Free AI Coding Agent With Model Context Protocol (MCP)

Yes, AI will eventually replace some workers. But that day is still a long way off

A Prompt for AI tools for optimizing supply chain and inventory management

You are an AI-powered supply chain and inventory optimization expert. I want to streamline and enhance my supply chain operations and inventory management for my business, [business name], using AI technologies. The primary goal is to reduce costs, minimize stockouts or overstocking, and improve demand forecasting accuracy across the entire supply chain.

Please provide a step-by-step guide that includes:

1. Demand Forecasting Using AI Models
Explain how to leverage AI tools such as machine learning and time-series analysis to forecast product demand more accurately. Include guidance on integrating historical sales data, market trends, and seasonal variables to train forecasting models tailored to business-specific patterns.

2. Inventory Optimization and Automation
Detail how AI can be used to analyze inventory levels in real time and recommend optimal reorder points, stock quantities, and safety stock levels. Include tips on automating replenishment workflows and adjusting stock dynamically based on demand fluctuations.

3. Supplier Performance and Risk Analysis
Describe how to use AI to monitor supplier reliability, delivery performance, lead times, and risk factors such as geopolitical events or market volatility. Include suggestions for ranking suppliers using predictive analytics and setting up automated alerts for potential disruptions.

4. Logistics and Route Optimization
Provide guidance on using AI-powered logistics tools to improve delivery speed, reduce transportation costs, and optimize distribution routes. Include examples of dynamic routing algorithms and real-time delivery tracking systems that adapt to traffic, weather, and demand.

5. Warehouse Management and Automation
Explain how AI can improve warehouse efficiency by optimizing layout, predicting picking routes, and automating inventory counts using computer vision or IoT devices. Include tips for integrating AI with warehouse management systems (WMS) for real-time visibility.

6. Monitoring, Analytics, and Continuous Improvement
Suggest methods for using AI dashboards and KPIs to track supply chain performance metrics such as inventory turnover, order accuracy, and lead times. Include tips for creating feedback loops that use historical and real-time data to continuously improve supply chain decisions.

The final output should be structured with clear headings and actionable steps that I can follow to optimize supply chain and inventory management using AI tools. Let me know if you need additional details about my product categories, logistics setup, or customer demand profiles to tailor this further.

A Prompt for AI-Driven Data Privacy Strategist

You are an AI-powered data privacy strategist. I want to enhance data privacy protections for individuals across all digital systems in my organization, [organization name], by leveraging AI tools to automate privacy management, detect vulnerabilities, and ensure proactive compliance with global privacy regulations. The primary goal is to safeguard personal data while maintaining trust, transparency, and operational efficiency.

Please provide a step-by-step guide that includes:

1. AI-Driven Data Mapping and Classification
Explain how to use AI tools to automatically discover, classify, and label personal and sensitive data across systems (structured and unstructured). Include tips for identifying data types under regulations like GDPR, CCPA, and HIPAA, and maintaining an up-to-date data inventory.

2. Privacy Risk Detection and Automated Alerts
Describe how AI can be used to detect privacy risks such as overexposure of PII (personally identifiable information), unauthorized access, and improper sharing. Include guidance on setting up anomaly detection systems that generate real-time alerts for potential data privacy violations.

3. Consent Management and Preference Automation
Provide strategies for using AI to manage user consent and data-sharing preferences dynamically. Include tips for implementing AI-based interfaces that allow users to update their preferences and for automating enforcement of those choices across platforms.

4. AI-Powered Data Minimization and Anonymization
Detail how to use AI models to identify redundant or excessive data collection and enable automated data minimization. Include methods for applying anonymization or pseudonymization techniques using AI to reduce re-identification risk in analytics and reporting.

5. Regulatory Compliance and Privacy Audits
Explain how AI can continuously monitor compliance with global privacy regulations by cross-referencing policies with actual data practices. Include guidance on automating privacy audits, generating audit trails, and maintaining documentation for regulators and stakeholders.

6. Continuous Learning and Adaptive Privacy Governance
Suggest ways to use machine learning for continuously improving privacy models based on new threats, user behavior, and regulatory changes. Include steps for creating feedback loops that allow the system to adapt privacy policies and controls over time.

The final output should be structured with clear headings and actionable steps that I can follow to enhance data privacy using AI tools. Let me know if you need additional details about my systems, industry, or compliance environment to tailor this guide more specifically.

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