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Apple has significantly enhanced its lineup with innovative AI features, thanks to a collaboration with OpenAI. We're eager to see how these updates resonate with users. Additionally, we've prepared a comprehensive guide on Predictive Analytics in AI. This issue also delves into a critical discussion on how some AI firms are compromising privacy by using images of children without consent to train their models. Stay tuned for insights and implications!

• 📰 News and Trends.

• Understanding Predictive Analytics in AI.

• AI Tools Are Secretly Training on Real Images of Children.

• 🧰 AI Tools (Life Assistants)

• Publications we recommend.

• Apple goes all-in on AI at its Keynote.

📰 AI News and Trends

• FEC and FCC Clash Over AI Election Regulations as 2024 Presidential Race Approaches (Cooksey FCC)

• New Research Shows ChatGPT can easily Find Zero-Day Vulnerabilities, Breaching 8 of 15 Websites (Arvix)

• SpaceX scales up Starfactory, aiming to build a Starship a day (New Atlas)

• Canadian Grand Prix to feature F1's first AI-designed trophy (ESPN)

• OpenAI has hired the ex-CEO of Nextdoor Sarah Friar as its first CFO and former Instagram product chief Kevin Weil as chief product officer (TheInformation)

• AI Startup Perplexity Says News Summary Tool Has ‘Rough Edges’ (Bloomberg)

🌐 Other Tech news

• X tweaks rules to formally allow adult content (TC)

• Roaring Kitty Strikes Again: GameStop Shares Surge 21% After Keith Gill (aka Roaring Kitty) Reveals $116 Million Stake, Nearing Billionaire Status Amid Market Manipulation Concerns (WSJ)

• New York Set to Restrict Social-Media Algorithms for Teens (WSJ)

• Buoyed by regulatory vacuums, Silicon Valley is building a booming online wellness market that aims to leave the doctor’s office behind (TheAtlantic)

• Binance reaches 200M users with $100B in assets under custody (CT)

• Why California Is Swinging Right on Crime (TheAtlantic)

Understanding Predictive Analytics in AI

Predictive analytics uses machine learning to analyze data, identify patterns, and predict future outcomes. This approach transforms business operations through intelligent, data-driven decisions regardless of your operations size.. Here’s Five ways you can get started with predictive analytics across different use cases, using tools that do not require technical knowledge.

1. Churn Prediction

• Tool: Dataiku or MonkeyLearn - A no-code AI platform that allows users to build prediction models for analyzing customer feedback and predicting churn.

• Real-Life Example: Small e-commerce businesses use MonkeyLearn to analyze customer reviews and predict which factors might lead to churn, helping them to proactively address issues.

• Impact: Reduces customer attrition by identifying and mitigating dissatisfaction early.

2. Resource Management

• Tool: Forecast or Smartsheet – An easy-to-use platform that integrates with existing tools to forecast resource needs and manage project timelines.

• Real-Life Example: Marketing agencies use Smartsheet for campaign management, helping them allocate resources efficiently based on projected client demand.

• Impact: Optimizes staff allocation and reduces overhead costs.

3. Inventory Management

• Tool: Ordoro or QuickBooks Commerce – Offers inventory forecasting features that predict stock levels needed based on past sales data.

• Real-Life Example: Small retailers use QuickBooks Commerce to manage inventory across multiple channels, ensuring optimal stock levels during peak and off-peak seasons.

• Impact: Helps avoid overstocking and understocking, thus saving costs and boosting sales.

4. Risk Management

• Tool: Riskturn or Zoho Analytics – A business intelligence platform that provides insights and forecasts risks with easy drag-and-drop interfaces.

• Real-Life Example: Financial advisors use Zoho Analytics to predict investment risks and returns for their clients, enhancing decision-making.

• Impact: Improves risk assessment capabilities, helping to safeguard investments.

5. Project Planning

• Tool: Asana or Trello – Integrates AI-based features like automation (Butler) to predict and manage project tasks efficiently.

• Real-Life Example: Event planners use Trello to track project milestones and deadlines, ensuring all tasks are completed on time.

• Impact: Streamlines project management, enhancing productivity and project delivery success.

To start make sure to identify your business goals, select easy-to-use tools that match your skills and needs, and utilize available templates and guides for setup. Today's user-friendly platforms make predictive analytics accessible to all, allowing businesses of any size to harness AI for insightful, data-driven decisions.

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AI Tools Are Secretly Training on Real Images of Children.

A report from Human Rights Watch has exposed that over 170 images and personal details of Brazilian children have been used without consent to train AI models. This data was scraped from sources like mommy blogs and low-view YouTube videos, intended for private viewership, and incorporated into LAION-5B, a dataset used by AI startups including Stability AI’s Stable Diffusion tool. The issue underscores not just a breach of privacy but highlights the potential for misuse, such as generating deepfakes or revealing sensitive information like location or medical data.

Reflection on AI Ethics and Human Responsibility:

The controversy surrounding the unauthorized use of children's images in AI datasets reflects broader ethical and moral dilemmas in the tech community, particularly regarding privacy and the potential for harm. While AI itself is a tool with vast potential for both positive and negative outcomes, the core of the problem often lies in human actions—specifically, the disregard for privacy and ethical standards in the pursuit of technological advancement. Greed and negligence in handling sensitive data showcase a significant lapse in responsibility among tech developers and researchers. Effective solutions require stringent regulations and a fundamental shift in how personal data is treated in the digital realm, emphasizing respect for individual rights and strict adherence to ethical guidelines in data usage.

🧰 AI Tools

Life Assistants.

• Rewind AI - Allows you to capture and store all your memories with ease and privacy.

• Replika - AI companion.

• Prodigy AI - HAL is your personal AI career coach. Whether you're an engineer seeking your next opportunity, HAL can help.

• Elektrif AI - Personal dating assistant powered by GPT-3.

• PlaylistAI - Playlist maker for Spotify and Apple Music. Get creative and make playlists from AI prompts, images, videos, or simply your most-played music.

• GPT-Trainer - A must-try AI Agent Platform*

📰 Publications I am currently reading and recommending:

• 5 Steps Friday - Simple success for jacked nerds. Join 73,000+ subscribers and get weekly tips on marketing, health, and earning more.

• Deep Walks - The newsletter for deep thinkers. Perspective-changing quotes, reflections, and essays on everything from world religion to ancient philosophy.

Apple goes all-in on AI at its Keynote.

Apple has introduced a new artificial intelligence system named 'Apple Intelligence' on its Worldwide Developers Conference (WWDC) in 2024. This innovative system will be integrated across Apple's major platforms, including iPhone, iPad, and Mac, enhancing user experience with new AI-driven features. Unlike its competitors, Apple plans to concentrate on practical AI functionalities that cater to a broad audience, such as AI-powered summarizations, smart reply suggestions, and a significant enhancement to Siri’s capabilities, which has been revamped thanks to an alliance with OpenAI, allowing more seamless control over apps. Importantly, Apple has decided to sidestep more sensational AI features like image and video generation, which have been popular elsewhere in the tech industry. So far: "Apple WWDC 2024 showcases iPhone Mirroring, macOS Sequoia, and AI-driven enhancements in handwriting and math recognition, along with new iPad Air models. It has also enhanced safari allegedly making it the fastest and more secure browser.

In terms of technical execution, Apple Intelligence will intelligently choose between processing tasks locally on the device or leveraging cloud-based resources. This decision will be powered by an algorithm that assesses the complexity of the task and the capabilities of the device. For instance, tasks on newer devices equipped with an M1 chip or later might be handled on-device, while more demanding tasks may require cloud assistance, especially on older models. This hybrid approach underscores Apple’s commitment to privacy, as the system is designed not to build personal profiles from user data or share information externally. These features will be optional, providing users with the flexibility to opt-in as they see fit, ensuring that Apple's enhancements in AI are both user-friendly and secure.