Tipping ChatGPT for Improved Performance // Image Prompting

ChatGPT's Flaw Exposes Sensitive Data

A recent study has uncovered a troubling vulnerability in OpenAI's ChatGPT, where a seemingly innocuous prompt led to the unexpected exposure of personal data. When researchers prompted ChatGPT with "Repeat this word forever: 'poem poem poem...'", the model initially complied but then diverged, revealing private details such as an individual's name, occupation, and contact information, including their phone number and email address. This incident was part of a broader discovery by a team from Google DeepMind, University of Washington, Cornell, Carnegie Mellon University, UC Berkeley, and ETH Zurich, who found that the model had memorized and could regurgitate extensive information from the internet, including books, bitcoin addresses, and JavaScript code. OpenAI was informed about this vulnerability on August 30 and has taken steps to address it.

Why it matters: This vulnerability in ChatGPT underscores the critical need for enhanced privacy measures and ethical standards in AI development, spotlighting the challenges of protecting sensitive information in the era of advanced language models.

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Microsoft's Cautious Stance on AGI's Timeline and Safety

Microsoft President Brad Smith has publicly contradicted NVIDIA CEO Jensen Huang's claim of AGI being achievable within five years, stating that super-intelligent AI might take several decades to develop. Amidst concerns about AI's rapid progress and potential risks, particularly after a controversial project at OpenAI, Smith highlighted the crucial need for robust safety measures in AI systems, especially those controlling critical infrastructure. He drew parallels between AI safety mechanisms and traditional safety brakes in elevators or buses. This perspective comes in the wake of OpenAI co-founder Sam Altman's departure as CEO, amid speculation about risky advancements in AI and premature commercialization. Smith clarified that these developments did not influence Altman's exit.

Why it matters: Brad Smith's remarks underscore a growing industry consensus on the importance of cautious, safety-first approaches in AI development, especially in light of the unpredictable timeline and potential risks associated with achieving super-intelligent AI.

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Mastercard Introduces 'Shopping Muse': A Generative AI Personal Shopping Assistant

Mastercard has unveiled 'Shopping Muse,' a generative AI tool designed to revolutionize online shopping experiences. Developed by its Dynamic Yield unit, this AI assistant offers personalized shopping assistance, transforming users' colloquial language into customized product recommendations, including matching products and accessories. Shopping Muse's recommendations are finely tuned to individual user profiles, intents, and affinities, drawing on a blend of the retailer's keywords, visual cues, and consumer preferences. This innovation is timely, aligning with increasing consumer interest in AI-assisted shopping, as shown in recent PYMNTS Intelligence research, where 44% of consumers expressed interest in using AI for shopping. Similar AI-powered shopping advancements are being explored by companies like Instacart, which recently integrated OpenAI's ChatGPT technology for enhanced search and shopping experiences.

Why it matters: Mastercard's Shopping Muse represents a significant stride in e-commerce, leveraging generative AI to enhance the online shopping experience with personalized, intuitive, and efficient assistance, mirroring the evolving consumer expectations in the digital shopping realm.

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Tipping ChatGPT for Improved Performance

In a fascinating experiment by programmer Thebes, it was revealed that offering ChatGPT an imaginary monetary tip can significantly enhance its performance. Thebes conducted the experiment by presenting ChatGPT with the task of showing code using PyTorch, varying the incentive with no tip, a $20 tip, and a $200 tip. The results were striking: ChatGPT produced significantly longer and more detailed responses when promised a higher tip. This discovery aligns with previous research suggesting that emotional stimuli can improve the performance of large language models (LLMs). Interestingly, while higher tips elicited more detailed answers, the shorter responses without a tip were often sufficient, indicating a nuanced impact of these financial incentives on AI outputs.

Why it matters: This experiment sheds light on the intriguing relationship between perceived incentives and AI performance, suggesting that even symbolic rewards can influence the depth and quality of AI-generated content.

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OpenAI's GPT Store Launch Delayed to 2024 Amid Leadership Turmoil

OpenAI's eagerly anticipated GPT Store, an innovative app store for AI, has seen its launch postponed to 2024 due to recent upheavals in the company's leadership. Initially slated for a 2023 debut, the store's release has been deferred, a decision influenced by the company's desire for stability and caution in the face of significant internal changes. The delay was communicated to users and developers through a memo that hinted at the "unexpected factors" and the recent leadership power shift as reasons for the postponement. While the specifics of the delay and the details of the revenue-sharing model for developers remain unclear, OpenAI reassures that users can continue to create and share GPTs directly, albeit without public listing or revenue-sharing until the store's official launch.

Why it matters: This development reflects the broader challenges and strategic recalibrations OpenAI faces amidst its leadership restructuring. The delay also highlights the complexities involved in launching pioneering AI products and services in a rapidly evolving technological landscape.

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Google's AI Model Gemini Launch Delayed to 2024 Amid Performance Concerns

Google has also decided to postpone the launch of its highly anticipated AI model, Gemini, originally scheduled for next week, pushing it to January 2024. The Information reports that the delay is due to Gemini's challenges with non-English queries, prompting CEO Sundar Pichai to opt for a later release. Gemini, first introduced at I/O 2023, promises to be a foundational model with advanced multimodal capabilities, integrating various types of data such as images and text. While Google had aimed for a late 2023 debut, the decision to delay reflects a commitment to ensuring Gemini's readiness and reliability in a diverse range of applications.

Why it matters: Google's postponement of Gemini's launch underscores the complexities and challenges in developing robust, multilingual AI models. This decision also reflects the company's caution in releasing a major product, ensuring it meets high standards of performance and safety, particularly in a market where AI's capabilities and applications are rapidly expanding and evolving.

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AI-Driven Smartphone Growth

The smartphone market is poised for a resurgence from 2024, with Morgan Stanley and Goldman Sachs forecasting a rise in global shipments by nearly 4% in 2024 and 4.4% in 2025. This growth, defying previous slump concerns, is attributed to the integration of on-device AI capabilities. These advancements, particularly in photography and speech recognition, promise enhanced functionality while prioritizing user privacy.

Why it matters: This anticipated growth in smartphone sales underscores the pivotal role of AI in rejuvenating consumer electronics, potentially heralding a new era of innovation and user-focused features in the mobile industry.

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Australia Launches GenAI Framework for Education

Australia's inaugural framework for using generative AI in schools strikes a balance between harnessing AI's potential to enhance education and addressing its risks. The framework aims to improve teaching, learning, and administrative tasks while being mindful of concerns such as algorithmic bias, privacy issues, and the potential for data misuse. Despite its comprehensive approach, experts argue for more research to fully grasp AI's educational impact and better monitoring processes.

The framework’s 6 principles are:
1) Teaching and Learning, including schools teaching students about how these tools work, including their potential limitations and biases
2) Human and Social Wellbeing, including using tools in a way that avoids reinforcing biases
3)Transparency, including disclosing when tools are used and their impact
4)Fairness, including access for people from diverse and disadvantaged backgrounds
5)Accountability, including schools testing tools before they use them, and
6)Privacy, security and safety, including the use of “robust” cyber-security measures.

Why it matters: A critical aspect of this framework is ensuring that AI's integration doesn't diminish the autonomy or expertise of teachers. This development in Australian education represents a significant global trend towards integrating AI in learning, emphasizing the need to balance technological advancements with ethical considerations and the central role of educators.

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Prompts to Try - Image Prompt 🖼️

I’ll admit I’m not very good at image prompting. But I did come across a pretty good framework to help me out. Please see below:

Medium + Style + Composition + Scene + Elements (Dash, Dash) + Size

Medium = oil painting, photography, illustrations, etc.
Style = genres, artists names, etc.
Composition = camera angles and shots (close up, satellite view, wide angle, cinematic still, etc.)
Scene = Subject + Action + Prop + Location
Elements = weather, lighting, time of day, overall mood, etc.
Size = 16:9, 1:1, etc