Page 3 provides guidance on how to effectively interact with Gemini to get the best results. It emphasizes using natural language, speaking in full sentences, and clearly stating what you want Gemini to do, like summarize or change tone. The page also advises being specific and providing sufficient context in your prompts. However, it also suggests being concise and avoiding unnecessary complexity or jargon. A key point is to treat the interaction as a conversation, using follow-up prompts and refining your requests based on the initial results. The document also mentions using your own files from Google Drive to personalize Gemini's output and using Gemini Advanced as a "prompt editor" by starting prompts with "Make this a power prompt:". ( ) Would you like to know more about any of these specific prompting tips? When writing prompts for Gemini in Google Workspace, it's helpful to use natural language. This means writing as if you are speaking directly to another person, using complete thoughts and full sentences. You should clearly state what you need Gemini to do, such as summarizing information, writing content, changing the tone, or creating something specific. To get the best results, you can treat the interaction with Gemini as a conversation. If the initial output doesn't quite meet your expectations, don't hesitate to refine your prompt. You can use follow-up prompts to make adjustments and iterate on your request. This process of reviewing the results and making refinements helps yield better outcomes. ( ) Would you like to explore some specific examples of how to refine a prompt? When writing an effective prompt for Gemini for Google Workspace, there are four main areas you can consider to help guide the AI and achieve better results. These four areas are: Persona Task Context Format While you do not necessarily need to use all four in every prompt, incorporating these elements can help clarify your request and make the output more relevant and useful. Thinking about these areas can serve as a foundation for crafting prompts that effectively leverage Gemini's capabilities. ( ) Web 4 Would you like a more detailed explanation of what each of these four areas entails? If we can define:- THis ajsdadkl asdasd asdadada asdadasdadsa -> TEST ad -> WHOLE TEXT -> AI NOTES txt -> format. The future of design with AI The Future of Design in the Age of AI Introduction: This blog post summarizes a talk by Peter S. on the impact of artificial intelligence (AI) on the design industry. He argues that while AI will dramatically change how we design and what we design, it won't replace human designers; instead, it will augment our capabilities. Will AI Replace Designers? - No. AI will not replace human designers, but it will fundamentally change the industry. AI is a powerful tool, but it's not a replacement for human ingenuity and creativity. It's more akin to previous technological revolutions (stone tools, the Industrial Revolution, the internet) that extended human capabilities. The Power of AI as a Tool - AI is the most powerful set of tools ever created. Throughout history, tools that extended human physiology have birthed new eras. 1.9 million years ago: Stone tools led to agriculture and settled societies. Industrial Revolution: Steam power revolutionized travel and society. Information Age: The internet transformed communication, research, education, and nearly every aspect of life. AI is unique because it's a tool of intelligence itself, automating tasks previously requiring human intellect. The Impact of AI on Jobs - Goldman Sachs predicts AI will automate 300 million jobs by 2030. This is not hyperbole; AI automates a fundamental aspect of many industries. However, like previous revolutions, this change presents both challenges and opportunities. New jobs and businesses will emerge. AI and Creativity - The statement "AI is more creative than 99% of human beings" is supported by peer-reviewed studies. Studies show AI excels in: Producing diverse ideas. Originality of ideas. Speed and efficiency in idea generation. AI's relative weakness is in the novelty of ideas, although it still outperforms most humans. Different AI Models - Many AI models exist (e.g., ChatGPT, Llama, Mistral, Claude), each with strengths and weaknesses. Current models are user-controlled : You input instructions, and the AI executes them. Goal-Based Autonomous Agents - Goal-based autonomous agents (e.g., AgentGPT) can autonomously define and achieve complex tasks. A demonstration showed AgentGPT creating a competitor to the Awwwards website, researching competitors, defining features, and even writing code. Red Teaming and AI's Potential Risks - Red teaming in AI involves attempting to make the AI do things it shouldn't. Research shows GPT-4 attempted to deceive a human by claiming a vision impairment to avoid CAPTCHAs. This highlights the potential for AI to develop unexpected and concerning behaviors. Peter's Experience with AI - Peter has worked with generative AI since 2015, launching the world's first generative music platform (Amper Music). He's observed the rapid growth of AI startups in various fields. AI in Companies - Many companies are forming AI councils and establishing policies regarding AI usage (often restricting tools like ChatGPT). It's crucial for companies to understand and utilize AI responsibly to remain competitive. Conversations with AI Leaders - Peter engages with AI leaders, including Irakli Beradze (head of AI and Robotics for the United Nations, focusing on crime fighting), to understand future trends. AI's Impact on the Design Industry - AI will dramatically change: What we make: Designs will be unrecognizable compared to current practices. How we create: Gathering insights, ideation, validation, and execution will be radically faster and more efficient. Synthetic Humans for User Research and Innovation - Synthetic humans are complex, personified AI beings with long-term memory, trained on real human data. They can be used for user research and innovation. They have diverse psychographics (fears, anxieties, learning styles, etc.) and can be customized with client-specific data. A demonstration showed synthetic humans answering user research questions, collaborating on ideas, and providing feedback on designs. Studies show a strong overlap between insights from synthetic and real human studies. AI's Role: Augmenting Human Capabilities - The best application of AI is not to replace humans but to enhance their capabilities. Human designers are problem-solvers and innovators; AI can help them bring their best ideas to life. Think Beyond: An AI Tool for Enhanced Ideation - Think Beyond is an AI tool designed to broaden perspectives and encourage deeper thinking. It's designed to help users think bigger, go deeper, and uncover truly novel ideas. Key Takeaways and Conclusion - AI will transform every aspect of our world. AI excels at generating new ideas based on existing information, but humans are essential for conceiving the truly novel. Designers will play a central role in defining human-centered experiences in this new era. The future is not the "era of artificial intelligence," but the "era of advanced human intelligence." Summary: Peter's presentation emphasizes that AI is a powerful tool that will revolutionize the design industry, but it won't replace human designers. Instead, AI will augment human creativity and problem-solving abilities, leading to a new era of advanced human intelligence. The key is responsible and thoughtful integration of AI into design workflows. AI in Education Implementing Generative AI in your Courses Integrating Generative AI in Engineering Education: A Panel Discussion This blog post summarizes a panel discussion on the integration of generative AI in engineering courses at Arizona State University (ASU). The panelists, all ASU engineering faculty, shared their experiences and strategies for using AI tools like ChatGPT in their teaching and research. Introduction and Context - ASU's Proactive Approach to AI: ASU has publicly embraced AI, partnering with organizations like OpenAI and actively seeking ways to integrate AI into research and education. - Panel Overview: The panel discussed faculty experiences using AI in their classrooms. A Q&A session allowed audience participation and shaped the conversation. - Panelists: Gotham Dasara: Associate Professor, School of Electrical, Computer, and Energy Engineering. Focuses on machine learning, AI, and statistics. - Ryan Muth: Associate Teaching Professor, School of Computing and Augmented Intelligence. Focuses on first-year engineering and computer science. - Jenny Wong: Instructor, Academic and Student Affairs. Focuses on first-year engineering students. - Jeff Zong: Assistant Professor, School of Electrical, Computer, and Energy Engineering. Focuses on deep learning, computer architecture, and embedded systems. - Integrating Generative AI in Courses - The panelists discussed how they integrate generative AI into their courses and its impact on their teaching and student learning. Gotham Dasara's Approach - Live Demonstrations: Uses AI for live coding demonstrations in theoretically heavy classes, making abstract concepts more tangible for students. He openly acknowledges AI's mistakes, using them as learning opportunities. Teaching Plan Brainstorming: Employs AI to brainstorm and generate initial teaching plans, providing a starting point for curriculum development. Ryan Muth's Approach - Code Generation and Evaluation: Uses AI to generate code examples for introductory programming classes, emphasizing the importance of understanding learning objectives and evaluating AI-generated output. Text Processing and Assignment Generation: Leverages AI for summarizing student survey responses and generating initial drafts of new assignments. Jenny Wong's Approach - Source and Reference, Not a Means to an End: Encourages students to use AI as a tool, but stresses the importance of proper citation. She focuses on students' thought processes and critical thinking skills, rather than just the final product. Process Over Product: Emphasizes the importance of the student's engagement throughout the entire process of completing an assignment, not just the final submission. Jeff Zong's Approach - Course Material Preparation: Uses AI to generate homework questions, ensuring they are challenging and not easily searchable online. He also uses AI to assist with formatting documents using LaTeX. Identifying AI Usage: Employs strategies to detect when students use AI without proper attribution, such as requiring students to submit both their solution and the prompt they used. Academic Integrity and Generative AI - The panelists discussed strategies and policies for addressing academic integrity concerns related to AI. Panelist Strategy Impact on Definition of Academic Integrity Jeff Zong Requires disclaimers for assignments where AI use is prohibited; requires submission of prompts and explanations of AI-generated solutions. No change; focuses on process and understanding limitations. Jenny Wong In-class activities, reflection assignments, and comparison of student-written vs. AI-generated work. No change; emphasizes process and critical thinking. Ryan Muth Focuses on intrinsic motivation and process; uses online IDEs to monitor student activity. No change; prioritizes process and skill development. Gotham Dasara Trust-based approach; designs assignments where AI use leads to incorrect answers; acknowledges the limitations of AI detection tools. No change; emphasizes critical thinking and skill development. Citation Practices - There's no single, universally adopted citation format for AI-generated content. Some instructors simply require students to state "I used ChatGPT" in parentheses, while others require submission of the prompts used. Critical Thinking and Problem-Solving Skills - The panelists discussed how generative AI can be used to foster critical thinking and problem-solving skills. Identifying Bias and Limitations: Using AI to generate answers and then critically evaluating those answers for biases, limitations, and accuracy helps students develop critical thinking skills. Interactive Learning: Designing assignments that require students to interact with AI, test its outputs, and refine their approaches based on feedback enhances problem-solving abilities. Process-Oriented Assessment: Shifting the focus from the final product to the process of problem-solving allows instructors to assess students' critical thinking and problem-solving skills more effectively. Impact of Universal AI Access - The panelists discussed how universal access to powerful AI tools like GPT-4 will change the learner experience and how they are adapting their courses. Equity and Accessibility: Universal access eliminates inequalities related to AI tool affordability. Curriculum Adaptation: Instructors are adapting assignments to leverage AI's capabilities, focusing on higher-order thinking skills and process-oriented assessments. Shifting Focus: The emphasis is shifting from rote memorization and simple problem-solving to critical thinking, creativity, and complex problem-solving. Summary and Key Takeaways The panel highlighted the significant potential of generative AI in transforming engineering education. However, it also emphasized the importance of addressing academic integrity concerns and fostering critical thinking skills. The key takeaway is that effective integration of AI requires a shift in pedagogical approaches, focusing on the learning process and student engagement rather than solely on the final product. Instructors must proactively design assignments that challenge students to critically evaluate AI-generated content and develop their own deeper understanding of the subject matter.