The Daily AI Show Scavenger Hunt: Recapping Our MOST MEMORABLE AI Moments in 2024

https://www.thedailyaishow.com In today's episode of the Daily AI Show, Brian, Beth, and Andy discussed the evolving art of prompt engineering in AI for 2025. They focused on the importance of clear instructions, the growing capabilities of AI models in various applications like image and video generation, and the need to adapt prompting techniques with advancements in technology to achieve desired outcomes effectively. Key Points Discussed: Continuous Improvement in Prompting: The hosts emphasized that while some core principles of prompt engineering remain, the models have significantly improved. This has made clarity in instructions more vital than ever, allowing for better AI-generated results. Innovative Approaches in Image and Video Generation: Beth highlighted the advancements in AI's capabilities for generating images and videos, stressing the importance of understanding specific languages and providing examples to achieve desired outcomes. Leveraging AI's Analysis Abilities: The discussion included insights on how new model capabilities in analyzing tasks and providing detailed outputs have fundamentally changed how prompts can be structured for research and problem-solving. Impact of Enhanced Search Features: Brian noted the substantial improvements in search capabilities within ChatGPT, which now allow for broader and more comprehensive data gathering without needing to specify multiple URLs, streamlining the research process for users. Testing and Iterative Improvement: The episode encouraged users to start prompting from their current skill level, iterate, seek model help for prompt refinement, and use multiple tools to overcome challenges, ultimately enhancing their expertise and outcomes. #AI, #PromptEngineering, #ImageGeneration, #AIVideo, #ChatGPT Episode Breakdown: 00:00:00 🎬 Intro & Topic Overview 00:00:33 👋 Welcome & 2025 Prompting 00:01:57 🤔 Continuous Prompting Principles 00:03:23 🎨 Image & Video Prompting 00:04:13 ✨ Clarity & Concise Instructions 00:06:49 🗣️ Specific Language in Prompts 00:09:39 📝 Starting Simple vs. Specific 00:12:02 🧐 Understanding Prompt Weight 00:13:50 🛠️ LLMs for Prompt Improvement 00:15:34 🎯 Intent & Desired Outcomes 00:17:46 🔎 ChatGPT Search Enhancements 00:21:44 🤔 Prompt vs. Instructions 00:24:14 🗣️ Conversational AI & Prompting 00:29:05 🚀 Future of Prompt Engineering 00:31:53 🙌 Hands-on Prompting & Iteration 00:35:29 🧐 Analysis & Chain of Thought 00:37:10 🔄 Switching Models ("The Punt") 00:39:11 🤖 Prompt Engineering & LLMs 00:41:02 💻 Artifacts & Canvas: New Tools 00:44:17 🖼️ Image & Video Prompting Techniques 00:48:33 🐶 Video Example: Detailed Prompts 00:50:57 ✨ Rapid Fire Prompting Tips 00:55:17 💡 Simplifying & Chaining Prompts 00:57:20 ✅ Avoiding Ambiguity & Prioritization 00:58:19 👋 Wrap Up & Future Shows

https://www.thedailyaishow.com In today's episode of the Daily AI Show, Brian and Andy, joined by co-host Jyunmi, explored the emergence of reasoning models like OpenAI's O1 and Google's Gemini 2.0. They discussed how these models offer more nuanced problem-solving capabilities, albeit with higher computational costs and response times. The conversation highlighted how these models can help achieve business and personal goals by breaking down complex inquiries into manageable parts. Key Points Discussed: Introduction to Reasoning Models: Andy explained that reasoning models such as O1 from OpenAI are designed for complex problem-solving, dynamically allocating compute time to deliver more comprehensive responses. These models are best suited for tasks requiring in-depth analysis, such as intricate math problems or nuanced science queries. 2025 Vision Planning: The crew related these models to goal setting and planning for the future. By using reasoning models, users can detail their current states and desired future outcomes, providing effective strategies and solutions for reaching goals. Practical Applications in Business: Jyunmi emphasized the utility of reasoning models in entrepreneurship and business strategy. These models can guide startups in navigating essential components and resources needed to lower the barriers to business success. Use of Platforms and Models: The hosts compared O1 with Gemini 2.0, noting differences in reasoning capabilities, latency, and context window size. While O1 is accessible to ChatGPT Plus users with limitations, Gemini 2.0 provides multimodal reasoning and faster response times. User Experience and Model Adaptation: They touched on platform developments allowing for model switching and memory features, such as OpenAI's automatic switching based on user needs, making reasoning models easier to work with. #AIModels #ReasoningAI #BusinessStrategy #OpenAI #FuturePlanning 00:00:00 🎬 Intro - Planning with AI Models 00:01:21 🤔 What are Thinking Models? 00:02:10 💡 Thinking Model Use Cases 00:05:00 🩺 Medical Reasoning with AI 00:06:12 🎯 Setting Goals for 2025 00:07:11 🤖 Setting Expectations for AI 00:08:28 📈 Business Use Cases 00:09:50 ❓ Asking the Right Questions 00:11:08 🎬 Creative Use Cases for AI 00:12:40 📝 Preparing to Use AI Models 00:14:18 📈 Example: Growing a Podcast 00:15:23 ⚙️ Model Switching and Agnosticism 00:17:59 💻 Choosing the Right Model 00:19:17 🪞 Vision Boards and Self-Improvement 00:22:05 ✨ Multimodal Capabilities 00:23:45 💰 Cost and Access to Models 00:25:43 🗣️ Reasoning Process Transparency 00:26:47 🤝 Aligning with AI's Understanding 00:28:55 📝 Defining Goals and Resources 00:30:30 🗓️ Implementation and Milestones 00:31:49 ✨ Defining Success Factors 00:32:07 💼 Project and Product Management 00:35:15 🎞️ Analyzing Video Content 00:37:00 🌐 Limitations of Current Models 00:38:07 ⚙️ Custom Instructions and Features 00:40:34 📝 Manual Custom Instructions 00:41:51 🧠 Reasoning Effort Parameter 00:43:11 ✨ Four Secrets to Using AI for Planning 00:44:54 💾 Memory and ChatGPT 00:46:15 📁 Uploading Files to O1 00:47:24 🗣️ Claude and Perplexity's Reasoning Abilities 00:48:16 👋 Outro and Next Show Preview

https://www.thedailyaishow.com In today's episode of The Daily AI Show, co-hosts Beth, Brian, Jyunmi, Karl, Andy, and Eran came together to celebrate New Year's Eve 2024 with a live show that covered their reflections on the year. They shared stories of their own funny moments, fails in AI projects, and insights into AI's future. They delved into everything from personal challenges and AI hiccups to the potential shockwaves AI developments might send through the tech industry. The conversation offered an engaging mix of humor and insights, perfectly wrapping up the year for the DAS crew. Key Points Discussed: 2024 Scavenger Hunt Beth led the discussion of humorous personal and public AI stories from 2024. This included the co-hosts’ personal fails and public AI mishaps, like the notorious cheese and nontoxic glue Google mishap, as well as their own technical challenges faced while deploying AI technologies. AI Fails and Funny Stories Brian shared a story about a custom GPT project that didn't go as planned, revealing the unpredictable nature of AI deployment. Meanwhile, Eran recounted AI-generated video fails with Hi Jen, and Karl shared an amusing anecdote about exploring AI solutions with an adult entertainment company. Future Shock and AI Potential Andy highlighted the arrival of DeepOrg’s V3, a more compute-efficient AI model that challenges the productivity and cost-effectiveness of current leading models. This reflects a major shift in AI capabilities and the landscape of competition among global tech companies. Impactful AI Trends in 2024 The team discussed how the hype cycle around AI has inflated expectations and noted the characteristically mixed success in meeting those expectations throughout the year. They pondered what 2025 might hold in store for the industry. Community Engagement The hosts interacted with their audience, exchanging memorable AI-related stories, and celebrated the New Year alongside listeners, ushering in 2025 with enthusiasm and anticipation for what lies ahead. #AITrends #2024Recap #DailyAIShow #FutureOfAI #AItechnology Timeline 00:00:00 🎬 Intro & 2024 AI Fails 00:04:20 🛠️ Custom GPT Fail Story 00:08:40 🤔 AI Deployment Challenges 00:11:25 😂 Funny AI Moments in 2024 00:16:33 🍕 Google's Pizza Glue Gaffe 00:19:00 🪨 Google's "Eat Rocks" Advice 00:21:32 🤣 AI Humor & Hype Cycle 00:24:24 🔞 AI in Adult Entertainment 00:33:08 💡 AI Marketing Insights 00:37:30 🤖 Replit Coding Fail Story 00:43:24 ⚠️ AI Customer Service Concerns 00:48:24 ✨ Future Shock: Mind-blowing AI 00:52:45 🇨🇳 DeepOrg's V3: Game Changer 00:56:30 🧄 Garlic Bread & Claude 00:58:21 🇦🇺 Happy New Year in Perth! 1:00:11 👋 Outro & Next Show Promo

https://www.thedailyaishow.com In today's episode of the Daily AI Show, hosted by Beth, Brian, Andy, and Jyunmi, the discussion revolved around a series of transformative AI stories that have potential implications for business professionals and tech enthusiasts alike. The co-hosts tackled exciting developments from Nvidia's focus on robotics to China's innovative progression despite US sanctions, and Meta's introduction of AI-generated social media users as well as other significant advancements in AI such as the groundbreaking Deep Seek model from China. Key Points Discussed: Advancements in Facial Expression Recognition: Julie started with a breakthrough from Osaka University addressing the "uncanny valley" with lifelike facial expressions in androids through waveform technology. This innovation could enhance human-robot interactions, making them more seamless and empathetic. Nvidia's Role in Robotics: Andy highlighted Nvidia's new small computer, Jetson Thor, meant for humanoid robots, and their acquisition of Run AI. These initiatives underscore Nvidia's commitment to providing foundational AI technology for global robotics development. China's Deep Seek and AI Innovation: Beth discussed the introduction of Deep Seek V3, a 671 billion parameter AI model from China. It demonstrates significant advancements in efficiency and processing speed, challenging US-restricted GPUs by using older models effectively. Meta's AI Characters on Social Platforms: Brian commented on Meta's plan to introduce AI-generated users on Facebook and Instagram, aimed at engaging younger demographics. The discussion opened up concerns and perspectives about the implications on genuine interaction versus entertainment. Hugging Faces' Small Agents: Brian also mentioned Hugging Face’s launch of Small Agents, a library that simplifies integrating agent capabilities into language models, allowing them to perform real-world actions and access external information more efficiently. OpenAI's Shift to Profit: The co-hosts also talked about OpenAI’s transition plan to become a Delaware public benefit corporation, seeking a balance between investor interests and societal benefits amidst legal challenges. #AIInnovation #NvidiaRobots #DeepSeek #MetaAI #OpenSourceAI Episode Timeline: 00:00:00 🤖 Intro & Nvidia Robotics 00:00:39 👋 Welcome to the Daily AI Show 00:01:02 🤖 Lifelike Android Expressions 00:02:05 🤔 The Uncanny Valley 00:03:05 🌊 Waveforms for Emotions 00:04:23 🤝 Human-Computer Interaction 00:05:16 ❓ Waveform Questions & Nvidia's Jetson Thor 00:07:16 🤖 Nvidia's Focus on Robotics 00:08:30 💻 Nvidia's AI Frameworks & Run AI Acquisition 00:09:13 💸 Nvidia & Run AI Acquisition Finalized 00:10:00 🇨🇳 ByteDance & Nvidia Chips 00:11:22 🤔 China's AI Innovation & DeepSeek Intro 00:12:15 ✨ DeepSeek's Massive Model 00:13:49 🚀 Multi-Token Prediction 00:14:55 💰 DeepSeek's Low Training Cost 00:16:03 💡 Efficient and Affordable AI 00:17:11 🔓 Open Source & Business Implications 00:18:16 💬 DeepSeek Identifying as ChatGPT & Home Use 00:19:32 🏠 Running DeepSeek at Home 00:21:39 💰 Cost Comparison: Data Center vs. Home 00:24:21 🤔 Ethical Considerations & Censorship 00:26:39 🤗 Hugging Face Small Agents 00:29:40 🤖 What are Agents? 00:31:56 💻 Small Agents: A Simple Library 00:33:50 🔌 Expanding AI Capabilities 00:35:36 🌐 Democratizing AI Development 00:36:31 ❓ What are Small Agents? 00:37:39 🧠 Meta's Large Concept Model 00:39:27 🤔 Beyond Token Prediction 00:40:27 🤖 Meta's AI-Generated Users 00:41:56 🤔 Impact on User Experience 00:42:28 🤔 Entertainment vs. Manipulation 00:45:09 💰 Manipulation & Data Collection 00:47:08 🤔 Meta's Research vs. Commercialization 00:49:05 🤖 AI in Facebook Groups & OpenAI's Transition 00:51:16 🤔 AI Moderators & OpenAI's Profit Plan 00:53:35 🖥️ Cerebras Systems & AGI Discussion 00:55:06 👋 Closing Remarks & Farewell

https://www.thedailyaishow.com In today's episode of the Daily AI Show, Brian, Beth, Karl, Andy, and Jyunmi gathered to discuss the latest and most intriguing AI developments making headlines. Topics ranged from advancements in AI-driven drunk detection cameras and real-time American Sign Language interpretation to innovative AI tools for hobbyists and compelling developments in micro-robotics for medical applications. Key Points Discussed: AI-Driven Traffic Safety: The crew discussed AI-enabled cameras being tested in the UK and Ireland to identify potentially drunk drivers. These systems alert local officers for further inspection, aiming to enhance road safety. Real-Time ASL Interpretation: Florida Atlantic University's project on AI technologies capable of interpreting American Sign Language was highlighted, showcasing potential to bridge communication gaps for the hearing-impaired. Innovative AI Tools: Andy introduced Nvidia's new affordable computer for hobbyists, the Orin Nano, which allows for localized AI function integration without the need for a large data center, opening up creative possibilities for edge AI applications. AI in Agriculture: The potential applications of Nvidia's Jetson for managing crops and livestock were explored, emphasizing its utility in revolutionizing agricultural practices. AI-Driven Medical Innovations: The use of microbots to treat infertility by clearing fallopian tube obstructions was detailed, providing hope for addressing specific female infertility cases. Industry Shifts: The episode also touched on significant industry news, including Google easing restrictions on AI use in sensitive areas with human oversight, and their substantial investment in renewable energy to power data centers. The hosts wrapped up with a rapid-fire segment discussing recent AI advancements across multiple companies, providing a comprehensive overview of the ever-evolving AI landscape. #AIAdvancements #AIInAgriculture #AIForSafety #RealTimeTranslation #AIInHealthcare Episode Timeline: 00:00:00 💡 Intro and Exciting AI News 00:01:04 🤔 Most Exciting News? 00:02:08 🚗 AI-Powered Drunk Driving Detection 00:05:54 🔮 Future of AI and Cameras 00:06:34 🙌 AI Interprets Sign Language 00:07:47 📱 Sign Language App Potential 00:09:34 🤔 Sign Language and Ethics 00:11:32 💻 Nvidia's New Jetson 00:13:20 🏡 Jetson Projects and Ideas 00:15:39 🎅 Christmas Elf AI 00:16:59 🐶 AI Companions and Anxiety 00:18:01 🆚 Nvidia vs. Halo Edge AI 00:18:21 🌾 AI in Agriculture 00:20:47 🌿 AI Weed Control 00:21:02 🧠 Worm-Inspired AI 00:23:03 🤔 Why Worm Brains? 00:24:39 ✨ Specialized AI Models 00:26:15 🕶️ Meta Smart Glasses Update 00:27:18 🌱 Real-World Glasses Use Cases 00:28:08 ⚖️ Google Relaxes AI Restrictions 00:29:38 ⚡️ Google's Renewable Energy Investment 00:31:25 ☀️ Solar Energy Cost Reduction 00:32:22 🤖 Tiny Robots for Infertility 00:34:19 ❤️ Other Medical Applications? 00:35:58 🧲 Magnetic Microbots 00:37:07 🏢 Grammarly and Coda Merge 00:38:55 ⚠️ Jailbreaking AI Models 00:40:17 🎞️ The Year of AI Video 00:42:47 🎬 AI Video Quality and Features 00:44:41 ✏️ AI and Narrative Cohesion 00:45:52 📰 AI News Roundup 00:49:00 🎙️ Outro and Upcoming Announcements

https://www.thedailyaishow.com In today's episode, the Daily AI Show crew, including Beth, Jyunmi, Brian, Andy, and Karl, gathered to discuss Google's recent advancements with their AI developments and tools. Shifting the spotlight away from OpenAI, they highlighted Google's progress over the past few weeks, sharing insightful discussions on Google's AI innovations and capabilities in comparison to its competitors. Key Points Discussed: Google AI Studio: The talk started with Karl demonstrating Google's AI Studio, particularly its real-time processing capabilities. He showcased how it could analyze and describe video content frame by frame, faster than real-time. The team speculated on its real-world applications, especially in various professional scenarios such as healthcare. Gemini 2.0: The group touched upon Google DeepMind's Gemini 2.0, emphasizing its performance improvements and advanced features. They elaborated on its practical implications, including real-time video processing and potential for engaging more effectively with large datasets. Project Mariner: A demonstration of Project Mariner, which could automate tedious, multi-step browser tasks, was shared. The team noted its potential to improve efficiency and productivity in professional environments, though current limitations were also acknowledged. Deep Research Capabilities: Highlighting Google's strengths, the panel discussed how AI can now conduct deep research by analyzing multiple sources to generate thorough reports, marking a significant advancement in automated data collection and analysis. Future Implications on Education: With AI tools being capable of performing complex research tasks, the crew anticipated changes in educational paradigms, where the focus might shift from effort-based evaluations to result-oriented assessments, fostering more critical thinking and analytical skills among students. Show Segments: 00:00:00 🌠 Intro and Initial Discussion 00:00:39 👋 Welcome and Google Focus 00:01:14 📰 Google's Recent AI Announcements 00:01:33 🧑‍🤝‍🧑 Introductions 00:02:10 📢 Show Reminders & Newsletter 00:02:59 🎤 Carl's Google AI Studio Demo 00:06:13 🎮 Real-Time Video Analysis 00:08:40 📑 Spreadsheet Calculations 00:11:14 ✨ AI Companion Potential 00:12:39 🔮 Minority Report-Style Interfaces 00:13:18 🕵️ How the AI Processes Video 00:14:45 🖥️ Sharing Screen with AI 00:17:03 🤔 How the AI Analyzes Video 00:18:42 🔄 Real-Time Feedback Loop? 00:19:48 💡 Business Use Cases 00:20:49 🧪 Testing with Simpler Videos 00:22:41 🗣️ Scene-by-Scene Description Test 00:24:15 ⏩ Faster than Real-Time Clarification 00:26:17 🕹️ Live Assistance in Gaming 00:28:45 🗺️ Visualizing the AI Process 00:29:21 ✨ Agentic Capabilities: Tool Use 00:30:11 🔎 Gemini Advanced Search Demo 00:33:08 🧐 Beth's Gemini Advanced Test 00:34:26 🍓 "Strawberry" Easter Egg? 00:35:20 🧭 Project Mariner Introduction 00:39:52 ⚙️ Mariner Web Navigation Demo 00:42:02 🖥️ Active Tab Limitation 00:44:02 🤖 Chrome Agent Potential 00:45:48 📈 Sales Prospecting Use Case 00:46:57 📝 Beth's Research Results 00:48:38 ✍️ Limerick and NotebookLM 00:49:24 👍 Research Quality and AI 00:50:36 📣 OpenAI's Output Summit & Search 00:51:09 🤔 Redefining "Do Your Own Research" 00:52:16 🏫 Impact on Education 00:53:07 ✨ Other Google Experiments 00:54:01 👋 Outro and Upcoming Shows #ArtificialIntelligence #GoogleAI #AIResearch #AIInnovations #DailyAIShow

https://www.thedailyaishow.com In today's episode of the Daily AI Show, co-hosts Brian, Jyunmi, Karl, and Beth discussed a variety of issues around AI's role in evolving business operations, particularly when it comes to the decreasing value of effort-based pricing. They tackled how AI is shifting the business landscape, challenging traditional models, and what this means for industries that depend heavily on human expertise. The conversation was enriched by insights into how companies are handling these changes and what future business models may look like. Key Points Discussed: AI and Effort-Based Pricing: The discussion began with the notion that businesses historically charge for services based on effort and time spent. The co-hosts explored how AI, with its ability to perform tasks at near-zero marginal cost, is disrupting this model. They pondered the challenges facing industries such as law and consulting, where high hourly rates are customary, as AI could potentially automate many of these costly tasks. Evolution of Business Models: Beth highlighted the shift towards value-based pricing models. This change, driven by AI efficiencies, requires companies to focus more on outcomes and results rather than time and labor. The group discussed the importance of re-evaluating traditional business models to stay competitive. Human Expertise and AI: Despite AI's capabilities, Brian noted the enduring importance of human expertise. He argued that AI should be seen as a tool that augments human capabilities rather than replaces them. The conversation emphasized the role of experts who can leverage AI effectively to deliver unique insights and add value in ways machines cannot. Business Strategy and Technology Integration: Karl and Jyunmi discussed the necessity for companies to reassess their processes in light of new technologies. They advocated for a shift from traditional methods to more innovative, AI-driven strategies that could transform operational efficiency and business outcomes. The Human Connection: The co-hosts emphasized the irreplaceable nature of the human element in business, underscoring how personalized customer service and unique human insights remain key differentiators in the age of AI. #AIrevolution #BusinessInnovation #AIintegration #HumanExpertise #FutureBusinessModels Episode Timeline: 00:00:00 🛠️ Intro - The Plumber Analogy 00:00:34 👋 Show Intro & Topic Overview 00:01:36 📰 Newsletter & OpenAI Updates 00:02:34 🤔 Ethan Mollick's AI Challenge 00:03:51 ⚖️ Law Firms & AI Disruption 00:05:08 📊 Value-Based Consulting 00:05:55 🤖 Sam Altman on AI Agents 00:08:02 📺 Technology Evolution & AI 00:09:29 🚀 The One-Person Billion-Dollar Company 00:11:33 🤔 Re-analyzing Systems with AI 00:13:21 🎥 AI Video Generation & Empowerment 00:14:17 🏢 Doing More with Less: Company Perspective 00:15:27 ⌛ The Future of Effort-Based Billing 00:17:06 📝 AI & Traditional Verification Systems 00:17:58 🤔 The Missing Point: Human Discernment 00:19:24 💰 From SaaS to Outcome-Based Pricing 00:22:28 🛠️ The Plumber Analogy Revisited 00:24:03 📝 Project-Based Pricing & Expertise 00:25:47 📸 The Digital Camera Conundrum 00:27:08 👨‍💼 Everyone's a Marketer (Until They're Not) 00:28:31 🤔 The Importance of Human Expertise 00:30:14 🤖 AI Consulting & The Human Element 00:33:12 ✏️ The Human as Editor 00:34:45 📧 AI in Sales: Personalization vs. Volume 00:35:23 🏋️‍♀️ CrossFit & Competition: Analogy 00:37:54 🤔 Choosing One Firm Over Another 00:40:37 🧑‍💼 Tailoring AI to Unique Businesses 00:41:22 🤔 The End of Experts? 00:44:32 📚 Expertise vs. Encyclopedias 00:45:46 🚀 AI for Business Outcomes 00:47:04 🤔 Taylorism Lens & Future Business 00:47:45 ✨ Wrap Up & Call to Re-evaluate 00:49:49🔮 Predictions & Show Schedule

https://www.thedailyaishow.com In today's episode of the Daily AI Show, our co-hosts Brian, Beth, Jyunmi, and Karl engaged in a compelling discussion about AI-driven podcast tools. They focused on several advanced platforms such as Google Notebook LM, Play AI, and Gen FM, delving into how these tools are transforming the auditory content landscape, the impressive features they offer, and their potential future impact. Key Points Discussed: AI Podcast Platforms: The hosts explored multiple podcast tools, including Google Notebook LM which offers innovative features like Audio Overviews that allows turning content into podcast-style outputs. Meanwhile, Play AI, the focus of today's discussion, provides a variety of features like AI-generated voices, the ability to clone voices, and multiple file uploads for creating unique audio content. Interactive Podcast Creations: Karl demonstrated Play AI's capability by using various voices, including Beth’s cloned voice for creating different types of audio outputs such as children’s stories and debates, highlighting the potential of AI in customizing audio experiences. Voice Cloning and Rights: The discussion highlighted the importance of voice cloning, diversity in voice generation, and the considerations surrounding intellectual property rights of cloned voices. This is significant as it touches on privacy and potential ethical implications in AI-generated audio content. The Future of AI in Audio Content: The panelists speculated on the future integrations of AI in daily life, envisioning interactive podcast experiences in vehicles and personalized listening experiences. They also reacted to the recent updates from Google, allowing live text interactions during audio overviews, signaling the immediate responsiveness and adaptability of AI innovations. Comparative Analysis: Through comparing Notebook LM and Play AI, the hosts underscored the nuances in audio quality and production capabilities, noting that while Notebook LM offered smooth, podcast-like outputs, Play AI opened up a broad spectrum of creative avenues. #AIPodcast #VoiceCloning #PodcastTools #AIInnovation #TheDailyAIShow Episode Timeline: 00:00:00 🎬 Intro & Friday the 13th 00:00:38 🗓️ 12 Days of OpenAI & Newsletter 00:01:28 🎙️ AI Podcast Face-Off: Play.ht vs NotebookLM 00:02:28 🗣️ Play.ht Features Overview 00:04:53 💻 Play.ht Demo: Uploading Files 00:06:31 🧒 Children’s Story & Voice Cloning 00:07:48 🎙️ Creating a Full Show with Play.ht 00:08:37 🗣️ Beth’s Voice Clone Demo 00:09:35 🗣️ Madge Voice Clone Demo & Discussion 00:11:52 🗣️ Tips for Voice Cloning & Inflections 00:13:41 🗣️ Introducing “Madge” 00:14:30 🤔 Voice Cloning Rights & Privacy 00:16:30 😬 Cloning Risks & Ethical Considerations 00:17:38 ⏩ Rapid Advancements in Voice Cloning 00:18:06 ⚔️ Debate Style Podcast Demo 00:19:46 ❓ Source Material & Analysis 00:20:28 👨‍💼 Executive Briefing Demo 00:21:31 🧸 Children’s Story Demo & Discussion 00:23:18 ⚖️ Play.ht Terms & Conditions: IP Ownership 00:25:16 🗣️ Comparing Play.ht and NotebookLM Output 00:27:09 💰 Play.ht Pricing & Use Cases 00:28:00 🎙️ NotebookLM Podcast Demo & Fluidity 00:29:15 🗣️ Voice Diversity & Representation 00:31:05 🌎 Language Support & Experimentation 00:32:57 🗣️ Language Preservation & Dubbing 00:33:32 🇮🇳 Hindi Hockey Conversation Experiment 00:36:00 ❓ Hindi Pronunciation Discussion 00:37:48 ⚠️ Trust but Verify: Translation Accuracy 00:39:04 🇮🇹 Italian Conversation Demo 00:40:14 ❓ Multilingual Capabilities & Future 00:41:17 🧠 Multimodal Models & Real-Time Processing 00:42:44 🚘 Interactive Podcasts in Cars 00:44:59 📱 Siri & Podcast Interaction 00:46:00 🤔 Interactive Podcast Ideas 00:47:41 🚶 Choose Your Own Adventure Podcasts 00:48:11 🚨 Breaking News: NotebookLM New Feature 00:49:29 💰 Monetization & Patreon (Joke) 00:50:08 🙏 Gratitude for Community & Comments 00:51:19 🗓️ Upcoming Shows & Newsletter Reminder 00:51:54 👋 Outro & Weekend Wishes

https://www.thedailyaishow.com In today's episode, The Daily AI Show crew, including Beth, Jyunmi, Brian, and later joined by Karl, explored the practical implementations of the newly released OpenAI Canvas features within custom GPT. Known as the "12 days of OpenAI," today's edition focused on showcasing how these tools can be utilized effectively for business professionals, especially in email drafting, task management, and Python programming. Key Points Discussed: Integration of Canvas with Custom GPT: The episode emphasized the seamless integration of Canvas, which allows for an interactive editing experience. This new feature offers a Google Doc-like interface for making live edits, enhancing the user experience. Use Cases Demonstrated: Brian demonstrated how Canvas can assist in drafting and editing emails, creating a dynamic environment for refining communication strategies with prospects. A smart to-do list example was shown, illustrating how this tool can manage and prioritize tasks, utilizing voice mode for easy input and updating points for task completion. A Python newbie feature was demonstrated, showing how new programmers can generate and run sample code directly in the Canvas for educational purposes. Overcoming AI System Limitations: The hosts discussed how different AI systems handle heavy loads and how users can troubleshoot or switch tools when systems like ChatGPT experience outages. Custom GPT Creation: Tips and insights were shared on creating custom GPTs, focusing on integrating new Canvas capabilities and delineating distinct user tasks to enhance utility. Challenges and Future Outlook: The conversation recognized the challenges faced during live demos and anticipated future developments from OpenAI's ongoing updates, speculating on the potential of GPT-5 or further enhancements to DALL-E. Episode Timeline 00:00:00 🎬 Intro & Context 00:00:25 👋 Welcome & Updates 00:01:49 🗓️ 12 Days of OpenAI 00:03:01 🚦 OpenAI Downtime & Adoption 00:04:22 🤔 Thoughts on Canvas 00:05:54 🧩 Integration Strategy 00:07:23 ✨ Prompt Engineering & Custom GPTs 00:09:30 👕 Custom GPTs as Tools 00:10:23 💡 Demo Introduction 00:12:36 📧 Email Writer Demo 00:18:50 ✅ To-Do List Demo 00:23:47 🐍 Python Newbie Demo 00:26:39 ✨ Canvas Integration Discussion 00:29:27 ⏱️ Custom GPT Creation Time 00:32:25 ✍️ Prompting Styles & Evolution 00:33:39 💻 Backend Deep Dive: Email Writer 00:38:17 📝 Backend: To-Do List & Instructions 00:42:25 🗣️ Recency Bias & Instructions 00:45:04 🔗 Multiple Custom GPTs in Canvas? 00:50:22 💪 Canvas Editing Features & Wrap-up 00:51:47 👋 Outro & OpenAI Day 6

https://www.thedailyaishow.com In today's episode of the Daily AI Show, Brian, Beth, Karl, and Jyunmi gathered to discuss the latest developments in the world of AI, focusing on OpenAI's recent announcements as part of their twelve days of updates, innovations in AI-driven healthcare, and the Canadian government's substantial investment in AI data centers. They also touched upon the evolution of YouTube's auto-dubbing feature and breakthroughs in quantum computing by Google. Key Points Discussed: OpenAI Announcements: The team recapped the first four days of OpenAI's announcement spree, highlighting the debut of ChatGPT Pro, Sora, and updates to the Canvas tool. They discussed the benefits of these updates for developers and users and speculated on what the remaining announcements might hold. AI in Healthcare: The discussion included a significant study by Deep Health and RadNet, which demonstrated a 21% improvement in breast cancer detection using AI technology in mammogram screenings, showcasing the potential of AI in improving healthcare outcomes. Quantum Computing: Google's new quantum chip, Willow, was spotlighted for its potential to revolutionize computing by significantly reducing errors and performing calculations at a speed unattainable by today's supercomputers, hinting at new realms of possibility in computational science. Canadian AI Initiatives: Karl shared insights into Canada's national efforts in advancing AI infrastructure, particularly the government's investment in Coheres' ambitious AI data center project, underlining the strategic role of AI in national economic and technological development. YouTube's Auto-Dubbing: The crew explored YouTube's rollout of an auto-dubbing feature focused on knowledge-centric content, discussing its implications for increasing content accessibility across different languages and the potential benefits for AI-focused shows like theirs. #AInews #OpenAI #HealthcareAI #QuantumComputing #YouTubeUpdates Episode Timeline: 00:00:00 🔬 AI Mammogram Detection 00:00:28 👋 Introductions and OpenAI Days Recap 00:01:47 🤔 Pressing News Topics 00:02:11 💻 OpenAI's 12 Days: First Four Announcements 00:06:14 🎨 Canvas in Custom GPTs 00:07:26 ✨ Excitement for OpenAI's Remaining Days 00:07:53 🏥 AI-Boosted Mammogram Study 00:10:09 🇨🇦 Canadian AI Data Center Investment 00:14:32 🏞️ Data Centers and Nature 00:17:04 🤔 Data Center Location and Infrastructure 00:17:41 🌐 YouTube Auto-Dubbing Feature 00:20:09 🗣️ Auto-Dubbing Demonstration 00:22:55 🌍 Language Barriers and Global Content 00:24:24 🧠 Evolved Universal Transformer Memory 00:28:44 🤖 Implications of NAMs for Robotics 00:30:14 🏠 Home Care Robots for Older Adults 00:31:49 💻 Google's Quantum Chip Willow 00:34:11 🤔 Quantum Computing and the Multiverse 00:37:14 ✨ Google's Gemini AI Agents 00:42:04 🤖 Real-World Gemini Applications 00:44:23 🖱️ Gemini's Multimodal Capabilities 00:46:01 ⚙️ Stainless SDKs for AI Platforms 00:49:35 💻 Automatic Acquires WP AI, Humane's Cosmos OS 00:54:01 👋 Conclusion and Newsletter Sign-Up