Episode #500. How AI Has Changed Us

Want to keep the conversation going?Join our Slack community at thedailyaishowcommunity.comIn this July 29th episode of The Daily AI Show, the panel takes on AI-powered dynamic pricing—how fixed prices are being replaced by fluid, algorithm-driven price tags. The crew looks at Delta’s AI pricing experiments and then digs into the social, economic, and ethical stakes as this trend spreads from airlines to retail, fast food, and beyond.Key Points Discussed• AI-powered dynamic pricing is moving from broad market signals to deeply personal “surveillance pricing,” raising questions about fairness, transparency, and data rights.• The team outlines three stages of dynamic pricing: traditional market-based changes, AI-powered real-time adjustments, and the controversial frontier of individualized pricing.• Real-world examples include Delta Airlines using AI to test new price models and the backlash when Wendy’s floated surge pricing for burgers.• The conversation covers potential upsides, like more equitable pricing in some sectors, but also the risks of discrimination and hidden costs for certain consumers.• There’s debate over whether competition and AI-powered agents will level the playing field or make it even harder for regular buyers to get a fair deal.• Data rights and consent are front and center, with calls for consumers to own and bargain with their own data, especially as “opt-in for lower prices” models expand.• The panel closes with a set of tough questions for the future: Is loyalty now a financial liability? Will trust in markets erode as pricing becomes a black box? How quickly will these changes become the new normal?Timestamps & Topics00:00:00 🏷️ Intro and overview: The end of fixed prices00:01:08 💸 Dynamic pricing basics and the move toward personalization00:03:25 🔄 Traditional vs. AI-powered vs. personalized pricing00:04:15 🌧️ Disney World, Delta, and real-life pricing stories00:05:33 🤖 AI-driven price changes at scale: Amazon, Delta, and more00:06:30 👤 Surveillance pricing and consumer pushback00:07:22 🤔 Panel reactions: Fairness, equity, and the upside/downside00:10:19 🚦 Airline loyalty programs, game-playing, and consumer strategies00:13:22 🎲 Overcomplication and the “arms race” between companies and buyers00:16:05 🧑‍🤝‍ Collective bargaining and potential AI-powered co-ops00:17:53 💰 Is personalized pricing just another tax—or a way to subsidize others?00:20:11 🏆 Who really wins: companies, rich buyers, or everyone?00:22:44 ⚖️ Black box algorithms and the fading art of “getting a deal”00:23:40 🥤 Personalized deals, loyalty apps, and opt-in data tradeoffs00:26:31 🔄 Messy realities: Short-term wins, long-term risks00:31:00 🪪 Who owns your data? Denmark’s approach and the future of rights00:34:04 📜 Contracts, terms of service, and the growing complexity of being a buyer00:36:00 🧑‍💻 Agents vs. companies: who will protect the consumer?00:41:06 🚗 When customer service and value trump low prices00:44:50 🕹️ The future of agent-driven buying and why “the house always wins”00:46:29 ❓ Tough questions for the next wave of AI pricing00:48:47 🏁 Wrap up and what’s next on The Daily AI ShowHashtags#DynamicPricing #AIandRetail #AlgorithmicPricing #DataRights #SurveillanceEconomy #ConsumerTech #AIFuture #PersonalizedPricing #DailyAIShow #AIEthicsThe Daily AI Show Co-Hosts:Andy Halliday, Beth Lyons, Brian Maucere, Eran Malloch, Jyunmi Hatcher, and Karl YehGuest Co-host: Anne Murphy

Want to keep the conversation going?Join our Slack community at thedailyaishowcommunity.comIntroIn this July 28th episode of The Daily AI Show, the team takes a “satellite view” of the entire AI landscape. Andy shares an agent-built taxonomy that organizes AI into five clusters and 15 domains, breaking down everything from core models and chips to applications and the social impact of AI. The conversation highlights how this structure can guide both newcomers and experts, and sets up future use cases for learning, consulting, and more.Key Points Discussed• AI is best understood as an ecosystem of five interconnected clusters, with 15 core domains ranging from technical foundations to societal impact.• The group explores how relative importance and relationships between domains shape where innovation and investment go in the field.• Practical tools like the Gen Spark taxonomy and Sensei are making it easier to turn AI’s complexity into structured, personalized learning.• The show debates the power of these maps to spark empathy and understanding across different roles, industries, and everyday life.• Interdisciplinary AI—such as intersections with biology, arts, and quantum computing—emerges as a key area of surprise and future growth.• The taxonomy is not static. It should update as the field evolves, with the goal of building dynamic, personalized education and consulting resources.• The coming week’s shows will tackle dynamic pricing, the broken AI hiring process, and best real-world use cases for AI agents.Timestamps & Topics00:00:00 🛰️ Framing the episode: AI as an ecosystem of models, chips, and applications00:02:07 🧭 Building a taxonomy: Five clusters and 15 knowledge domains in AI00:04:36 🔵 Core technical foundations and why they matter00:06:33 🤖 Key domains: ML, NLP, computer vision, robotics, and more00:08:20 🟢 Implementation and applications: Industry, consumer, and infrastructure00:12:10 🏥 AI by sector: Healthcare, finance, supply chain, retail, and more00:13:22 🟡 Chips, infrastructure, and energy/resource questions00:15:09 🌐 Relative importance and network relationships between AI domains00:17:29 🏛️ Markets, future trends, and the academic cluster00:19:00 📚 The role of history and innovation in shaping the landscape00:21:17 💡 Visualizing connections and what matters most (size, weights, links)00:22:23 🧑‍🎓 Personalizing the map for different careers and learning paths00:26:33 🗺️ Taxonomy as a foundation for Sensei and guided AI learning00:31:00 🌱 Interdisciplinary AI: Where cognitive science, biology, and physics meet00:35:15 🧠 The value of cognitive maps for recall, empathy, and consulting00:39:00 🚰 Empathy and understanding AI’s impact in everyday life00:46:56 🎒 How this approach will change personalized education00:50:29 ⚡ Top takeaways: Societal impact, knowledge work disruption, and the economics of superintelligence00:54:10 🗓️ What’s coming this week: dynamic pricing, AI in hiring, and practical agent use cases00:56:43 🌺 Outro and signoffHashtags#AITaxonomy #AIEducation #AgentMode #GenSpark #Sensei #AIConsulting #PersonalizedLearning #DailyAIShow #AIClusters #Empathy #AIImpact #FutureOfAIThe Daily AI Show Co-Hosts:Andy Halliday, Beth Lyons, Brian Maucere, Eran Malloch, Jyunmi Hatcher, and Karl Yeh

Taste feels like freedom. People try things, love some, reject others, and over time believe they know themselves a little better. This process shapes identity. You choose the music that calms you, the books that challenge you, the foods that feel like home. But today, AI systems predict your preferences before you do. From playlists to shopping to what recipes show up in your feed, models analyze your mood, your schedule, your past choices, and even your tone of voice to suggest what fits “you.”At first, this feels like relief. No more standing in the cereal aisle unsure what to buy. But over time, choosing from a list of what feels “just right” may not feel like choosing at all. You still click, swipe, and approve—but the system shaped the options. If your favorites keep arriving effortlessly, are you expressing yourself, or accepting a version of yourself that was quietly built for you?Some will argue this saves people from decision fatigue and lets them focus on what matters. Others will wonder if taste itself, once a sign of personality, becomes a polished reflection of the system’s design.The conundrumIf AI shapes your choices until everything feels right, are you discovering your true self—or slowly trading free will for comfort that feels like freedom?

Want to keep the conversation going?Join our Slack community at thedailyaishowcommunity.comIntroIn this July 25th episode of The Daily AI Show, the team holds their Friday “Recaps and Rabbit Holes” show. With no set topic, the crew lets the conversation flow, covering everything from the future of Dungeons & Dragons with AI to hands-on impressions of new tools like Perplexity’s Comet and ChatGPT’s Agent Mode. The episode blends personal tech routines, business realities, and predictions for where these tools might fit in both work and play.Key Points Discussed• Dungeons & Dragons fans are split on AI’s role—should a model ever replace the Dungeon Master, or just help behind the scenes?• The Comet browser from Perplexity offers integrated search and an AI assistant, but the team is still testing how much real productivity it delivers compared to Chrome.• ChatGPT’s Agent Mode has rolled out to more users, and the team explores its strengths and early limitations in real sales and research workflows.• Current AI agent tools are promising, but true automation and reliability for complex tasks like lead generation still have a long way to go.• Conversation covers deep research features in Gemini, ChatGPT, and Perplexity—what works, what doesn’t, and why layering tools matters for power users.• The pace of AI adoption has surged in just the last two months, with consulting work and client demand suddenly spiking.• The group reflects on the “future shock” of working with these tools every day and how most people still don’t realize how much is already possible.• The conversation wraps up by previewing next week’s shows, including hiring challenges in the age of AI and the future of dynamic pricing for everyday products.Timestamps & Topics00:00:00 🎙️ Show intro, “Recaps and Rabbit Holes” explained00:01:07 👋 Co-host hellos, time zones, and audience shoutouts00:02:12 🐉 Dungeons & Dragons, AI Dungeon Masters, and player pushback00:05:07 🧑‍💻 Can AI help or ruin the D&D experience?00:08:00 🎲 The value of analog, pen-and-paper play00:10:07 🌍 Technology at the D&D table and remote play tools00:13:17 🖥️ First impressions of Perplexity’s Comet browser and integrated assistant00:16:23 🦾 Agent Mode in ChatGPT: availability, team tests, and first use cases00:18:07 🏆 Agent Mode for sales and complex lead generation workflows00:22:05 🤔 Automation vs true AI agents—what’s actually different?00:24:39 🔒 Security and permissions concerns in multi-agent environments00:26:00 📈 AI for lead gen, real-world client needs, and consulting pain points00:29:21 🤳 Social media hype vs. real agent workflows00:30:37 🌐 AI browser control and the future of web automation00:32:00 🛡️ Risks of Agent Mode in team environments00:34:16 💬 Nicole Leffler’s LinkedIn post and best practices for teams00:35:06 📚 Gemini’s deep research powers: playbooks, personas, and marketing projects00:37:08 ✈️ Using Gemini for military aviation content and topic generation00:39:16 🤝 Deep research: conversational vs. “set it and forget it” styles00:40:10 🗂️ Using multiple AI tools to prep for meetings and content00:43:13 ⏳ Real-time reflection on how fast AI habits change00:44:39 🔥 Surging demand for AI consulting and client work at Skaled00:46:32 🚀 Scaling internal processes and challenges for AI consultants00:48:26 💼 Impact of AI on marketing jobs and client relationships00:49:49 📅 Preview of next week’s episodes: AI and hiring, dynamic pricing, and more00:53:39 💌 Newsletter plug and how to join the Slack community00:54:30 🎲 Teaser for tomorrow’s “Conundrum” episode00:55:01 🌺 Outro and signoffHashtags#AIProductivity #AgentMode #AIBrowsers #DungeonsAndDragons #PerplexityComet #GeminiAI #DeepResearch #DynamicPricing #AIJobs #DailyAIShow #AIConsulting #AIFutureThe Daily AI Show Co-Hosts:Andy Halliday, Beth Lyons, Brian Maucere, Eran Malloch, Jyunmi Hatcher, and Karl Yeh

Want to keep the conversation going?Join our Slack community at thedailyaishowcommunity.comIntroIn this July 24th episode of The Daily AI Show, the team tackles China’s accelerating dominance in AI and electric vehicles. Kicking off with Ford CEO Jim Farley’s reaction to visiting China’s EV industry, the crew discusses how Chinese automakers like BYD are outpacing legacy brands and how AI is becoming visibly embedded in Chinese cities—from humanoid robots to smart suspensions. They explore what’s driving this speed and why the West might already be falling behind.Key Points Discussed• Ford CEO Jim Farley calls China’s EV industry “the most humbling thing” he’s ever seen after multiple visits.• Chinese automaker BYD leads the global EV market with cheaper, smarter cars powered by AI-enhanced design.• Humanoid robots are already appearing on public streets in China, showing a cultural normalization of advanced AI.• China's government made early strategic bets in AI and EV infrastructure dating back to 2007–2008.• American and European automakers are slowed by politics, regulations, and lingering fossil fuel incentives.• Cars like the BYD YangWang U7 feature AI-powered suspension systems that scan the road 1,000 times per second.• The U7 can jump over obstacles, drive on three wheels, and adjust in real time to harsh terrain.• The team questions if the US is focused too much on model development and not enough on real-world AI deployment.• There’s a growing gap between what Western companies are building and how fast Chinese firms are putting it to use.#ChinaAI #BYD #YangWangU7 #AIEVs #Ford #JimFarley #AIInfrastructure #DailyAIShow #HumanoidRobots #EVInnovation #FutureOfTransportation #AgenticAIThe Daily AI Show Co-Hosts:Andy Halliday, Beth Lyons, Brian Maucere, Eran Malloch, Jyunmi Hatcher, and Karl Yeh

The team explores the week’s most compelling AI news. With a Dungeons & Dragons twist, the crew journeys through stories about open-source AI from Alibaba, seismic sensing via AI in Yellowstone, Furiosa’s mysterious tech alliance, and more. It’s an entertaining but grounded look at where AI is pushing boundaries and rewriting rules.Key Points Discussed• Alibaba releases powerful open-source AI models, potentially reshaping global access to cutting-edge capabilities.• Yellowstone’s AI-driven quake sensing reveals 86,000 previously undetected tremors, raising new questions about data interpretation and natural disaster risk.• “Furiosa” (a stand-in for Stability AI’s Emad Mostaque) reportedly partners with an unnamed financial backer, signaling new moves post-departure from Stability.• The AI community wrestles with trust and transparency—how do we vet information in a world of automated content and hallucinated facts?• Microsoft’s Copilot+ Recall feature, which records everything on your screen, stirs up major privacy concerns.• Meta pushes forward with AI-generated ads but continues to dodge deeper transparency and ethical debates.• The rise of AI-powered NPCs in gaming (like Darth Vader in Fortnite) brings delight—and disaster—as players manipulate them in unintended ways.• Agentic systems like Runner H and GenSpark show how fast automation is growing, but also how fragile these systems still are.• New research on the “Darwin Gödel Machine” shows self-evolving agents are now a real pursuit, not just a theory.• Hollywood’s obsession with AI continues, including a biopic in the works about Sam Altman and the OpenAI boardroom drama.Timestamps & Topics00:00:00 🏰 Fantasy-style intro kicks off the AI news adventure00:01:34 🧙 Alibaba drops open-source AI magic00:04:20 🌋 Yellowstone's 86,000 hidden earthquakes uncovered by AI00:07:52 🧩 Furiosa forms a mysterious new alliance00:11:16 🧠 Trust in AI, truth, and hallucinated content00:14:00 👀 Microsoft Recall and screen-recording AI agents00:16:42 💸 Meta’s AI ads raise new ethical flags00:18:10 🎮 AI NPCs go rogue in Fortnite00:22:03 ⚙️ GenSpark and Runner H demo agentic automation00:26:31 🧬 Darwin Gödel Machine introduces self-evolving agents00:30:15 🎥 OpenAI biopic planned, adds drama to the AI narrative00:33:20 🧑‍⚖️ Surveillance risks, bias, and political misuse of AIHashtags#AIWeeklyNews #OpenSourceAI #DarwinGodelMachine #MicrosoftRecall #AlibabaAI #AICompanions #AgenticAI #DailyAIShow #OpenAI #AITrust #AIinGaming #AIPrivacyThe Daily AI Show Co-Hosts:Andy Halliday, Beth Lyons, Brian Maucere, Eran Malloch, Jyunmi Hatcher, and Karl Yeh

Want to keep the conversation going?Join our Slack community at thedailyaishowcommunity.comFrom visual effects to script rewrites, hosts explore how AI is reshaping filmmaking after the 2023 double strike. They discuss ethical risks, creative opportunities, and how much AI-generated content audiences are already consuming without realizing.Key Points DiscussedThe 2023 WGA and SAG-AFTRA strikes secured rules requiring explicit consent for actor likeness and voice replication.Writers Guild agreements clarify AI can’t replace human writers but can be used as a tool under human oversight.Studios like Netflix are now aggressively using AI for VFX, set design, previsualization, script polishing, and scheduling.AI-trained models from companies like Runway, OpenAI, and Sora are now integrated into production pipelines.AI’s capacity to rapidly generate or edit backgrounds, lighting, and assets accelerates timelines and cuts costs.“AI slop” fears are valid—audiences may consume AI-enhanced content unknowingly as studios don’t label AI contributions.Debate over where human creativity ends and AI assistance begins in collaborative filmmaking.AI enables visual effects for mid-budget productions that previously couldn’t afford complex post-production.Concerns persist about overuse of AI for lead roles, dialogue generation, and automated camera movement decisions.AI video models struggle with consistency and continuity, requiring human supervision to avoid visual artifacts.The team noted that regulatory protections may fail to keep pace with rapid AI adoption in global film markets.Generative tools like Sora could turn small production companies into VFX-heavy content creators.Ethical and aesthetic questions remain about de-aging, posthumous performances, and synthetic actors.Long-term, studios may prioritize AI-enhanced production pipelines to maintain competitiveness, regardless of audience transparency.Timestamps & Topics00:00:00 🎬 AI in Hollywood - does Netflix have any chill?00:01:36 ⚖️ 2023 strikes and consent rules00:04:50 🎥 AI now shaping VFX, backgrounds, and scripts00:08:19 🛠️ Runway, Sora, and OpenAI models in production00:10:47 📉 Cost savings and timeline reductions00:13:06 🎭 AI slop vs. invisible enhancements00:16:50 🧠 Collaboration or replacement of human creativity?00:20:25 💸 Mid-budget films now get blockbuster-level VFX00:25:04 ⚠️ Risks: lead roles, dialogue, automated scenes00:30:17 📊 Why AI content lacks continuity without human review00:35:32 🌍 Regulatory lag outside U.S. film industry00:40:00 🖥️ Sora democratizing video generation00:44:25 🚧 De-aging, synthetic actors, and ethics00:49:51 🎬 Netflix and studios chasing competitive AI pipelines00:55:13 📅 Wrap-up and upcoming shows#AIinHollywood #NetflixAI #AIVideo #AIContent #SoraAI #GenerativeVideo #AIEthics #RunwayML #SyntheticActors #FilmmakingAI #DailyAIShowThe Daily AI Show Co-Hosts:Andy Halliday, Beth Lyons, Jyunmi Hatcher

Want to keep the conversation going?Join our Slack community at thedailyaishowcommunity.comIntroIn this July 21st episode of The Daily AI Show, the team explores the question of whether we can trust AI models at all. Prompted by a paper signed by over 50 researchers from OpenAI, Google DeepMind, Anthropic, Meta, and the UK’s AI Security Institute, the conversation focuses on the role of transparency, chain-of-thought auditing, and psychoanalyzing models to detect misalignment. Hosts debate whether current models are “fake empathizers,” hidden manipulators, or just tools waiting for proper oversight.Key Points DiscussedOver 50 researchers from major AI labs called for persistent analysis of models to detect hidden risks and early signs of misalignment.Chain-of-thought prompting is discussed as both a performance tool and a transparency tool, allowing models to “think out loud” for human oversight.Andy raised concerns that chain-of-thought logs might simply output what the model expects humans want to see, rather than genuine reasoning.The conversation explored whether chain-of-thought is cognitive transparency or just another interface layer masking true model processes.Comparison to human sociopaths—models can simulate empathy, display charm, but act with hidden motivations beneath the surface.Brian noted most people mistake AI output for genuine reasoning because it’s presented in human-readable, narrative forms.Discussion questioned whether models are optimizing for truth, coherence, or manipulation when crafting outputs.Andy referenced the Blackstone principle, suggesting oversight must avoid punishing harmless models out of fear while catching real risks early.The team explored whether chain-of-thought audits could detect unsafe models or if internal “silent reasoning” will always remain hidden.The debate framed trust as a systemic design issue, not a user-level decision—humans don’t “trust” AI like a person, they trust processes, audits, and safeguards.They concluded that transparency, consistent oversight, and active human evaluation are necessary if AI is to be safely integrated into critical systems.Timestamps & Topics00:00:00 🚨 AI trustworthiness: oversight or fantasy?00:00:18 🧪 Researchers call for persistent model audits00:01:27 🔍 Chain-of-thought prompting as a transparency tool00:03:14 🤔 Does chain-of-thought expose real reasoning?00:06:05 🛡️ Sociopath analogy: fake empathy in AI outputs00:09:15 🧠 Cognitive transparency vs human-readable lies00:12:41 📊 Models optimizing for manipulation vs accuracy00:15:29 ⚖️ Blackstone principle applied to AI risk00:18:14 🔎 Chain-of-thought audits as partial oversight00:22:25 🤖 Trusting systems, not synthetic personalities00:26:00 🚨 Safety: detecting risks before deployment00:29:41 🎭 Storytelling vs. computational honesty00:33:45 📅 Closing reflections on trust and AI safetyHashtags#AITrust #AIOversight #ChainOfThought #AIMisalignment #AISafety #LLMTransparency #ModelAuditing #BlackstonePrinciple #DailyAIShow #AIphilosophy #AIethicsThe Daily AI Show Co-Hosts:Andy Halliday, Brian Maucere

People have long accepted mass-produced connection. A birthday card signed by a celebrity, a form letter from a company CEO, or a Christmas message from a president—these still carry meaning, even though everyone knows thousands received the same words. The message mattered because it felt chosen, even if not personal.Now, AI makes personalized mass connection possible. Companies and individuals can send unique, “handwritten” messages in your tone, remembering details only a model can track. To the receiver, it may feel like a thoughtful, one-of-a-kind note. But at scale, sincerity itself starts to blur. Did the words come from the sender’s heart—or from their software?The conundrumIf AI lets us send thousands of unique, heartfelt messages that feel personal, does that deepen connection—or hollow it out? Is sincerity about the words received, or the presence of the human who chose to send them?This podcast is created by AI. We used ChatGPT, Perplexity and Google NotebookLM's audio overview to create the conversation you are hearing. We do not make any claims to the validity of the information provided and see this as an experiment around deep discussions fully generated by AI.

Want to keep the conversation going?Join our Slack community at thedailyaishowcommunity.comIntroIn this July 18th episode of The Daily AI Show, the team showcases real-world AI use cases in what they call their “Be About It” show. Hosts demonstrate live projects and workflows using tools like GenSpark, Perplexity Spaces, ChatGPT Projects, MidJourney, and OpenAI’s Sora, focusing on actual tasks they’ve automated or solved using AI. This episode emphasizes practical wins—how AI is saving them hours on complex work, from document audits to image generation and business operations.Key Points DiscussedAndy demoed a 50-lesson course built using Lovable, ChatGPT Projects, and infographics generated through iterative feedback inside ChatGPT 4.GenSpark agents were used to analyze complex tax payments and vehicle purchase discrepancies, leading to actionable insights and letters for the DMV.Beth showcased image generation pipelines using Sora, ChatGPT image generation, and MidJourney’s editing tools to produce YouTube thumbnails and animated video intros.Brian demonstrated using Perplexity Spaces to generate dynamic travel planning prompts, showing how to create reusable agentic workflows inside Spaces without heavy prompting skills.Karl walked through OpenAI’s Agent Mode analyzing folder-based invoice matching against Google Sheets, automating tasks that typically take hours for finance teams.The group criticized OpenAI’s consumer-focused demos (like shoe shopping), urging labs to highlight complex business use cases that show real time savings.Agent Mode’s strength lies in handling document-heavy, tedious tasks where traditional no-code platforms falter.MidJourney’s seamless image background expansion and animation were highlighted as powerful tools for visual content creators.Perplexity Spaces can act like lightweight document research agents when properly configured, making knowledge extraction easier for non-coders.Real-world stories included AI helping with dermatology guidance, audio hardware troubleshooting, and reducing content production bottlenecks with Opus Clip’s multi-speaker cropping tool.The show concluded with reflections on the importance of UI and workflow design in AI tool adoption—features alone aren’t enough without good user experience.Timestamps & Topics00:00:00 🎬 Show kickoff and intro to “Be About It”00:01:37 📚 Andy’s 50-lesson AI prompting course build00:06:14 📊 Infographic generation via ChatGPT projects00:13:30 🎨 Beth’s YouTube thumbnail image pipeline00:20:45 🐃 MidJourney image extension and animation demo00:27:23 ⚙️ GenSpark for complex tax error investigation00:31:45 ✉️ GenSpark drafts demand letters for refunds00:32:05 🛫 Brian builds a travel assistant in Perplexity Spaces00:40:49 🛠️ Agent Mode vs. Perplexity for structured forms00:43:52 📂 Karl’s invoice matching with Agent Mode and Google Drive00:51:08 ⚒️ Agent Mode better for complex, document-heavy work00:56:26 🎙️ Beth uses AI to fix audio gear and routing01:01:19 🩺 ChatGPT solves Brian’s daughter’s skincare routine01:02:32 🎥 Brian demos Opus Clip’s multi-speaker video cropping01:07:09 🖥️ Why UI beats small feature wins01:10:55 🐘 Beth’s animated elephant video thumbnails01:12:08 🎥 Animated thumbnails as future YouTube preview01:13:44 📅 Show wrap-up and sci-fi show previewHashtags#AIUseCases #AgentMode #GenSpark #Perplexity #ChatGPTProjects #MidJourney #SoraAI #Automation #AIAgents #ImageGeneration #WorkflowAutomation #DailyAIShowThe Daily AI Show Co-Hosts:Andy Halliday, Beth Lyons, Brian Maucere, Karl Yeh