The Daily AI Show

The Daily AI Show Crew - Brian, Beth, Jyunmi, Andy, Karl, and Eran

The Daily AI Show is a panel discussion hosted LIVE each weekday at 10am Eastern. We cover all the AI topics and use cases that are important to today's busy professional. No fluff. Just 45+ minutes to cover the AI news, stories, and knowledge you need to know as a business professional. About the crew: We are a group of professionals who work in various industries and have either deployed AI in our own environments or are actively coaching, consulting, and teaching AI best practices. Your hosts are: Brian Maucere Beth Lyons Andy Halliday Eran Malloch Jyunmi Hatcher Karl Yeh

  1. -2 J

    Is Sora 2 Just AI Slop? and Other AI Stories

    Intro The October 3rd episode of The Daily AI Show was a Friday roundup where the hosts shared favorite stories and ongoing themes from the week. The discussion ranged from OpenAI pulling back Sora invite codes to the risks of deepfakes, the opportunities in Lovable’s build challenge, and Anthropic’s new system card for Claude 4.5. Key Points Discussed OpenAI quietly removed Sora invite codes after people began selling them on eBay for up to $175. Some vetted users still have access, but most invite codes disappeared. Hosts debated OpenAI’s strategy of making Sora a free, social-style app to drive adoption, contrasting it with GPT-5 Pro locked behind a $200 monthly subscription. Concerns were raised about Sora accelerating deepfake culture, from trivial memes to dangerous misuse in politics and religion. An example surfaced of a church broadcasting a fake sermon in Charlie Kirk’s voice “from heaven.” The group discussed generational differences in media trust, noting younger people already assume digital content can be fake, while older generations are more vulnerable. The team highlighted Lovable Cloud’s build week, sponsored by Google, which makes it easier to integrate Nano Banana, Stripe payments, and Supabase databases. They emphasized the shrinking “first mover” window to build and deploy successful AI apps. Support experiences with Lovable and other AI platforms were compared, with praise for effective AI-first support that escalates to humans when necessary. Google’s Jules tool was introduced as a fire-and-forget coding agent that can work asynchronously on large codebases and issue pull requests. This contrasts with Claude Code and Cursor, which require closer human interaction. Anthropic’s system card for Claude 4.5 revealed the model can sometimes detect when it’s being tested and adjust its behavior, raising concerns about “scheming” or reasoned deception. While improved, this remains a research challenge. The show closed with encouragement to join Lovable’s seven-day challenge, with themes ranging from productivity to games and self-improvement tools, and a reminder about Brian’s AI Conundrum episode on consent. Timestamps & Topics 00:00:00 💡 Friday roundup intro and host banter 00:05:06 🔑 OpenAI removes Sora invite codes after resale abuse 00:08:29 🎨 Sora’s social app framing vs GPT-5 Pro paywall 00:11:28 ⚠️ Deepfakes, trust erosion, and fake sermons example 00:15:50 🧠 Generational divides in recognizing AI fakes 00:22:31 📱 Kids’ digital-first upbringing vs older expectations 00:24:30 ☁️ Lovable Cloud’s build week and Google sponsorship 00:27:18 ⏳ First-mover advantage and the “closing window” 00:34:07 🛠️ Lessons from early Lovable users and support experiences 00:40:17 📩 AI-first support escalation and effectiveness 00:41:28 💻 Google Jules as asynchronous coding agent 00:43:43 ✅ Fire-and-forget workflows vs Claude Code’s assisted style 00:46:42 📑 Claude 4.5 system card and AI scheming concerns 00:51:23 🎲 Diplomacy game deception tests and model behavior 00:54:12 🕹️ Lovable’s seven-day challenge themes and community events 00:57:08 📅 Wrap up, weekend projects, and AI Conundrum promo The Daily AI Show Co-Hosts: Andy Halliday, Beth Lyons, Brian Maucere, Eran Malloch, Jyunmi Hatcher, and Karl Yeh

    58 min
  2. -3 J

    Building With Claude Code

    On October 2, The Daily AI Show focused on Claude Code and how it can be used for business productivity—not just coding. Karl walked through installing Claude Code in Cursor or VSCode, showed how to connect it to tools like Zapier, and demonstrated how to build custom agents for everyday workflows such as reporting, email, and invoice consolidation. Key Points Discussed • Claude Code is not just for developers—it can function as a new operating system for business tasks when set up inside Cursor or VSCode. • Installing Claude Code in a controlled test folder is recommended, since it gives the agent access to all subfolders. • Users can extend Claude Code with MCP servers, either through Zapier (broad access to 3,000+ apps) or third-party servers on GitHub. • Zapier MCPs are convenient but limited by credits and cost, while third-party MCPs often offer richer functionality but carry security risks like prompt injection. • Enterprise-level MCP managers exist for safer oversight but cost thousands per month. • Claude Code can manipulate local files, move folders, compare PDFs and spreadsheets, and generate reports on command. • Whisper Flow integration allows voice-driven control, making it easy to speak tasks instead of typing. • Creating agents inside Claude Code is a breakthrough: users can build dedicated assistants (e.g., email agent, payroll agent, invoice agent) and call them with slash commands. • Combining agents with MCPs enables multi-step automation, such as generating a report, emailing results, and logging data into external systems. • Security and IT concerns remain—Claude Code’s deep access to local environments may alarm administrators, but the productivity unlock is significant. Timestamps & Topics 00:00:00 🎙️ Intro: Claude Code beyond coding 00:01:55 💻 Setting up in Cursor or VSCode 00:03:12 🔌 Installing Claude Code via extension or terminal 00:05:18 📂 Creating a test folder to control access 00:06:07 🖥️ Cursor vs. VSCode, terminal environments 00:08:52 ⚙️ Commands and model options (Sonnet 4.5, Opus) 00:10:16 🔗 Using MCPs via Zapier and third-party servers 00:12:29 📊 Zapier limits and costs after Sept 18 changes 00:15:23 🏢 SaaS integration challenges and authentication 00:19:34 📧 Drafting emails and sending Slack messages through Zapier MCP 00:22:12 🔍 Comparing native vs. third-party MCP tool calling 00:24:07 🛡️ Security risks of third-party MCPs and prompt injection 00:31:39 🔒 Enterprise-grade MCP manager for oversight 00:34:42 📑 Automating monthly reporting across tools 00:38:39 📂 File manipulation and invoice consolidation demo 00:42:17 🤖 Creating custom agents for repeat workflows 00:45:27 📦 Agents as mini-GPTs with tool access 00:47:49 🧑‍💼 Multi-agent orchestration: invoice + email + payroll 00:50:29 📋 Agents stored in project folder and reusable 00:52:46 📝 Claude.md file as global instruction set 00:56:42 🆚 Claude Code vs. Codex: strengths and tradeoffs 00:58:46 ⚠️ Security, IT reactions, and real-world risks 01:02:24 🚀 Unlocking productivity with agent armies 01:03:02 🌺 Wrap-up and Slack invite Hashtags #ClaudeCode #MCP #Zapier #Cursor #VSCode #AIagents #WorkflowAutomation #AITools #DailyAIShow The Daily AI Show Co-Hosts: Andy Halliday, Beth Lyons, Brian Maucere, Eran Malloch, Jyunmi Hatcher, and Karl Yeh

    1 h 4 min
  3. -4 J

    Sora 2, Alexa+, and all the latest AI News

    Want to keep the conversation going? Join our Slack community at thedailyaishowcommunity.com Intro On October 1, The Daily AI Show opened news day with a packed lineup. The team covered model releases, AI science breakthroughs, social apps, regulation, and the latest in quantum computing. Key Points Discussed • Anthropic releases Claude Sonnet 4.5, positioned as its most capable and aligned model to date, with strong coding and computer-use improvements. • OpenAI and DeepMind researchers launch Periodic Labs with $300M in backing from Bezos, Schmidt, Andreessen, and others, building “self-driving labs” to accelerate materials discovery like superconductors. • Los Alamos National Lab unveils Thor AI, a framework solving a 100-year-old physics modeling challenge, cutting supercomputer work from thousands of hours to seconds. • Amazon updates Alexa with “Alexa Plus” across new devices and expands AWS partnerships with sports leagues for AI-driven insights. • The Nothing Phone 3 debuts with on-device AI that lets users generate their own apps and widgets by prompt. • X.ai introduces “Grokpedia,” an AI-powered competitor to Wikipedia, raising concerns about accuracy and bias. • Corwin lands $14.2B in infrastructure deals with Meta and $6.5B with OpenAI, deepening ties to hyperscalers. • OpenAI rolls out Sora 2, with TikTok-style social app features and more physics-faithful video generation. Early impressions highlight improved realism but lingering flaws. • AI actress Tilly Norwood signs with an agency, sparking debate over synthetic influencers competing with human talent. • Quantum computing updates: University of South Wales hits a key error-correction benchmark using existing silicon fabs, while Caltech sets a record with 6,100 neutral atom qubits. • California passes SB 53, the first US frontier model transparency law, requiring big labs to disclose safety frameworks and report incidents. Timestamps & Topics 00:00:00 📰 News day kickoff and headlines 00:01:49 🤥 Deepfake scandals: Musk, Swift, Johansson, Schumer 00:03:40 📱 Nothing Phone 3 launches with on-device AI app generation 00:06:15 📚 X.ai announces Grokpedia as Wikipedia competitor 00:07:56 💰 Corwin lands $14.2B Meta deal and $6.5B with OpenAI 00:09:23 🗣️ Amazon unveils Alexa Plus, AWS partners with NBA 00:12:04 🔬 Periodic Labs launches with $300M to build AI scientists 00:14:17 ⚡ Los Alamos’ Thor AI solves configurational integrals in physics 00:17:34 🤖 Robots handling repetitive lab work in self-driving labs 00:18:59 🏠 Amazon demos edge AI on Ring devices for community use 00:23:43 🛠️ Lovable and Bolt updates streamline backend integration 00:29:47 🔑 Authentication, multi-user access, and Claude Sonnet 4.5 inside Lovable 00:33:26 🧑‍🔬 Quantum computing milestones: South Wales and Caltech 00:39:08 🎭 AI actress Tilly Norwood signs with agency 00:45:30 🎥 Sora 2 launches TikTok-style app with cameos 00:47:59 🏞️ Sora 2 physics fidelity and creative tests 00:57:22 💻 Web version and API for Sora teased 01:07:23 ⚖️ California passes SB 53, first frontier model transparency law 01:10:18 🌺 Wrap-up, Slack invite, and show previews Hashtags #AInews #ClaudeSonnet45 #Sora2 #PeriodicLabs #ThorAI #QuantumComputing #AlexaPlus #NothingPhone3 #Grokpedia #AIActress #SB53 #DailyAIShow The Daily AI Show Co-Hosts: Andy Halliday, Beth Lyons, Brian Maucere, Eran Malloch, Jyunmi Hatcher, and Karl Yeh

    1 h 10 min
  4. -5 J

    How to Fix AI's Major Traffic Jam

    Want to keep the conversation going? Join our Slack community at thedailyaishowcommunity.com Intro On September 30, The Daily AI Show tackles what the hosts call “the great AI traffic jam.” Despite more powerful GPUs and CPUs, the panel explains how outdated chip infrastructure, copper wiring, and heat dissipation limits are creating bottlenecks that could stall AI progress. Using a city analogy, they explore solutions like silicon photonics, co-packaged optics, and even photonic compute as the next frontier. Key Points Discussed • By 2030, global data centers could consume 945 terawatt hours—equal to the electricity use of Japan—raising urgent efficiency concerns. • 75% of energy in chips today is spent just moving data, not on computation. Copper wiring and electron transfer create heat, friction, and inefficiency. • Co-packaged optics brings optical engines directly onto the chip, shrinking data movement distances from inches to millimeters, cutting latency and power use. • The “holy grail” is photonic compute, where light performs the math itself, offering sub-nanosecond speeds and massive energy efficiency. • Companies like Nvidia, AMD, Intel, and startups such as Lightmatter are racing to own the next wave of optical interconnects. AMD is pursuing zeta-scale computing through acquisitions, while Intel already deploys silicon photonics transceivers in data centers. • Infrastructure challenges loom: data centers built today may require ripping out billions in hardware within a decade as photonic systems mature. • Economic and geopolitical stakes are high: control over supply chains (like lasers, packaging, and foundry capacity) will shape which nations lead. • Potential breakthroughs from these advances include digital twins of Earth for climate modeling, real-time medical diagnostics, and cures for diseases like cancer and Alzheimer’s. • Even without smarter AI models, simply making computation faster and more efficient could unlock the next wave of breakthroughs. Timestamps & Topics 00:00:00 ⚡ Framing the AI “traffic jam” and looming energy crisis 00:01:12 🔋 Data centers may use as much power as Japan by 2030 00:04:14 🏙️ City analogy: copper roads, electron cars, and inefficiency 00:06:13 💡 Co-packaged optics—moving optical engines onto the chip 00:07:43 🌈 Photonics for data transfer today, compute tomorrow 00:09:14 🌍 Why current infrastructure risks an AI “dark age” 00:12:28 🌊 Cooling, water usage, and sustainability concerns 00:14:07 🔧 Proof-of-concept to production expected in 2026 00:17:16 🌆 Stopgaps vs. full rebuilds, Venice analogy for temporary fixes 00:20:31 📊 Infographics from Google Deep Research: Copper City vs. Photon City 00:21:25 🔀 Pluggable optics today, co-packaged optics tomorrow, photonic compute future 00:23:55 🏢 AMD, Nvidia, Intel, TSMC strategies for optical interconnects 00:27:13 💡 Lightmatter and optical interposers—intermediate steps 00:29:53 🏎️ AMD’s zeta-scale engine and acquisition-driven approach 00:32:23 📈 Moore’s Law limits, Jevons paradox, and rising demand 00:34:15 🏗️ Building data centers for future retrofits 00:37:00 🔌 Intel’s silicon photonics transceivers already in play 00:39:43 🏰 Nvidia’s CUDA moat may shift to fabric architectures 00:41:08 🌐 Applications: digital biology, Earth twins, and real-time AI 00:43:24 🧠 Photonic neural networks and neuromorphic computing 00:46:09 🕰️ Ethan Mollick’s point: even today’s AI has untapped use cases 00:47:28 📅 Wrap-up: AI’s future depends on solving the traffic jam 00:49:31 📣 Community plug, upcoming shows (news, Claude Code, Lovable), and Slack invite Hashtags #AItrafficJam #Photonics #CoPackagedOptics #PhotonicCompute #DataCenters #Nvidia #Intel #AMD #Lightmatter #EnergyEfficiency #DailyAIShow The Daily AI Show Co-Hosts: Andy Halliday, Beth Lyons, Brian Maucere, Eran Malloch, Jyunmi Hatcher, and Karl Yeh

    50 min
  5. -6 J

    The AI Robot OS Showdown: Meta vs Google vs Nvidia

    The September 29th episode of The Daily AI Show focused on robotics and the race to merge AI with machines in the physical world. The hosts examined how Google, Meta, Nvidia, Tesla, and even Apple are pursuing different strategies, comparing them to past battles in PCs and smartphones. Key Points Discussed Google DeepMind announced Gemini Robotics, a “brain in a box” strategy offering a transferable AI brain for any robot. It includes two models: Gemini Robotics E 1.5 for reasoning and planning, and Gemini Robotics 1.5 for physical action. Meta is pursuing an “Android for robots” approach, building a robotics operating system while avoiding costly hardware mistakes from its VR investments. Nvidia is taking a vertically integrated path with simulation environments (Isaac SIM, Isaac Lab), a foundation model (Isaac Groot N1), and specialized hardware (Jetson Thor). Their focus on synthetic data and digital twins accelerates robot training at scale. Tesla remains a major player with its Optimus humanoid robots, while Apple’s direction in robotics is less clear but could leverage its massive data ecosystem from phones and wearables. Trust was raised as a differentiator: Meta faces skepticism due to its history with data, while Nvidia is viewed more favorably and Google’s DeepMind benefits from its long-term vision. Apple’s wearables and sensors could provide a unique edge in data-driven humanoid training. Google’s transferable learning across robot types was highlighted as a breakthrough, enabling skills from one robot (like recycling) to transfer to others seamlessly. Real-world disaster recovery use cases, such as hurricane cleanup, showed how fleets of robots could rapidly and safely scale into dangerous environments. Nvidia’s Brookfield partnership signals how real estate and construction data could train robots for multi-tenant and large-scale building environments. The discussion connected today’s robotics race to past technology battles like PCs (Microsoft vs Apple) and smartphones (iOS vs Android), suggesting history may rhyme with open vs closed strategies. The show closed with reflections on future possibilities, from 3D-printed housing built by robots to robot operating systems like ROS that may underpin the ecosystem. Timestamps & Topics 00:00:00 💡 Intro and framing of robotics race 00:02:20 🤖 Google DeepMind’s Gemini Robotics “brain in a box” 00:04:11 📱 Meta’s Android-for-robots strategy 00:05:57 🟢 Nvidia’s vertically integrated ecosystem (Isaac SIM, Groot N1, Jetson Thor) 00:07:28 💰 Meta’s cash-rich poaching of AI talent 00:10:15 🧪 Nvidia’s synthetic data and digital twin advantage 00:13:22 🍎 Apple’s possible robotics entry and data edge 00:14:51 📊 Trust comparisons across Meta, Nvidia, Google, Apple, and Tesla 00:19:26 🛠️ Nvidia’s user-focused history vs Google’s scale 00:23:09 🔄 Google’s cross-platform transfer learning demo (recycling robot) 00:27:15 ⚠️ Risks of robot societies and Terminator analogies 00:28:01 🌪️ Disaster relief use case: hurricane cleanup with robots 00:34:07 🦾 Humanoid vs multi-form factor robots 00:35:11 🧩 Nvidia’s Isaac SIM, Isaac Lab, Groot N1, and Jetson Thor explained 00:38:02 🖥️ Parallels with PC and smartphone history (open vs closed) 00:41:03 📦 Robot Operating System (ROS) origins and role 00:42:54 🔗 IoT and smart home devices as proto-robots 00:45:23 🎓 Stanford origins of ROS and Open Robotics stewardship 00:45:45 🏢 Nvidia-Brookfield partnership for construction training data 00:47:14 🏠 Future of robot-built housing and 3D-printed homes 00:49:24 🌐 Nvidia’s reach into global robotics players 00:49:47 📅 Wrap up and preview of possible photonics show The Daily AI Show Co-Hosts: Andy Halliday, Beth Lyons, Brian Maucere, Eran Malloch, Jyunmi Hatcher, and Karl Yeh

    50 min
  6. 26 SEPT.

    Brian & Beth Have Deep Thoughts About AI

    On September 26, The Daily AI Show was co-hosted by Brian and Beth. With the rest of the team out, the conversation ranged freely across AI projects, personal stories, hallucinations, and the skills required to work effectively with AI. Key Points Discussed • Brian shared recent projects at Skaled, including integrating TomTom traffic data into Salesforce workflows, showing how AI and APIs can automate enrichment for sales opportunities. • The discussion explored hallucinations as a feature of language models, not an error, and why understanding pattern generation vs. factual lookup is key. • Beth connected this to diplomacy, collaboration, and trust—how humans already navigate situations where certainty is not possible. • Ethan Mollick’s argument about “blind trust” in AI was referenced, noting we may need to accept outputs we cannot fully verify. • Reflections on expertise: AI accelerates workflows but raises questions about what humans still need to learn if machines handle more foundational tasks. • Beth highlighted creative uses of MidJourney, including funky furniture and hybrid creatures, as well as work on AI avatars like “Madge” that blend performance and generative models. • The panel considered how improv and play help people interact more productively with AI, framing experimentation as a skill. • Teaching others to work with AI revealed the challenge of recognizing dead ends, pivoting effectively, and building repeatable processes. • Both hosts closed by emphasizing that AI use requires reps, intuition, and comfort with uncertainty rather than expecting perfection. Timestamps & Topics 00:00:00 🎙️ Friday kickoff, Brian and Beth hosting 00:02:34 💼 Job market realities and “job hugging” 00:06:43 🛣️ TomTom traffic data project integrated with Salesforce 00:11:27 🤖 Seeing prospects with enriched AI data 00:13:12 🔬 Sakana’s “Shinka Evolve” open-source discovery framework 00:17:38 🔄 Multi-model routing as a way to reduce hallucinations 00:23:16 📊 What hallucination really means in language models 00:26:09 🗂️ Boolean search vs. pattern-based reasoning 00:27:24 😂 Proposal story, storytelling vs. strict accuracy 00:30:42 💭 ChatGPT “whispering sweet nothings” as it guides workflows 00:32:20 🤝 Diplomacy, trust, and moving forward without certainty 00:34:56 📚 Ethan Mollick’s “blind trust” idea and co-intelligence 00:37:05 🔡 Spell check analogy for offloading human expertise 00:42:01 🎨 Beth’s creative AI projects in MidJourney and funky furniture 00:46:00 🎭 AI avatars like “Madge” and performance-based models 00:49:38 🎤 Improv skills as a foundation for better AI interaction 00:52:30 📑 Teaching internal teams, recognizing dead ends 00:55:42 🚀 Mentorship, passing on skills, and embracing change 00:57:56 🌺 Closing notes, weekend wrap, newsletter and conundrum tease Hashtags #AIShow #AIHallucinations #SalesforceAI #SakanaAI #MidJourney #AIavatars #ImprovAndAI #DailyAIShow The Daily AI Show Co-Hosts: Andy Halliday, Beth Lyons, Brian Maucere, Eran Malloch, Jyunmi Hatcher, and Karl Yeh

    59 min
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À propos

The Daily AI Show is a panel discussion hosted LIVE each weekday at 10am Eastern. We cover all the AI topics and use cases that are important to today's busy professional. No fluff. Just 45+ minutes to cover the AI news, stories, and knowledge you need to know as a business professional. About the crew: We are a group of professionals who work in various industries and have either deployed AI in our own environments or are actively coaching, consulting, and teaching AI best practices. Your hosts are: Brian Maucere Beth Lyons Andy Halliday Eran Malloch Jyunmi Hatcher Karl Yeh

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