AI Ketchup 🍅 | Your Business's Secret Sauce

Elina Lesyk
  • 0.0 (0)
  • 创业
  • 一日一更

AI is your new hire. Learn how to train it. Join Elina, ex-AWS Cloud & AI Architect, as we crack open the playbooks of leaders who’ve slashed costs, automated workflows, and scaled revenue using AI. No jargon. No fluff. Just battle-tested tactics from: ✅ Founders who built 7-figure businesses with AI ✅ CEOs who automated 40% of operations (and kept their teams happy) ✅ Skeptics-turned-advocates surviving the AI learning curve A new episode biweekly if you hit a "Subscribe".

  1. 8月28日

    How to Rank Higher in AI Overviews | Pahul Hallan

    Is traditional SEO dead? As AI Overviews begin to dominate search results, the rules for getting discovered online are being rewritten. In this episode, ML engineer Pahul Hallan explains why the new landscape is a "winner takes all" game and breaks down the essentials of AI Engine Optimization (AEO). Discover the technical and content strategies your e-commerce business needs to implement today to not just survive, but thrive in the age of AI-powered search and rank higher than your competition. Guest: Pahul Hallan, Machine Learning Engineer with 5+ years of experience in e-commerce search, ranking, and recommendation systems. Find our guest here: https://www.linkedin.com/in/pahulhallan/ Main Topics & Takeaways: The Shift from SEO to AEO: Understand the fundamental differences between traditional keyword search and modern AI Engine Optimization. Winner-Takes-All Search: Why AI search drastically reduces the number of competitors and what it takes to be one of the top results. Technical SEO for AI: How to use standardized schemas (Schema.org) and configure your robots.txt file to ensure AI models can find and understand your content. "Hand-Feeding the LLM": Actionable content strategies, including using Q&A formats and creating detailed, story-driven product pages that AI loves. The Future of Recommendations: How multimodal contextual embeddings are making product recommendations hyper-personalized. Privacy in the AI Era: A look at the "right to be forgotten" and how to manage your digital footprint as data collection becomes more sophisticated. AI search is a "winner-takes-all" environment. Unlike traditional search with 10+ results, you might only be competing against two or three products in an AI-generated answer. Structure your website content in a Q&A format. It's more effective than simple listicles because it directly provides the structured answers that LLMs are designed to find. SEO isn't dead; it's the foundation. AEO adds a new layer on top of existing best practices like quality backlinks and secure connections. Reverse engineer the process. Take your own webpage, feed it into an LLM, and ask it questions a customer would. If the answers aren't what you expect, your content is likely too confusing. Authenticity is crucial. Trying to "game the system" with keyword stuffing or bot farms will ultimately get you penalized and hurt your credibility. Embrace multimodal content. Provide video transcripts, use tables for comparisons, and add descriptive alt-text to images. This makes your site more accessible and easier for AI to parse. Over time, high-quality, original content will win. As more AI-generated content floods the internet, unique and valuable insights will stand out and keep users engaged longer.Schema.org: A collaborative community resource for creating and maintaining standardized schemas for structured data on the internet. Chapters: 00:39 Welcome to the New Era of Search: AI Engine Optimization 02:06 The Evolution from Keyword Search to Contextual Search 03:48 How AI Changes the Game for E-commerce 05:40 The "Winner Takes All" Nature of AI Search 08:55 5 Technical Tips to Rank Higher in AI Overviews 10:30 Why Standardized Schemas (schema.org) Matter 12:10 Making Your Site Discoverable with robots.txt 15:27 What is AI Engine Optimization (AEO)? 17:15 Content Strategy: How to "Hand-Feed" the LLM 18:30 The Power of Multimodal Content (Video, Text, Tables) 21:52 How LLMs are Supercharging E-Commerce Recommendation Systems 27:17 Managing Your Digital Footprint & The Right to Be Forgotten 31:24 The Future of Search & The Risk of Homogenized Content 35:51 Key to Success: Understand the Fundamentals of How AI Works Follow AI Ketchup for bi-weekly stories of AI builders turning ideas into successful tech products. Don't forget to like, subscribe, and leave a review! Website: https://pod.elinalesyk.com/ LinkedIn: https://www.linkedin.com/company/ai-ketchup/

    38 分钟

  2. 7月31日

    How Voice AI Boosts NPS by 180% & Creates Unicorns | Stefan Ostwald

    Is the future customer experience spoken? Discover the massive shift from clunky, frustrating automated systems to truly helpful AI Agents that can increase customer satisfaction by 180%. In this episode, we sit down with Stefan Ostwald, co-founder and Chief AI Officer of the AI unicorn Parloa, to uncover how they found product-market fit by solving the biggest pain points in customer service. Learn how modern voice AI is moving beyond a cost center to become a powerful tool for building brand loyalty, driving revenue, and redefining the entire customer experience. Guest: Stefan Ostwald, Co-founder and Chief AI Officer at Parloa. Website: https://parloa.com/ LinkedIn: https://www.linkedin.com/in/stefan-ostwald/ What You'll Learn The inside story of how Parloa pivoted from a voice agency to a billion-dollar AI product company Why modern AI agents are succeeding where old chatbots failed, and how they are delighting customers Key learnings on scaling an organization from 10 to 350 people and the challenges faced at each stage How to structure your company and teams around your product to maximize autonomy and speed Using voice AI to move beyond surface-level analytics and truly understand the root cause of customer issues How continuous AI conversations will transform brand relationships and turn service into a revenue driver. Key Insights & Actionable Takeaways True product-market fit is found when your technology solves a deep, painful problem, not just a "nice-to-have" one. For Parloa, this was shifting from smart speaker apps to enterprise customer service. Don't just focus on automating the successful 70% of cases. Your strategy must include a robust plan for the other 30%—the failures and edge cases—to ensure a consistently high-quality customer experience. The "why" behind a customer call is the most valuable data. Natural language conversations allow you to capture this intent directly, unlike interpreting click paths on a website. Structure your organization to mirror your desired product architecture, not the other way around (Conway's Law). Define product domains first to create team autonomy and enable independent scaling. As a founder or leader in a scaling company, your job changes completely every six months. The skills that got you here won't get you there; you must constantly adapt to what the company needs next. Chapters 00:00 From Unhappy Chatbots to Helpful AI Agents  01:31 The Journey to a Unicorn Valuation  02:37 Why Bet on Voice AI in 2017?  04:20 Finding Product-Market Fit in Customer Service  08:05 How to Stand Out in a Crowded AI Market  12:17 The Evolving Role of a Founder in a Scaling Company  15:23 The Biggest Scaling Challenge: Growing from 50 to 350+  17:01 Using Product Architecture to Design Your Org Structure  19:19 How AI Will Fundamentally Change the Way We Work  23:43 The 30% Problem: Why Handling AI Failures is Critical  26:20 Using LLMs to Understand the "Why" Behind Customer Calls  30:11 Turning Customer Service from a Cost Center to a Revenue Driver  32:45 Why NPS Can Skyrocket with AI Agents  36:41 Parloa's Roadmap and Expansion to the US Market Follow AI Ketchup for bi-weekly stories of AI builders turning ideas into successful tech products. Don't forget to like, subscribe, and leave a review! Our website: https://pod.elinalesyk.com/. Listen on Spotify, Apple Podcasts, and YouTube. Follow us on LinkedIn & Twitter.

    38 分钟

  3. 7月24日

    How to Build a True AI-First Education Company | Moritz Heininger

    Are you overwhelmed by the constant flood of new AI tools, feeling you have "FOMO" about what's truly relevant? This episode cuts through the noise. We're joined by Moritz Heininger, founder of the leading German AI education platform, SnipKI, to reveal how he built a true AI-first company that automates nearly everything—from daily content publishing to B2B lead qualification. Forget abstract theory; Moritz shares a practical blueprint for integrating AI and automation into your core business processes, helping you avoid common mistakes and transform your team's productivity. Listen now to learn how to move from being curious about AI to becoming competently AI-driven. Guest: Moritz Heininger, Co-Founder of SnipKI. Find our guest here: Website: SnipKI LinkedIn: Moritz Heininger Building an AI-First Engine: How SnipKI automates its entire content pipeline, from video transcription and image generation to social media posting. The "KI Führerschein": The concept of an "AI Driver's License" and why structured, company-wide upskilling is essential for adoption. A Go-To-Market Secret: How building trust through high-quality content on LinkedIn has driven all inbound growth for SnipKI without any outbound sales. The 3 Stages of AI Transformation: Understand the evolution from using AI for (1) Efficiency, to gaining (2) Superpowers, to finally (3) Reinventing your core product. Actionable First Steps: Moritz’s 3 practical exercises for anyone to become AI-literate, involving strategic thinking with LLMs, "vibe coding" with no-code tools, and building your first automation. The Biggest Mistakes to Avoid: Why you can't fix a broken process with AI and why the worst thing you can do is fail to start experimenting. You cannot fix a flawed process by simply adding AI. Start by optimizing the process itself, then strategically apply automation. Don't start with a grand, top-down AI strategy. Instead, identify one significant, daily problem your team faces and solve it with a simple AI tool or automation. The most successful companies will view AI not just as a tool for efficiency, but as a source of "superpowers" that enables them to create more and better products than was previously possible. The biggest mistake is not starting. You must experiment and accept that some initiatives will fail. The cost of waiting for the "perfect" AI is falling behind your competition. Treat the latest AI models (like Claude 3 or GPT-4o) as a strategic partner. Give them deep context on a business problem and use them to brainstorm and structure new concepts. Tools: AI Education: SnipKI Data Analysis: Julius AI AI-Assisted Coding: Cursor, Replit, Lovable Automation Platforms: Make.com, n8n, ZapierB2B Prospecting: Clay Chapters: 02:26 The OMR Story: From Cassette Tapes to Personalized AI Websites 05:02 Why Moritz Built SnipKI: A Cure for Frustrating AI Courses 07:18 Filtering the Noise: How SnipKI Designs Its Practical AI Curriculum 10:29 The "KI Führerschein": Why Every Company Needs an AI Driver's License 11:36 The Inbound Machine: Growing a Business on Trust and LinkedIn 14:04 Under the Hood: Automating the Entire Content Creation Pipeline 18:36 A Blueprint for Business Owners to Become AI-First 21:12 The Biggest Mistakes Companies Make When Adopting AI 23:26 The 3 Stages of AI Transformation: Efficiency vs. Superpowers 27:09 How AI Changed the Angel Investing Game Forever 29:27 SnipKI's Bold Vision: AI Skills Will Be as Common as Excel 31:09 Your First 3 Steps to Become Genuinely AI Literate Follow AI Ketchup for bi-weekly stories of AI builders turning ideas into successful tech products. Don't forget to like, subscribe, and leave a review! Newsletter & Website: AI Ketchup Follow on LinkedIn: AI Ketchup Podcast

    33 分钟

  4. 7月17日

    Why Your Next AI Project Should Be Open-Source | Mike Bird

    Is locking down powerful AI in the hands of a few companies a risk we can't afford to take? In this episode, we're joined by open-source visionary Mike Bird to explore why the future of humanity might depend on open-source AI. We dive deep into the strategic advantages of building in the open, how to decide what parts of your business to open-source, and the practical tools and frameworks that can help developers and companies thrive. Guest: Mike Bird, open-source advocate, contributor to Open Interpreter, AI & Engineering Lead at BoxOne Ventures and host of the Tool Use YouTube channel. Our guest: X: https://x.com/MikeBirdTech LinkedIn: https://www.linkedin.com/in/mikebirdtech/YouTube: https://www.youtube.com/@MikeBirdTech What You'll Hear About: The Philosophical Debate: Why centralizing AI in a few corporations is a high-risk scenario for humanity. Strategic Open-Sourcing: How companies can build trust and attract talent by strategically open-sourcing parts of their tech stack without losing their competitive edge. Practical AI Workflows: Three game-changing use cases for AI in your daily life, including voice transcription, building tool generators, and leveraging code assistants like Cursor. The Future of AI Agents: Will open-source or closed-source frameworks dominate the next wave of AI agent technology? Security in the Open: How to navigate the risks of open-source, from malicious actors to ensuring the safety of tools like MCP servers with projects like ToolHive. Key insights: Open-sourcing parts of your software is a powerful way to build trust in an age of increasing digital skepticism. You don't have to open-source your core product. Contributing to the libraries and tools your business relies on is a valuable way to participate. The argument against open-source AI often ignores the second-order effect: concentrating power in a few opaque organizations is a greater long-term risk. Use AI tools like Cursor not just for development, but as a learning tool to understand complex codebases and make meaningful contributions. The most important skills in the age of AI are curiosity, agency, and taste. Learn to experiment, act on your ideas, and develop a sense for quality user experience. Tools Mentioned: Open Interpreter: An open-source project for running code on your computer https://github.com/openinterpreter/open-interpreter . Cursor: An AI-powered code editor. Cal.com: An open-source scheduling alternative to Calendly. AgentStack: A tool for tracing and building reliable AI systems https://github.com/AgentOps-AI/AgentStack. Bitwarden: An open-source password manager. Superwhisper / Whisperfile: Voice transcription tools https://github.com/cjpais/whisperfile. Obsidian: A note-taking app that works on local Markdown files. ToolHive: A project for secure secret management with MCP servers. Augment Toolkit & Transformer Lab: Tools for creating fine-tuned models https://github.com/e-p-armstrong/augmentoolkit https://transformerlab.ai/. Chapters 00:00 The High-Stakes Future of Open-Source AI 01:15 Mike Bird's Journey into the AI Ecosystem 03:55 Why Open-Source is a Public Good for Humanity 05:30 Building Trust: How Companies Can Benefit from Open-Source 07:15 What to Open Source (And What to Keep Proprietary) 11:19 The Philosophical Argument: Is Open-Source AI a Necessity? 15:01 Open-Source vs. Closed-Source as a Societal Choice 17:35 Why Did OpenAI Abandon Its Open-Source Roots? 22:47 The Future of AI Agents: Who Will Win? 28:25 Mike's Top 3 AI Use Cases for Daily Productivity 30:10 Building a Tool That Builds More Tools 33:26 Navigating Security with MCP Servers and ToolHive 36:06 Final Principles: Stay Curious, Keep Humans in the Loop, and Develop Good Taste Follow AI Ketchup for bi-weekly stories of AI builders turning ideas into successful tech products. Don't forget to like, subscribe, and leave a review! Website: pod.elinalesyk.com LinkedIn: linkedin.com/company/ai-ketchup/

    40 分钟
  5. Rewiring an 800-Person Powerhouse with AI Agents | Aytekin Tank

    7月3日

    Rewiring an 800-Person Powerhouse with AI Agents | Aytekin Tank

    Is it possible to transform a 20-year-old bootstrapped company into an AI powerhouse? Aytekin Tank, founder of Jotform, reveals the “cheat codes” he used to scale to 30 million users and revolutionize his own business with AI agents. Discover how Jotform went from building simple forms to developing sophisticated AI that resolves 75% of customer support inquiries automatically. This episode is a masterclass in product evolution, leveraging user feedback, and the future of AI-driven customer interaction for any business owner looking to innovate and automate. Find our guest here: Website: Jotform.com Book: Automate Your Busywork LinkedIn: Aytekin Tank on LinkedIn What You'll Learn in the Episode: The Genesis of Jotform: How Aytekin’s experience as a developer led to the creation of a 30-million-user company. The "Cheat Code" Philosophy: How using your own product and leveraging a massive user base provides an unparalleled advantage in development. From Forms to AI Agents: The surprising user behavior that pivoted Jotform from an AI form-filler to a full-fledged AI agent platform. Dogfooding to Perfection: How Jotform became its own biggest customer to increase its AI's support resolution rate from 25% to 75% in just three months. The RAG Revolution: The critical role of Retrieval-Augmented Generation (RAG) and the specific tech that unlocked a 10% jump in resolution rates. Automating Laziness: Why understanding user laziness is the key to designing powerful and effective website chatbots and AI tools. The Future of Websites: Aytekin's vision for "v3" of the web, where AI agents become the primary interface for every business. Email Automation Mastery: The 3-label system Aytekin uses to cut down his email processing time to just 1 hour daily. Key Takeaways: Being your own biggest user is a "cheat code." It allows you to identify and fix problems faster than any feedback loop, directly benefiting your entire user base. Pay close attention to unexpected user behavior. 90% of Jotform's early AI users ignored the main feature and used the chatbot, revealing a massive market opportunity. True customer preference isn't for human support; it's for quick support. A well-trained AI can provide the instant gratification that builds customer loyalty. Automate laziness. People don't want to search your website; they want to ask a question. An AI chatbot turns this "laziness" into a powerful tool for user research and engagement. The biggest gains in AI performance often come from foundational technology choices, like the right RAG and vector database solution. Implement a strict email prioritization system. By categorizing emails into priority levels, you can focus your attention on what truly matters and reclaim hours of your day. Every business, regardless of size, can have its own "ChatGPT" to serve its customers 24/7, handling everything from sales to complex support inquiries. Chapters: 00:00 The Two "Cheat Codes" for a Successful Product 02:12 The Origin: Solving a Developer's Repetitive Task 04:02 How Internal Hack Weeks Led to AI Agents 05:45 Users Wanted a Chatbot, Not an AI Form-Filler 08:24 Dogfooding: How Jotform Became Its Own Biggest AI Customer 10:11 The 3-Month Journey from 25% to 75% AI Resolution Rate 12:28 How They Pinpointed and Solved AI Failures 13:48 The Power of RAG: How New Tech Caused a 10% Jump in Success 15:20 Building API Tools for the AI to Use 17:55 Leveraging 30 Million Existing Users 19:22 The #1 Use Case: Automating "User Laziness" on Websites 22:42 The Future of Websites is AI-Powered 25:05 Why Every Business Needs Its Own "ChatGPT" for Customers 27:51 Beyond Support: Using AI for Sales and Lead Generation 30:47 Getting Internal Buy-In for a Massive AI Transformation 34:54 How to Save 5 Hours a Day on Email with a 3-Label System Follow AI Ketchup for bi-weekly stories of AI builders turning ideas into successful tech products. Website: pod.elinalesyk.com LinkedIn: AI Ketchup on LinkedIn

    39 分钟

  6. 6月3日

    Can Europe Build Private AI? Meet Nebul’s Proof | Arnold Juffer

    Why should you care about who really owns the servers that power your cloud workloads and AI?? In this episode, Nebul CEO Arnold Juffer reveals how European businesses can run private GPTs—free from hyperscaler lock-in, Cloud Act subpoenas, and data-leak nightmares. TOPICS DISCUSSED: 1. European AI SovereigntyHow geopolitical tensions underscore the need for a Europe-owned AI infrastructure. 2. Private Cloud and ComplianceBuilding “secure by default” private clouds that turn compliance into a competitive advantage. 3. Model Bias & HallucinationAddressing bias in foreign-trained models and reducing hallucinations using RAG and guardrails. 4. European AI Act & RegulationChallenges around traceability requirements and prohibited model sizes under the AI Act. 5. B2B AI AdoptionA workshop-to-MVP approach for enterprises exploring private AI workloads. 6. AI as Operational InterfaceLeveraging AI agents for 24/7 infrastructure monitoring and as the new front-end for business applications. INSIGHTS:- Sovereignty over data and models is critical for economic and geopolitical security. - Running open-source stacks under European jurisdiction prevents foreign “phone-home” risks. - RAG dramatically improves factual accuracy and reduces bias/hallucinations. - The AI Act’s traceability mandate and model-size limits can stifle innovation if not refined. - A fast-paced, time-boxed MVP process de-risks enterprise AI adoption. - AI agents can surface patterns in massive log streams and replace routine interfaces. TOOLS AND TECHNOLOGIES MENTIONED: - Nebul Private GPTs- Retrieval-Augmented Generation (RAG)- Open-source models: DeepSeek, Qwen, Llama 4- GPU-based private cloud clusters CONTACT INFO:- Nebul's Blog Website: nebul.com/news- Nebul Contact Page: The Nebul Contact Page CHAPTERS01:32 Private Cloud & Sovereignty Discussion02:25 Nebul’s Infrastructure Approach03:06 Compliance as a Competitive Advantage04:22 Industries Benefiting from Sovereign AI06:10 US Cloud Act & FISA Impact08:54 Geographic Adoption Differences09:45 Ensuring European-Hosted Models’ Privacy11:07 Addressing Model Bias & Guardrails12:53 RAG to Combat Hallucinations14:03 European LLM Provider Landscape15:51 Europe’s Role in AI Race & Infrastructure Gaps16:18 Barriers to European Model Development20:49 AI Act Challenges: Traceability & Model Size23:59 Traceability vs. Chain-of-Thought Debate25:09 E-commerce Example for Sovereign AI28:13 Open-Source vs. Proprietary Solutions32:03 AI as Competitive Differentiator33:28 B2B Focus & Product Maturity36:31 AI Agents for Operations & Interfaces39:41 Nebul’s Customer Onboarding Process43:16 Where to Learn More & Next Steps Follow us at AI Ketchup for bi-weekly stories of AI builders and founders turning ideas into successful tech products.

    44 分钟

  7. 5月8日

    Inside the $100K MRR AI Automations Community | Jack Roberts

    Do you know what AI automation your business needs today? Let's find out! Join us for an insightful conversation with Jack Roberts, founder of the AI Automations community, on making AI automation work for your business, building vibrant online communities, and combining cutting-edge AI tools with strategic execution. TOPICS DISCUSSED: 1. Community Building in AI Automations Jack explains why “social media 3.0” is really about micro-interactions, culture and value—and how to keep churn around 7% through consistent engagement. 2. The “So What?” Layer of AI Automations How to move beyond models and agents into applications that actually drive time savings, revenue and customer impact. 3. Execution & Early Adopter Advantage Why it feels saturated but you’re still extremely early, and how habitual learning plus “copying what works” beats overthinking. 4. Data-Driven Content & YouTube Workflows Automating transcript analysis, thumbnail A/B tests, title refinement and even auto-translating videos to reach new markets. 5. High-ROI Automations to Build Today From goodwill-investing tactics to email segmentation and auto-draft responses—pick automations that save the most time and cognitive load. INSIGHTS: - Investing goodwill yields ROI far above hourly rates.- Fun + value is the secret sauce for community stickiness.- You’re never “too late”—execution and pivots create your unfair advantage.- Stack your top 1% skill sets to become a one-in-a-million operator.- Automate only the tasks where AI cuts volume or mental friction most. TOOLS AND TECHNOLOGIES MENTIONED: make.com (formerly Integromat)n8nDeep ResearchChatGPT Voice / Sesame Conversational AI CONTACT INFO: - Skool community: https://www.skool.com/aiautomationsbyjack- YouTube: https://www.youtube.com/@Itssssss_Jack EXCLUSIVE JACK'S YOUTUBE FRAMEWORK Tap into Jack's checklist for YouTube videos, it's meta!AI Ketchup Resource: Jack's YouTube Framework CHAPTERS 01:16 Community Building: Social Media 3.0 03:38 Launching & Growing AI Automations Community 06:32 The “So What?” of AI Automations 10:00 Balancing Product vs. Education Focus 16:39 Execution & Market Saturation Myths 20:07 Unfair Advantages: 1% Skill Sets 23:52 Growth Strategies: Consistency & Pivoting 29:19 AI Adoption Beyond the Bubble 32:33 Top Automation Services in Demand 37:23 YouTube Automation Workflow Insights 41:04 Favorite AI Tools & Platforms 45:38 High-ROI Automations & Cognitive Load 46:53 Recommended Automation: Email Segmentation 47:27 Closing Remarks Follow us at the AI Ketchup Podcast for bi-weekly stories of AI builders and founders turning ideas into successful tech products.

    48 分钟

  8. 4月24日

    Digital Renaissance, Consentful Data Sharing, and Impact-Driven Communities | Jean Arnaud

    Can the marriage of philosophy and technology create a more ethical AI future? Discover how Jean Arnaud, a philosopher turned AI innovator, is pioneering a revolutionary approach to responsible AI development through his concept of "digital renaissance." Jean shares his fascinating journey from teaching philosophy in France, UK, and the US to founding Nova and co-founding Aethos, a nonprofit AI innovation hub fostering collaboration between researchers, entrepreneurs, and artists. TOPICS DISCUSSED: 1. Jean's Unique Background From an academic background in philosophy to rock band musician to AI founder, Jean explains how his versatile education and ADHD contributed to his multidisciplinary approach to innovation. 2. The Birth of Nova Jean shares how his transformative experience at Stanford led him to create Nova, an AI-powered research tool that helps researchers navigate scientific literature more efficiently and combat misinformation in academic papers. 3. Aethos: A Community for Responsible AI How a nonprofit AI innovation hub came to life, bringing together founders, researchers, and artists committed to building human-centered AI solutions across multiple locations, starting in Cambridge. 4. Ethics in AI Development Jean discusses his approach to evaluating startups for ethical considerations, the importance of transparency in AI model training, and how to implement responsible practices in AI development. 5. Digital Renaissance The philosophical concept that AI can augment human capabilities and help us become "multi-experts" like Renaissance figures, enabling a new era of human flourishing if anchored in humanistic values. 6. Copyright and Intellectual Property Jean shares his contrarian view that intellectual property ultimately belongs to humanity, challenging conventional notions of copyright and ownership in the AI age. 7. Community-Driven Innovation How Aethos fosters peer-to-peer learning, self-organization, and collective intelligence through initiatives like "pods" and "Unconferences." INSIGHTS: - The integration of philosophy, art, and technology creates a more holistic approach to AI development - Transparency in AI training is crucial for building responsible AI systems - Peer-to-peer learning and community intelligence often yields better results than traditional top-down leadership - AI can help us become "multi-experts" and achieve greater human flourishing - "There is no point to have a technology without consciousness" (adapting Montaigne's philosophy) - The artist/founder ego is often overrated; creation should benefit humanity as a wholeCONTACT INFO: - LinkedIn: Jean Arnaud - Organizations: Aethos, Nova CHAPTERS 02:01 From Philosophy Professor to AI Founder 05:00 The Three Pillars: Education, Art, and Entrepreneurship 08:54 The Birth of Nova 10:13 Nova's Evolution and Pivot 15:14 Founding Aethos as a Nonprofit AI Hub 17:04 The Mission of Responsible AI Innovation 19:56 Evaluating Ethical AI Startups 22:51 Implementing Responsible AI in Practice 26:45 Transparency in AI Model Training 29:03 Rethinking Copyright in the AI Age 32:25 The Future of Ownership and Decentralization 35:58 Creating a Collaborative Innovation Environment 40:35 The Power of Community Intelligence 43:43 Building Your Own Meaning Through Impact 49:37 The Concept of Digital Renaissance Follow us at AI Ketchup for bi-weekly stories of AI builders and founders turning ideas into successful tech products.

    51 分钟
查看全部 20 集

关于

AI is your new hire. Learn how to train it. Join Elina, ex-AWS Cloud & AI Architect, as we crack open the playbooks of leaders who’ve slashed costs, automated workflows, and scaled revenue using AI. No jargon. No fluff. Just battle-tested tactics from: ✅ Founders who built 7-figure businesses with AI ✅ CEOs who automated 40% of operations (and kept their teams happy) ✅ Skeptics-turned-advocates surviving the AI learning curve A new episode biweekly if you hit a "Subscribe".

信息