Podcasts about enterprise ai

Breaking: Google just released Gemini Enterprise.

Jason Droege is the CEO of Scale AI, a company that provides foundational training data to every major AI lab. He previously co-founded Scour with Travis Kalanick and built Uber Eats from idea to $20 billion in revenue. In this conversation, Jason shares lessons from getting sued for $250 billion, discovering restaurant economics by weighing sandwich ingredients, and over 25 years of launching transformative technology businesses.What you'll learn:What actually happened with Meta's $14 billion investment in Scale AIWhy AI models still need human experts to improve, and how that relationship is evolvingHow AI models learn from experts building websites and debugging codeThe business lessons from building Uber Eats from zero to $20 billionWhy most enterprise data is useless for AI models todayWhy urgent daily problems beat super-valuable occasional problems when building productsHow to think independently when building new products and businesses—Brought to you by:Merge—The fastest way to ship 220+ integrations: http://merge.dev/lennyFigma Make—A prompt-to-code tool for making ideas real: https://www.figma.com/lenny/Mercury—The art of simplified finances: https://mercury.com/—Transcript: https://www.lennysnewsletter.com/p/first-interview-with-scale-ais-ceo-jason-droege—My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/174979621/my-biggest-takeaways-from-this-conversation—Where to find Jason Droege:• X: https://x.com/jdroege• LinkedIn: https://www.linkedin.com/in/jasondroege/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Jason Droege(06:01) Jason's early career and lessons learned(10:27) The current state of Scale AI(12:37) The shift to expert data labeling(17:02) Challenges and strategies in finding experts(18:48) Reinforcement learning and AI environments(28:18) The future of AI and human involvement(31:21) The role of evals(35:25) What AI models will look like in the next few years(41:43) Building Uber Eats and understanding customer needs(48:19) The importance of independent thinking(50:45) Setting high standards for new businesses(53:03) Exploring and selecting business ideas(57:07) The McDonald's story(01:00:13) The role of gross margins in business feasibility(01:04:49) Why Jason says, “Not losing is a precursor to winning”(01:09:12) Hiring and building teams(01:12:11) AI corner(01:14:47) Lightning round and final thoughts—Referenced:• Travis Kalanick on X: https://x.com/travisk• Scour: https://en.wikipedia.org/wiki/Scour_Inc.• Scale: https://scale.com/• Alexandr Wang on X: https://x.com/alexandr_wang• Why experts writing AI evals is creating the fastest-growing companies in history | Brendan Foody (CEO of Mercor): https://www.lennysnewsletter.com/p/experts-writing-ai-evals-brendan-foody• Brendan Foody's post on X about knowledge work changing: https://x.com/BrendanFoody/status/1970163503702188048• MIT Finds 95% of GenAI Pilots Fail Because Companies Avoid Friction: https://www.forbes.com/sites/jasonsnyder/2025/08/26/mit-finds-95-of-genai-pilots-fail-because-companies-avoid-friction/• Uber Eats: https://www.ubereats.com/• Stephen Chau on X: https://x.com/thestephenchau• a16z Podcast: https://a16z.com/podcasts/a16z-podcast/• F1: The Movie: https://www.imdb.com/title/tt16311594/• V03: https://v03ai.com/• Careers at Scale: https://scale.com/careers—Recommended books:• The Selfish Gene: https://www.amazon.com/Selfish-Gene-Anniversary-Introduction/dp/0199291152• The Road Less Traveled: A New Psychology of Love, Traditional Values, and Spiritual Growth: https://www.amazon.com/Road-Less-Traveled-Timeless-Traditional/dp/0743243153/• Good to Great: Why Some Companies Make the Leap . . . And Others Don't: https://www.amazon.com/Good-Great-Some-Companies-Others/dp/0066620996• Thinking, Fast and Slow: https://www.amazon.com/Thinking-Fast-Slow-Daniel-Kahneman/dp/0374533555/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

If most companies are using the same AI systems, how can they stand out and get ahead? And as agentic AI becomes table stakes, what do enterprises need to keep in mind to make AI work? And how can we even trust an AI-powered workplace when most people can't even explain the basics of AI? We're learning from the experts. Accenture's Mary Hamilton joins the Everyday AI show to talk about building trust in an autonomous workplace, how we can prepare for the future of work, and four emerging AI trends you can't miss. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Thoughts on this? Join the convo and connect with other AI leaders on LinkedIn.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:AI-Powered Autonomy Shaping Future WorkGenerative AI's Impact on Business TransformationAccenture Technology Vision 2025 OverviewKey Trends: Autonomy and Enterprise AI AdoptionHuman Capability Expansion via AI ToolsTrust, Explainability, and Responsible AI PracticesAgentic AI Models and Productivity ShiftsContinuous Learning Loops in Workplace AIAI-Powered Robotics and Multimodal IntegrationPersonalization and Brand Voice with AI AgentsTimestamps:00:00 "AI's Impact on Business Autonomy"03:33 Accenture's Global Consultancy Overview09:48 Technology as a Game-Changing Partner12:16 Reinventing Responsible Tech Use14:31 Building Trust Through AI Interactions18:17 Building Trust in Enterprise Data23:20 Embracing AI: Active Learning Loop26:24 "Embracing Efficiency with AI Agents"Keywords:AI powered autonomy, generative AI, large language models, future of work, automation, business transformation, Accenture, innovation centers, strategic visioning, co-creation, ecosystem partners, digital core, technology consultancy, technology reinvention, enterprise AI adoption, operational efficiency, Technology Vision 2025, AI trends, human-like capabilities, language barrier, technology acceleration, digital agents, digital transformation, customer interaction, trust in AI, responsible AI, data platform, knowledge graphs, AI-driven robotics, warehouse automation, personalization at scale, brand voice in AI, digital twin, agentic models, observability, traceability, explainability, continuous learning loop, employee upskilling, generative AI productivity, change management, value-driven outcomes, super agents, utility agents, orchestrator agents, AI partner, human agency, AI collaboration, AI model accuracy, enSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner

Tom Drummond, Managing Partner at Heavybit, joins the show to break down what it takes to build and scale AI “picks and shovels” companies for the enterprise. We dive into the realities of selling into one of the hardest markets to reach, why differentiation matters more than ever, and how startups can wedge their way into massive opportunities despite fierce competition.Key Takeaways• Enterprise attention is more competitive than ever—breaking through requires clarity and category creation.• Cold email and traditional outbound are saturated—startups must iterate quickly on channels and messaging.• Landing enterprise deals often starts with developers and end users, not CIOs—grassroots adoption is powerful.• Narrow wedges matter—solve one painful, high-value problem better than anyone else, then expand.• Timing the industry cycle is critical—knowing when markets fragment and when they consolidate can define outcomes.Timestamped Highlights02:03 — Why enterprise attention has never been harder to win04:55 — Differentiation in a sea of lookalike AI infrastructure startups07:34 — Cold email vs content, billboards, and unconventional channels08:35 — The Pareto rule of enterprise revenue and why developer adoption is key11:47 — Competing with big tech incumbents: the power of the narrow wedge21:03 — Where the market is headed: cycles of expansion, contraction, and consolidationA line that stuck“You don't win by being another tool—you win by defining the category everyone else has to fit into.”Call to ActionIf you enjoyed this conversation, share it with a founder or tech leader who's navigating the enterprise market. Make sure to follow the show for more unfiltered conversations with people shaping the future of software and AI.

“When I saw Google change the destiny of the planet, I could not imagine doing anything else but working with brilliant entrepreneurs.”-Asha Jadeja Motwani and her husband, Rajeev Motwani, the Silicon Valley legend of technical startups, are together the founding stakeholders of Google.In the late 1990s, they came to the United States as most Indians, as students. From being part of Google's early days to their journey as investors and now, extending that into an active participation in American politics. She speaks about Rajeev's pivotal role in mentoring Larry Page and Sergey Brin, co-authoring the PageRank paper, and helping shape Google's DNA. Today, through the Motwani Jadeja Foundation, Asha continues to build on that legacy; funding entrepreneurs, supporting Indian voices in global think tanks, and opening doors at Davos and Washington. Asha also reflects on how the Indian diaspora can play a far greater role in shaping the future of India-US partnership and why entrepreneurs are critical to the future of this relationship.If you're an entrepreneur building in the India–US corridor, or curious about the opportunities the two nations are creating for startups, then this episode is for you.00:00  – Trailer01:25 – How Rajeev became founding stakeholder of Google03:48 – The early days of Google: first office to first funding07:52 – Investments of Dot Edu Ventures10:03 – Asha's role in American politics10:45 – How Indians in Silicon Valley can strengthen US–India corridor12:18 – The lack of Indian scholars in think tanks13:14 – Do Indians have enough influence in American politics?13:52 – Is Silicon Valley & the Indian diaspora shifting right?15:00 – The impact of Trump on India–US relations17:36 – Asha's role in opening doors for India globally21:09 – How the Motwani Foundation selects projects and people24:08 – Entrepreneurs as a critical part of US–India value creation24:54 – What's missing in US–India value creation?26:33 – Report on “jailed for doing business” in India27:56 – The legacy of Rajeev Motwani-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us a text

Nikola Mrkšić, Co-founder and CEO of PolyAI, joins Alex Theuma on the SaaS Revolution Show to reveal how voice AI agents are driving millions in revenue for its enterprise customers. Nikola shares his journey from competing in math olympiads to building a leading global AI company. They discuss the evolution of AI, its role in social mobility, the impact on customer service, effective enterprise sales and AI pricing strategies, and more. This episode covers: - Nikola's background and how it shaped his approach to AI. - Why AI has the potential to transform customer service even further. - Why building a successful company requires delighting customers and improving products. - The challenges and opportunities that come from rapid AI development. - Sales strategies that align with enterprise customers. - The challenges of outcome-based pricing and why it's powerful. - How AI voice agents can deliver significant ROI for businesses. - The future of PolyAI focuses on scaling impact and improving customer experience. - A look ahead to Nikola's upcoming keynote at SaaStock Europe. Guest links: LinkedIn: https://www.linkedin.com/in/nikola-mrksic/ Website: https://poly.ai/       Check out the other ways SaaStock is helping SaaS founders move their business forward: 

Matt McLarty, CTO at Boomi, joins the show to break down what enterprise AI adoption really looks like in 2025. From navigating the hype cycle to identifying practical first steps, Matt shares what separates companies that are seeing value from those stuck in endless pilots. If you're a tech leader wondering how to move beyond experimentation and into measurable outcomes, this episode is your playbook.Key Takeaways• AI adoption is not binary—it's a spectrum, and success depends on linking it to business value, not just “using AI.”• Orientation matters: every company needs an honest assessment of where they are on their digital maturity curve before jumping in.• Small, low-risk bets build the organizational muscle memory required for bigger wins.• The fastest wins often come from augmenting existing automation rather than chasing moonshots.• Companies that succeed treat AI as a tool to solve business problems, not as an end goal.Timestamped Highlights01:38 – Why AI's hype cycle feels like “Mount Everest” compared to cloud and mobile04:50 – Why AI adoption can't be compared to past waves like blockchain or cloud07:36 – The hidden foundation: digital transformation work still matters11:11 – The inversion that changes everything: AI isn't the goal, business outcomes are16:26 – Defining “adoption” as a multi-dimensional spectrum, not a checkbox19:50 – How to recover if your first AI projects fall short28:04 – Building adaptability as a core enterprise competency31:25 – The common traits of companies succeeding with AI right nowA standout moment“AI isn't the end goal—it's just another tool. The real question is, what business problems can we finally solve with it?” – Matt McLartyCall to actionIf this episode gave you a clearer path toward enterprise AI adoption, share it with a colleague and follow the show so you never miss a conversation on where tech leadership is heading.

This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support.   Joel Hron, Chief Technology Officer at Thomson Reuters, joins Eye on AI to unpack the future of agentic systems and what it takes to build them responsibly at enterprise scale. We dive into the shift from prompt-based AI to true agentic workflows capable of planning, reasoning, and executing complex tasks. Joel breaks down how Thomson Reuters is deploying generative AI across law, tax, risk, and compliance, while keeping human experts in the loop to ensure trust and accuracy in high-stakes domains. Topics include: - What separates agentic AI from simple prompt-based tools - How “agency dials” (autonomy, tools, memory) change system behavior - Infrastructure and architecture required for multi-agent collaboration - Why human verification and user experience design are essential for trust - The future of coding, engineering skills, and AI adoption inside enterprises If you want to understand how a 170-year-old company is reinventing itself with AI — and what's next for agentic systems in business and knowledge work — this conversation is a must-listen. Stay Updated: Craig Smith on X:https://x.com/craigssEye on A.I. on X: https://x.com/EyeOn_AI

Cybercrime is predicted to drain the world of $10.5 trillion annually by 2025, making it one of the greatest threats to modern business.Shikhil Sharma, co-founder & CEO of Astra Security, is building one of today's most trusted pentesting platforms. Just last year, Astra uncovered over 2 million vulnerabilities across customer systems, preventing more than $69 million in potential lossesShikhil shares why Astra was built as a product- and marketing-first company, how storytelling helped the brand connect with people by clearly showing its purpose and expertise and how founder–investor relationships are built on conviction and trust. He breaks down why pricing transparency is no longer optional for B2B companies and how trust is emerging as the true currency of go-to-market. We discuss what it takes to build a SaaS company in today's AI-first world, from raising leaner rounds and running with smaller teams to creating products that customers love from day zero. Beyond the playbooks, this is a conversation about building durable companies and the mindset that drives Shikhil as a founder: success isn't bought, it's rented, and the rent is due every day.0:00 — Trailer0:56 — Early college days that led to a startup5:00 — AI could cut startup costs and team size by 80%8:43 — Why seed rounds should be under $500K11:45 — Marketing can beat sales in early-stage SaaS16:07 — Is Google search under threat from consumer AI?20:23 — Why B2B startups must display pricing transparently25:41 — What VCs lend founders beyond capital?28:36 — How 42 CIOs backed Atomicwork30:58 — Replace GTM with COT- currency of trust33:34 — Why 20-year SaaS playbooks no longer works35:37 — How AI is changing cybersecurity41:38 — How the founders first met in college46:33 — Are “hard startups” actually easier to build?51:50 — Neon X Astra Security-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us a text

“Push something a millimetre in the private sector, you make an inch of progress. In the public sector, it's a mile of progress.”Subroto Bagchi started his career as a clerk in the Odisha government in 1976, leaving postgraduate studies. Today, eight years after serving at the rank of cabinet minister in the same government, he has certainly changed countless lives, not nameless faces. In this conversation, he passionately shares stories of young men and women from Odisha who overcame generational challenges by getting skilled, gaining not just jobs but identity.While this conversation could have focused on his remarkable journey building Mindtree in 1999 with 9 Co-founders and taking it to IPO, it goes beyond entrepreneurship. It's about stories from hinterland India, seen through the eyes of a founder who spent 16 years in the private sector before serving his home state. Subroto also reflects on India's big picture: instead of just chasing the trillion-dollar goal, we should also focus on improving quality of life for the 94% in the unorganized sector. This episode shares stories beyond metros, it highlights how building scalable solutions in business can translate into meaningful social impact. 0:00  – Trailer1:47 – 10-6-4-2 Method to evaluate ITIs6:15 – Muni Tigga: Locomotive Pilot story9:12 – Basanti Pradhan: Story of 50% of garment workers in Tiruppur from Orissa15:49 – Sumati Nayak: How skills give us identity19:16 – Joy of building Mindtree vs. joy of working in govt20:35 – The difficult stories of people moving away for Jobs23:32 – How Mr.Subroto accepted the Job?31:13 – The story behind “The Day the Chariot Moved”33:26 – How 8 years in hinterland India changed Mr. Subroto37:14 – India vs. Bharat42:04 – India's priorities beyond the $5 trillion economy43:43 – Quality of life for a gig worker in India vs. a developed country45:29 – Reality of 94% India that is unorganised47:50 – What India gives its vocationally trained students?49:09 – Stereotypes about govt, that maybe not true anymore52:03 – The highly efficient & incorrupt politicians54:00 – Where the government has succeeded in delivery?-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Find Mr.Subroto Bagchi's latest book here: The day the Chariot MovedSend us a text

"I think the biggest trap to potentially fall into is, "Hey, it's moving so fast, so much is changing. Let's just wait it out." Completely the wrong approach. You just gotta get started." Nick Eayrs from Databricks "As tech people within the shipping industry, how do we explain, how do we make it accessible to all our users? So that's where we came up with the idea of a data supermarket, with in mind really the target of enabling self-service for our business. So by giving the analogy of a supermarket, it was much easier at the beginning to explain our business." - Simon Fassot from Hafnia Fresh out of the studio, Nick Eayrs, Vice President of Field Engineering for Asia Pacific and Japan at Databricks, and Simon Fassot, General Manager and Head of Global Data and Analytics at Hafnia, join us to explore how data intelligence is transforming enterprise AI across diverse industries in Asia. Nick explained the fundamental distinction between general intelligence and data intelligence - emphasizing how enterprises gain competitive advantage by training AI on their proprietary data rather than public knowledge. Nick showcased customer success stories including Standard Chartered Bank and TechComBank and shared his perspectives on how senior executives can take advantage of AI by moving fast rather than wait and see. Last but not least, Nick offered what great would look like for Databricks in Asia Pacific and Japan in serving their customers. Adding the lens of the customer, Simon shared Hafnia's transformation from legacy SQL Server systems to a unified Databricks architecture serving their global shipping operations and elaborated on how the company is breaking down silos with their data supermarket and "Marvis" AI copilot for maritime operations based on retrieval augmented generation. This is Part 1 from Databricks Data + AI Event Singapore.  Episode Highlights: [00:00] QOTD by Nick Eayrs and Simon Fassot [00:49] Introduction: Nick Eayrs from Databricks [03:32] Customer obsession means deeply understanding their business context [05:22] Data intelligence versus artificial general intelligence explanation begins [06:42] AI trained on your data creates competitive advantage [08:17] Only 15% of companies have correct AI infrastructure ready [11:17] Don't wait for AI perfection, just get started now [12:30] Agent Bricks simplify AI development using natural language [13:49] Standard Chartered Bank cybersecurity use case with SIEM [16:22] TechCom Bank in Vietnam customer brain with 12,000 customer attributes [18:32] Shared responsibility model for ethical AI deployment [25:24] Asia Pacific psychology focuses on future, not past [26:28] Most important question: How do you get started? [30:18] What does great look like for Databricks? [33:16] Introduction: Simon Fassot from Hafnia [35:18] How Hafnia transformed to full cloud architecture centralizes data through Databricks [36:28] Self-service access needed for 300 onshore, 4000 vessel employees [37:00] Three user types: operations, business intelligence, domain experts and Use Cases for Hafnia [41:32] Unity catalog controls data quality for AI cases [42:21] Two-phase Gen AI: ingest unstructured, then consume data [44:25] How to implement Generative AI: One bad AI answer loses all user trust [45:31] How reports in Hafnia use RAG embedded in workflows [46:47] Data supermarket analogy simplifies self-service for business [48:39] Marvis AI personalizes Gen AI within company context [49:46] Neo4j partnership adds graph capabilities to ecosystem [53:33] DNA Port platform unifies scattered dashboards and applications [54:22] Databricks enables focus on business value over operations Profiles: Nick Eayrs, Vice President of Field Engineering, Asia Pacific & Japan at Databricks LinkedIn: https://www.linkedin.com/in/nick-eayrs/ Simon Fassot, General Manager and Head of Global Data and Analytics at Hafnia LinkedIn: https://www.linkedin.com/in/simon-fassot-68b95135/ Podcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format. Here are the links to watch or listen to our podcast. Analyse Asia Main Site: https://analyse.asia Analyse Asia Spotify: https://open.spotify.com/show/1kkRwzRZa4JCICr2vm0vGl Analyse Asia Apple Podcasts: https://podcasts.apple.com/us/podcast/analyse-asia-with-bernard-leong/id914868245 Analyse Asia LinkedIn: https://www.linkedin.com/company/analyse-asia/ Analyse Asia X (formerly known as Twitter): https://twitter.com/analyseasia Sign Up for Our This Week in Asia Newsletter: https://www.analyse.asia/#/portal/signup Subscribe Newsletter on LinkedIn https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=7149559878934540288

This episode features a deep dive into the current state of AI model progress with Ari Morcos (CEO of Datalogy AI and former DeepMind/Meta researcher) and Rob Toews (partner at Radical Ventures). The conversation tackles whether model progress is genuinely slowing down or simply shifting into new paradigms, exploring the role of reinforcement learning in scaling capabilities beyond traditional pre-training. They examine the talent wars reshaping AI labs, Google's resurgence with Gemini, the sustainability of massive valuations for companies like OpenAI and Anthropic, and the infrastructure ecosystem supporting this rapid evolution. The discussion weaves together technical insights on data quality, synthetic data generation, and RL environments with strategic perspectives on acquisitions, regulatory challenges, and the future intersection of AI with physical robotics and brain-computer interfaces. (0:00) Intro(2:59) Debate on Model Progress(8:03) Challenges in AI Generalization and RL Environments(15:44) Enterprise AI and Custom Models(20:27) Google's AI Ascent and Market Impact(24:30) Valuations and Future of AI Companies(27:55) Evaluating xAI's Position in the AI Landscape(30:31) The Talent War in AI Research(35:45) The Impact of Acquihires on Startups(42:35) The Future of AI Infrastructure(48:28) The Potential of Brain-Computer Interfaces(54:45) The Evolution of AI and Robotics(1:00:50) The Importance of Data in AI Research With your co-hosts: @jacobeffron - Partner at Redpoint, Former PM Flatiron Health @patrickachase - Partner at Redpoint, Former ML Engineer LinkedIn @ericabrescia - Former COO Github, Founder Bitnami (acq'd by VMWare) @jordan_segall - Partner at Redpoint

How do we get from today's AI copilots to true human-level intelligence? In this episode of Eye on AI, Craig Smith sits down with Eiso Kant, Co-Founder of Poolside, to explore why reinforcement learning + software development might be the fastest path to human-level AI. Eiso shares Poolside's mission to build AI that doesn't just autocomplete code — but learns like a real developer. You'll hear how Poolside uses reinforcement learning from code execution (RLCF), why software development is the perfect training ground for intelligence, and how agentic AI systems are about to transform the way we build and ship software. If you want to understand the future of AI, software engineering, and AGI, this conversation is packed with insights you won't want to miss. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) The Missing Ingredient for Human-Level AI(01:02) Eiso Kant's Journey(05:30) Using Software Development to Reach AGI(07:48) Why Coding Is the Perfect Training Ground for Intelligence(10:11)  Reinforcement Learning from Code Execution (RLCF) Explained(13:14) How Poolside Builds and Trains Its Foundation Models(17:35) The Rise of Agentic AI(21:08)  Making Software Creation Accessible to Everyone(26:03) Overcoming Model Limitations(32:08) Training Models to Think(37:24) Building the Future of AI Agents(42:11) Poolside's Full-Stack Approach to AI Deployment(46:28) Enterprise Partnerships, Security & Customization Behind the Firewall(50:48) Giving Enterprises Transparency to Drive Adoption  

Brian Mendenhall, Worldwide Head, Security & Identity Partner Specialists of Amazon Web Services, reveals the insider framework for transforming enterprise AI security, including the three-pillar approach and partnership strategies that leading companies use to navigate AI governance challenges.Topics Include:At AWS everything starts with security as core principleConsulting partners follow three-phase model: assess, remediate, then fully manage securityTraditional security framework covers threat detection, incident response, and data protectionAI compliance spans multiple governance bodies with stacking requirements and regulationsEU AI Act affects any company globally if Europeans access their applicationsThree pillars: security OF AI, AI FOR security, security FROM AI attacksAWS launches AI security competency program with specialized partner categories and certificationsEnterprise AI spans five risk levels from consumer apps to self-trained modelsLegal liability dramatically increases as you move toward custom AI implementationsSafety means preventing harm; security means preventing breaches - both critical distinctionsCurrent AI hallucination rates hit 65-75% across major platforms like PalantirShared responsibility model determines who's liable when AI security tools failIndustry evolution progresses from machine learning to generative AI to autonomous agentsMajor prototype-to-production gap caused by governance, security, and scalability challengesSuccessful AWS partnerships require clear use cases, differentiation, and targeted go-to-market strategyParticipants:Brian Mendenhall - WW Head, Security & Identity Partner Specialists, Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Description/ShownotesWhat if your company could launch its first AI agent in just two weeks? That's exactly what Mollie Bodensteiner, SVP of Operations at Engine, accomplished — and the results are game-changing: $2M in projected annual savings, a 67% lift in sales rep productivity, and CSAT scores above 90%. Mollie shares the real story of implementing AI at scale, why ruthless prioritization matters, how to avoid the “Frankenstack” trap, and why AI should be seen as a growth enabler, not a cost-cutting exercise. Whether you're leading a small team or scaling globally, Mollie's practical playbook will help you cut through the noise, drive adoption, and build AI solutions that stick. Tune in to hear how Engine's agile approach turned imagination into execution—and why trust, people, and culture are still the ultimate differentiators. Key Moments: 00:00 AI Philosophy & Common Challenges02:44 Ruthless Prioritization and AI Rollout08:04 Mollie Bodensteiner's Background and Engine's AI Journey14:40 AI Implementation and Customer Experience Impact28:07 AI Agents in Sales and Coaching34:48 AI in Professional Training and Education38:06 Human-AI Collaboration and Adoption Challenges48:34 Ensuring AI Quality and Risk Management51:45 Choosing and Evaluating AI Tools01:00:54 Underhyped AI Applications01:03:00 Lightning Round  –Are your teams facing growing demands? Join CX leaders transforming their AI strategy with Agentforce. Start achieving your ambitious goals. Visit salesforce.com/agentforce Mission.org is a media studio producing content alongside world-class clients. Learn more at mission.org Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

On Wednesday, Enterprise AI model-maker Cohere said it raised an additional $100 million in an extension to a round announced in August, bumping its valuation to $7 billion. The company said at the time that the  August round was an oversubscribed $500 million round at a $6.8 billion valuation. Also, Waymo's ever-expanding robotaxi aspirations have spread to the corporate world. The Alphabet-owned self-driving vehicle unit has launched “Waymo for Business,” a new service designed for companies to set up accounts so their employees can access robotaxis in cities like Los Angeles, Phoenix, and San Francisco. Learn more about your ad choices. Visit podcastchoices.com/adchoices

In this episode, Catherine Hammond, Research Director, and Adaora Okeleke, Principal Analyst, explore how operators can generate new revenue by offering AI services to enterprise customers. They draw on recent research to discuss the most promising AI solutions, opportunities for differentiation and how telecoms operators can compete with hyperscalers and other technology providers. Access the related report: Enterprise AI services: 13 operator case studies and analysis Read the associated articles: Operators' enterprise AI service portfolios extend far beyond AI infrastructure services Operators can generate substantial revenue from AI services even without big investments in infrastructure

Discover how enterprises can successfully adopt and scale agentic AI to create real business impact in this conversation with Florian Douetteau, CEO and co-founder of Dataiku. Florian shares why democratizing AI across the enterprise is essential, how to prevent agent sprawl, and what it takes to build a governance framework that keeps your data secure while enabling innovation. Learn about Dataiku's enterprise AI blueprint, its partnership with NVIDIA, and how global companies are using agentic workflows to accelerate R&D, optimize operations, and stay competitive. If you're a business leader, CTO, or data professional looking to scale AI safely and effectively, this episode is your playbook for the future of enterprise AI. Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI 00:00 Intro 00:31 Florian's Background & Dataiku's Founding   03:00 Enterprise Blueprint for AI with NVIDIA   05:13 Unique Needs of Financial Services   07:09 Building Agents on Dataiku   09:22 Permissioning & Governance   11:17 Agent Lifecycle Management   13:20 State of Agent-to-Agent Systems   15:02 Real-World Use Cases of Agents   16:28 The Most Complex Agents in Production   19:01 Future Vision: Headless Organizations   21:04 Human-Like Qualities of Agents   24:56 The LLM Mesh & Model Abstraction   28:55 Guardrails & Compliance   31:12 No-Code + Code-Friendly Collaboration   36:12 Breaking Silos & Centers of Excellence   41:36 Distribution & Seat Allocation   43:34 Most Common Agents by Industry   47:02 The State of Enterprise AI Adoption  

CIO Classified is back! More CIO secrets. More battle-tested IT wisdom. Straight from leading CIOs across a wide range of industries. In this episode, host Ian Faison and co-host Yousuf Khan dive into the deep end of technology leadership in manufacturing. Ben Davis, Executive Vice President of IT at Cambria, joins the show to talk about his sweeping digital transformation at the quartz manufacturing leader, and shares how his startup past helped him turn IT from a reactive function to a trusted business advisor. Plus much more:How Cambria is leveraging AI in demand forecastingHow to optimize supply chains and improve customer experience How to do it all while managing a legacy infrastructure and cybersecurityThis episode is a must-listen for the modern CIO looking to bridge the gap between traditional industries and modern technologies without sacrificing security or business continuity. About the Guest: Ben Davis, EVP  IT, Cambria, is a technical leader who is passionate about introducing new technology, improved processes and unexplored data sets to businesses in a manner that allows them to achieve scalable revenue growth. He does this by helping business-minded technologists use automation, prioritization and critical thinking to deliver technology, process improvement and data in a high-value, cost-effective way. Timestamps:02:30 – From startups to manufacturing: Applying entrepreneurial DNA07:00 – Communicating tech value across the organization09:30 – Why AI in manufacturing is a game-changer15:00 – Cybersecurity training, scorekeeping, and zero-trust realities17:30 – Modernizing legacy infrastructure in manufacturing23:00 – AI adoption vs. business architecture readiness26:00 – Staying close to the customer experience as CIO28:00 – Building, retaining, and empowering high-impact IT teams31:00 – Governance, shadow IT, and the rise of internal agents35:00 – AI tooling, data gaps, and minimizing technical debt38:00 – Manufacturing success, excitement, and the human side of techGuest Highlights:“ I think everybody under spends on cybersecurity. If I had an unlimited budget, I'd put the money towards that. I would also spend the money on data scientists, data modeling, data governance, mass data management to ensure that our data was ready to really take advantage of AI.”Get Connected:Ben Davis on LinkedInYousuf Kahn on LinkedInIan Faison on LinkedInHungry for more tech talk? Check out past episodes at ciopod.com: Ep 60 - Why the Smartest CIOs Are Becoming Business StrategistsEp 59 - CIO Leadership in AI Security and InnovationEp 58 - AI-Driven Workplace TransformationLearn more about Caspian Studios: caspianstudios.com Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Ashu Garg has backed companies like Databricks, Turing, Cohesity, Jasper, and Eightfold.ai as General Partner at Foundation Capital. Over the years, he's seen multiple waves of innovation but in his words, nothing in the last 45 years comes close to the transformation AI is bringing right now.Ashu discusses how the next wave of AI products will be driven by combining reasoning with reinforcement learning, and cautions every startup building on top of foundation models: that their vendors will also be their competitors.He also talks about how agents are moving from simple copilots to autonomous workers, how the internet itself will have to be reinvented for an agentic world, and what happens when your agent can not only draft emails but also buy plane tickets or make payments on your behalf.We also get into the realities of building AI companies today: why your competitor isn't GPT-5 but GPT-7, where startups can actually outcompete big tech, whether geography still matters, and how relationships and access still shape outcomes in an age that feels completely digital.This is one of the most insightful conversations you'll hear on what it takes to build durable AI companies in this era and where the next generation of billion-dollar startups will come from.0:00- Trailer0:42 – Foundation models as biggest competitor of AI startups4:19 – Agents are visible; reasoning is underneath6:20 – The leap of AI from autonomous to automation9:27 – Why the internet must be reinvented for AI10:49 – What if agents act (and do payments) on your behalf? 13:06 – Is Ashu using agents for himself?13:54 – No tech shift in 45 years compares to today15:38 – Who is accountable for what your agent does?17:57 – Who has advantage: first-time or repeat founders?19:27 – Does geography matter for founders anymore?21:19 – Whose AI will become the user's default?25:44 – Where do startups have an edge in AI?28:25 – How can startups outdo their model providers31:21 – Does distribution still matter in the Agentic era?33:29 – Why experience and access will always matter35:36 – Startups today must compete with GPT-7, not GPT-537:09 – Why Dollars on talent poaching in AI makes sense42:20 – Are only 1,000 people at AI's cutting edge?43:32 – What does Ashu garg look for in a founder?45:15 – How to build more billion-dollar companies?-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us a text

The Australian technology sector is running hot — the S&P/ASX All Technology Index has surged more than 35% over the past 12 months. In this episode of Talk Money To Me, Felicity Thomas sits down with Jules Cooper, Senior Research Analyst at Shaw and Partners, to unpack the latest reporting season and explore what's next for Aussie tech.We cover:

Send us a textIn this episode, Matt Brown sits down with Korina Skhinas, Partnerships and Events Marketing Director at Invisible, to explore the intersection of artificial intelligence, enterprise transformation, and the enduring value of human connection. Korina shares insights on why 95% of enterprise AI initiatives fail, how Invisible built the infrastructure powering 80% of the world's leading language models, and why humans in the loop remain critical for trust and scale. The conversation dives into enterprise adoption challenges, the role of events in building meaningful relationships, and practical lessons on integrating AI without losing the human touch.Support the show

What does it take to transform a brilliant AI model from a research paper into a product customers can rely on? We're joined by Elizabeth Lingg, Director of Applied Research at Contextual AI (the team behind RAG), to explore the immense challenge of bridging the gap between the lab and the real world. Drawing on her impressive career at Microsoft, Apple, and in the startup scene, Elizabeth details her journey from academic researcher to an industry leader shipping production AI. Elizabeth shares her expert approach to measuring AI impact, emphasizing the need to correlate "inner loop" metrics like accuracy with "outer loop" metrics like customer satisfaction and the crucial "vibe check." Learn why specialized, grounded AI is essential for the enterprise and how using multiple, diverse metrics is the key to avoiding model bias and sycophancy. She provides a framework for how research and engineering teams can collaborate effectively to turn innovative ideas into robust products. Check out:Register now: Closing the AI gap: Exceeding executive expectations for AI productivityFollow the hosts:Follow BenFollow AndrewFollow today's guest(s):Learn more about Contextual AI: Contextual.ai WebsiteFollow Contextual AI on Social Media: LinkedIn | X (formerly Twitter)Connect with Elizabeth: LinkedInReferenced in today's show:Throwing AI at Developers Won't Fix Their ProblemsWhy language models hallucinatei ran Claude in a loop for three months, and it created a genz programming language called cursedSupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

To get to the benefits that AI offers, organizations have to address their technology infrastructure in ways that are much broader than historical approaches. Senior analyst Greg Macatee joins host Eric Hanselman to delve into what's required and what enterprises are identifying in the recent Voice of the Enterprise AI and Machine Learning study. Enterprises are struggling with raising the success levels of AI projects. Over 60% report moderate to severe challenges in achieving AI success. Bringing together the computational power and the right quality data in the right locations can be complicated in the hybrid environments that more are operating. It's not just a matter of being more selective with use cases, AI requires a set of organizational skills that have to be honed. Starting small and iterating can reduce risk while building competency.  Infrastructure has to shift in new ways, as well. Data management processes that can build the necessary data pipelines to feed AI applications bring together a broader set of tech disciplines. There are new wrinkles in AI infrastructure ecosystems, with new providers looking to address supply chain constraints, like the Neocloud or GPU as a Service  (GPUaaS) providers. Even hyperscalers are looking to them to meet surging demand in a tight market. Those new options offer new choices, but enterprises need to match them with their AI goals. More S&P Global Content: Navigating the AI infrastructure landscape The path from LLMs to agentic AI Next in Tech | Ep. 225: Security for MCP For S&P Global Subscribers: AI infrastructure strategies evolve amid widespread data challenges – Highlights from VotE: AI & Machine Learning Generative AI Market Monitor & Forecast AI infrastructure: Trends, thoughts and a 2025 research agenda Credits: Host/Author: Eric Hanselman Guest: Greg Macatee Producer/Editor: Adam Kovalsky Published With Assistance From: Sophie Carr, Feranmi Adeoshun, Kyra Smith

The Information's Jing Yang talks with TITV Host Akash Pasricha about the latest developments in US-China trade negotiations in Spain, where TikTok and NVIDIA are now central to the talks. We also talk with reporters Cathy Perloff & Ann Gehan about Perplexity's cautious approach to advertising and e-commerce, and we get into AI valuations with Menlo Ventures' newest partner Deedy Das. Lastly, we talk with You.com's CEO Richard Socher about his company's pivot to AI enterprise search.Articles discussed on this episode: https://www.theinformation.com/articles/search-has-its-goliath-could-richard-socher-be-its-davidTITV airs on YouTube, X and LinkedIn at 10AM PT / 1PM ET. Or check us out wherever you get your podcasts.Subscribe to:- The Information on YouTube: https://www.youtube.com/@theinformation4080/?sub_confirmation=1- The Information: https://www.theinformation.com/subscribe_hSign up for the AI Agenda newsletter: https://www.theinformation.com/features/ai-agenda

Discover how Sema4.ai is redefining enterprise AI with a platform built to help businesses build, operate, and scale SAFE AI agents. In this conversation, CTO and co-founder Ram Venkatesh explains why simply generating insights isn't enough and why enterprises need AI that can act on those insights reliably, securely, and at scale. If you want to understand the future of agentic AI and how to safely scale AI across your organization, this episode is a must-watch. Stay Updated:Craig Smith on X: https://x.com/craigssEye on A.I. on X: https://x.com/EyeOn_AI (00:00) The Data-to-Action Gap (00:38) Ram's Big Data Background (03:22) Why RPA Failed & Agents Win   (04:39) Conversational Agents vs Manual Workflows   (06:28) The Power of a Semantic Layer   (08:20) Runbooks: Capturing Intent, Not Just Steps   (11:16) Connecting Data Across Systems   (15:12) How Sema4.ai Keeps AI Secure   (17:37) From 20 to 2,000 Agents: Scaling the Fleet   (20:20) Choosing the Right Agent Platform   (26:22) Process Architects: The New Role in AI   (29:00) Why Finance & Healthcare Lead in Adoption   (30:04) Sema4.ai's Pricing & Adoption Playbook   (41:29) Scaling Faster with Snowflake Deployment   (43:10) ISVs & Domain Experts as Agent Builders  

A full founder's arc: starting small, building global SaaS companies from Hyderabad, taking one to IPO, another to a billion-dollar exit, and then choosing to begin again (and again).Kiran Darisi began at Zoho, founding team member of Freshworks at 25, and stayed twelve years till the company went public. Today he is building Atomicwork, reinventing service management in the AI era. Sreedhar Peddineni started with Host Analytics back when SaaS was still called application service provider, went on to create the customer success category with Gainsight, and is now on his third venture with GTM Buddy.In this episode, we talk about what it takes to build companies that last for decades. We discuss how startups can find the “Goldilocks zone”,why smaller teams are creating more value than ever, and the mistakes founders often make when moving from SMB to enterprise.Both founders share how AI is reshaping every layer of SaaS, why it's both eating the pie and expanding it and what's left for entrepreneurs when the biggest AI companies are chasing every vertical.This conversation looks back at some of India's iconic SaaS companies, shares lessons from two decades of building, and looks ahead to the future of SaaS from India.0:00 — Atomicwork x GTM Buddy1:17 — Why They Chose to Be Founders Again8:27 — How to generate pipeline predictability at a startup?16:46 — Becoming Freshworks' Co-Founder at 2519:43 — How Atomicwork Co-Founders Connected & Chose Their Problem23:25 — Building Companies That Last for Decades27:18 — Why Smaller, High-Quality Teams Win30:21 — 1st vs 2nd Founders: What They Get Wrong31:56 — Scaling: SMB → Mid-Market → Enterprise33:36 — Category Creation at Gainsight40:03 — Disrupting vs Expanding Large Categories44:08 — How to Choose the Right Market49:08 — Why Atomicwork Chose This Category53:11 — The 'Goldilocks Zone' for a Startup Category57:11 — Can Salesforce Be Replaced?58:26 — Neon Fund x Atomicwork1:01:27 — Neon Fund x GTM Buddy1:03:44 — If Big AI Goes Everywhere, What's Left for B2B SaaS?1:07:36 — What to Build in the AI Era?1:10:35 — Is AI Expanding the Pie While Eating It?1:17:03 — How Useful Are Custom GPTs for Companies?1:20:34 — Workflows vs AI Workforce-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us a text

Discover how Glean AI is transforming enterprise productivity with AI-powered search and intelligent agents.About the episode:Join Nataraj as he explores the evolution of enterprise AI with Arvind Jain, CEO of Glean. From its roots as an AI-powered search solution, Glean has transformed into a comprehensive AI agent platform, helping companies like Zapier, Carta, and Grammarly boost productivity. Arvind shares his journey, the challenges of building a universal AI assistant, and his vision for the future of AI at work. Discover how Glean is helping enterprises leverage AI to streamline workflows and enhance employee efficiency. Learn how Glean ensures AI delivers value safely and securely.What you'll learnUnderstand the evolution of Glean from an AI-powered search tool to a comprehensive AI agent platform.Discover how Glean helps enterprises address productivity challenges by providing quick access to internal knowledge.Learn about the techniques Glean employs to reduce hallucinations and ensure accurate, reliable AI-driven insights.Explore the diverse use cases of AI agents in sales, customer service, engineering, and legal departments.Gain insights into Arvind Jain's vision for the future of work, where AI proactively assists employees in their daily tasks.About the Guest and Host:Arvind Jain: CEO of Glean, work AI platform, and co-founder of Rubrik.Connect with Guest:→ LinkedIn: https://www.linkedin.com/in/jain-arvind→ Website: glean.comNataraj: Host of the Startup Project podcast, Senior PM at Azure & Investor.→ LinkedIn: https://www.linkedin.com/in/natarajsindam/→ Substack: ⁠https://startupproject.substack.com/⁠In this episode, we cover(00:01) Introduction to Arvind Jain and Glean AI(01:13) What Glean does: AI-powered search and conversational AI assistant(03:43) The origin story of Glean: Solving productivity challenges in fast-growing companies(06:46) The evolution from search to an AI assistant(09:45) The advantages of tackling hard problems in startups(12:37) Techniques to reduce AI hallucinations and ensure accuracy(17:31) Model Hub: The different models Glean uses(20:16) Use cases for AI agent platforms across various departments(24:42) Workflow agents and the importance of integrations(31:59) The future of work: Proactive AI companions(37:14) Glean's cross-platform vision(39:07) How AI is changing the business of fast-growing startups(43:39) How Glean is becoming more AI-first internally(47:04) Ideas Arvind would explore if starting over with AI(49:49) Key metrics Arvind watches at Glean AIDon't forget to subscribe and leave us a review/comment on YouTube Apple Spotify or wherever you listen to podcasts.#GleanAI #EnterpriseAI #AISearch #AIAgents #FutureofWork #Productivity #ArtificialIntelligence #Innovation #SaaS #Startups #BusinessInsights #Technology #AIPlatform #WorkflowAutomation #MachineLearning #DeepLearning #AIStrategy #DigitalTransformation #AIinBusiness #TechPodcast

Jay Alammar is Director and Engineering Fellow at Cohere and co-author of the O'Reilly book “Hands-on Large Language Models.” Subscribe to the Gradient Flow Newsletter

Enterprise AI Agents for Work, Service and Process: www.kore.ai Kore.ai founder and CEO Raj Koneru breaks down how enterprises are moving beyond chatbots into agentic AI that actually ships. We get into the no-code tooling behind multi-agent workflows, agentic RAG, guardrails that keep outputs in scope, and why a control layer for governance is now essential. Raj shares real scale numbers, the three Kore.ai product lanes for customer and employee experience, and how partnerships with Microsoft and AWS let teams build where they already run. If you care about building secure, explainable AI agents that integrate fast and scale cleanly, this one is for you. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) Raj Koneru's Journey & The Birth of Kore.ai (03:10) From Chatbots to Enterprise-Grade Agents(06:33) Security, Scale & Proof in the Market(07:04) What Agentic AI Really Means(12:16) Building & Governing AI Agents(17:26) Kore.ai's Product Lines & Differentiation(20:22) Industry Applications & Case Studies(28:17) User Experience & Change Management(34:46) Governance, Identity & Cost Controls(39:56) Adoption Timelines & Market Outlook(43:51) Roadmap & Partnerships(47:38) Future of the Enterprise AI Landscape

Lindsey S. Mignano is the founder of SSM Legal, an entrepreneurial Silicon Valley corporate lawyer representing emerging technology companies and industry-adjacent firms and small businesses. Her practice spans technology company business formation and expansion into US markets, M&A (flips, entity or asset sales), commercial and technology transactions, and venture financing. Lindsey has been recognized as a “Rising Star” by Super Lawyers every year from 2016-2024, an honor awarded to only 2.5% of attorneys under the age of 40. In 2025, she was awarded the Super Lawyers distinction for the first time at the age of 40, an honor awarded to only 5% of attorneys. Separate from her law practice, Lindsey speaks often about diversity issues in the fields of law, tech, and venture. In 2023, Lindsey founded Venture Betches, a venture fund of funds, and Syndicate Betches, a real estate syndicate fund of funds, both with a social justice mission to bring investment opportunities to historically underrepresented accredited limited partners who identify as female and/or BIPOC/minorities.

On Mission Matters, Adam Torres interviews Smriti Kirubanandan, a technology executive, during the Milken Global Conference. Smriti shares her journey from robotics and public health to enterprise AI, the barriers companies face in scaling, and why responsible governance and cultural readiness are crucial. She highlights how AI can simplify healthcare, improve outcomes, and create sustainable impact when scaled responsibly. This interview is part of our Global Milken Conference series. Big thank you to Milken Institute! Follow Adam on Instagram at https://www.instagram.com/askadamtorres/ for up to date information on book releases and tour schedule. Apply to be a guest on our podcast: https://missionmatters.lpages.co/podcastguest/ Visit our website: https://missionmatters.com/ More FREE content from Mission Matters here: https://linktr.ee/missionmattersmedia Learn more about your ad choices. Visit podcastchoices.com/adchoices

On Mission Matters, ⁠Adam Torres⁠ interviews ⁠Smriti Kirubanandan⁠, a technology executive, during the Milken Global Conference. Smriti shares her journey from robotics and public health to enterprise AI, the barriers companies face in scaling, and why responsible governance and cultural readiness are crucial. She highlights how AI can simplify healthcare, improve outcomes, and create sustainable impact when scaled responsibly. This interview is part of our Global Milken Conference series. Big thank you to Milken Institute! Follow Adam on Instagram at ⁠https://www.instagram.com/askadamtorres/⁠ for up to date information on book releases and tour schedule. Apply to be a guest on our podcast: ⁠https://missionmatters.lpages.co/podcastguest/⁠ Visit our website: ⁠https://missionmatters.com/⁠ More FREE content from Mission Matters here: ⁠https://linktr.ee/missionmattersmedia⁠ Learn more about your ad choices. Visit podcastchoices.com/adchoices

A 14-year journey from bootstrap to scale.Exotel's story is one of India's most remarkable SaaS journeys. Shivakumar Ganesan, started Exotel in 2011, bootstrapping it from the ground up. In 2012, he raised a seed round of ₹2.5 crore, but for the next eight years, the company grew without any external funding. Then came COVID and revenue went from $10M to $5M and what followed were bold strategic moves.3 funding rounds, 2 major acquisitions, and the decision to stay focused on the Indian market despite advice to go global first. Today, Exotel powers calls for delivery executives, cab drivers, and banking relationship managers across the country.In this conversation, Shivku shares what it's like to tackle India's unique AI challenge of building voicebots in 30+ languages, and how automation could reduce contact center jobs by as much as 80%. He talks about the tough transition from serving SMBs to enterprise customers and how he has built a ₹2500 crore+ business without leaving India.If you're interested in B2B companies built from India, this episode is full of insights on timing, reading the market, and creating deep moats in overlooked opportunities.0:00 – Trailer0:42 – Exotel enabling 2 Billion Calls Monthly5:04 – 4 Fundraises & 2 M&A's in 18 Months12:06 – How Acquisitions Affect Company Finances18:11 – Why 90% of M&As Fail22:02 – Why Acquisitions Are Extremely Hard22:59 – How AI Will Change Customer Relations26:46 – How Customer Spending Will Shift with AI29:10 – AI Could Reduce 80% of Jobs30:27 – Where AI Offers Hope31:47 – India's Unique AI Challenges34:60 → Actually 35:00 – Building in India for the US Market38:17 – Why Exotel Didn't Enter the US Market39:49 – Indian SaaS Co's Should Go Public42:50 – The Mega Cycles of Tech Transformation45:37 – Customer Segments: SMBs to Startups to Enterprise56:45 – Find Large Uniquely Indian Markets to Solve59:44 – India's Shift from Price to Quality Is 20 Years Away-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us a text

In this episode, Anant Bhardwaj, CEO of Instabase, provides a pragmatic guide for AI practitioners building enterprise solutions. Subscribe to the Gradient Flow Newsletter

Maisa AI is built on the premise that enterprise automation requires accountable AI agents, not opaque black boxes. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Here's the thing. Most enterprise AI talk today starts with chatbots and ends with glossy demos. Meanwhile, the data that actually runs a business lives in rows, columns, and time stamps. That gap is where my conversation with Vanja Josifovski, CEO of Kuma.ai, really comes alive. Vanja has spent two and a half decades helping companies turn data into decisions, from research roles at Yahoo and Google to steering product and engineering at Pinterest through its IPO and later leading Airbnb Homes. He's now building Kuma.ai to answer an old question with a new approach: how do you get accurate, production-grade predictions from relational data without spending months crafting a bespoke model for each use case? Vanja explains why structured business data has been underserved for years. Images and text behave nicely compared to the messy reality of multiple tables, mixed data types, and event histories. Traditional teams anticipate a prediction need, then kick off a long feature engineering and modeling process. Kuma's Relational Foundation Model, or RFM, flips that script. Pre-trained on a large mix of public and synthetic data warehouses, it delivers task-agnostic, zero-shot predictions for problems like churn and fraud. That means you can ask the model questions directly of your data and get useful answers fast, then fine-tune for another 15 to 20 percent uplift when you're ready to squeeze more from your full dataset. What stood out for me is how Kuma removes the grind of manual feature creation. Vanja draws a clear parallel to computer vision's shift years ago, when teams stopped handcrafting edge detectors and started learning from raw pixels. By learning directly from raw tables, Kuma taps the entirety of the data rather than a bundle of human-crafted summaries. The payoff shows up in the numbers customers care about, with double-digit improvements against mature, well-defended baselines and the kind of time savings that change roadmaps. One customer built sixty models in two weeks, a job that would typically span a year or more. We also explore how this fits with the LLM moment. Vanja doesn't position RFM as a replacement for language models. He frames it as a complement that fills an accuracy gap on tabular data where LLMs often drift. Think of RFM as part of an agentic toolbox: when an agent needs a reliable prediction from enterprise data, it can call Kuma instead of generating code, training a fresh model, or bluffing an answer. That design extends to the realities of production as well. Kuma's fine-tuning and serving stack is built for high-QPS environments, the kind you see in recommendations and ad tech, where cost and latency matter. The training story is another thread you'll hear in this episode. The team began with public datasets, then leaned into synthetic data to cover scenarios that are hard to source in the wild. Synthetic generation gives them better control over distribution shifts and edge cases, which speeds iteration and makes the foundation model more broadly capable upon arrival. If you care about measurable outcomes, this episode shows why CFOs pay attention when RFM lands. Vanja shares examples where a 20 to 30 percent lift translates into hundreds of thousands of additional monthly active users and direct revenue impact. That kind of improvement isn't theory. It's the difference between a model that nudges a metric and a model that moves it. By the end, you'll have a clear picture of what Kuma.ai is building, why relational data warrants its own foundation model, and how enterprises can move from wishful thinking to practical wins. Curious to try it yourself? Vanja also points to a sandbox where teams can load data and ask predictive questions within a notebook, then compare results against in-house models. If your AI plans keep stalling on tabular reality, this conversation offers a way forward that's fast, accurate, and designed for the systems you already run.

The software that powers 25% of India's e-commerce transactions, processes a billion orders each year, and in 2025 alone fulfilled 20 million quick-commerce orders: Unicommerce sits at the core of India's digital retail ecosystem. It is one of the few SaaS companies from India to go public, doing so after nearly a decade of steady growth without fresh primary capital until its IPO in 2024.In this episode of The Neon Show, we sit down with Kapil Makhija, CEO of Unicommerce, the company quietly running India's $60B E-retail market (set to hit $2 Trillion in the next two decades). The conversation goes beyond the company's journey to unpack how perceptions of Indian SaaS customers are changing: from the old belief that they “don't pay” to a more nuanced reality where they value communication, support expectations, and long-term relationships define success.We also look ahead to the future of SaaS in India: from the impact of AI, to the challenges of scaling from zero to $100M, to the balance between pricing and value, and identifying the sectors most ready for building large SaaS companies.This episode is for anyone curious about the story of SaaS in India, from how it is being built, scaled & the opportunities ahead.00:00 – Trailer01:15 – India makes you product-ready & pressure-tested03:45 – GTM: India doesn't reward size, it rewards focus05:00 – Joining Unicommerce the week Snapdeal acquired it10:10 – Digital-first brands vs. traditional brands12:36 – Why Excel and manual ops were the real competition?14:25 – The acquisition of Shipway17:02 – How will the company achieve 1000 Cr Revenue?19:40 – How the decision to go public was made23:40 – Success in SaaS isn't sign-ups, it's retention29:31 – The myth that Indian customers don't pay33:30 – Do Indian customers want Enterprise support but SMB pricing?36:40 – The impact of AI on SaaS39:10 – Founder vs. CEO: Is there a difference?47:29 – White spaces in e-commerce waiting to be built50:35 – Q-commerce vs. E-commerce: where are brands betting?52:07 – How SaaS companies decide if they're IPO-ready?55:10 – Can India build billion-dollar SaaS companies at home?58:15 – How long does the 0 → $100M journey really take?01:01:15 – How to build a ₹100 Cr SaaS company today?01:09:53 – Are pricing advantages in SaaS sustainable?01:12:22 – How much do brands actually spend on tech?-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us a text

In this episode of Campus Technology Insider Podcast Shorts, hosted by Rhea Kelly, we explore the latest in higher education technology. Highlights include Tripti Sinha taking over as president and CEO of Internet2, a report from Anthropic on how faculty utilize generative AI, and an MIT Media Lab report revealing the shortcomings of enterprise AI investments. For more in-depth stories and analysis on higher ed tech, visit campustechnology.com. 00:00 Introduction to Campus Technology Insider 00:15 New Leadership at Internet2 00:55 Generative AI in Academia 01:34 Enterprise AI Reality Check 02:05 Conclusion and Further Resources Source links: Internet2 Announces a New President and CEO to Step Up in October Top 3 Faculty Uses of Gen AI MIT Report: Most Organizations See No Business Return on Gen AI Investments   Campus Technology Insider Podcast Shorts are curated by humans and narrated by AI.

Enterprise AI is still in its infancy, with less than 1% of enterprise data currently used to fuel AI, according to Raj Verma, CEO of SingleStore. While consumer AI is slightly more advanced, most organizations are only beginning to understand the scale of infrastructure needed for true AI adoption. Verma predicts AI will evolve in three phases: first, the easy tasks will be automated; next, complex tasks will become easier; and finally, the seemingly impossible will become achievable—likely within three years. However, to reach that point, enterprises must align their data strategies with their AI ambitions. Many have rushed into AI fearing obsolescence, but without preparing their data infrastructure, they're at risk of failure. Current legacy systems are not designed for the massive concurrency demands of agentic AI, potentially leading to underperformance. Verma emphasizes the need to move beyond siloed or "swim lane" databases toward unified, high-performance data platforms tailored for the scale and complexity of the AI era.Learn more from The New Stack about the latest evolution in AI infrastructure: How To Use AI To Design Intelligent, Adaptable InfrastructureHow to Support Developers in Building AI Workloads Join our community of newsletter subscribers to stay on top of the news and at the top of your game. 

Drawing upon insights from the ebook, “Critical Success Factors of Enterprise AI ”, we'll explore key strategies for prioritizing AI use cases, demonstrating business value, optimizing resources, ensuring data quality, and driving AI adoption. The discussion will provide actionable takeaways for business leaders looking to navigate the complexities of AI implementation and maximize its transformative potential. The ebook is available at: https://forms.workday.com/en-us/ebooks/critical-success-factors-to-enterprise-ai-adoption/form.html?refCamp=7014X000002XN5WQAW&step=step1_default

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support. In this episode of Eye on AI, we sit down with Leon Song, VP of Research at Together AI, to explore how open-source models and cutting-edge infrastructure are reshaping the AI landscape.    From speculative decoding to FlashAttention and RedPajama, Leon shares how Together AI is building one of the fastest, most cost-efficient AI clouds—helping enterprises fine-tune, deploy, and scale open-source models at the level of GPT-4 and beyond.   We dive into Leon's journey from leading DeepSpeed and AI for Science at Microsoft to driving system-level innovation at Together AI. Topics include: The future of open-source vs. closed-source AI models Breakthroughs in speculative decoding for faster inference How Together AI's cloud platform empowers enterprises with data sovereignty and model ownership Why open-source models like DeepSeek R1 and Llama 4 are now rivaling proprietary systems The role of GPUs vs. ASIC accelerators in scaling AI infrastructure   Whether you're an AI researcher, enterprise leader, or curious about where generative AI is heading, this conversation reveals the technology and strategy behind one of the most important players in the open-source AI movement. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI

This week's World of DaaS LM Brief looks at new research from MIT, which finds that 95% of generative AI pilot programs inside companies are failing to deliver meaningful financial impact.The issue is not model quality but enterprise integration and a steep organizational learning gap. The report shows ROI is strongest in back-office automation even as most budgets flow to sales and marketing, and that success comes from buying specialized solutions and forming strategic partnerships rather than building in-house.Listen to this short podcast summary, powered by NotebookLM.

The 21st century has shattered old assumptions about diplomacy.Relationships between nations are no longer guided by ideology or morality, but driven by pragmatism and national interest.This week, former diplomat Rajiv Sikri who served 36 years in the Indian Foreign Service, offers a deep dive into how global power dynamics are shifting. We discuss why the United States still remains the only true great power, yet its tariff policies are reshaping global trade and forcing countries like India to rethink their strategies. And explores how the Russia–Ukraine conflict has reshaped security and political choices. For India, Russia remains a vital partner, while Europe has chosen to cut ties despite its heavy dependence on Russian energy and Britain continues to commit billions to Ukraine even with its own economy struggling. Rajiv also examines China's growing alignment with Pakistan and what this means for India's long-term security and economic positioning. Rajiv also argues that a future global conflict may not involve every country, but rather regional conflicts with worldwide consequences.This episode provides a clear-eyed analysis of global diplomacy; its complexities, evolving alignments, and the choices India faces in navigating an increasingly multipolar world.0:00 – Why US remains the world's true great power3:35 – Has the WTO collapsed?5:23 – How US Tariffs have destabilised the world7:12 – Can India become an Agri-exporter?11:32 – Why Trump puts the MAGA base first13:21 – The Russia-Ukraine war explained22:24 – Diplomatic relationships are no longer based on ideology25:22 – Why Europe cutting ties with Russia may backfire27:52 – Why Britain funds Ukraine despite its weak economy29:57 – Did Operation Sindhoor reveal open Chinese support to Pakistan?33:32 – What China risks from India's rise?37:24 – Why morality doesn't exist in global politics38:30 – Will China's attitude towards India change?39:28 – How China dominates global manufacturing44:40 – Why global investors should bet on India49:20 – Israel's War Acts53:17 – How will WW3 actually be?56:07 – Can the world create an organisation not dominated by the West?59:29 – Why India must act cold-blooded in its national interest1:01:13 – Are India's global moves headed in the right direction?1:03:43 – Lessons from 36 years as a diplomat-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us a text

AI projects often fail not due to technology, but because organisations struggle with change. In this episode, we explore practical strategies for enterprise leaders to drive successful AI adoption through structured change management. Using the SHIFT framework, we cover aligning strategy with purpose, managing human emotions, integrating robust frameworks, fostering psychological safety, and turning resistance into momentum. Designed for managers, consultants, and transformation leaders, this episode provides actionable insights to accelerate adoption, build trust, and deliver measurable business impact. 

NLW recently collaborated with KPMG on a 7-part enterprise AI-focused series called You can with AI. On this Saturday bonus preview, we share episode 7 of the series, all about the trends shaping the AI-ready organization of the future. Featuring Steve Chase, KMPG Global Head of AI and Digital Innovation.Learn more about the series: https://www.kpmg.us/aipodcasts

OpenAI's rollout of GPT-5 came with some bumps for users, but we dig into how the new model could be boosting the company's enterprise business. 

Shay Levi (@shaylevi2, CEO @UnframeAI) & Larissa Schneider (COO @UnframeAI) discuss the complexities of building an enterprise-grade AI platform. Topics include what an AI platform is, the advantages of adoption, and the efficiencies gained.SHOW: 948SHOW TRANSCRIPT: The Cloudcast #948 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK:  http://bit.ly/cloudcast-cnotwNEW TO CLOUD? CHECK OUT OUR OTHER PODCAST:  "CLOUDCAST BASICS"SPONSORS:[VASION] Vasion Print eliminates the need for print servers by enabling secure, cloud-based printing from any device, anywhere. Get a custom demo to see the difference for yourself.[DoIT] Visit doit.com (that's d-o-i-t.com) to unlock intent-aware FinOps at scale with DoiT Cloud Intelligence.SHOW NOTES:Unframe websiteTopic 1 - Shay & Larissa, welcome to the show!  Give everyone a brief introduction and a little about your background. Topic 2 - Today, we're discussing AI Security and Enterprise Platforms. What are the problems or issues you see with AI development today?Topic 3 - Is this where an AI platform comes into play? I'm seeing more and more about this term and wondering what it truly means to be a platform. What is your definition of a platform, and what are the advantages?Topic 4 - Shay, considering your background in APIs and API security, how does that knowledge transfer into this space?Topic 5 - Larissa, with your background in operations, where do you see the inefficiencies in AI development and lifecycle management of the AI models and the datasets?Topic 6 - Let's talk about Unframe. Give everyone an overview. Is this a SaaS service? How and where does it fit into your typical AI development stack?FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

In this episode from Cisco Live, Maribel Lopez sits down with two Cisco executives, Vijoy Pandey, SVP of Outshift at Cisco and Nathan Jokel, SVP of Corporate Strategy and Alliances at Cisco, to discuss how AI is fundamentally changing enterprise infrastructure over the next year. The conversation explores the evolution from deterministic to probabilistic computing, the emergence of agentic workflows, and practical advice for business leaders navigating the AI transformation.Host: Maribel LopezGuests:Vijoy Pandey, SVP of Outshift at CiscoNathan Jokel, SVP of Corporate Strategy and Alliances at CiscoRecorded at: Cisco LiveEpisode OverviewIn this episode from Cisco Live, Maribel Lopez sits down with two Cisco executives to discuss how AI is fundamentally changing enterprise infrastructure over the next year. The conversation explores the evolution from deterministic to probabilistic computing, the emergence of agentic workflows, and practical advice for business leaders navigating the AI transformation.Key Topics DiscussedThe Three Waves of AI Infrastructure EvolutionWave 1: AI training in public cloud (mostly behind us)Wave 2: AI inference moving to enterprise data centers for control, security, and economic reasonsWave 3: AI moving to the edge with physical and embodied AI requiring new infrastructure for robots and devicesFrom Deterministic to Probabilistic ComputingVijoy explains the fundamental shift happening in computing:Traditional computing: deterministic, machine-speed but limitedHuman intelligence: agentic but slowNew paradigm: AI agents with human-like behavior operating at machine speed and scaleThe Internet of AgentsA collaboration platform where AI agents from different vendors can:Get discovered and authenticatedCompose workflows togetherExecute tasks collaborativelyBe evaluated for performanceReal-world example: Building a sales funnel portal using agentic interfaces from Salesforce, ServiceNow, Microsoft, and Cisco security - all working together without manual UI clicking.AI and Energy ChallengesThe Problem: By 2028, projected 63 gigawatt shortfall for new data center capacitySolutions:Invest in diverse energy sources (nuclear, renewables, battery storage)Build data centers near power sources (e.g., Cisco's Middle East partnerships)Develop more energy-efficient infrastructureFocus on smaller, specialized models instead of racing for maximum parametersCisco's Specialized AI ModelsFoundation SAC 8B: 8 billion parameter model specialized for security policyDeep Network Model: Expert model trained on network configurationsOutshift: Cisco's Innovation EngineCisco's internal incubator tackling problems adjacent to core business in:Space: Areas adjacent to networking, security, observability, collaborationTime/Risk: Higher-risk ventures that can't enter at Cisco scale initiallyCurrent Big Hairy Audacious Goals (BHAGs):Internet of AgentsQuantum Internet - building quantum networks for distributed quantum computing

Is AI finally ready for the enterprise? In this AI Infra Summit 2025 interview, Luke Norris, CEO of Kamawaza, reveals how Fortune 500 and Global 2000 companies are moving beyond AI experiments to real-world, production-level deployments—saving millions and reshaping industries.Luke shares insights from Kamawaza's groundbreaking work with over 20 Fortune 500 clients, including a live demo with the Department of Homeland Security and massive cost savings for major enterprises. Learn why consulting firms are feeling the heat, how the AI partner ecosystem is evolving, and what's next for enterprise AI—including game-changing breakthroughs in open-source models like Quen 3.0 and the rise of Model Context Protocol (MCP).