Inside AsembleAI: DeepTech, AI & Science

Mac & Sam

AsembleAI brings you thought-provoking conversations at the nexus of artificial intelligence, innovation, and leadership. In each episode, hosts Mac and Sam, veterans in data and tech world, sit down with AI researchers, fast‑scaling founders, Fortune 500 executives, and pioneering technologists to reveal how AI is reshaping business strategy, sparking breakthrough product development, and guiding executive decisions. Tune in for actionable insights, compelling case studies, and forward‑looking perspectives on the promises and pitfalls of AI‑driven innovation.RSSVERIFY

  1. 13 h fa

    EP 62: 95% of AI Pilots Fail. Here's Why | Mohamed Battisha, VP of Engineering at WEX

    What actually separates a data platform built for AI agents from the data warehouse most enterprises already have?  Recorded live at Ai4 conference in Vegas, AsembleAI co-host Sam sits down with Mohammed Battisha - who leads the data engineering team at WEX and previously built Saudi Arabia's national AI platform as CTO of SDAIA (Saudi Data and AI Authority), with earlier leadership roles at LinkedIn, Salesforce, and Microsoft - to find out answer to the question.  Topics covered: The shift from "collect, transform, report" data platforms to context-aware, agent-ready platformsWhy the semantic layer is the core of any AI-native architectureGoverned execution: giving AI agents boundaries and full auditabilityLessons from building a sovereign nation's AI platform at SDAIAWhy MIT's research shows 95% of enterprise AI pilots fail — and what disconnects business and technologyWEX's crawl-walk-run framework for AI adoptionClaim AI: how WEX automated a multi-day claims process down to minutesHow WEX measures AI maturity and data maturity across seven dimensionsAdvice for data and AI engineers: why business awareness matters more than technical depth aloneConnect with Mohammed : LinkedIn: https://www.linkedin.com/in/mohamedbattisha/ WEX: https://www.linkedin.com/company/wexinc/

    EP 62: 95% of AI Pilots Fail. Here's Why | Mohamed Battisha, VP of Engineering at WEX

  2. 20 h fa

    EP 61: "Shadow AI" — And No One's Watching | Rafi Khardalian, Actualyze AI

    This episode was recorded live from the Ai4 conference podcast pavilion, where host Mac Goswami sat down with Rafi Khardalian — CEO & co-founder of Actualyze AI, and a former technology leader at Cisco who helped build its container and Kubernetes platforms — about the governance, security, and orchestration layer most enterprises are missing. What's Covered: The Foundation for Enterprise AI — Rafi lays out why a patchwork of point solutions doesn't cut it, and how Actualyze unifies governance and security across every model and provider — at the inference level. The "Shadow AI" Problem — Employees signing up for AI tools on their own, with no governance, no visibility, no controls. Why fragmentation is a company-wide risk, not a per-team one. One Endpoint to Govern Them All — By becoming the sole endpoint for all inference, Actualyze can mask PII, catch secrets and passwords, apply guardrails, and allow or block MCP tool calls — enforcing policy in one place instead of trusting each provider. Why AI ROI Keeps Failing — Rafi's take: the hardest transformation isn't technical, it's cultural. Over-ambitious projects, unbudgeted bills, weak controls — and the trap of building a proprietary LLM you can't scale. Reliable vs. Impressive — What decades of Kubernetes, OpenStack, and large-scale distributed systems taught him about production reliability over demo magic. The Next Five Years — Why the over-rotation on frontier models will give way to small, open-weight, and purpose-built models — and why the real bottleneck is organizational readiness, not technology. Key Quote: "It really comes down to organizational readiness rather than technology readiness. A lot is ready today." Connect with Rafi: LinkedIn: https://www.linkedin.com/in/rkhardalian/ Actualyze AI: https://actualyze.ai/ Follow and subscribe to AsembleAI: Spotify | Apple Podcasts | Amazon Music | iHeart Radio | YouTube | Substack

    EP 61: "Shadow AI" — And No One's Watching | Rafi Khardalian, Actualyze AI

  3. 1 g fa

    EP 60: Feeding the World with AI: Inside Syngenta's Data Playbook

    Agriculture is the oldest industry in the world — and one of the least represented at AI conferences. In this episode, Sam talks with Jeremy Groeteke, CIO of Syngenta's vegetable division, about how a company operating in 90+ countries with 50,000 employees is building AI infrastructure to help feed the world. Topics covered: Syngenta's approach to merging AI, data science, and physical science in agricultureUsing computer vision for early disease and pest detection in cropsWhy general-purpose LLMs like ChatGPT and Claude give farmers overly generic recommendations — and why domain fine-tuning mattersThe shift from data lakes to data mesh at SyngentaSingle-agent vs. multi-agent AI architectures — and why accuracy often favors single agents right nowThe "metadata problem": why having data isn't enough without context about how it was collectedCropwise AI — Syngenta's tool for turning insight into actionable recommendationsWhy agriculture's long biological cycles make it a poor fit for typical VC/tech timelinesAdvice for technologists looking to break into agtechGuest Bio: Jeremy Groeteke is CIO for Syngenta's vegetable division, overseeing digital strategy for an organization that provides crop protection, biologicals, digital tools, and genetics to growers in over 90 countries. Connect: Find Jeremy on LinkedIn to learn more about Syngenta's work in AI and agriculture.

    EP 60: Feeding the World with AI: Inside Syngenta's Data Playbook

  4. 1 g fa

    EP 59: "The Attackers Have the Advantage" — AI's SATAN Moment in Cybersecurity | Fred Rica, BDO

    This episode was recorded live from the Ai4 conference podcast pavilion, where host Mac Goswami sat down with Fred Rica — cybersecurity leader at BDO USA, former Big Four partner, and a regular voice at RSA and Black Hat — about why AI is cybersecurity's "SATAN moment" and what defenders have to change to survive it. What's Covered: "The Attackers Have the Advantage" — Fred's blunt read on where defenders stand today: back on their heels, facing external attacks and blind spots in their own internal agents at the same time. AI's SATAN Moment — The 1995 parallel. When SATAN — the first real automated scanner — arrived, defenders thought it was the end of the internet. It wasn't, but it changed everything. Fred explains why AI (and Mythos) feels the same, and why the era of large patch windows is over. The Patch Window Is Zero — Why vulnerability management is breaking down and giving way to exposure management and attack-path thinking. Fred's "why is the number going up?" story — printers, missing context, and the CFO on the nightly call — is a masterclass in what's broken. If You're a CISO Today — Fred's three priorities: patch at machine speed ("automated but not automatic," with a human in the loop on critical systems), rewrite the zero-day playbook, and train teams under real pressure. AI Governance Done Right — Anchor to a framework (NIST, ISO, EU AI Act), keep a "big red button," and demand AI cards from every vendor using AI in your ecosystem — the new version of the SOC report. AI Slop & the Agent Problem — On the "10 billion agents" hype, why visibility and a control plane are job one, and where agentic AI genuinely earns its place: continuous monitoring, testing, and SOC tier 1/2 that "don't stand a chance unless they're AI-enabled." Key Quote: "I truly believe that AI is gonna fix AI. I'm a strong believer in the power of AI to transform humanity. However, we have a little bit of work to do at the moment." Connect with Fred: LinkedIn: https://www.linkedin.com/in/fredrica/ BDO: https://www.bdo.com/ Follow and subscribe to AsembleAI: Spotify | Apple Podcasts | Amazon Music | iHeart Radio | YouTube | Substack

    EP 59: "The Attackers Have the Advantage" — AI's SATAN Moment in Cybersecurity | Fred Rica, BDO

  5. 23 ago

    EP 58: Every Millisecond Matters: Diffusion LLMs and the Future of Voice AI | Aditya Grover, Inception

    Recorded live at the Ai4 Podcast Pavilion, Sam wraps Day One with Aditya Grover, Co-Founder & CTO of Inception, on why the next generation of LLMs won't look anything like the ones we use today. What's Covered: "Every Millisecond Matters" — Why latency, not intelligence, is the real bottleneck holding back voice agents and multi-step AI agents alike. How Mercury Actually Generates Text — Instead of predicting one token at a time like every autoregressive model, Mercury generates a rough draft of the full response and refines it into coherence — diffusion, applied to language instead of images. Solving Voice AI's Impossible Tradeoff — Fast-but-lower-quality, or high-quality-but-too-slow: Aditya explains how Mercury 2 finally delivers both. A Term Coined Live at This Conference — From Aditya's own Ai4 keynote: "We're moving from token maxing to value maxing." Advice for the Next Generation — Ten-plus years into AI research, Aditya's honest take on why this is still the best time to pursue a PhD, join a startup, or do both. The Next 5-10 Years of Voice AI — A prediction for a future where voice becomes humans' predominant mode of interacting with AI, the same way it is with each other. Key Quote: "Sequential generation is not a law of nature... AI can have a different way of generation, one that's more parallelizable." Connect with Aditya: LinkedIn: https://www.linkedin.com/in/aditya-grover/ Inception: https://www.inceptionlabs.ai/ Subscribe: Spotify | Apple Podcasts | Amazon Music | iHeart Radio | YouTube | Substack #Ai4Conference #InceptionLabs #DiffusionLLM #VoiceAI #AsembleAI

    EP 58: Every Millisecond Matters: Diffusion LLMs and the Future of Voice AI | Aditya Grover, Inception

  6. 23 ago

    EP 57: Ai4 Podcast - Why "The Context Layer" Is What Enterprise AI Is Actually Missing | Andrei Manolache, Designverse

    Recorded live at Ai4, Mac sits down with Andrei Manolache, Founder & CEO of Designverse, an AI platform that builds and delivers complex enterprise software by ingesting a company's own documentation, codebase, and internal rules. What You'll Learn: 🔹 The Model Plateau Everyone's Noticing — Andrei's central argument: the industry banked on models just getting better, but the ROI curve has flattened. Companies like Uber, Microsoft, and Anthropic have already voiced concerns about frontier models being oversold out of the box. 🔹 You Don't Need a 3-Trillion-Parameter Model — With the right context layer, a 150-billion-parameter model can match frontier-model coding performance. Andrei explains why context — not raw model size — is becoming the real differentiator. 🔹 Same Model, Different Company, Wildly Different Output — If two companies use the identical LLM, what separates the results? According to Andrei, it's entirely how well each company's own architecture, testing standards, and business logic have been translated into a usable context layer. 🔹 Why Trust Is the Real Product — Enterprises are being asked to hand over 10-30 years of proprietary code and documentation. Andrei breaks down how Designverse earns that trust — full transparency on data usage, small proof-of-concepts before any real integration, and IP that's never exposed outside the client relationship. 🔹 Why Finance and Healthcare, Specifically — Regulated industries are forced to maintain rigorous documentation — which, counterintuitively, makes them better candidates for context-layer ingestion, not harder ones. 🔹 The Future Software Team: Humans + Agents, Together — Andrei's five-year prediction: small, highly specialized teams — a mix of human engineers and AI agents working side-by-side on individual features — replacing today's large, centralized engineering departments. 🔹 The Honest Answer on AI's Limits — With hundreds of billions of dollars invested industry-wide, Andrei doesn't dodge the hard question: AI still cannot autonomously build and ship a million-line-of-code enterprise application. It can help build a narrow internal tool for 15 people. It cannot yet replace a real engineering team at scale. 🔹 Demo vs. Reality — Why Designverse refuses to sell off a generic demo: "A high schooler can build a demo with Replit and a prompt." Real enterprise buyers, especially in the U.S. right now, are optimizing AI spend hard — and won't pay for anything that isn't solving a real, currently-unsolved pain point. Key Quote: "It's not really about the model — it's more about how you govern this data, and how you give it in the best way possible to a model, whether it's 150 billion or 1 trillion parameters, to write only the more consistent output." About Designverse:  Designverse is an AI-native software development platform that ingests an organization's existing codebase, documentation, and architecture to build a "context layer" — enabling any underlying model to generate code that's consistent with how that specific company actually operates. Backed by a $5.5M seed round from operators at Adobe, UiPath, and LSEG. Subscribe: Spotify | Apple Podcasts | Amazon Music | iHeart Radio | YouTube | Substack | Instagram #Ai4Conference #EnterpriseAI #AIcoding #ContextEngineering #Designverse #LegacyModernization #AgenticAI #AsembleAI

    EP 57: Ai4 Podcast - Why "The Context Layer" Is What Enterprise AI Is Actually Missing | Andrei Manolache, Designverse

  7. 22 ago

    EP 56: Ai4 Podcast - Why AI-Generated Code Needs Its Own Kind of Security | Anand Revashetti, Lineaje

    Recorded live from the Ai4 podcast pavilion, Sam talks with Anand Revashetti, Co-Founder & CEO of Lineaje, about a problem most companies don't realize they have: they're confident their AI-generated code is secure, but very few actually have visibility into it. What's Covered: Where the Trust Gap Comes From — Executives see AI adoption metrics and productivity gains. Security teams see code shipping thousands of times a day with no clear record of who — or what — generated it. Anand explains exactly where that disconnect forms inside real organizations. A New Class of Attack — Reasoning-based attacks that exploit a model's decision weights directly, with no traditional vulnerability involved. Anand walks through how a small test exploit can scale into a multi-million-dollar fraud incident. Not a Roadblock, a Provenance Layer — How Lineaje operates inside the developer's own environment, attaching a clear record — which developer, which AI model, which skills — to every piece of code, without slowing anyone down. The Bad Habit Nobody's Talking About — Unlike traditional software that stayed stable for years, AI models get effectively rewritten on every release. Anand explains why that breaks the old maintenance playbook, and what continuous assurance actually looks like instead. On the AI Job Apocalypse — A grounded, experience-based take on the doom rhetoric circulating the conference: from a security standpoint, AI has been a genuine boon, not a threat to the field. Key Quote: "The worst thing you can do to a person who is driving and enjoying on a speedway is implement some sort of roadblock. Lineaje doesn't try to be a roadblock — but we manage all your policies." Connect:  https://www.linkedin.com/in/arevashe/ https://www.lineaje.com/ Subscribe: Spotify | Apple Podcasts | Amazon Music | iHeart Radio | YouTube #Ai4Conference #Lineaje #AISecurity #SoftwareSupplyChain #AsembleAI

    EP 56: Ai4 Podcast - Why AI-Generated Code Needs Its Own Kind of Security | Anand Revashetti, Lineaje

  8. 17 ago

    Ep 55: Ai4 Podcast - Turning 35 Years of Paper Archives into AI Training Data | Dilo Wijesuriya, ARC

    Recorded live from the Ai4 conference floor in Las Vegas, Sam sits down with Dilo Wijesuriya, President & COO of ARC Document Solutions, to talk about the unglamorous but essential layer of enterprise AI: getting decades of paper archives into a format models can actually learn from. What's Covered: The Technology — ARC holds patents for OCR on wide-format documents (architectural drawings, engineering blueprints) that standard scanning tools can't accurately process, backed by a 200-person engineering team in India. Security & Compliance — SOC 2, SOC 3, ISO 27001, and HIPAA compliant, running on AWS — built for regulated industries like healthcare and financial services. Will Paper Disappear?  Dilo's view: not for a long time. Most organizations' most critical institutional knowledge still exists only on paper, meaning today's LLMs simply can't learn from it yet. The Book Destruction Debate — A direct response to recent controversy over companies destroying physical books after digitizing them, and why ARC's non-destructive robotic scanning preserves originals for high-value collections at universities, libraries, and museums. Looking Ahead — Why Dilo believes the next competitive advantage for most enterprises isn't a better model — it's finally accessing the data already sitting in their own archives. Key Quote: "The challenge isn't finding more data. It's making existing information accessible." Connect with Dilo and ARC: Dilo Wijesuriya: https://www.linkedin.com/in/dilo-wijesuriya/ ARC Document Solution: https://www.e-arc.com/ Subscribe: Spotify | Apple Podcasts | Amazon Music | iHeart Radio | YouTube #Ai4Conference #DocumentDigitization #AIReadyData #EnterpriseAI #OCR #AsembleAI

    Ep 55: Ai4 Podcast - Turning 35 Years of Paper Archives into AI Training Data | Dilo Wijesuriya, ARC
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Descrizione

AsembleAI brings you thought-provoking conversations at the nexus of artificial intelligence, innovation, and leadership. In each episode, hosts Mac and Sam, veterans in data and tech world, sit down with AI researchers, fast‑scaling founders, Fortune 500 executives, and pioneering technologists to reveal how AI is reshaping business strategy, sparking breakthrough product development, and guiding executive decisions. Tune in for actionable insights, compelling case studies, and forward‑looking perspectives on the promises and pitfalls of AI‑driven innovation.RSSVERIFY

Informazioni

  • Creatore
    Mac & Sam
  • Anni di attività
    2025 - 2026
  • Puntate
    62
  • Classificazione
    Contenuti adatti a tutti
  • Copyright
    © Mac & Sam 2025
  • Sito web del podcast
    Inside AsembleAI: DeepTech, AI & Science
  • Fornitore

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