POPULARITY
19 episodes with enterprise ai
13 episodes with enterprise ai
16 episodes with enterprise ai
17 episodes with enterprise ai
17 episodes with enterprise ai
7 episodes with enterprise ai
3 episodes with enterprise ai
5 episodes with enterprise ai
5 episodes with enterprise ai
6 episodes with enterprise ai
3 episodes with enterprise ai
5 episodes with enterprise ai
3 episodes with enterprise ai
3 episodes with enterprise ai
4 episodes with enterprise ai
2 episodes with enterprise ai
3 episodes with enterprise ai
2 episodes with enterprise ai
Glean started as a Kleiner Perkins incubation and is now a $7B, $200m ARR Enterprise AI leader. Now KP has tapped its own podcaster to lead it's next big swing. From building go-to-market the hard way in startups (and scaling Palo Alto Networks' public cloud business) to joining Kleiner Perkins to help technical founders turn product edge into repeatable revenue, Joubin Mirzadegan has spent the last decade obsessing over one thing: distribution and how ideas actually spread, sell, and compound. That obsession took him from launching the CRO-only podcast Grit (https://www.youtube.com/playlist?list=PLRiWZFltuYPF8A6UGm74K2q29UwU-Kk9k) as a hiring wedge, to working alongside breakout companies like Glean and Windsurf, to now incubating Roadrunner which is an AI-native rethink of CPQ and quoting workflows as pricing models collapse from “seats” into consumption, bundles, renewals, and SKU sprawl. We sat down with Joubin to dig into the real mechanics of making conversations feel human (rolling early, never sending questions, temperature + lighting hacks), what Windsurf got right about “Google-class product and Salesforce-class distribution,” how to hire early sales leaders without getting fooled by shiny logos, why CPQ is quietly breaking the back of modern revenue teams, and his thesis for his new company and KP incubation Roadrunner (https://www.roadrunner.ai/): rebuild the data model from the ground up, co-develop with the hairiest design partners, and eventually use LLMs to recommend deal structures the way the best reps do without the Slack-channel chaos of deal desk. We discuss: How to make guests instantly comfortable: rolling early, no “are you ready?”, temperature, lighting, and room dynamics Why Joubin refuses to send questions in advance (and when you might have to anyway) The origin of the CRO-only podcast: using media as a hiring wedge and relationship engine The “commit to 100 episodes” mindset: why most shows die before they find their voice Founder vs exec interviews: why CEOs can speak more freely (and what it unlocks in conversation) What Glean taught him about enterprise AI: permissions, trust, and overcoming “category is dead” skepticism Design partners as the real unlock: why early believers matter and how co-development actually works Windsurf's breakout: what it means to be serious about “Google-class product + Salesforce-class distribution” Why technical founders struggle with GTM and how KP built a team around sales, customer access, and demand gen Hiring early sales leaders: anti-patterns (logos), what to screen for (motivation), and why stage-fit is everything The CPQ problem & Roadrunner's thesis: rebuilding CPQ/quoting from the data model up for modern complexity How “rules + SKUs + approvals” create a brittle graph and what it takes to model it without tipping over The two-year window: incumbents rebuilding slowly vs startups out-sprinting with AI-native architecture Where AI actually helps: quote generation, policy enforcement, approval routing, and deal recommendation loops — Joubin X: https://x.com/Joubinmir LinkedIn: https://www.linkedin.com/in/joubin-mirzadegan-66186854/ Where to find Latent Space X: https://x.com/latentspacepod Substack: https://www.latent.space/ Chapters 00:00:00 Introduction and the Zuck Interview Experience 00:03:26 The Genesis of the Grit Podcast: Hiring CROs Through Content 00:13:20 Podcast Philosophy: Creating Authentic Conversations 00:15:44 Working with Arvind at Glean: The Enterprise Search Breakthrough 00:26:20 Windsurf's Sales Machine: Google-Class Product Meets Salesforce-Class Distribution 00:30:28 Hiring Sales Leaders: Anti-Patterns and First Principles 00:39:02 The CPQ Problem: Why Salesforce and Legacy Tools Are Breaking 00:43:40 Introducing Roadrunner: Solving Enterprise Pricing with AI 00:49:19 Building Roadrunner: Team, Design Partners, and Data Model Challenges 00:59:35 High Performance Philosophy: Working Out Every Day and Reducing Friction 01:06:28 Defining Grit: Passion Plus Perseverance
Sales, and Matt Hobbs, Cloud Engineering and Data Analytics Platform Leader and Partner at PwC US. Together, they explore how companies can stop overpaying for cloud and instead fund AI innovation by shifting spend from legacy and suboptimal cloud deployments into modern architectures, multi-cloud strategies, and enterprise-grade AI capabilities that actually move the needle on growth, margin, and new business models.Smarter Cloud, Bigger AIThe Big Themes:Built to Cost Less: Oracle entered the cloud market later and designed OCI from the “bare metal up” with off-box virtualization, a low-latency non-blocking network, and significantly lower egress pricing. That means Oracle's own cost to deliver infrastructure is structurally lower, so they don't need to “race to zero” with margin-crushing discounts. When customers compare OCI run-rates to first-generation hyperscalers, it's common to see 40–70% savings at list-to-net, not just in special deals.Turning Technical Debt Into Innovation Budget: Hobbs notes that roughly 40% of internal tech budgets are often tied up in technical debt rather than innovation. PwC sees executives searching for ways to unlock capital for AI and growth initiatives, not just trim expenses. Its “Fit for Growth” program looks at where money is tied up in non-differentiating costs (cloud infrastructure being one of the biggest line items) and reallocates that spend into value-creating initiatives. When PwC runs side-by-side economics, they've seen OCI's promised 40–70% savings show up in real deals.OCI + PwC: budget creation meets execution: The Oracle–PwC collaboration stands out, the guests argue, because both sides are relentlessly focused on the client outcome rather than maximizing any one platform. PwC validates OCI's economics and brings the talent to design and execute migrations, process re-invention, and agentic AI programs; Oracle brings a cost-efficient, multi-cloud-friendly infrastructure designed for price-performance and portability.The Big Quote: “You can burn a lot of money chasing ghosts in this game if you really don't have a very specific use case." Visit Cloud Wars for more.
In 1992, Roopa Kudva walked into CRISIL's CEO Pradeep Shah's office without an appointment, starting her 23-year career there. She spent over two decades at CRISIL, rising from analyst to CEO. Roopa has spent over 3 decades in leadership roles in India and has witnessed three key phases in India's growth: the closed economy in the 80s, the post-liberalisation era, and the rise of tech entrepreneurs.She shares bold decisions that defined her journey. Like when she proposed to the then CRISIL CEO to create the Chief Ratings Officer role and pitched herself for it. She got the role, which set her on the path to becoming CEO. We also discuss the leaders who shaped her thinking, K.V. Kamath of ICICI, Piyush Gupta of DBS, and Katharine Graham of the Washington Post.Throughout the conversation, Roopa returns to one idea: there is no single leadership style or fixed playbook. Her journey shows how ambition and initiative to act at the right moment can define a career and the organizations one builds along the way.0:00 —Trailer01:21 — IIM to IDBI03:54 — Work Culture in the 80s05:58 — Rise of New-Age Companies06:55 — The Aha Moment of Leadership View08:52 — Leaving CRISIL After 23 Years10:49 — Choosing Omidyar & Impact Investing16:03 — India's Evolving Risk Appetite20:40 — Deciding the Next Career Move26:08 — How She Got the CRISIL Job31:09 — Asking for the CRO Role35:48 — Promotions Are Bets on the Future37:37 — The Leader Who Changed Her Philosophy43:40 — ICICI as a Women-CEO Factory45:36 — What Holds Women Back from Rising51:38 — DBS: The Piyush Gupta Transformation55:06 — Entrepreneurs for the Next Half Billion1:02:47 — The New Indian Founder Profile-------------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 AI Breakdown: Daily Artificial Intelligence News and Discussions
Today's episode breaks down new reports from OpenAI and Menlo Ventures that show enterprise AI adoption accelerating quickly, with coding emerging as the first true killer use case, reasoning models driving deeper workflow integration, and the gap between leaders and laggards widening as frontier firms compound their advantages. The conversation also looks at early agent deployments and what these trends signal for the 2026 boom-versus-bubble debate. In the headlines: Anthropic donates MCP as OpenAI, Anthropic, and Block form the Agentic AI Foundation, rumors swirl around GPT-5.2 and a new image model, OpenAI launches AI Foundations certifications, and the US military unveils its GenAI.milBrought to you by:KPMG – Discover how AI is transforming possibility into reality. Tune into the new KPMG 'You Can with AI' podcast and unlock insights that will inform smarter decisions inside your enterprise. Listen now and start shaping your future with every episode. https://www.kpmg.us/AIpodcastsGemini - Build anything with Gemini 3 Pro in Google AI Studio - http://ai.studio/buildRovo - Unleash the potential of your team with AI-powered Search, Chat and Agents - https://rovo.com/AssemblyAI - The best way to build Voice AI apps - https://www.assemblyai.com/briefLandfallIP - AI to Navigate the Patent Process - https://landfallip.com/Blitzy.com - Go to https://blitzy.com/ to build enterprise software in days, not months Robots & Pencils - Cloud-native AI solutions that power results https://robotsandpencils.com/The Agent Readiness Audit from Superintelligent - Go to https://besuper.ai/ to request your company's agent readiness score.The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614Interested in sponsoring the show? sponsors@aidailybrief.ai
For episode 651 of the BlockHash Podcast, host Brandon Zemp is joined by Andrew Sobko, CEO of Argentum AI, an Enterprise level ready AI-powered compute marketplace.Andrew Sobko is a serial entrepreneur with a background in building transformative marketplaces. He founded one of the fastest-growing companies in America, recognized by the Financial Times and honored by Goldman Sachs' Builders & Innovators award. Andrew has raised over $200 million from leading global investors including Sequoia Capital, Brookfield, and others. ⏳ Timestamps: (0:00) SUMSUB(0:44) Introduction(0:53) Who is Andrew Sobko?(5:50) Argentum Marketplace(9:28) Advantages of Argentum(13:58) Trust & validation for Argentum clients(14:37) SUMSUB(16:00) Argentum Token(18:50) How to contribute compute(19:42) Future of Enterprise AI(22:05) Argentum roadmap for 2026(25:03) Events & conferences(25:30) Website & socials
In this episode of the Identity at the Center Podcast, hosts Jeff and Jim sit down with Tobin South, co-chair of the OpenID Foundation's AI Identity Management Community Group, to delve into the intricacies of identity management in the age of agentic AI. They discuss the challenges and solutions related to AI agents, the role of the Model Context Protocol (MCP), and the concept of recursive delegation and scope attenuation. Additionally, the conversation covers practical advice for developers and enterprises on preparing for AI-driven identity management and explores the cultural touchstone of coffee from various global perspectives.Connect with Tobin: https://www.linkedin.com/in/tobinsouth/OpenID Foundation: https://openid.net/Identity Management for Agentic AI (OpenID Whitepaper): https://openid.net/wp-content/uploads/2025/10/Identity-Management-for-Agentic-AI.pdfConnect with us on LinkedIn:Jim McDonald: https://www.linkedin.com/in/jimmcdonaldpmp/Jeff Steadman: https://www.linkedin.com/in/jeffsteadman/Visit the show on the web at http://idacpodcast.comChapter Timestamps:00:00 – Jeff and Jim banter about unopened iPads and conference season05:55 – Introduction to Tobin South and his AI identity background07:00 – How AI has evolved from machine learning to generative models09:00 – The OpenID AI Identity Management Community Group10:30 – ChatGPT's impact on the AI perception shift12:00 – Users vs. Agents: What's the difference?14:00 – Letting the right bots in: AI agents vs. bad bots17:00 – AI impersonation, delegation, and the risk of shared credentials20:00 – Impersonation vs. Delegation – what practitioners need to know23:00 – Governance, oversight, and delegated authority for agents26:00 – Liability and “who is responsible” in agentic systems30:00 – How developers can prepare for agent identity and access management32:00 – Explaining the Model Context Protocol (MCP)36:00 – Enterprise use cases for MCP and internal automation38:00 – Is MCP the next SAML?42:00 – Recursive delegation and scope attenuation explained46:00 – The one key takeaway for IAM professionals48:00 – Lighter note: Coffee talk – from Sydney to San Francisco54:00 – Wrap-up and where to find more IDAC contentKeywords:IDAC, Identity at the Center, Jim McDonald, Jeff Steadman, Tobin South, OpenID Foundation, AI Identity Management, Agentic AI, Delegated Authority, Impersonation vs Delegation, Model Context Protocol (MCP), Recursive Delegation, Scope Attenuation, Identity Access Management, IAM, AI Governance, AI Standards, Enterprise AI, AI Agents, Identity Security
Peloton welcomes three new instructors to its fitness team.Get the details on major updates to the PSL schedule.A new Club Peloton perk offers members early access to classes.Peloton's Chief Marketing Partnership Director has departed the company.Peloton's CTO sparked conversation with a discussion on ChatGPT integration.The company is hiring a Sr. Director of Digital Innovation & Enterprise AI.New yoga instructor Johanna Ricouz gives a running class a try.Jess Sims has a hilarious NSFW moment on live television.Denis Morton is at the center of "Hairgate 2.0."Instructor Cliff Dwenger has released a new song.DJ John Michael celebrates his 10-year anniversary with Peloton and drops a new remix.The latest Artist Series spotlights the music of Michael Bublé.Wicked: For Good themed classes are now available.Kristin McGee launches her very first program on the Tonal platform.Our TCO Top Five recap of the community's favorite Peloton classes.This Week at Peloton: A rundown of what's happening on the platform.TCO Radar: We highlight upcoming fitness classes you won't want to miss.Bradley Rose & Benny Adami have new rides themed around Stranger Things.A new "Meet Your New Yoga Instructors" challenge is live.Get ready for a new Holiday fitness challenge.Sam Yo's popular Top Gun ride has been removed from the class library.Happy Birthday to Peloton instructor Tunde Oyeneyin on December 5th.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Maribel Lopez reports live from AWS re:Invent 2025 in Las Vegas, unpacking why the AI experimentation phase is officially over. With statistics that say 95% of AI projects are failing and enterprise budgets tightening, 2026 demands production-quality AI—not more proof-of-concepts. This episode explores the critical shift from building agents to deploying them safely at scale.Key ThemesThe Reality Check (2025 Recap)MIT study reveals 95% AI project failure rateMcKinsey and BCG document widespread implementation strugglesBoard-level AI initiatives now demand real ROI, not just innovation theaterThe POC gold rush is over—experimentation budgets are drying upAgentic AI Grows Up The conversation has evolved from "can we build agents?" to "can we trust them in production?" Three critical roadblocks:Security & Orchestration: How agents interact without creating vulnerabilitiesPolicy & Governance: Preventing rogue agents and establishing guardrailsObservability: Real-time monitoring to ensure agents perform as intendedAWS re:Invent 2025 HighlightsAgent Core ImprovementsEnhanced policy frameworks defining agent boundaries and permissionsHuman-in-the-loop controls for high-stakes decisionsBetter cross-stack orchestration for multi-agent workflowsThe Discoverability ProblemAWS Marketplace now features natural language searchUpload requirements documents instead of filling rigid formsAI-suggested prompts help non-technical users navigate complex decisionsSmarter filtering for nuanced needs (performance vs. cost vs. compliance)The Full-Stack MaturityRecognition that AI "takes a village"—no single vendor owns the entire stackGrowing emphasis on open standards (A2A, MCP) for SaaS integrationTools designed for all skill levels, not just data scientistsKey TakeawayEnterprise AI in 2026 isn't about doing more—it's about doing it right. The winners will be organizations that prioritize governance, observability, and practical deployment over flashy demos.Host: Maribel LopezRecorded: AWS re:Invent, Las Vegas, December 2025Follow-up: Stay tuned for next week's deep-dive episode with demos and vendor interviews
Most conversations in startups begin at zero: what's the idea, who's the customer, how big is the market. But the stage before that, when you know you're ready to be a founder yet the direction is still completely undefined. That strange, uncomfortable, high-potential zone Aditya Agarwal calls “minus one.”In this episode, Aditya and Prateek Mehta breaks down what happens in this “figuring out” stage. The questions people avoid, the habits that matter, and why some of the best companies begin long before their founders have any conviction.We get into how this stage is evolving in the AI era. Exploration cycles are faster, technical founders can test more directions than ever, and the gap between “I'm experimenting” and “I'm running a real company” has narrowed. India's builder ecosystem is shifting too: more second-time founders, more people with real outcomes behind them, and far more comfort sitting with ambiguity.Aditya shares his own minus-one moment after Facebook, his startup acquisition, Dropbox's IPO, and Flipkart, and why that transitional period changed the way he thinks about early-stage startups. Prateek brings on-the-ground view from Bangalore, where ambition, technical depth, and the appetite to explore hard problems from robotics to voice models to AI infra are rising.This episode is for anyone who feels they're between missions. Anyone who wants to understand why the most important part of building a company might actually be the time you spend before you even know what you're building.00:00- Trailer01:06- Aditya's journey to starting SPC after Facebook & Dropbox 03:48- A “learning club” for people in figuring-out stage06:23- 3 Northstars of the SPC community07:02- How SPC evolved from a community to a fund10:32- Not everyone should be a founder11:51- 1% selection rate13:53- Building conviction in 1 of 3 outcomes16:36- SPC is at PMF stage18:38- Mismatch of traditional VC's v/s rapid pace startups19:04- How AI has impacted investing at SPC26:32- How AI has changed VC firms29:02- Axis of curiosity replacing thesis30:17- Star Companies of SPC US33:34- Binny Bansal's role in starting SPC India37:16- Questions & confusions as founders in early stage39:50- Number of great entrepreneurs is NOT small41:49- Talent density in India vs Bay Area44:04- Founders don't need a culture of permission45:08- India tier 2 and 3 does invest heavily in AI46:11- AI is truly democratizing tech49:09- Math gives India advantage in AI51:48- A lot of science fiction is coming true-------------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
Episode SummaryAs AI systems become increasingly integrated into enterprise workflows, a new security frontier is emerging. In this episode of The Secure Developer, host Danny Allan speaks with Nicolas Dupont about the often-overlooked vulnerabilities hiding in vector databases and how they can be exploited to expose sensitive data.Show NotesAs organizations shift their focus from training massive models to deploying them for inference and ROI, they are increasingly centralizing proprietary data into vector databases to power RAG (Retrieval-Augmented Generation) and agentic workflows. However, these vector stores are frequently deployed with insufficient security measures, often relying on the dangerous misconception that vector embeddings are unintelligible one-way hashes.Nicolas Dupont explains that vector embeddings are simply dense representations of semantic meaning that can be inverted back to their original text or media formats relatively trivially. Because vector databases traditionally require plain text access to perform similarity searches efficiently, they often lack encryption-in-use, making them susceptible to data exfiltration and prompt injection attacks via context loading. This is particularly concerning when autonomous agents are over-provisioned with write access, potentially allowing malicious actors to poison the knowledge base or manipulate system prompts.The discussion highlights the need for a "secure by inception" approach, advocating for granular encryption that protects data even during processing without incurring massive performance penalties. Beyond security, this architectural rigor is essential for meeting privacy regulations like GDPR and HIPAA in regulated industries. The episode concludes with a look at the future of AI security, emphasizing that while AI can accelerate defense, attackers are simultaneously leveraging the same tools to create more sophisticated threats.LinksCyborgOWASP LLM Top 10Snyk - The Developer Security Company Follow UsOur WebsiteOur LinkedIn
AI That Acts, Not Just Chats: The Integration Advantage | feat. Craig Stasila
In this special Cloud Wars report, Bob Evans sits down with Michael Ameling, President and Chief Product Officer of SAP Business Technology Platform, for a deep dive into how SAP is helping customers navigate the fast-moving AI Era. Ameling and Evans discuss how SAP's Business Data Cloud, partnerships with Snowflake and Databricks, HANA Cloud innovations, and new AI-powered tools and agents are helping SAP evolve from an applications powerhouse into a data-and-AI-driven business platform for the next generation.SAP's AI Data FutureThe Big Themes:SAP HANA Cloud Becomes an AI-Optimized Database: SAP HANA Cloud is evolving into “the database AI was looking for." As a multi-model system supporting spatial, graph, vector, and document storage, HANA Cloud enables AI workloads to run more efficiently and contextually. Recent additions, like vector engines and Knowledge Graph capabilities, give customers powerful tools for retrieval-augmented generation (RAG), contextual reasoning, and advanced analytics.Developers Are 'The AI Revolution': Developers aren't observing the AI Revolution, they are the revolution. With modern AI tools, developers can innovate faster, solve bigger problems, and directly influence business outcomes. SAP is investing heavily in meeting developers where they are by enhancing IDEs, building business-aware development tools, and providing context-rich assets such as APIs, business objects, and process insights. AI acts as a teammate, not a replacement.SAP: An Applications and a Data Company: SAP must be both an applications and a data company. Customer value emerges when applications, data, and AI converge seamlessly. SAP's decades of industry expertise give it unparalleled business context, which becomes even more powerful when embedded into AI agents and data platforms. With more than 34,000 SAP HANA Cloud customers and rapidly expanding AI adoption, SAP is positioning itself as the platform where business process knowledge meets modern AI capability.The Big Quote: " . . what we need to understand that AI is our teammate. It's like asking your best friend who has a lot of knowledge, but you can ask multiple friends at the same time. Not everything is always right, but you can ask questions, you can continuously improve. If we understand that pattern, we understand that AI helps us to solve much bigger problems as a developer, and then, of course, having much more impact on real business."More from Michael Ameling and SAP:Connect with Michael Ameling on LinkedIn, or get more insights from SAP TechEd. Visit Cloud Wars for more.
If you're a startup selling to enterprises, understanding how a CIO discovers and evaluates you can change everything. Most founders believe that cold emails and polished decks drive attention, but Karthik Chakkarapani, CIO of Zuora shares that nearly 80% of the startups he evaluates are found through outbound - while researching solutions, through peers, or even on LinkedIn. For many startups, this alone can reshape how they think about go-to-market.How does an enterprise decide whether to buy from a startup or not? Karthik walks us through Zuora's three-step buying process. It starts with understanding the problem the startup solves and how quickly the product can show value. If the early signals are strong, the next step is a deeper look at ROI, integration, security and whether the company is mature enough to be a long-term partner. The final stage is legal and procurement, which is where many early-stage startups slow down.If you're building a startup, this episode offers a practical look into how CIOs think, how they make decisions and what it really takes to go from a first conversation to a signed contract.0:00 – Trailer0:53 – Buying process of startups05:19 – How Zuora's SaaS portfolio looked 2 years ago09:00 – Inbound vs outbound10:53 – How initial contact with potential customers works13:34 – Startups should be thought partners16:57 – How long it takes to create value for customers19:59 – Where startups draw the line in growth vs efficiency23:06 – Top 5 largest spends24:01 – Why only 1-year contracts for new AI startups?26:12 – Why legal & procurement struggle to understand startups29:46 – 20% of portfolio is 0–5 year old companies30:46 – Are startups not backed by VCs a red flag?34:29 – 60% in growth + 40% in day-to-day37:42 – Learnings from peer CIOs41:38 – Featurely: Case Study45:14 – Atomicwork: Case Study46:55 – Trupeer: Case Study47:51 – How Zuora uses OpenAI & Anthropic49:39 – How AI is helping personal productivity51:26 – How agents will be managed54:02 – Number of SaaS apps will go down, agents will go up55:45 – Building the right security for AI56:31 – India vs US: where founders are building from-------------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
Dell Technologies and NVIDIA are delivering the future of enterprise AI with advancements to the Dell AI Factory with NVIDIA. These advancements provide simplicity, performance and flexibility for advanced environments and support enterprises across AI applications, from traditional to agentic. Why it Matters A new era of high-performance computing (HPC) and enterprise AI is here. As enterprises scale, many face challenges such as managing complex ecosystems of hardware and software or gaining control over their data. According to recent research, 95% of enterprises believe working with a trusted technology partner like Dell Technologies reduces the risks associated with adopting new technologies. Additionally, 90% agree that bringing AI to their data creates greater value through enhanced control, fresh insights, and secure access. Enter the Dell AI Factory with NVIDIA - a game-changer for enterprises looking to accelerate outcomes, reduce complexity and maximise ROI. By integrating Dell's robust end-to-end infrastructure with NVIDIA AI technology, backed by expert guidance from Dell Professional Services, organisations can transform ideas into tangible results and stay ahead of evolving technologies and scaling needs. Accelerate deployment with integrated, automated platforms Dell's storage and AI solutions offerings help enterprises automate deployments, optimise performance and deliver real-time AI applications with greater efficiency and reliability. Dell ObjectScale and PowerScale, the Dell AI Data Platform's storage engines for unstructured data, are now integrated with the NVIDIA NIXL library, part of NVIDIA Dynamo. This integration enables scalable KV Cache storage, reuse and sharing, achieving a 1-second Time to First Token (TTFT) at a full context window of 131K tokens - 19X faster than standard vLLM - while reducing infrastructure costs and overcoming GPU memory capacity bottlenecks.[iv] The Dell AI Factory with NVIDIA now includes solutions with Dell PowerEdge XE7740/XE7745 servers featuring NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs and NVIDIA Hopper GPUs. These proven and validated offers feature next-level AI acceleration and computing power to execute advanced use cases - from large-scale multimodal models to emerging agentic AI applications and from enterprise-grade inferencing to training workloads. The Dell Automation Platform, now expanded to the Dell AI Factory with NVIDIA, will deliver smarter, more automated experiences by deploying validated, optimised solutions with a secure framework. This approach will produce repeatable outcomes, eliminate guesswork, and help unlock the full potential of AI-driven use cases powered by NVIDIA accelerated computing. Software-driven tools like the AI code assistant with Tabnine and the agentic AI platform with Cohere North are now automated, getting AI workloads into production faster, streamlining operations and enhancing scalability. Beyond the traditional data centre, Dell's ecosystem enablers for AI PCs offer organisations expanded silicon options, now supporting NVIDIA RTX Blackwell GPUs and NVIDIA RTX Ada GPUs, ensuring compatibility across a broader range of Dell devices. Dell Professional Services provides turnkey interactive AI use case pilots using real customer data to validate business value ahead of scaled investments. These expert-led pilots offer a hands-on preview for experimentation with clear success metrics and KPIs, delivering tangible ROI. Uplevel AI performance with next-generation infrastructure Dell infrastructure updates accelerate HPC and AI innovation by delivering platforms with powerful performance, scalability, and streamlined management. These solutions will help organisations build efficient systems for modern workloads. The Dell PowerEdge XE8712 server, available next month, sets a new standard by delivering the industry's highest GPU density in a standard rack with up to 144 NVIDIA Blackwell GPUs per Dell IR7000 rack. This b...
In this episode, we sit down with Solution Architect Robert Alvarez to discuss the technology behind Pure Key-Value Accelerator (KVA) and its role in accelerating AI inference. Pure KVA is a protocol-agnostic, key-value caching solution that, when combined with FlashBlade data storage, dramatically improves GPU efficiency and consistency in AI environments. Robert—whose background includes time as a Santa Clara University professor, NASA Solution Architect, and work at CERN—explains how this innovation is essential for serving an entire fleet of AI workloads, including modern agentic or chatbot interfaces. Robert dives into the massive growth of the AI Inference market, driven by the need for near real-time processing and low-latency AI applications. This trend makes the need for a solution like Pure KVA critical. He details how KVA removes the bottleneck of GPU memory and shares compelling benchmark results: up to twenty times faster inference with NFS and six times faster with S3, all over standard Ethernet. These performance gains are key to helping enterprises scale more efficiently and reduce overall GPU costs. Beyond the technical deep dive, the episode explores the origin of the KVA idea, the unique Pure IP that enables it, and future integrations like Dynamo and the partnership with Comet for LLM observability. In the popular “Hot Takes” segment, Robert offers his perspective on blind spots IT leaders might have in managing AI data and shares advice for his younger self on the future of the data management space. To learn more about Pure KVA, visit purestorage.com/launch. Check out the new Pure Storage digital customer community to join the conversation with peers and Pure experts: https://purecommunity.purestorage.com/ 00:00 Intro and Welcome 02:21 Background on Our Guest 06:57 Stat of the Episode on AI Inferencing Spend 09:10 Why AI Inference is Difficult at Scale 11:00 How KV Cache Acceleration Works 14:50 Key Partnerships Using KVA 20:28 Hot Takes Segment
Kent Bye—host of the Voices of VR podcast and one of XR's most prolific journalists with over 1,680 published interviews—joins Charlie and Ted for a wide ranging conversation on the state of immersive storytelling, the ethics of AI, and why XR's future might be less about consumer headsets and more about embodied presence and human connection. Kent's decade-long commitment to documenting artists, creators, and developers at the ground level offers a counterpoint to hype-driven tech coverage, revealing the messy, vital ecosystem sustaining VR through festival circuits, location-based entertainment, and government-funded experimental projects that rarely make headlines.The conversation opens with Jeff Bezos's new AI robotics company Prometheus, Amazon's one-to-one human-robot workforce parity, and the implications of industrial AI automation. Ted shares his recent appearance on cinematographer Roger Deakins's podcast, where they discussed AI as a creative tool rather than a threat—a perspective Kent echoes when discussing artists who use AI to critique AI's "colonizing force." Kent explains his philosophy of "boots on the ground" journalism inspired by Knight Ridder's Iraq War reporting, focusing on developers and creators closest to the work rather than corporate press releases.Kent reveals why he's been lukewarm on smart glasses despite industry excitement—monocular displays give him headaches, his prescription is too strong for current hardware, and most importantly, there's no compelling narrative content yet. He contrasts this with VR's rich immersive storytelling at festivals like Venice Immersive, Sundance New Frontier, IDFA DocLab, and Tribeca, where government-funded European projects push the medium's boundaries in ways U.S. startups can't afford to explore. The discussion touches on Meta's Ray-Ban AI glasses, the impracticality of Meta's neural band input, and why Snap's developer platform remains the most interesting AR ecosystem despite limited consumer traction.Guest HighlightsPublished 1,682 VR interviews with 1,000+ unpublished; focused on artists, creators, and developers over corporate narratives.Covers 30+ hours of immersive content per festival at Venice, Sundance, IDFA DocLab—documenting ephemeral art that may never distribute widely.Started in 2014 after buying Oculus DK1; began by capturing oral history at Silicon Valley VR Conference's first gathering.Background as F-22 Raptor radar systems engineer turned documentary filmmaker—blends hardcore technical knowledge with artistic sensibility.Advocates for XR as antidote to smartphone addiction—technologies that foster embodied presence rather than infinite distraction.News HighlightsJeff Bezos launches Prometheus AI robotics company—focusing on industrial applications where enterprise adoption will drive innovation faster than consumer markets.Amazon hits one-to-one human-robot workforce parity—roughly 1 million humans, 1 million robots, with plans to shed 100K+ workers over five years.Warner Brothers settles with AI music company Udio—following Axel Springer, AP, and Fox licensing deals as New York Times litigation drags on.Enterprise AI startups raise massive rounds—Stut (collections automation, $29.5M from Andreessen), Albatross (real-time personalization, $12.5M), signaling vertical-specific AI SaaS wave.HaptX acquired by Ohio manufacturer—haptic glove company pivots to industrial training applications after years targeting consumer VR.Thanks to our sponsors Zappar and VitureNew episodes every Tuesday. Hosted on Acast. See acast.com/privacy for more information.
Dr. Jure Leskovec is the Chief Scientist at Kumo.AI and a Stanford professor, working on relational foundation models and graph-transformer systems that bring enterprise databases into the foundation-model era.Relational Foundation Models: Unlocking the Next Frontier of Enterprise AI // MLOps Podcast #348 with Jure Leskovec, Professor and Chief Scientist, Stanford University and Kumo.AI.Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractToday's foundation models excel at text and images—but they miss the relationships that define how the world works. In every enterprise, value emerges from connections: customers to products, suppliers to shipments, molecules to targets. This talk introduces Relational Foundation Models (RFMs)—a new class of models that reason over interactions, not just data points. Drawing on advances in graph neural networks and large-scale ML systems, I'll show how RFMs capture structure, enable richer reasoning, and deliver measurable business impact. Audience will learn where relational modeling drives the biggest wins, how to build the data backbone for it, and how to operationalize these models responsibly and at scale.// BioJure Leskovec is the co-founder of Kumo.AI, an enterprise AI company pioneering AI foundation models that can reason over structured business data. He is also a Professor of Computer Science at Stanford University and a leading researcher in artificial intelligence, best known for pioneering Graph Neural Networks and creating PyG, the most widely used graph learning toolkit. Previously, Jure served as Chief Scientist at Pinterest and as an investigator at the Chan Zuckerberg BioHub. His research has been widely adopted in industry and government, powering applications at companies such as Meta, Uber, YouTube, Amazon, and more. He has received top awards in AI and data science, including the ACM KDD Innovation Award.// Related LinksWebsite: https://cs.stanford.edu/people/jure/https://www.youtube.com/results?search_query=jure+leskovecPlease watch Jure's keynote:https://www.youtube.com/watch?v=Rcfhh-V7x2U~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our Slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Jure on LinkedIn: /leskovecTimestamps:[00:00] Structured data value[00:26] Breakdown of ML Claims[05:04] LLMs vs recommender systems[10:09] Building a relational model[15:47] Feature engineering impact[20:42] Knowledge graph inference[26:45] Advertising models scale[32:57] Feature stores evolution[38:00] Training model compute needs[42:34] Predictive AI for agents[45:32] Leveraging faster predictive models[48:00] Wrap up
Fresh out of Oracle AI World 2025, Chris Chelliah, Senior Vice President of Technology and Customer Strategy for Japan and Asia Pacific at Oracle, joins us to unpack how Oracle is positioning itself as the definitive enterprise AI platform across the region. He shares his career journey from a computer science geek working on distributed databases to leading technology strategy across a market representing two-thirds of the world's population. Chris explains Oracle's comprehensive four-tier AI stack—infrastructure, data platform, applications, and agentic orchestration—emphasizing how this unique full-stack ownership enables enterprises to consume AI out of the box and extend seamlessly without ripping and replacing existing systems. He highlights compelling use cases from financial fraud detection and healthcare automation to precision agriculture and energy grid optimization. Closing the conversation, Chris shares his vision for what great Oracle will look like in Asia Pacific, continuing its 50-year legacy as the behind-the-scenes platform provider powering everything from OpenAI and TikTok to global banking infrastructure. What's been consistent for Oracle is to be a platform provider that helps organizations unlock full value of their data. Today it is all about AI and unlocking the value of your data in AI, and cloud is a mandatory enabler. With AI and agentic AI, an agent is effectively an employee—it's an automated employee, a process, a workflow. You want your employees to be within your ecosystem, within your firewall. AI thrives at the edge because that's where inference happens. With AI and agentic AI, an agent is effectively an employee—it's an automated employee, a process, a workflow. You want your employees to be within your ecosystem, within your firewall. AI thrives at the edge because that's where inference happens. - Chris ChelliahProfile: Chris Chelliah, Senior Vice President of Technology and Customer Strategy for Japan and Asia Pacific at Oracle https://www.linkedin.com/in/chrischelliah/Episode Highlights: [00:00] Quote of the day by Chris Chelliah[02:10] Chris's journey from computer science to enterprise tech[03:13] Technology tinkering and Oracle's innovation culture explained[04:17] Two-thirds world population drives APJ market potential[05:06] Career advice: Find passion, own your brand[06:54] Oracle's mission: Unlocking data value for enterprises[07:58] 47,000 customers, 44% yearly consumption growth in JPAC[08:51] Oracle AI World 2025: AI changes everything announcement[09:12] Four-tier stack: Infrastructure, data, applications, agents[11:25] AI Data Platform enables production-grade AI systems[14:14] AI Agent Studio and Marketplace solve scaling challenges[15:12] Agents as higher-level abstraction for enterprise automation[16:27] Real-world AI use cases across industries shared[18:49] Multi-cloud strategy accelerates enterprise AI adoption[21:16] Partners enable scale with 100 marketplace solutions[23:01] Convergent AI: Consume applications then extend capabilities[26:51] Multi-cloud and multi-model future requires strong governance[27:31] Four-tier security isolation from infrastructure to applications[29:57] AI agents need enterprise-level data residency controls[31:02] Using AI to accelerate cloud migration skills[[33:08] Design thinking to working prototype in days[36:10] Success metrics: Beat your personal best daily[39:55] Why Oracle differs: Only four-tier stack player[43:01] What great looks like for Oracle in the Asia Pacific[45:51] Closing 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.
In today's Cloud Wars Agent and Copilot Minute, I look at how screen-aware Copilots, task-based agents, and multimodal interfaces are reshaping enterprise work — and why identity, permissions, and access guardrails now matter more than ever.Highlights00:30 — Two experts, Brian Madden, Vice President and Field Technology Officer and Futurist at Citrix, and Marco Casalaina, Vice President of Products, Core AI and an AI Futurist at Microsoft, hosted a session at this year's Microsoft Ignite conference titled “Develop Your Enterprise Playbook to Prepare for the AI of Tomorrow.”00:58 — I want to share some key takeaways. Madden laid out a seven-stage roadmap for human–AI collaboration. Steps included simple prompt and paste, the first introduction to AI; next, AI as an analyst for colleagues; followed by AI watching your screen; AI using your computer for you; AI using your computer without you watching; multi-agent AI communication; and the final step: AI-orchestrated work.01:55 — Ultimately, AI needs to work where human knowledge workers work, because the world we live in today is built for humans, and the way that AI will succeed is by operating within this user space and emulating humans in practice. Users talk to AI, and AI talks to the applications and workflows on behalf of the user.02:34 — The discussion moved on to the notion of apps dissolving into data, ultimately AI talking directly to the data without going through an application. Casalaina demonstrated this by running Anthropic's Claude on Azure and giving it the skills to create a PowerPoint. It did — without using PowerPoint. It made the slides in HTML and then converted them without ever opening the PowerPoint application. Visit Cloud Wars for more.
The promise of agentic AI has been massive, autonomous systems that act, reason, and make business decisions, but most enterprises are still struggling to see results.In this episode, host Chris Brandt sits down with Sumeet Arora, Chief Product Officer at Teradata, to unpack why the gap exists between AI hype and actual impact, and what it takes to make AI scale, explainable, and ROI-driven.From the shift toward “AI with ROI” to the new era of human + AI systems and data quality challenges, Sumeet shares how leading enterprises are moving from flashy demos to measurable value and trust in the next phase of AI. CHAPTER MARKERS00:00 The AI Hackathon Era03:10 Hype vs Reality in Agentic AI06:05 Redesigning the Human AI Interface09:15 From Demos to Real Economic Outcomes12:20 Why Scaling AI Still Fails15:05 The Importance of AI Ready Knowledge18:10 Data Quality and the Biggest Bottleneck20:46 Building the Customer 360 Knowledge Layer23:35 Push vs Pull Systems in Modern AI26:15 Rethinking Enterprise Workflows29:20 AI Agents and Outcome Driven Design32:45 Where Agentic AI Works Today36:10 What Enterprises Still Get Wrong39:30 How AI Changes Engineering Priorities55:49 The Future of GPUs and Efficiency Challenges -- This episode of IT Visionaries is brought to you by Meter - the company building better networks. Businesses today are frustrated with outdated providers, rigid pricing, and fragmented tools. Meter changes that with a single integrated solution that covers everything wired, wireless, and even cellular networking. They design the hardware, write the firmware, build the software, and manage it all so your team doesn't have to.That means you get fast, secure, and scalable connectivity without the complexity of juggling multiple providers. Thanks to meter for sponsoring. Go to meter.com/itv to book a demo.---IT Visionaries is made by the team at Mission.org. Learn more about our media studio and network of podcasts 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.
After 20+ years at some of the most important Silicon Valley tech companies like Yahoo, LinkedIn, Oracle, Informix and NerdWallet, Bhaskar today leads investment of enterprise infrastructure companies at 8 VC.Bhaskar Ghosh spent 20+ years at some of the most important Silicon Valley tech companies before moving into venture capital as a Partner at 8VC.After completing his PhD in computer science from Yale, he worked across Yahoo, LinkedIn, Oracle, Informix and NerdWallet. He brings this experience to founders building the next generation of enterprise infrastructure companies.In this episode Bhaskar explains how IT services are being reimagined for India, a country that over the last 25 years turned its skilled workforce into a global services engine. We discuss the shift happening inside workflows most people do not think about: mid-office ops, call centers, insurance, travel and HR. These are areas where thousands of people move information every day, and where AI is now good enough to take over entire workflows.Bhaskar talks about the founders already building in this space, including those buying traditional services companies and rebuilding them with AI at the core. He also explains why this new wave will not behave, scale or be valued like SaaS, because this is no longer pure software. It is the reinvention of services.If you are a founder making engineering decisions, someone curious about the less visible layers of software, or interested in people who move technology forward, this conversation with Bhaskar is for you.00:00 –Trailer03:03 – How India will reimagine IT services (TCS, Infosys)04:32 – “why now” of services06:07 – How unstructured data became easier to handle?07:53 – What LLMs can do today with high precision10:35 – Use of GenAI will increase margins in services11:54 – Front & mid offices will become more productive and lean14:30 – Will a pure services business scale anymore?15:55 – Legacy service businesses + AI-first software20:04 – Real challenge to operate and scale such businesses20:33 – 3 reasons on why SaaS companies get higher multiples?22:06 – Network-effect players win big in SaaS24:18 – Replacing software v/s replacing services26:16 – Business without inherent network effects (yet)28:22 – Is AI unlocking TAM larger than Software era?30:57 – How prosperity of a country influences growth of Co's32:50 – India's tech talent is key to India-US corridor39:36 – Deeply disruptive AI Co's will come from India43:04 – How new-age AI services companies of India should grow in US?44:39 – Current BPOs have an unfair advantage47:21 – Will older BPOs understand the importance of AI?49:22 – A Moat in outcome-based pricing can replace old businesses51:50 – Has the US ever been sensitive to cost?55:23 – The new AI-enabled services have a Palantir-risk flavour58:47 – Where to build when model Co's eat forward & backward revenue?01:06:10 – What type of founding teams are needed?01:08:10 – How founders think about GTM is changing-------------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/theneonSend us a text
AI Unraveled: Latest AI News & Trends, Master GPT, Gemini, Generative AI, LLMs, Prompting, GPT Store
Welcome to AI Unraveled (November 20, 2025): Your daily strategic briefing on the business impact of AI.Today's Highlights: Saudi Arabia signs landmark AI deals with xAI and Nvidia; Europe scales back crucial AI and privacy laws; Anthropic courts Microsoft and Nvidia to break free from AWS; and Google's Gemini 3 climbs leaderboards, reinforcing its path toward AGI.Strategic Pillars & Topics:
You ever see a new AI model drop and be like.... it's so good OMG how do I use it?
Have you ever wondered what happens when the browser stops being a simple window to the web and starts becoming the control point for how AI touches every part of enterprise life? That was the starting point for my conversation with Michael Shieh, founder and CEO of Mammoth Cyber. What followed was a detailed look at why the browser is turning into the foundation of enterprise AI and why the shift is arriving faster than many expect. Michael shared why employees already spend most of their working lives inside a browser and how this makes it the natural place for AI to support decisions, speed up routine work, and act as the interface between people, applications, and data. But we also spoke about the uncomfortable reality behind that convenience. When consumer AI browsers rush ahead with features that harvest data or request wide-reaching permissions, the trade off between speed and governance becomes harder to ignore. Michael explained how this gap leaves security teams unable to see where sensitive data is being sent or how shadow AI creeps into daily workflows without oversight. During our conversation he broke down what makes an enterprise AI browser different. We talked about policy controlled access, device trust, identity federation, and the safeguards that protect AI from hazards like indirect prompt injection. Michael also described how the Mammoth team built a multi layer security model that monitors what the AI can view, what it cannot view, and how data moves across applications in real time. His examples of DLP at the point of use, low friction controls for workers, and granular visibility for security teams showed how the browser is becoming the new enforcement boundary for zero trust. We also covered the growing tension between traditional access models like VPNs or VDI and the faster, lightweight deployment Mammoth is offering to large enterprises. Hearing Michael explain how some customers replaced heavy remote access stacks in weeks made it clear that this is more than a new product category. It hints at an early move toward AI shaped workflows running directly at the endpoint rather than through centralised infrastructure. As he looked ahead to the next few years, Michael shared why he expects the browser to operate as a kind of operating system for enterprise AI, blending native AI agents, web apps, and policy controls into a single environment. This episode raises an important question. If the browser becomes the place where AI reads, writes, and interprets information, how should enterprises think about identity, trust, and control when the pace of AI adoption accelerates again next year? I would love to hear your thoughts.
Dell Technologies has unveiled enhancements to the Dell AI Factory designed to simplify and accelerate the enterprise AI journey. These portfolio additions boost performance and automation for AI workloads while removing bottlenecks, delivering greater control with integrated, resilient on-premises infrastructure. Why it matters In today's digital landscape, organisations increasingly rely on AI to stay competitive and foster innovation. The momentum is clear with 85 percent of enterprises planning to move AI on-premises within the next 24 months. Seventy-seven per cent of those seeking AI are looking for one holistic infrastructure vendor to provide capabilities across their AI journey. Dell's expanded portfolio addresses these needs with the industry's broadest end-to-end AI portfolio designed to streamline AI adoption and deliver impactful results. Simplified and automated AI journey The Dell Automation Platform, now expanded to the Dell AI Factory, will deliver smarter, more automated experiences by deploying validated, optimised solutions with a secure framework. This approach will produce repeatable outcomes, eliminate guesswork, and help unlock the full potential of AI-driven use cases across Dell's ecosystem of technology partners. Key advancements include: Software-driven tools like the AI code assistant with Tabnine and agentic AI platform with Cohere North are now automated, getting AI workloads into production faster, streamlining operations and enhancing scalability. Dell Professional Services provide turnkey interactive AI use case pilots using real customer data to validate business value ahead of scaled investments. These expert-led pilots offer a hands-on preview for experimentation with clear success metrics and KPIs, delivering tangible ROI. Breakthrough performance and efficiency for AI workloads Enhanced Data Management: How organisations manage, secure and scale that data will separate the winners from the laggards. Updates to Dell PowerScale and Dell ObjectScale, the Dell AI Data Platform's storage engines, boost performance, scalability, and data discovery capabilities. Dell PowerScale will soon be available as an independent software license on qualified Dell PowerEdge servers like the Dell PowerEdge R7725xd. This news is the latest in Dell software-driven storage innovation following the announcement of a new software-defined Dell ObjectScale. These new Dell PowerScale and Dell ObjectScale configurations will help organisations like cloud service providers realise even greater AI performance while having the flexibility to adopt the latest server and networking technologies to meet infrastructure needs. Dell PowerScale parallel NFS (pNFS) support with Flexible File Layout will enable two-way communication between the metadata server and client, allowing for better parallel distribution of data across multiple nodes in a PowerScale cluster. Deliver significant throughput, performance gains and linear scalability with parallel I/O across multiple pathways. This update is designed to provide increased parallelism, delivering massive scalability and throughput tailored for demanding AI workflows. Dell ObjectScale AI-Optimised Search offers two complementary AI-optimised search capabilities for Dell ObjectScale storage - S3 Tables and S3 Vector. These two specialised APIs provide high-speed access to complex data stored directly on ObjectScale to support analytics and key AI workloads like inferencing and retrieval-augmented generation (RAG), empowering faster decision-making and easier storage, retrieval and search of expanding datasets. PowerEdge Innovations: Dell PowerEdge servers provide the foundation for enterprise AI, delivering faster training, distributed inference and reduced time to insights - all while offering flexible cooling options to align with diverse enterprise strategies: Dell PowerEdge XE9785 and XE9785L are purpose-built for next-generation AI and HPC workloads. The air-cooled XE97...
What happens when enterprise AI moves faster than the data foundations meant to support it? That question guided my conversation with Sumit Mehra, CTO and Co-Founder of Tredence, who joined me while travelling between customer meetings on the US West Coast. Sumit has a clear view of what is coming next, and he believes we are entering a phase he calls data Darwinism. In his view, the next stage of AI advantage will not be won by the companies with the most models or the flashiest demos, but by those with the strongest data habits. Clean, governed, connected data is now the primary fuel for autonomous decision systems, and the enterprises that fail to address this will struggle to move past surface level gains. As we unpacked this shift, it became obvious how much of the real work in AI has only just begun. Over the years, Tredence built a reputation for solving the last mile of analytics by bringing insights out of slide decks and into the hands of the people doing the work. Sumit described that early chapter with a sense of pride, but he was quick to point out that another transition is already here. With agents now influencing and making decisions across supply chains, forecasting, and customer experience, enterprises are moving from reviewing insights to reviewing decisions. That shift demands stronger data platforms, tighter governance, and a cultural adjustment that many organisations are still wrestling with. Sumit spoke openly about how teams need support to trust agent driven outcomes, and how the leadership layer plays a major role in closing the long standing divide between business and technical groups. Our discussion also moved into the rise of real time decision systems, the move toward unified data platforms, and how vertical AI is reshaping expectations inside industries that rely on precision. Whether it was supply chain visibility, marketing personalisation, or the growing need for credible governance models, Sumit emphasised that organisations can no longer rely on siloed data or fragmented strategies. As Tredence expands deeper into regulated industries through its acquisition of Further Advisory, the work ahead touches everything from finance to healthcare. It left me thinking about how ready most companies truly are for this next phase, where every agent is only as reliable as the data beneath it. Where do you stand on data Darwinism, and how prepared do you think your own organisation is for what comes next? Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.
130 IPOs from over 400 startups. IVP is now in its 18th fund, with companies like Perplexity, Glean, Slack, Figma, Twitter, Uber, and Abridge in its portfolio. Somesh Dash, general partner at the 45-year-old firm, has been part of IVP for more than 20 years.We start with something we are both passionate about, building in the US-India corridor. Somesh talks about the group of people who put the silicon in Silicon Valley, the immigrants. From Andy Grove to Elon Musk to Chennai-born Aravind Srinivas.He recalls the first time he met Aravind at a WeWork, when Perplexity had just 20 employees and a beta product or how Dylan (Founder of Figma) had the vision nobody else had on the future of design, way before ai. The early signals Somesh saw in these founders, long before any signs of massive success were visible. He also talks about the companies they missed, giants like DoorDash, OpenAI, and Anthropic.Though this seasoned investor truly believes in AI, he says the sector is due for a correction. The bubble will burst. Most Gen 1.0 AI companies are unlikely to reach billion-dollar valuations or go public. But as always in tech, the lessons from this first wave will shape Gen 2.0 companies. And the teams that understand and adapt from this early wave will build the next generation of successful AI companies. Also, when the bubble bursts, that's the time to invest. Why?Somesh Dash shares in this episode.0:00 – Trailer1:12 – Immigrants who built Silicon Valley4:27 – India's incredible contribution to the Valley5:30 – How the India–US friction will actually help6:29 – What's at stake for both countries10:42 – Where India stands in AI11:45 – First meeting with Aravind Srinivas13:47 – Why IVP invested in Perplexity two years ago17:11 – In AI, don't take product–market fit for granted18:43 – Courage to fail & double down on early wins19:36 – Why multiple investors on a cap table isn't bad22:14 – How IVP invested in Figma24:28 – IPO is a milestone, not the end25:56 – Why US public markets are not overvalued27:50 – How a VC defines startup success31:08 – The best thing about failed startups32:12 – Why IVP missed DoorDash34:54 – How IVP decides to invest or pass38:27 – The doctor who builds tech45:05 – Future of Content is honesty and vulnerability47:11 – Meeting OpenAI & Anthropic in the early days48:52 – AI “startups” with capex the size of nations49:53 – The power law in venture capital50:45 – Why we're close to an AI correction54:11 – Gen 2.0 startups are built on Gen 1.0 foundations56:45 – Will the AI bubble burst?1:01:32 – Do high valuations during peaks still make sense?1:05:04 – What keeps IVP strong for five decades1:08:11 – The Co's making IVP more bullish on India–US corridor-------------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-------------Send us a text
Most AI startups die before they even ship. Worse: they spend months building the wrong thing.This week on Zero to One, Ankur Patel (Multimodal / AgentFlow) dropped some of the clearest, most brutal (and useful) advice we've heard for anyone trying to go from zero to one in enterprise AI.
When Shreesha Ramdas left Medallia after a $6.5B acquisition he decided it was time to reinvent.At his 4th startup Lumber, before writing a single line of code, he hired a sales person and ran 200+ interviews across the industry to understand the real pain points. The interviews gave Shreesha the insight that though payments were a problem, it was neither big enough nor urgent. But it was very difficult to hire workers, and even more difficult to retain skilled craft workers. In the U.S alone 41% of construction workers will retire in the next six years, leaving a massive gap in talent and experience. As a big believer in vitamin vs. painkiller, Shreesha is now building where the pain is deepest. We discuss what truly needs to happen before building a startup, the foundation that will shape everything that follows. From his days at Yodlee during the dot-com boom to leading StrikeDeck and selling it to Medallia, he is now building again with clarity and intent for one of the most traditional industries: construction. But here's one thing that probably tells you more about Shreesha than the companies he has built and scaled. He said, “My heart beats for other founders. Startup is my world, this community is my tribe.”0:00 – Trailer1:04 – Why build tech for Construction industry?3:54 – 200+ interviews to find the real customer pain5:05 – Big believer in Vitamin vs. Painkiller6:25 – The 2 core problems in this industry7:02 – Repeat founders Know structure better7:42 – First startup during the dot-com boom8:29 – Bay Area is Disney Land for tech founders9:23 – From engineering → sales → marketing10:37 – Founders should trust the team, above everything11:55 – The survey company that banned “survey”12:17 – First startup was all about me; now it's all about team13:57 – Dream big, but execute in small steps15:47 – The cost of speed in startups16:18 – I'm a marketing-first CEO17:27 – Hire a salesperson before the product exists18:17 – Is Founder-led selling good or bad?19:37 – Mean, lean & go all in23:55 – Don't bring humility to storytelling27:25 – How the story should evolve as startups scale35:30 – How Lumber will challenge giants in construction38:53 – Do repeat founders build more in verticals?43:39 – How to hire right people from traditional industries44:29 – What wealth unlocked for Shreesha45:34 – Legacy is moving the industry forward46:38 – What the next 20 years mean for software founders49:18 – AI should remove soul-draining work51:19 – “My heartbeats for other founders”-------------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
Today's guest is Raul Monroig, People Organization Vice President for the Intercon Region at Bristol Myers Squibb. Bristol Myers Squibb manufactures prescription medicines across oncology, hematology, immunology, cardiovascular disease, and neuroscience. With a truly global footprint, the company's research, manufacturing, and commercial presence spans more than 60 countries, and with such scale, of course, comes the complexity of managing a vast workforce. Raul joins Emerj Editorial Director Matthew DeMello to discuss how global HR teams can embrace AI to tackle critical challenges in workforce development. With AI adoption accelerating at breakneck speed, it may be that focusing on a small set of essential skills like curiosity, agility, and customer service orientation — rather than training employees on everything all at once — may be the paradigm shift that helps drive organisational success. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.
You rarely meet someone who has built and sold five companies. Sachin Aggarwal is now building his sixth, Stackgen. The depth of lessons from someone who has been through that journey five times and still chooses to build again is simply unmatched. Even after five successful exits, he still builds like a first-time founder. He studies every new domain from scratch, speaks to 60 or 70 people before committing to an idea, and surrounds himself with people who are smarter than him. What stood out most is his mindset. That is what truly sets him apart. We have always been told that time is money, but he believes timing is money. Founders should time everything, including their exits because the best startups are always bought, not sold. From building his first company during the Asian Financial Crisis in Indonesia, to creating a healthcare startup that grew with Obamacare, to pioneering cloud security before it became mainstream, Sachin has mastered the art of timing. 0:00 – Trailer0:46 – From KPMG to becoming an entrepreneur2:05 – Why the best startups are bought, not sold4:30 – Does luck play a role in repeated success?5:24 – Why is timing money?6:46 – Exit at $8M ARR in just 18 months8:10 – The first exit that gave financial freedom10:14 – 26-year-old who bought an Indonesian Co.12:42 – What drives repeat founders?13:53 – Co's are either Born secure or they're not19:40 – Founders must master timing21:24 – How tech-savvy should a tech founder really be?22:35 – The right way to time your exits27:07 – How to observe new markets to build?28:30 – The process behind starting a company29:32 – How to find the right co-founders?31:53 – What really builds trust?33:05 – What founders learn building across industries35:25 – How Stackgen's founders met43:36 – Industries with the best Timing today44:41 – Where should young founders build?48:06 – Winning InMobi as a customer51:11 – What AI agents are doing at Stackgen55:14 – How Stackgen could be a billion-dollar opportunity?=-------------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
Description:AI agents from OpenAI, Google, and Anthropic promise to act on your behalf—booking flights, handling tasks, making decisions. What kind of agency do these systems actually have? And whose interests are they serving?Enterprise AI agents are already deployed in customer support, code generation, and task automation. Consumer agents—ChatGPT Agent Mode, personal task assistants—face a wider gap between marketing promises and actual capabilities.The alignment problem: agents need access to your calendar, email, and personal preferences to help you effectively. But the agent that knows you well enough to serve you is also positioned to steer you. When you delegate decisions to an agent, who decides what success looks like?To stay in touch, sign up for our newsletter at https://www.superprompt.fm
** AWS re:Invent 2025 Dec 1-5, Las Vegas - Register Here! **Learn how Anyscale's Ray platform enables companies like Instacart to supercharge their model training while Amazon saves heavily by shifting to Ray's multimodal capabilities.Topics Include:Ray originated at UC Berkeley when PhD students spent more time building clusters than ML modelsAnyscale now launches 1 million clusters monthly with contributions from OpenAI, Uber, Google, CoinbaseInstacart achieved 10-100x increase in model training data using Ray's scaling capabilitiesML evolved from single-node Pandas/NumPy to distributed Spark, now Ray for multimodal dataRay Core transforms simple Python functions into distributed tasks across massive compute clustersHigher-level Ray libraries simplify data processing, model training, hyperparameter tuning, and model servingAnyscale platform adds production features: auto-restart, logging, observability, and zone-aware schedulingUnlike Spark's CPU-only approach, Ray handles both CPUs and GPUs for multimodal workloadsRay enables LLM post-training and fine-tuning using reinforcement learning on enterprise dataMulti-agent systems can scale automatically with Ray Serve handling thousands of requests per secondAnyscale leverages AWS infrastructure while keeping customer data within their own VPCsRay supports EC2, EKS, and HyperPod with features like fractional GPU usage and auto-scalingParticipants:Sharath Cholleti – Member of Technical Staff, AnyscaleSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/
Why most enterprise AI fails — and how Cat Valverde's 4-week adoption framework shows that the fix is just 15 minutes a week.Most enterprises are stuck in AI pilot purgatory — running endless experiments that never scale. In this episode of Unchurned, Josh Schachter sits down with Cat Valverde, founder of Enterprise AI Group, to break down what's really blocking enterprise adoption.Cat shares her research-backed 15-Minute Rule, a simple 4-week framework that's doubled or tripled adoption rates — all by making AI implementation human-centered instead of tool-centered.If you're a leader trying to take AI from pilot to production, this is your playbook.What You'll Learn- Why most enterprise AI initiatives fail to scale past pilot stage- How to reduce adoption friction and create lasting behavior change- The psychological levers that improve user buy-in and learning retention- How to structure a simple 4-week rollout for any AI tool or workflow- What metrics actually matter when evaluating AI adoption successTimestamps: 0:00 – Preview & Intro1:02 – Meet Kat Valverde 1:42 – What buyers and sellers say in enterprise AI roundtables3:11 – The challenge of internal adoption 6:20 – The 15-Minute Rule; a 4-week micro-adoption framework11:45 – The psychology behind AI adoption12:18 – 2–3× adoption rates and major cost savings14:45 – Closing thoughtsKey Takeaways- Pilot fatigue is real — the biggest blocker to enterprise AI adoption isn't money, it's time and cognitive load.- The true KPI: internal adoption, not just model accuracy or ROI.- Fear ≠ just job loss. It's the fear of asking “dumb” questions or not keeping up with peers.- The 15-Minute Rule: a 4-week program built on psychology that uses micro-commitments to build momentum.- Outcomes: 2–3× higher adoption and ~50% training-cost reduction per user.---Check out the Key Takeaways & Transcripts: https://www.gainsight.com/presents/series/unchurned/---Where to Find Cat:LinkedIn: https://www.linkedin.com/in/catvalverde/Enterprise AI Group: https://www.eais.io/Where to Find Josh: LinkedIn: https://www.linkedin.com/in/jschachter/---Resources: The Power of Habit: https://www.charlesduhigg.com/the-power-of-habit
Hasan Rizvi, EVP, Database Engineering, Oracle, talks to Bob Evans in this latest episode of Cloud Wars Live. They explore the launch of Oracle AI Database 26ai, the Autonomous AI Lakehouse, and breakthroughs in multi-cloud deployment. Rizvi also discusses vector search, agentic AI, and how Oracle is simplifying complex architectures for the AI era. It's a compelling look at how Oracle is reshaping enterprise data strategy for the age of AI.Oracle's Next-Gen Data StrategyThe Big Themes:AI Demands a Modern Data Foundation: As AI shifts operations from human scale to machine speed, enterprises must ask: “Is my data foundation ready?” Without intelligent data structures, comprehensive access, real‑time performance, and strong security, organizations will struggle to compete. The introduction of Oracle AI Database 26ai is positioned as that foundation. The urgency of this shift is clear: companies that delay risk being left behind.Agentic AI and Vectors Come to the Enterprise Database: Generative AI and autonomous agents require new data types and workflows. Oracle has built vector data types and vector indexes into the database so enterprises can perform similarity search, retrieval‑augmented generation (RAG) and agent workflows directly on their private data. Further, Oracle is enabling annotations (metadata) so LLMs can understand enterprise data schemas, improving accuracy. Finally, agentic workflows (AI that takes action) are supported within the database, reducing data movement, improving performance and strengthening security.Start‑Ups and Established Enterprises Both Benefit: The case study of Retraced (a fashion supply‑chain company) underscores how smaller, agile firms are using Oracle's autonomous AI database to innovate quickly: multi‑datatype support, agentic AI, automatic scaling, and reduced operational overhead. At the same time, Oracle's heritage in mission‑critical enterprise systems means large companies with massive workloads benefit from the same platform. The point: whether you're a start‑up or a Fortune 500, the difference will be how fast you move.The Big Quote: “We really believe that in in the age of AI, where you have to move much faster, you really don't have a choice but to start simplifying your environment. Otherwise, you're going to get left behind."More from Hasan Rizvi and Oracle:Connect with Hasan on LinkedIn and learn more about Oracle AI Database 26ai. Visit Cloud Wars for more.
India is the 2nd largest startup ecosystem now. But, can it be at par with Silicon Valley?With 37 years of experience in the valley, Avanish sahai believes it can. But what made Silicon Valley the ultimate startup ecosystem? It was investors, universities and an environment where people dreamed to come live and work. And, in the last 25 years India has been going through the same transformation. And the changes are nothing short of admirable.Avanish started his career from a Mckinsey office in 1999 which ideated India's software dream, with policy changes the country needed to lead in Technology. Since then, he's held senior roles at Oracle, Salesforce, ServiceNow, and Google Cloud, and served on HubSpot's board through its journey from $500M to $2B.Avanish talks with great passion about startups that are disrupting the world today, taking lessons from small companies that took over legends who were believed to be indestructible. Even with all the hype around AI, Avanish reminds us that ultimately it's all about people. 0:00 – Trailer1:13 – 37 years in Silicon Valley2:33 – McKinsey's “Vision 2020” for India (in 1980)7:30 – When only $8 was allowed for migrants to the U.S.?9:48 – “India is the ultimate definition of a startup ecosystem”11:30 – How openness to the world has changed India13:08 – India's tech stack should go global14:09 – Why “India is hot” right now17:41 – Global disruptors building for the world19:48 – Think big and fail often24:09 – HubSpot: Single product → multi-product → platform27:11 – How today's startups can compete with legends30:45 – Salesforce had APIs from day one (in 1999)35:51 – How AI is redefining Legends vs. startups41:51 – Life as a Stanford DCI fellow42:53 – How should the world adapt for 20–25 extra years?45:29 – How to spot the right wave and players in Career45:16 – Get mentors, stay curious, and take risks48:00 – Why it's still all about PEOPLE51:53 – How AI could disrupt vertical SaaS industries-------------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
What if business intelligence didn't stop at answering what happened, but could finally explain why? In this episode of Tech Talks Daily, I sit back down with Alberto Pan, Chief Technology Officer at Denodo, to unpack how Deep Query is redefining enterprise AI through reasoning, transparency, and context. We explore how Deep Query functions as an AI reasoning agent capable of performing open-ended research across live, governed enterprise data. Instead of relying on pre-built dashboards or static reports, it builds and executes multi-step analyses through Denodo's logical data layer, unifying fragmented data sources in real time. Alberto explains how this semantic layer provides the business meaning and governance that traditional GenAI tools lack, transforming AI from a surface-level Q&A system into a trusted analytical partner. Our conversation also digs into the bigger picture of explainable AI. Deep Query reports include a full appendix of executed queries, allowing users to trace every insight back to its source. Alberto breaks down why this level of auditability matters for enterprise trust and how Denodo's support for the Model Context Protocol (MCP) opens the door to more interoperable, agentic AI systems. As we discuss how Deep Query compares with RAG models and data lakehouses, Alberto offers a glimpse into the future of business intelligence—one where analysts become guides for AI-driven research assistants, and decision-makers gain faster, deeper, and more transparent insights than ever before. So what does the rise of reasoning agents like Deep Query mean for the next generation of enterprise AI? And how close are we to a world where AI truly understands the why behind the data? Tune in and share your thoughts after listening. Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.
Welcome back to Trending in Education! This week, we dive headfirst into the accelerating world of emerging technology with Gerry White, Dean of Academic Technology for ECPI University. Gerry, an English and Music major turned tech enthusiast, shares his fascinating career trajectory and the work he is doing to keep ECPI University at the forefront of the AI revolution. We explore the current landscape of AI in higher education, noting the split between institutions that forbid its use (even reverting to blue books and oral exams) and those that are running with the technology. Gerry advocates for integrating AI responsibly, modeling its use for students, and leveraging it as a powerful tool for deeper critical thinking and better writing. We also discuss the very real dangers of over-reliance—the "training wheels problem"—where students risk losing critical thinking skills and agency by letting the AI write for them. For Gerry, the loss of human agency is perhaps the biggest threat posed by this new technology. Finally, we shift into the sci-fi lane as Gerry shares details about his recent science fiction novel, Edge of Control, which explores the dystopian possibilities of an integrated, unregulated Enterprise AI. We wrap up with practical advice for listeners to start experimenting with AI tools like ChatGPT and Gemini, and look ahead at the next horizon: Augmented Reality (AR) glasses that integrate with AI.
What makes a great venture capitalist — luck, timing, or the ability to see what others miss?Brij Bhushan (Prime Venture Partners) and Pratik Poddar (Nexus Venture Partners) talk about the long game of venture capital; the waiting, the lessons hidden in mistakes, and the emotional ride of backing founders through years of uncertainty.With Pratik, we dive into some of the biggest names in the Nexus portfolio: his first meeting with Rapido's founder before he even joined Nexus, the Meesho pitch that became a big miss, and his first call with Zepto's founders. Nexus was one of Zepto's earliest investors and has backed the company in every round since. Pratik speaks with great clarity about conviction, timing, and what truly defines great investing.Brij reflects on his decade of building Magicpin, what it means to “build the same company three times,” and how that journey reshaped the way he now works with founders. Having lived through the chaos of scaling, near-failure, and reinvention, he brings the founder's perspective back into venture capital.Together, Brij and Pratik capture the essence of the VC game — how the industry is evolving, why consensus rarely creates outliers, how real decisions are made inside funds, and why the best founders often seem “too early” rather than too late. We talk about everything that shapes a VC's everyday life, and above all why Brij and Pratik believe it's still the best job in the world.0:00 – Trailer01:59 – Biggest learnings from 10 years as a VC05:00 – Rapido as a counterintuitive bet06:49 – Meesho was a big miss10:20 – Why Venture capital is the best job?12:35 – Every meeting could be life-changing14:54 – Knowing you are NOT in an Operating role16:55 – How often are VCs wrong about market size?18:58 – Where to invest in Consumer companies?25:33 – How consumer VCs bet on behavior change27:12 – Is e-commerce truly built for young users?28:10 – How do Investors deal with Bias?30:04 – Are VCs only remembered for success stories?37:45 – Why good deals rarely come from Consensus?39:24 – The first call with Zepto's founders41:10 – How often do you meet truly exceptional founders?43:45 – Should VCs react to market shifts?46:42 – How long VC's take to make an investment decision?50:53 – How founders should approach fundraising54:27 – Can India produce 50 decacorns in the next few years?55:51 – Best way to play VC game is to have right fund size56:42 – Not Knowing is a pre-requisite for a VC1:00:41 – Exceptional founders have this superpower1:02:02 – Where Indian founders have a real edge1:05:14 – Building AI in India: local maxima or global maxima?1:09:00 – When will Indian Co's acquire Indian startups for $Billions?1:11:55 – Why Zomato & Swiggy aren't true Consumer Co's?-------------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/siddharthaa7Send us a text
On this episode of the Scouting For Growth podcast, Sabine VdL talks to Ulrich (Uli) Homann, Corporate Vice President, Microsoft, and Mark Luquire, EY Global Microsoft Alliance Co-innovation Leader, about how to build an agentic AI enterprise that doesn't just work faster, but works smarter and, most importantly, works for everyone. KEY TAKEAWAYS In the past automation has been very task driven and specific, things had to go in a certain order and you needed to know that order ahead of time. While you need some of that with generative AI, we now have a system that can help do some of that thinking, so if things change in the process along the way, you can deal with it. Now you can rethink what processes even need to exist and focus on the outcome and how to get to it in a new way. By giving everyone at EY access to generative AI a couple of years ago we learned that people were able to accomplish more more quickly. They used it as a thought-partner, used it as a way to fine tune the product they were working on. Being able to see the evolution of generative AI to now where it's coding applications on its own almost, seeing the new agent capabilities and tools, and being able to take action on its own with very little prompting, it opens the doors to possibilities and what you'll be able to do in the future. BEST MOMENTS ‘Focus on where you want to be and then rethink how you're going to get there, that's the real key.' ‘It's not just an assistant to you, providing you with information, it's actually taking on work it's actually thinking through and processing those things as well.' ABOUT THE GUESTS Ulrich (Uli) Homann is a Corporate Vice President & Distinguished Architect in the Cloud + AI business at Microsoft. As part of the senior engineering leadership team, he's responsible for the customer-led innovation efforts across the cloud and enterprise platform portfolio. Previously Homann was the Chief Architect for Microsoft worldwide enterprise services, having formerly played a key role in the business' newly formed Platforms, Technology and Strategy Group. Prior to joining Microsoft in 1991, he worked for several small consulting companies, where he designed and developed distributed systems and has spent most of his career using well-defined applications and architectures to simplify and streamline the development of business applications. Mark Luquire leads the EY organization's global efforts to co-develop innovative solutions with Microsoft and clients, driving growth and accelerating technology strategy. He oversees cross-functional teams spanning sectors and service lines, serving as a key liaison to Microsoft's product and engineering teams. Previously, Mark headed Platform Adoption for EY Global, leading enterprise-wide AI and cloud enablement, including integrating generative AI tools like EYQ, GitHub Copilot and Microsoft Copilot. He also created the first EY Global DevOps Practice and led cloud transformation efforts, making EY a leader in Microsoft Azure usage. Mark's career includes leadership roles in large healthcare enterprises and technology startups, where he established scalable operations, spearheaded digital transformation, and built high-performing global teams. ABOUT THE HOST Sabine is a corporate strategist turned entrepreneur. She is the CEO and Managing Partner of Alchemy Crew a venture lab that accelerates the curation, validation, & commercialization of new tech business models. Sabine is renowned within the insurance sector for building some of the most renowned tech startup accelerators around the world working with over 30 corporate insurers, accelerated over 100 startup ventures. Sabine is the co-editor of the bestseller The INSURTECH Book, a top 50 Women in Tech, a FinTech and InsurTech Influencer, an investor & multi-award winner. Twitter LinkedIn Instagram Facebook TikTok Email Website This Podcast has been brought to you by Disruptive Media. https://disruptivemedia.co.uk/
As agentic AI becomes a defining force in enterprise innovation, infrastructure has moved from a back-office concern to the beating heart of business transformation. On today's episode of the 'AI in Business' podcast, Ranjan Sinha, IBM Fellow, Vice President, and Chief Technology Officer for watsonx and IBM Research, joins Emerj Editorial Director Matthew DeMello to discuss the future of scalable AI infrastructure — from neuromorphic and quantum processing to open-source AI platforms built for trust and governance. Ranjan explains how enterprises are transitioning from isolated experiments to mission-critical AI applications, revealing why today's Fortune 500 leaders must reimagine compute, governance, and data pipelines to sustain automation and reliability at scale. He details IBM's breakthroughs in specialized processors, including the NorthPole neuromorphic chip and the company's roadmap for fault-tolerant quantum computing by 2029. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the 'AI in Business' podcast! If you've enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show! Watch Matthew and Ranjan's conversation on our new YouTube Channel: youtube.com/@EmerjAIResearch.
When RateGain went public, it made history as India's first SaaS listingFounder Bhanu Chopra talks about what went into that call, how investors saw it, and what it revealed about the Indian capital market. He shares how RateGain built its global presence before turning to India, and why he bet big on a $250 million acquisition.Today, travel is changing faster than ever with travellers planning differently, hotels pricing dynamically, and APAC leading the global recovery. Bhanu breaks down how RateGain powers this, from AI that talks directly to hotels and travellers, to India's hospitality industry that aims to grow 100% every year.Valued at nearly $1Billion with over $120 million in annual revenue, RateGain counts some of the biggest names in travel among its customers including Airbnb, makemytrip, Marriott, Hyatt, IHG, Expedia, and Booking.com. From taking RateGain from zero to IPO and growing revenue tenfold in a decade, Bhanu's journey offers a grounded view of what it takes to build companies that last. This episode is about more than travel or tech, it's about how India's next generation of founders can think global.0:00 — Trailer1:00 — How RateGain became India's first SaaS IPO6:31 — Was India ready for a SaaS IPO?7:31 — The $250M acquisition that cost 25% of market cap10:58 — Why Indian SaaS is listing locally14:48 — Travel is booming in APAC15:34 — RateGain's business Explained19:09 — AI that talks to consumers and hotels21:00 — Building a billion-dollar company is totally possible23:03 — Why the hotel industry is too complex for LLMs25:40 — $300M of $7.5B TAM26:45 — Indian hotel chains aims to grow at 100%29:39 — Travel trends across the US, Europe and APAC32:25 — How travel behaviour changed after COVID?33:34 — The 0→1, 1→10 and 10→100 journey37:57 — What growth means to Bhanu as a founder-------------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
Secure the Future of Multifamily AI As AI adoption rapidly advances in the multifamily industry, the importance of governance, security, and data integrity has never been greater. Don’t miss the next Multifamily Talks Live session, where Krista Hurley, Industry Principal at RealPage, will host an insightful discussion with Lance French, Chief Information Officer at RealPage, and Kris Kimmerle, VP, AI Risk and Governance at RealPage. Together, they’ll explore how multifamily leaders are navigating the steep AI value curve while protecting their operations and data. Key takeaways include: The critical role of governance and security in scaling AI for enterprise-class value. How to balance innovation with risk management to protect residents, properties, and profitability. Actionable strategies for building a secure, data-driven foundation for AI adoption. This is your chance to learn how to confidently embrace AI while maintaining the integrity and trust that your business and residents depend on. Connect with Lance, Kris and Krista on LinkedIn for more expert insights!
Secure the Future of Multifamily AI As AI adoption rapidly advances in the multifamily industry, the importance of governance, security, and data integrity has never been greater. Don’t miss the next Multifamily Talks Live session, where Krista Hurley, Industry Principal at RealPage, will host an insightful discussion with Lance French, Chief Information Officer at RealPage, and Kris Kimmerle, VP, AI Risk and Governance at RealPage. Together, they’ll explore how multifamily leaders are navigating the steep AI value curve while protecting their operations and data. Key takeaways include: The critical role of governance and security in scaling AI for enterprise-class value. How to balance innovation with risk management to protect residents, properties, and profitability. Actionable strategies for building a secure, data-driven foundation for AI adoption. This is your chance to learn how to confidently embrace AI while maintaining the integrity and trust that your business and residents depend on. Connect with Lance, Kris and Krista on LinkedIn for more expert insights!
How do the best CEOs think, prepare, and leave a lasting legacy? Shiv Shivakumar, former CEO of PepsiCo and Nokia reflects on decades of leading some of the most iconic companies. He shares insights on what makes a great leader, from the mindset required to the qualities that define people with a fighter's instinct.Shiv explains why commitment and curiosity often matter more than degrees or pedigrees, and why only about 7% of those who aspire to be CEOs actually become one. He also discusses how to navigate co-founder disagreements, knowing when a company needs you, and how to hire the right people for lasting impact.Through stories from his own journey leading companies across sectors, Shiv highlights why unit economics, honest market sizing, and investing in innovation rather than cutting prices are critical for founders. He also emphasizes the importance of understanding culture, asking the right questions, and building trust in shaping a company's success.Whether you are an aspiring founder, a manager, or simply curious about how leadership works in practice, this conversation with one of India's most experienced CEOs is for you.0:00 – Trailer0:55 – 3 qualities of people with a fighter's instinct2:40 – The biggest sin of a CEO: Past forward5:51 – How a CEO of 20 years prepare using data?7:56 – Why the information pyramid today is upside down8:55 – If it doesn't surprise competition, it's waste of time9:53 – The art of asking great questions10:28 – Brands shouldn't age: keep your core, but stay relevant12:28 – Why Shiv calls himself a Brand person?13:40 – Rich buy brands for vanity, poor for security15:03 – Manyavar: Nationalism reflected in buying choices17:15 – The Suta story18:10 – Clothing Industry is waiting for innovations19:28 – Brand person vs. Manufacturing person21:27 – Why only 7% become CEOs23:08 – CEOs Shiv admires23:47 – Be the best prepared person in any room24:09 – Always stress-test your assumptions25:04 – Sending letters to great professors of the 90s29:32 – Opportunities in India vs. abroad36:59 – Understand culture before joining any company40:11 – What young people should expect from work?41:04 – People who leave a legacy42:49 – How to hire the right people?45:43 – Be a full-number, not decimal-point manager46:25 – Never hire for degree or background48:54 – Building relationships for the company's interest51:07 – How co-founders should handle disagreements?52:56 – Be honest about your addressable market54:00 – Founders overestimate idea, underestimate rigour54:30 – ID Fresh: Founder & Opportunity57:06 – The business model in publishing needs to change58:58 – Is ghostwriting alright?1:02:00 – The old model of distribution: Nokia Story1:04:09 – Why CEOs should work across industries?1:09:12 – When you need the company vs. when it needs you1:15:31 – Future hiring: soft skills first, train hard skills-------------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:Send us a text
This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support. How is Coxwave Redefining AI Evaluation? In this episode of Eye on AI, host Craig Smith is joined by Yeop Lee, Head of Product at Coxwave. Together they explore how teams move beyond accuracy-only metrics to outcome focused evaluation with Coxwave's Align. We look at how Align measures satisfaction, trust, and task completion across chat, email, and voice, how LLM as judge pairs with human review, and how product teams search conversations to find hidden failure patterns that block adoption. Learn how leading companies design an evaluation stack that guides prompts, agents, and UX, which pitfalls to avoid when shipping updates, and which metrics matter most for success, including completion rate, CSAT, retention, and cost per resolution. You will also hear how to run experiment tracking with model and prompt change logs, set up governance that prevents regressions, and choose between SaaS and on premise deployments that meet security and compliance needs. Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI
This episode features Rob Toews from Radical Ventures and Ari Morcos, Head of Research at Datology AI, reacting to Andrej Karpathy's recent statement that AGI is at least a decade away and that current AI capabilities are "slop." The discussion explores whether we're in an AI bubble, with both guests pushing back on overly bearish narratives while acknowledging legitimate concerns about hype and excessive CapEx spending. They debate the sustainability of AI scaling, examining whether continued progress will come from massive compute increases or from efficiency gains through better data quality, architectural innovations, and post-training techniques like reinforcement learning. The conversation also tackles which companies truly need frontier models versus those that can succeed with slightly-behind-the-curve alternatives, the surprisingly static landscape of AI application categories (coding, healthcare, and legal remain dominant), and emerging opportunities from brain-computer interfaces to more efficient scaling methods. (0:00) Intro(1:04) Debating the AI Bubble(1:50) Over-Hyping AI: Realities and Misconceptions(3:21) Enterprise AI and Data Center Investments(7:46) Consumer Adoption and Monetization Challenges(8:55) AI in Browsers and the Future of Internet Use(14:37) Deepfakes and Ethical Concerns(26:29) AI's Impact on Job Markets and Training(31:38) Google and Anthropic: Strategic Partnerships(34:51) OpenAI's Strategic Deals and Future Prospects(37:12) The Evolution of Vibe Coding(44:35) AI Outside of San Francisco(48:09) Data Moats in AI Startups(50:38) Comparing AI to the Human Brain(56:07) The Role of Physical Infrastructure in AI(56:55) The Potential of Chinese AI Models(1:03:15) Apple's AI Strategy(1:12:35) The Future of AI Applications 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
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
© 2020-2025 Ivy Podcast Discovery LLC
