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TechSurge: Deep Tech Podcast: Daily Summaries Delivered
by Celesta Capital | Deep Tech Venture Capital Firm
The TechSurge: Deep Tech VC Podcast explores the frontiers of emerging tech, geopolitics, and business, with conversations tailored for entrepreneurs, technologists, and investment professionals. Presented by Celesta Capital, and hosted by Founding Partners Nic Brathwaite, Michael Marks, and Sriram Viswanathan. Each discussion delves into the intersection of technology advancement, market dynamics, and the founder journey, offering insights into the vast opportunities and complex challenges ahead. Episode topics include AI, data center transformation, blockchain, cyber security, healthcare innovation, VC investment trends, tips for first-time founders, and more. Tune in to hear directly from Silicon Valley leaders, daring new founders, and visionary thinkers. Past guests include investor Vinod Khosla, former PepsiCo CEO Indra Nooyi, the Global Head of McKinsey, and executive leaders from Microsoft, OpenAI, and other leading tech.
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- Yesterday1h 11m
The Moving Bottleneck: Networking, Power, Memory, and the Race to Win AI
Artificial intelligence is often discussed through models and GPUs. This episode looks beneath that surface, at the power delivery and networking required to make AI work at scale.Host Sriram Viswanathan speaks with Rajiv Khemani, a serial deep tech entrepreneur whose career has tracked several major infrastructure cycles: internet networking, cloud switching, blockchain compute and now AI networking. Khemani reflects on his early work at NetBoost and Intel, his operating role at Cavium, and the founding of Innovium, which Marvell agreed to acquire for $1.1 billion in 2021. He also explains how work on low-power blockchain silicon led his team toward the infrastructure demands created by generative AI.The discussion examines why incumbents often overlook emerging markets, why purpose-built hardware can outperform systems inherited from an earlier technology cycle, and how founders decide whether to keep financing a company or sell while the outcome remains attractive. Khemani describes the concentration risk of selling to a small number of hyperscalers, the fragility of semiconductor supply chains, and why leading-edge chip development now demands much larger balance sheets.The conversation then turns to AI’s emerging bottlenecks. Large models require many accelerators to operate as one computer, making low-latency scale-up and scale-out networks central to performance. The episode explores heterogeneous compute, open networking standards, memory scarcity, AI’s growing electricity demand, and the competition between AI and Bitcoin mining for energy. Speaker Profiles and LinksSriram Viswanathan: Founding Managing Partner, Celesta Capital — https://www.linkedin.com/in/onesriram/ Rajiv Khemani: Co-founder and Executive Chairman, Upscale AI; deep-tech entrepreneur and IIT Delhi alumnus LinkedIn: https://www.linkedin.com/in/rajivkhemani/ Profile and contribution to the IIT, Delhi, Yardi School of Artificial Intelligence : https://scai.iitd.ac.in/rajiv-khemani References Mentioned and Further ReadingUpscale AI : https://upscaleai.com/ Upscale AI Launch Announcement : https://upscaleai.com/press-release/ Velaura AI : https://velaura.ai/ Acquisition of Innovium and cloud data-centre switching rationale, Marvell: https://www.marvell.com/company/newsroom/marvell-to-acquire-innovium-accelerates-cloud-growth-with-expanded-ethernet-switching-portfolio.html Cavium combination and infrastructure semiconductor strategy, Marvell: https://www.marvell.com/company/newsroom/marvell-and-cavium-to-combine-creating-an-infrastructure-solutions-powerhouse.html Energy and AI, International Energy Agency: https://www.iea.org/reports/energy-and-aiEnergy demand from AI, International Energy Agency: https://www.iea.org/reports/energy-and-ai/energy-demand-from-ai Tokenisation in the context of money and other assets, Bank for International Settlements : https://www.bis.org/cpmi/publ/d225.pdf Leveraging tokenisation for payments and financial transactions, Bank for International Settlements : https://www.bis.org/publ/othp92.pdf Collective communication for clusters exceeding 100,000 GPUs, Meta researchers : https://arxiv.org/abs/2510.20171 Load balancing for AI training workloads, UC Berkeley researchers : https://arxiv.org/abs/2507.21372 Reliability in large-scale machine-learning clusters : https://arxiv.org/abs/2410.21680 Bitcoin: A Peer-to-Peer Electronic Cash System : https://bitcoin.org/bitcoin.pdf Timestamps:</
- 2 weeks ago1h 9m
Physical AI, Quantum, and Bio-Innovation: Inside Canada’s Research Frontier
Canada produces world-leading science, engineering, and AI research. So why does so much of that research still commercialize outside of Canada?In this episode of TechSurge, host Nic Brathwaite puts that question to four leaders at two of Canada's top research universities: Mary Wells (Dean of Engineering) and Chris Houser (Dean of Science) at the University of Waterloo, and Heather Sheardown (Dean of Engineering) and Gianni Parise (VP Research) at McMaster.At Waterloo, Mary Wells traces how the university's origin produced one of the world's most influential co-op programs and a creator-owned IP policy that lets inventors keep their ideas, making the school a talent engine for global tech. The group digs into Canada's AI paradox, foundational research and talent but far less of the economic value, and what quantum, robotics, and advanced manufacturing show about getting research to market.McMaster runs a different model, built on health sciences, nuclear research, and problem-based learning. Heather Sheardown explains the McMaster Method and why it matters in an AI-shaped future. Gianni Parise argues for commercialization as a core university function, with work spanning AI-assisted drug discovery, inhaled vaccines, critical-mineral-free motors, and a campus nuclear reactor that supplies much of the world's iodine-125 for prostate cancer treatment. They also unpack Fusion Pharmaceuticals, the McMaster spin-out acquired by AstraZeneca, and what it reveals about university commercialization.Together, these conversations ask what universities must become in an era defined by AI, deep tech, national competitiveness, and the urgent need to move ideas from the lab into the world.Sign up for our newsletter at techsurgepodcast.com for updates on upcoming TechSurge Live Summits and future episodes.Speaker Profiles and LinksMary Wells - University of Waterloo Profile: https://uwaterloo.ca/engineering/about/dean-engineerinChris Houser - University of Waterloo profile: https://uwaterloo.ca/earth-environmental-sciences/profile/chouserHeather Sheardown - McMaster Engineering profile: https://www.eng.mcmaster.ca/chemeng/faculty/dr-heather-sheardown/Gianni Parise - McMaster Experts Profile: https://experts.mcmaster.ca/people/parisegChapters: 0:00 Highlights0:56 Welcome 2:39 Waterloo’s origin story 4:51 Creator-owned IP and the Waterloo model 7:42 The Co-op Flywheel 8:56 Canada’s AI paradox: world-class research, slower domestic value capture 10:21 AI, Regulation, Trust, and Canadian Competitiveness 17:09 Rethinking the PhD for Commercialisation 21:43 Inside Waterloo’s labs 30:14 What Waterloo wants to be in ten years: builders of the country 32:39 Meet McMaster: health sciences, nuclear capability, and research intensity 34:12 The McMaster Method 35:11 Research, Health, and Commercialisation 40:45 McMaster Labs: Heat, Motors and Health Innovation 47:13 Bioinnovation, Nuclear Research and Fusion Pharmaceuticals 58:43 The university of 2035: less lecture, deeper societal impact References Mentioned and Further ReadingUniversity of Waterloo Policy 73 - Intellectual Property Rights: https://uwaterloo.ca/secretariat/policies-procedures-guidelines/policies/policy-73-intellectual-property-rightsUniversity of Waterloo - Our IP policy: https://uwaterloo.ca/entrepreneurship/our-ip-policyUniversity of Waterloo Co-op programs: https://uwaterloo.ca/future-students/co-opUniversity of Waterloo - Academy of Research Commercialization: https://uwaterloo.ca/conrad-school-entrepreneurship-business/graduate-students/academy-research-commercialization-arcOpen Quantum Design: https://openquantumdesign.org/Institute for Quantum Computing, University of Waterloo: https://uwaterloo.ca/institute-for-quantum-computing/CIFAR - Pan-Canadian Artificial Intelligence Strategy: https://cifar.ca/ai/Government of Canada / ISED - Pan-Canadian
- 4 weeks ago1h 18m
Google's Chief Technologist on Intelligent Search in the Age of AI
TechSurge is sponsored by Notion. From product roadmaps to investor updates, Notion is where modern teams plan, write, and ship together. Get started at http://notion.dev/techsurge.Search began as a way to find pages. AI is turning it into a way to ask, reason, decide, and act.Search has always been more than a technical problem. It is a way of organising knowledge, connecting intent with information, and increasingly, turning questions into actions. In the age of artificial intelligence, that basic function is being redefined.In this episode of TechSurge, host Sriram Vishwanath speaks with Prabhakar Raghavan, Chief Technologist at Google, about the long arc of search: from the early web and link analysis to knowledge graphs, language models, transformers, Gemini, and the unresolved question of how AI will change the way we find, trust, and use information.Prabhakar reflects on his career as a computer scientist, researcher, and technology leader, beginning with his time at IBM Research, where he worked on algorithms, optimization, databases, and early information retrieval. He explains how the explosion of unstructured data on the web created a new class of technical and economic problems. Search was not simply about indexing pages; it was about imposing structure on a chaotic information environment and building mechanisms that could connect supply, demand, relevance, authority, and trust.The conversation traces how early search evolved through link analysis and PageRank, drawing on ideas from scholarly citation analysis, graph theory, and algorithmic ranking. Prabhakar describes why authority and trust became central to search as the web grew, and why users themselves changed alongside the technology. As search engines became more capable, people moved from looking for simple webpages to asking richer, more contextual questions that required intent understanding rather than mere document retrieval.Sriram and Prabhakar then explore the transition from classical search to AI-infused products. Through examples such as Gmail Smart Reply, Smart Compose, Google Drive recommendations, and knowledge graphs, Prabhakar shows how prediction, context, and language modelling were already reshaping user experiences well before the current generative AI wave. These systems were early signals of a broader shift: computers moving from retrieving information to anticipating what users might need next.The episode also offers a technical tour of the major algorithmic milestones that led to today’s AI systems, including deep learning, sequence-to-sequence models, attention mechanisms, transformers, and the compute architectures needed to train and serve large models. Prabhakar explains why attention changed the quality of language modelling, why AI systems appear increasingly conversational, and why compute remains one of the central constraints in the field.At the heart of the discussion is the central tension facing search today: if AI systems can generate answers directly, what becomes of search as we know it? Prabhakar does not frame AI as the end of search, but as its next transformation. The future of search may be less about finding a page and more about understanding intent, synthesising knowledge, reasoning through ambiguity, and helping users complete complex tasks.The conversation closes with deeper questions about AI world models, hallucination, test-time compute, diffusion models, recursive self-improvement, theorem proving, and whether AI systems can ever reason with the same grounded understanding as humans. For Prabhakar, the challenge is not only to build more powerful models, but to understand their limits, failure modes, and relationship to truth.This episode is a wide-ranging exploration of how search became one of the defining technologies of the internet age—and how artificial intelligence may now force us to rethink what it means to search at all.Sign up for our newsletter at techsurgepodcast.com for updates on upcoming TechSurge Live Summits and future episodes.Links:Prabhakar Raghavan - Google Research profile: https://research.google/people/prabhakarraghavan/?&type=googlePrabhakar Raghavan - Google blogs and writing: https://blog.google/authors/prabhakar-raghavan/Refer
- Jun 16, 202653 min
Battle for the AI Data Center: Deep Dive on the Semiconductor Supercycle
Semiconductors have moved from the background of the technology stack to the center of the AI economy. What used to be a specialized industry discussed mostly by engineers and investors is now shaping the speed, cost, and strategic direction of modern computing.In this episode of TechSurge, host Michael Marks speaks with Stacy Rasgon, Managing Director and Senior Analyst covering U.S. semiconductors and semiconductor capital equipment at Bernstein Research. Stacy has spent years analyzing the chip industry across cycles, but argues that the current moment feels different in scale: AI demand has created an unprecedented scramble for compute, memory pricing has surged, and companies across the stack are being forced to rethink capacity, architecture, and capital allocation.The conversation explains the 4 different kinds of semiconductor cycles—supply, inventory, product, and demand — and why Stacy believes the industry is currently in a demand cycle of unusual magnitude. The discussion also unpacks the distinction between DRAM and NAND, why high-bandwidth memory is becoming strategically central to AI systems, and how the physical realities of wafer capacity and silicon area are constraining supply in ways the broader market often misses.Stacy and Michael also discuss the hardware economics behind the current boom, with Michael pressing Stacy on why compute remains so scarce and how companies are improving performance through packaging and system design. Michael then moves the conversation beyond market headlines to the core business questions: who is actually paying for this compute, which use cases are generating real revenue, and whether AI spending is creating durable economic value or simply shifting costs elsewhere. Together, these questions highlight two of the episode's clearest insights: coding may be one of the earliest AI applications with meaningful willingness to pay, and inference, not training, is the real test of whether the current buildout becomes a lasting business or just another expensive wave of infrastructure.Stacy explains the concentration of power among the major wafer fabrication equipment players, the rise of ASICs as a meaningful share of AI silicon, Broadcom's rapidly expanding AI opportunity, and the growing role of Chinese companies as new entrants, especially in memory and semiconductor equipment. Along the way, the conversation asks the defining question facing the sector: is this just another semiconductor upswing, or the first true supercycle the industry has seen? Stacy believes that this might be the biggest supercycle he has seen in his career.Sign up for our newsletter at techsurgepodcast.com for updates on upcoming TechSurge Live Summits and future episodes.Links:Stacy Rasgon on LinkedIn: https://www.linkedin.com/in/stacy-rasgon-6924963Bernstein: https://www.alliancebernstein.com/corporate/en/home.htmlReferences Mentioned During the DiscussionNVIDIA Blackwell Platform: https://www.nvidia.com/en-us/data-center/blackwell-platform/High Bandwidth Memory (HBM) overview from Micron: https://www.micron.com/products/memory/hbmDRAM overview from IBM: https://www.ibm.com/think/topics/dramNAND flash overview from IBM: https://www.ibm.com/think/topics/nand-flash-memoryFurther ReadingMcKinsey on the semiconductor industry outlook: https://www.mckinsey.com/industries/semiconductors/our-insights/the-semiconductor-industry-in-2025Semiconductor Industry Association: 2025 State of the U.S. Semiconductor Industry: https://www.semiconductors.orgNVIDIA on the Blackwell architecture and AI infrastructure roadmap: https://www.nvidia.com/en-us/data-center/blackwell-platform/Broadcom AI investor materials and infrastructure commentary: https://investors.broadcom.comASML on lithography and advanced chip manufacturing: https://www.asml.com/en/technologyMicron on HBM and AI memory demand: https://www.micron.com/products/memory/hbmChapters<p
- Jun 2, 20261h 28m
In-Orbit Manufacturing, AI Data Centers, and the New Space Economy with MIT’s Ariel Ekblaw
For most of human history, space has been a place we visited. The next chapter may be about building there.For decades, space was the domain of governments, astronauts, and science fiction. Today, falling launch costs, reusable rockets, and a new generation of ambitious founders are turning orbit into something else entirely: a place to build. The question is no longer whether humanity can construct large-scale infrastructure in space, but what we should build first—and why.In this episode of TechSurge, host Sriram Vishwanath speaks with Dr. Ariel Ekblaw, Founder and CEO of Aurelia Institute, Research Affiliate at MIT’s Space Exploration Initiative, and founder of Rendezvous Robotics. Ariel has spent her career exploring one of the most fundamental challenges of the emerging space economy: how to build structures in orbit that are far larger than anything that can fit inside a rocket.Ariel explains the origins of TESSERAE, her pioneering work on autonomous self-assembling space architecture, and how ideas borrowed from biology, swarm intelligence, and modular construction could unlock a future of massive solar arrays, communications infrastructure, orbital laboratories, and eventually human habitats in space.The conversation explores the rapidly emerging market for in-orbit infrastructure, including AI data centers in space, space-based solar power, and the technologies needed to support a permanent industrial presence beyond Earth. Ariel breaks down the engineering realities behind these ideas—why cooling data centers in space is harder than most people assume, how autonomous assembly could solve the scale problem, and why the future of orbital infrastructure may look more like a business park than a collection of standalone satellites.Sriram and Ariel also discuss the broader implications of humanity’s return to space: the economics unlocked by reusable launch systems, the opportunities created by dramatically lower transportation costs, and the second-order innovations that may emerge from building an industrial ecosystem in orbit. Along the way, they examine space debris, stewardship of the orbital commons, artificial gravity, and what it will take to make long-term human habitation in space viable.At the heart of the discussion is Ariel’s belief that space is not an escape from Earth’s problems, but a tool for solving them. Whether through advanced manufacturing, new energy systems, biotechnology research, or entirely new industries, she argues that the next era of space exploration should be focused on improving life here at home.Sign up for our newsletter at techsurgepodcast.com for updates on upcoming TechSurge Live Summits and future episodes.Links:Ariel Ekblaw on LinkedIn:https://www.linkedin.com/in/arielekblawAurelia Institute:https://www.aureliainstitute.orgRendezvous Robotics:https://www.rdvrobotics.comMIT Space Exploration Initiative:https://www.media.mit.edu/groups/space-exploration/overview/How Aurelia is Designing Self-Assembling Space Stations: https://www.fastcompany.com/91242689/how-the-aurelia-institute-is-designing-a-self-assembling-space-stationOverview Energy (Space-Based Solar Power): https://www.overviewenergy.comStarCatcher Industries (Space-to-Space Power Transmission): https://www.starcatcherindustries.comImpulse Space (Orbital Transportation): https://www.impulsespace.comReferences Mentioned During the DiscussionEarthrise - The Apollo 8 Photograph: https://www.nasa.gov/image-article/apollo-8-earthrise/Carl Sagan’s “Pale Blue Dot”: https://www.planetary.org/worlds/pale-blue-dotBuckminster Fuller Institute: https://www.bfi.orgWatch Ariel’s Talks & InterviewsAurelia Institute YouTube Channel: https://www.youtube.com/@AureliaInstituteAriel’s TED Talk: https://youtu.be/IHrGK3Mu5K4?si=QwGHq1BEoB-QMUjkSpace Business Podcast - Self-Assembling Space Habitats with Ariel Ekblaw: <a href="https://spacebusiness.podbean.com/e/137-self-assembling-space-habitats-ariel-ekblaw-founder-ceo-aurelia-institute/
- May 21, 202647 min
The U.S. – China Deep Tech Arms Race
For years, the United States told itself a reassuring story: China could manufacture and copy, but it couldn't innovate. That story is no longer credible. From DeepSeek's compute-efficient AI model to BYD's dominance of the global EV market, China is producing both volume and quality across sectors that matter. The question is no longer whether China can compete — it's whether the United States is playing its own hand well.In this episode of TechSurge, host Michael Marks speaks with Vivek Chilukury, Senior Fellow at CNAS, where he focuses on U.S.–China technology competition, AI policy, and digital geopolitics. Vivek's path from counter-terrorism work at the State Department to tech policy in the Senate gives him an unusually grounded perspective on how government actually functions — and where it keeps failing itself.Vivek and Michael work through the full competitive landscape: the wake-up moments that shifted Washington's focus from manufacturing to technology dominance, why the dual-use nature of advanced technology has pulled the national security community into conversations once left to industry, and what Made in China 2025 actually achieved — and where it fell short.The conversation goes deep on America's policy toolkit: what the CHIPS Act accomplished and why it wasn't enough, how export controls on advanced semiconductors are working and what they're missing, and why Washington is far too weighted toward restriction at the expense of the "run faster" side of the equation. Vivek is also candid about what DeepSeek really tells us — not just about Chinese innovation, but about the gap between building a model and deploying AI at scale.They also explore the global dimension: China's "easy button" approach to technology exports, what the U.S. AI exports program is trying to do in response, the rise of "AI sovereignty" movements from Brussels to Delhi, and why the talent and immigration decisions of the past year amount to a serious self-inflicted wound.The United States still holds the best hand in the world for this competition. The question Vivek keeps returning to is whether we're playing it well — and right now, his honest answer is no.Sign up for our newsletter at techsurgepodcast.com for updates on upcoming TechSurge Live Summits and future Season 2 episodes.Episode Links:Connect with Vivek: https://www.linkedin.com/in/vivekchilukuri/Learn more about CNAS: https://www.cnas.orgTimestamps:[02:11] Wake-Up Calls: Chips & 5G[04:17] Atoms vs Bits in AI[07:27] China's Innovation Surge[10:57] Systems Capital vs Planning[14:14] Made in China 2025 Scorecard[17:23] US Tools: Chips & Controls[24:12] DeepSeek & Compute Scarcity[26:47] Energy Constraints & Scaling[29:01] AI Exports & the Easy Button[32:43] Allies & AI Sovereignty[36:13] Talent Flows & Immigration[39:04] Beyond AI: The Biotech Frontier[43:30] Founder Advice: Global South[45:20] Wrap-Up & Key Takeaways
- May 7, 202657 min
Rare Earth Rush: Strategic Minerals and Tech's New Resource Wars
For thirty years, the United States largely ignored critical minerals. We mined less, processed less, and stockpiled less — while China quietly built the most dominant mineral supply chain in modern history. When China imposed rare earth export restrictions in 2024, manufacturers from Detroit to Tokyo scrambled. The invisible inputs powering electric vehicles, semiconductors, AI data centers, and defense systems had suddenly become visible — and vulnerable.In this episode of TechSurge, host Sriram Viswanathan speaks with Dr. Gracelin Baskaran, Director of the Critical Mineral Security Program at the Center for Strategic and International Studies. A mining economist with over a decade of field experience across Africa, Latin America, Asia, and the Middle East, Gracelin is one of the sharpest minds working on how the world secures the raw materials that make advanced technology possible.Gracelin brings a clarifying perspective to a topic that is often framed as a geopolitical contest: the real challenge, she argues, is economic. Until mining in allied countries is genuinely profitable — until the capital, energy infrastructure, processing technology, and policy stability are all in place — supply chain security remains aspirational, regardless of how many executive orders get signed.Sriram and Gracelin work through the full landscape: what critical minerals actually are and why the term matters, how China built its dominance not just through geology but through industrial strategy and foreign policy, and why the 29-year average timeline from mineral discovery to production creates a fundamental tension with the pace of technology investment. They examine the gap the CHIPS Act left unfilled, the case for aggregating allied demand to change the economics of new mines, and what tech CEOs are dangerously wrong to assume about their own supply chains.They also dig into the emerging policy architecture: Project Vault as a demand-driven civilian stockpile, the critical minerals ministerial that brought 55 countries to Washington, and the role of recycling and AI-driven exploration in accelerating a supply chain that cannot be built on mining alone.Ultimately, Gracelin argues that America's greatest advantage is not its geology — it is its capacity to innovate. But innovation without investment, and investment without durable policy, will not be enough. The window is open. The question is whether the commitment holds.If you enjoy this episode, please subscribe and leave us a review on your favorite podcast platform.Sign up for our newsletter at techsurgepodcast.com for updates on upcoming TechSurge Live Summits and future Season 2 episodes.Episode Links:Connect with Gracelin: https://www.linkedin.com/in/gracelinbaskaran/ Learn more about CSIS Critical Minerals Security Program: https://www.csis.org/programs/energy-security-and-climate-change-program/critical-minerals-securityTimestamps:[00:00] China’s Rare Earth Wake-Up Call[02:57] The Origin Story Behind Gracelin[05:02] What “Critical Minerals” Actually Means[08:17] Saudi Arabia’s Mineral Strategy Playbook[10:33] Why Economics Matters More Than Geology[13:54] Why New Mines Take Decades to Build[16:42] China’s Supply Chain Dominance Explained[24:57] America’s Workforce and Processing Problem[27:05] Innovation vs Scale in the Mineral Race[29:54] Can the US Rebuild Mineral Processing?[33:10] Startups, Capital, and the Mining Challenge[35:02] Belt and Road, Security, and Global Supply[41:19] The CHIPS Act’s Missing Ingredient[46:21] The Policy Blueprint for Critical Minerals[51:59] Project Vault Explained[53:54] Rapid-Fire Takeaways and Final Reality Check
- Apr 16, 202656 min
The US Crypto Awakening
For years, crypto policy in the United States was defined less by clear rules than by the threat of enforcement. Startups and institutions building in the space operated in a gray zone: no clear guidance, no path to compliance, and always the possibility of a regulatory hammer coming down. In 2025, that began to change.In this episode of TechSurge, host Sriram Viswanathan speaks with Commissioner Hester Peirce of the U.S. Securities and Exchange Commission — one of Washington's most closely watched voices on digital asset policy. Known informally as "Crypto Mom" for her consistent advocacy that markets work best with clear rules and room to innovate, Commissioner Peirce was designated in 2025 to lead the SEC's first Crypto Task Force, signaling a more structured, collaborative approach to digital asset regulation.Commissioner Peirce brings a rare perspective: a regulator who believes that ambiguity does not protect investors — it protects incumbents and rewards bad actors. In this conversation, she explains what has actually changed in 2025, what it means for companies building in crypto, and what it will take to make this regulatory progress durable beyond any single administration.Sriram and Commissioner Peirce work through the full landscape: why "crypto" is not one thing but several, how the SEC thinks about Bitcoin as a commodity, what tokenization of traditional securities actually requires, and where real policy gaps remain. They also examine the role of stablecoins and CBDCs, the tension between investor protection and permissionless innovation, and how vertical integration in crypto markets raises the same questions the financial system has always faced — just with new architecture underneath.Ultimately, Commissioner Peirce argues that the best regulatory framework is one that lets markets identify where technology is useful, enforces rules fairly and consistently, and makes enough room for people to build real things that solve real problems. Once those products exist and are woven into daily economic life, she argues, they become durable — regardless of who is in office.If you enjoy this episode, please subscribe and leave us a review on your favorite podcast platform.Sign up for our newsletter at techsurgepodcast.com for updates on upcoming TechSurge Live Summits and future Season 2 episodes.Episode LinksConnect with Hester: https://x.com/HesterPeirce Learn more about the SEC Crypto Task Force: sec.gov/crypto Timestamps00:00 Permissionless Innovation 02:05 Crypto Basics Explained 09:25 State of US Crypto Policy 11:13 Howey Test and Tokenization14:25 Crypto as Strategic Advantage23:17 2025 Policy Turning Point 30:06 DeFi Consumer Protection 40:01 Bitcoin’s Unique Role
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About TechSurge: Deep Tech Podcast
The TechSurge: Deep Tech VC Podcast explores the frontiers of emerging tech, geopolitics, and business, with conversations tailored for entrepreneurs, technologists, and investment professionals. Presented by Celesta Capital, and hosted by Founding Partners Nic Brathwaite, Michael Marks, and Sriram Viswanathan. Each discussion delves into the intersection of technology advancement, market dynamics, and the founder journey, offering insights into the vast opportunities and complex challenges ahead. Episode topics include AI, data center transformation, blockchain, cyber security, healthcare innovation, VC investment trends, tips for first-time founders, and more. Tune in to hear directly from Silicon Valley leaders, daring new founders, and visionary thinkers. Past guests include investor Vinod Khosla, former PepsiCo CEO Indra Nooyi, the Global Head of McKinsey, and executive leaders from Microsoft, OpenAI, and other leading tech.
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