3334: How Phison and StoreOne Are Making AI Training More Accessible

What if the songs we love and the artists behind them could finally be compensated fairly, across every platform, every play, and every country? In today’s episode, I sit down with Michael Huppe, President and CEO of SoundExchange, to unpack how this music tech nonprofit is challenging the very foundations of how royalties are calculated and distributed. Michael shares how SoundExchange, which has now distributed over $12 billion to artists and rights holders, is not just administering royalties but actively shaping the policies and technologies that govern the future of music. We explore their groundbreaking use of AI for fraud detection and royalty matching, as well as the advocacy behind the American Music Fairness Act, a long-overdue effort to ensure artists are paid for terrestrial radio plays, a right still denied in the US but granted nearly everywhere else. The conversation turns toward the growing tension between innovation and creator protection in the age of generative AI.  Michael discusses how SoundExchange is balancing these forces by backing ethical standards like the Human Artistry Campaign and lobbying for policies that prioritize consent, credit, and compensation. He also touches on fascinating use cases for AI in music, such as voice localization, signature sound licensing, and even resurrecting voices of beloved artists like Randy Travis. We also discuss SoundExchange’s vision for the future, one where its expertise in large-scale, data-driven payouts could help solve the thorny question of compensating artists whose works are used to train generative AI models. From indie musicians to global superstars, the impact of this work is vast, nuanced, and increasingly urgent. So, how do we build a future where technology and creativity can coexist and both thrive? And who’s making sure the voices behind our favourite tracks aren’t lost in the noise of innovation? I’d love to hear your thoughts. Are we doing enough to protect artists in the digital era? Let me know  

After meeting on the IT Press Tour,  I enjoyed a conversation with Michael Wu, President and General Manager of Phison US, about the revolutionary advances in AI-enabled storage technology.  We begin by exploring Phison's AdaptivePlus platform and its integration with StoreOne's AI solution, making AI training more accessible and affordable for businesses. We also discuss the technical innovations behind their storage-based AI acceleration, including their new E28 controller and Pascari SSDs.  Finally, we discuss the future of AI workloads and how Phison's technology is preparing to handle models with up to 2 trillion parameters. This episode is packed with insights for IT leaders, business executives, and anyone interested in the intersection of storage technology and artificial intelligence.

In a candid conversation with Zendesk CTO Adrian McDermott, it's become clear that enterprise AI has reached a pivotal moment. We're witnessing the end of AI theater and the emergence of practical platforms delivering real business value.   "We're moving from chapter one to chapter two of the application of generative AI," McDermott explains. "It's not just party tricks anymore - it's platforms. And we're really building things that have value and meaning." The Rise of Platform Thinking The shift from isolated AI features to comprehensive platforms marks a significant evolution in enterprise technology. Companies are no longer satisfied with flashy demonstrations - they demand measurable outcomes and clear ROI. This transformation is evident in Zendesk's new resolution platform, which integrates multiple AI capabilities into a cohesive system. The New Economics of AI Implementation Zendesk has pioneered outcome-based pricing for AI agents in the customer experience industry - a significant departure from traditional seat-based pricing models. This approach aligns vendor success directly with customer outcomes.   "You should really be able to run a model that would prove and predict the ROI upfront," McDermott notes, highlighting the increasing sophistication of AI implementation. Customers now expect vendors to demonstrate clear business value before deployment. Voice: The Critical Escalation Channel Despite predictions of voice's decline, it remains crucial in an AI-first world. McDermott explains: "In a world of automation, the escalation channel is voice, and you need it to be tightly integrated."   The future of voice in customer service is being reimagined through: Seamless integration with AI systems Warm handoffs between digital and voice channels Enhanced context preservation across interactions Real-time analytics and support The Resolution Platform Framework Zendesk's resolution platform represents a comprehensive approach to customer service, incorporating: Customer-facing AI agents Agent copilot systems Automated content generation Continuous analysis and quality assurance Unified governance and measurement Looking Ahead: The iPhone Moment? McDermott poses a crucial question: "Are we building Windows Mobile on top of generative AI, or is there innovation and disruption to come?" This reflection suggests we're still in early stages, with significant disruption ahead. Key Takeaways Enterprise AI has matured beyond demonstrations to delivering measurable outcomes Platform approaches are replacing point solutions Voice remains critical in an AI-first service strategy Economic alignment between vendors and customers is essential Continuous innovation and adaptation are necessary The shift from AI theater to practical platforms marks a new era in enterprise technology. Organizations must now focus on building comprehensive, outcome-driven AI strategies rather than chasing individual features or capabilities.

As AI continues to dominate headlines and crypto continues to evolve behind the scenes, the real story may lie in their convergence. In this episode of Tech Talks Daily, I sat down with Dan Kim from Coinbase to discuss how these two technologies are shaping the future of digital commerce and development. Dan leads the Coinbase Developer Platform, a project focused on simplifying blockchain development for millions of developers worldwide. He shared how the platform abstracts away complexity through familiar SDKs and APIs, removing the need for deep blockchain expertise. This isn’t just about making it easier to code on-chain. It’s about opening the door for new kinds of applications, many of which are being driven by AI. We dug into the emerging concept of "agentic commerce," where AI agents can autonomously carry out transactions using blockchain infrastructure. These agents are now capable of acting on our behalf, making purchases and managing digital assets within defined parameters. This shift is already changing how developers think about building tools for e-commerce, travel, and digital services. Dan also discussed the evolving role of creators in this new landscape. Blockchain technology combined with AI is creating new ways to monetize content, build applications, and launch experiences without relying on traditional platforms. He even shared a personal example—his own AI-powered music project that turns complex crypto topics into relatable Top 40 tracks. From the reawakening of HTTP’s long-forgotten 402 payment code to the real-world implications of AI agents handling financial transactions, this conversation revealed just how quickly things are moving. For developers and business leaders alike, the fusion of AI and crypto is no longer speculative. It’s here, and it’s changing how we interact, build, and pay.

What happens when a customer service platform stops thinking like a vendor and starts operating like a partner? In this episode of Tech Talks Daily, I sit down with Andrew Lawson, EVP and GM for Zendesk Europe, to explore how the company is redefining the future of customer experience through AI, innovation, and a customer-first mindset. Zendesk may be a global name, but its European roots and strategic growth across the continent tell a story of evolution. From its founding in Copenhagen to becoming a powerhouse that supports over 100,000 customers globally, Zendesk has remained focused on one thing: being the best in customer service. Andrew and I unpack how this commitment translates into real-world outcomes, from faster resolution times to dynamic partnerships with top UK brands like Tesco, Next, and Liberty London. One of the standout themes of our discussion is the company’s investment in Agentic AI, designed to handle up to 80 percent of customer interactions while leaving high-touch cases to human agents. We also dive into Zendesk’s outcome-based pricing model, a shift that aligns success with resolution rather than licenses or agent seats. Andrew offers insights into why this change reflects a broader market expectation for ROI-driven platforms. We also touch on the company’s five acquisitions over the last 18 months, including Local Measure, and how these moves strengthen Zendesk’s capabilities in the CCAS space and deepen integrations with platforms like AWS Connect. As AI continues to shape customer and employee experiences, the conversation explores not just the technology but also the challenges, especially around execution, platform stability, and cybersecurity. So, what should business leaders be doing right now to balance rapid AI adoption with responsible deployment? How are enterprise expectations evolving in the face of economic pressure and customer demand? And what does it mean to lead in customer service when the rules are changing fast? Tune in to hear Zendesk’s perspective from the frontlines of transformation.      

In a world where payments have evolved from a back-office utility into a strategic business driver, how do you build a platform that truly puts control back into the hands of merchants? On this episode of Tech Talks Daily, I sat down with Dwaine Thomas, CIO of PXP, to explore how the company is transforming the payment landscape with its next generation platform, PXP Unity. PXP has been a force in fintech for over 30 years, processing over €30 billion in payments annually for some of the world’s most recognised retail, hospitality, entertainment, and online gaming brands. But rather than rely on legacy systems, PXP has gone all in on greenfield development with PXP Unity, a fully API driven orchestration platform that enables merchants to plug into the services they need without the complexity of managing the entire payment stack. Dwaine walked me through how Unity empowers businesses with real-time data aggregation, smart routing, and complete transparency, all delivered through an intuitive interface. He also shared how the platform supports seamless scaling during high-demand periods, like Black Friday, and provides merchants with both control and automation to optimise payment performance across channels. What stood out was the clear shift in mindset. Sixty-four percent of merchants now view payments as a growth enabler, not just a necessity. With Unity, merchants gain the flexibility to adapt strategies on the fly, personalise the payment experience, and align payments with broader business goals. We also explored the growing role of AI in PXP’s roadmap, from driving development efficiencies to enabling future use cases like AI agents within payment flows. As regulation evolves, Dwaine highlighted how initiatives like the FCA’s AI sandbox point to a more proactive and structured approach to innovation in the payments space. So how can enterprises unlock new value from their payments infrastructure? How do you build for performance, resilience, and adaptability in equal measure? And what happens when payments become central to customer experience and brand loyalty? Tune in to hear how PXP is answering those questions with technology that is both powerful and practical.

What happens when you stop thinking of satellites as data collectors and start thinking of them as data analysts? That is precisely the shift we explore in today's episode of Tech Talks Daily with Michael Bartholomeusz, CEO of NOVI. Traditionally, Earth observation has relied on satellites to capture massive volumes of raw data, which is then transmitted back to Earth for processing. However, this model presents several significant challenges: cost, latency, and complexity. NOVI is flipping this model on its head. Instead of sending terabytes of data back down, their satellites analyze it in orbit and only transmit the results. That means smaller data packets, faster insights, and drastically reduced costs. Michael and I dig into how NOVI's space-based edge computing infrastructure is opening new opportunities in defense, agriculture, mining, and more. With multiple sensors onboard each satellite and a proprietary AI processing platform, NOVI enables organizations to fuse and process Earth observation data in real time. It is a shift from intelligence as a feature to intelligence as the foundation. We also discussed NOVI's evolving roadmap as it transitions from Department of Defense projects to a dual-use model that includes commercial services. Their commercial constellation is set to launch in early 2026 aboard SpaceX Transporter missions, and the company is already onboarding early adopters who are building custom inference models in preparation for this launch. What stands out in this conversation is NOVI's goal of democratizing Earth observation. Their open-access platform enables users to retain full ownership of their data, marking a significant departure from the closed systems that currently dominate the industry. Lower cost, faster processing, and open access could change who benefits from space data and how. So, what does it take to process AI in orbit? How do we reimagine satellites as part of the compute layer, not just the sensor layer? And what happens when access to real-time Earth intelligence becomes available to more than just governments and large enterprises? Listen in to find out.  

Just two years ago, the launch of GPT-4 required the support of hundreds of experts, intensive computing power, and vast coordination. Today, that same process could be executed by a team of five. That is not an exaggeration. It is a signal of just how rapidly AI development is accelerating. In this episode of Tech Talks Daily, I’m joined by Gagan Tandon, Managing Director of AI & Data Services at TELUS Digital Solutions, to explore what is behind this extraordinary shift. From the evolution of AI chip design to the efficiency gains from smarter algorithms and open-source tools, Gagan offers a clear and grounded look at how AI training has become more accessible and less resource-intensive. But the bigger question is, what can we do with that efficiency? For Gagan, the answer lies in impact. Whether it is addressing bottlenecks in global supply chains, enhancing diagnostics in healthcare, or reducing fraud in financial services, these advances in AI development are not just theoretical. They are opening new doors for innovation across industries. We also explored how TELUS Digital Solutions supports enterprise transformation through its Fuel iX platform, which helps organisations transition from GenAI pilots to scalable, secure, ethical, and practical production systems. Gagan shared examples of how large-scale transformation can be approached with agility, especially when AI is aligned to specific business outcomes rather than simply layered on top of existing systems. This conversation goes far beyond model training. It is about what's next in AI operationalization, what business leaders should prioritize when it comes to adoption, and how to avoid common pitfalls as technology continues to evolve faster than many are prepared for. So how did we go from 300 engineers to five? What should enterprises be doing right now to take advantage of this momentum? And how can we make sure that efficiency does not come at the cost of responsibility? Join us as we explore the answers.

When I last spoke with Gaurav Kapoor five years ago, we were in the thick of a global pandemic. Remote work was still a novelty for many, AI was a distant concept for most businesses, and regulatory frameworks were trying to keep pace with the speed of technological change. Fast forward to today, and the conversation around AI and governance, risk, and compliance (GRC) has shifted dramatically. This made it the perfect time for a long-overdue catch-up. In this episode, I welcomed back Gaurav, Vice Chairman and Co-founder of MetricStream, to discuss the changing face of GRC in an AI-driven world. AI has now reached a level of ubiquity that places it alongside electricity and Wi-Fi as a foundational layer of both business and everyday life. But with that integration comes risk, and with risk comes the need for smarter, more adaptive governance. Gaurav shared how AI is no longer just about efficiency gains. It is becoming embedded into the fabric of enterprise risk frameworks, from real-time regulatory monitoring to predictive analytics and risk forecasting. We talked about the impact of the current political climate, including policy shifts following President Trump’s return to office and how deregulation narratives are colliding with the complexity of global compliance expectations. This was not just a theoretical discussion. Gaurav broke down real-world use cases that show how large enterprises are navigating everything from redundant compliance testing to emerging threats discovered through AI-driven analysis. He also spoke candidly about the challenges ahead, how companies can fall behind if they wait too long to modernize their frameworks, and what is at stake when they fail to build trust into their AI systems. So how do you evolve GRC in an age where the pace of change is relentless? What role does AI really play in risk leadership today? And how can companies move from reactive to proactive without losing control? Join me as we explore the next chapter of GRC with one of its leading voices.

In today’s episode of Tech Talks Daily, I sat down with Matt Dawes, Head of Enterprise Sales at HALOS, to explore the fast-moving world of security technology and how body-worn cameras are rapidly transforming the way businesses approach accountability, staff safety, and incident response. HALOS is rethinking body-worn video with a fresh approach that doesn’t stop at hardware. From their subscription-based service model to a real-time AI-powered backend system, their tech stack is designed to meet the growing demands of both frontline teams and the organizations supporting them. During our conversation, Matt shared how the company’s origins during the COVID-19 period shaped its purpose and culture and how it has scaled across the UK, Ireland, and the US following its Series A funding in early 2024. We explored how HALOS uses AI for proactive threat detection and fall detection, which is still under development, and how their cloud-based platform, Bolt, plays a critical role in evidence management and seamless integration with broader security ecosystems. Matt also shared insights into how their system is already making an impact in sectors such as retail, where the focus isn’t solely on theft prevention but also on ensuring frontline workers feel supported and protected against a backdrop of increasing aggression and workplace incidents. One of the standout aspects of the conversation was HALOS’ pricing model, which offers all features, including panic alerts and live streaming, under one monthly subscription. This structure eliminates the hidden costs that often hinder full deployment, allowing clients to scale their coverage without compromise. So, how is the security technology space evolving? What role does AI play in improving situational awareness? And how can tech leaders ensure their investment protects people on the ground? Please tune in to hear how HALOS is positioning itself at the intersection of innovation and frontline security.