Tech Talks Daily

Tech Talks Network
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If every company is now a tech company and digital transformation is a journey rather than a destination, how do you keep up with the relentless pace of technological change? Every day, Tech Talks Daily brings you insights from the brightest minds in tech, business, and innovation, breaking down complex ideas into clear, actionable takeaways. Hosted by Neil C. Hughes, Tech Talks Daily explores how emerging technologies such as AI, cybersecurity, cloud computing, fintech, quantum computing, Web3, and more are shaping industries and solving real-world challenges in modern businesses. Through candid conversations with industry leaders, CEOs, Fortune 500 executives, startup founders, and even the occasional celebrity, Tech Talks Daily uncovers the trends driving digital transformation and the strategies behind successful tech adoption. But this isn't just about buzzwords. We go beyond the hype to demystify the biggest tech trends and determine their real-world impact. From cybersecurity and blockchain to AI sovereignty, robotics, and post-quantum cryptography, we explore the measurable difference these innovations can make. Whether improving security, enhancing customer experiences, or driving business growth, we also investigate the ROI of cutting-edge tech projects, asking the tough questions about what works, what doesn't, and how businesses can maximize their investments. Whether you're a business leader, IT professional, or simply curious about technology's role in our lives, you'll find engaging discussions that challenge perspectives, share diverse viewpoints, and spark new ideas. New episodes are released daily, 365 days a year, breaking down complex ideas into clear, actionable takeaways around technology and the future of business.

  1. -22 Ч

    Pluralsight CEO on AI’s Role in Rewiring Human Intelligence

    Some interviews stick because they take a noisy topic and bring it back to reality. This was one of them. I spoke with Erin Gajdalo, CEO of Pluralsight, about what it actually takes to upskill a workforce in an AI era that seems to change by the week. We compared boardroom intent with day-to-day practice, and Erin was refreshingly clear about both. Pluralsight began more than twenty years ago in classrooms, moved online as the market shifted, and now supports Fortune 500 teams with expert-led courses, hands-on labs, and the admin tools leaders need to measure progress at scale. The thread running through the whole story is simple: people learn by doing, and companies get value when that learning maps to real work. We talked about AI in her own workflow first. Erin uses it to draft presentations, crunch data, and speed up research, then pushes that mindset across the company through focused sprints where every department experiments and reports back. That culture piece matters. Pluralsight’s latest research found that 61 percent of respondents still think using generative AI is “lazy,” which drives employees to adopt tools in the shadows and exposes the business to avoidable risk. Her answer is clear guidance, safe environments to practice, and permission to test without fear of failure. The payoff shows up in real examples. One financial services firm raised prompt engineering efficiency by 20 percent and saved 1,600 hours in three months by pairing assessments with prescriptive learning paths and hands-on practice. We also explored the fear that keeps people quiet. Layoff headlines travel faster than case studies, and that skews the mood inside many teams. Erin makes a straightforward case. Treat AI as an assistant that improves standard and repetitive tasks, protect the business with clear policies, then invest in education for everyone, not only engineers. Close the confidence gap with data. Baseline skills, prescribe learning, measure proficiency, and tie improvements to actual tasks. When leaders show their own work and give teams room to try things, adoption follows. The conversation finished on the future. Technical skills will keep evolving, but the standout advantage will be a willingness to learn and the soft skills that carry ideas from prototype to production. Erin also shared a personal goal that resonated with me. She would love a private breakfast with Serena Williams to talk about Serena Ventures and backing founders from underrepresented groups. It fit the theme of the episode. Talent is everywhere. Opportunity appears when someone opens a door and stays long enough to help you through it. If you want the full story, including how Pluralsight is updating its platform for scale and how leaders can reduce “shadow AI” without slowing innovation, you can find their research and resources at Pluralsight.com.  ********* Visit the Sponsor of Tech Talks Network: Land your first job  in tech in 6 months as a Software QA Engineering Bootcamp with Careerist https://crst.co/OGCLA

    24 мин.

  2. -1 ДН.

    t3rn, Interoperability, and the Next Wave of Real Adoption

    Here’s the thing. We have had brilliant ideas in Web3 for years, along with better tooling and plenty of enthusiasm, yet adoption still feels slower than it should be. In my conversation with Maciej Baj, founder of t3rn, we got under the skin of why that is and what it might take to change the pace. His starting point is simple to state and hard to deliver at scale: make cross-chain interactions feel seamless for users and predictable for developers. If you can do that, the door opens to practical products rather than experiments that only the bravest try. Maciej describes t3rn as a universal execution layer for cross-chain smart contracts, and the phrase matters because it changes how we think about interoperability. Instead of stitching together a mess of bridges and oracles, t3rn lets a contract access state and data across multiple chains from one place. Today it is mapped to the EVM for broad compatibility, but the design is chain agnostic by intent. That choice is less about tribal loyalties and more about meeting developers where they already build while keeping the door open to other ecosystems as the market evolves. Trust shows up in the details, and atomic execution is one of those details that changes behavior. If a multi-chain transaction cannot complete in full, it reverts. No half-finished transfers. No manual recovery adventures. This mirrors what smart contracts already offer on a single chain, which means developers can reason about outcomes without inventing fresh playbooks for every hop. It also reassures users, who care less about the plumbing and more about knowing that funds either arrive or return. Cost matters too. t3rn has been engineered for cost-efficient token movement across chains, which sounds mundane until you price a complex strategy that touches multiple venues. Lower friction makes new use cases economical. Maciej outlined a few that caught my eye. Trading algorithms that read and act on signals from multiple chains without duct tape. Simpler asset movement across ecosystems that do not share a wallet culture or UX conventions. Agent-driven executors that can watch for arbitrage or rebalance a portfolio without constant human oversight. The theme is the same throughout. Reduce the number of hoops and you increase the number of people willing to try something new. We also looked ahead. t3rn is preparing an integration with hyperliquid and rolling out a builder program to widen the ecosystem on top of its execution layer. An SDK is on the way so the community can help bring in new chains faster, rather than waiting for a core team to do all the heavy lifting. There is a governance track forming as well, aimed at giving the community more say in integrations and priorities. None of this guarantees success, but it signals a path from protocol to platform. I left the conversation with a clearer view of why interoperability still matters in 2025. The multi-chain world is not going away. Users move between ecosystems. Developers deploy to several environments at once. Liquidity, identity, and logic already live in many places. A universal execution layer that is reliable, cost aware, and easy to build on is the kind of boring-sounding foundation that ends up changing behavior. ********* Visit the Sponsor of Tech Talks Network: Land your first job  in tech in 6 months as a Software QA Engineering Bootcamp with Careerist https://crst.co/OGCLA

    32 мин.

  3. -2 ДН.

    AI Trading Without Lag: EZ Trading Computers on Building the Right Setup

    When we think about what separates winning traders from those who struggle, we usually picture strategies, indicators, or a bit of insider know-how. But what if the biggest edge has been sitting on your desk all along? In this episode, I sit down with Eddie Z, also known as Russ Hazelcorn, the founder of EZ Trading Computers and EZBreakouts. With more than 37 years of experience as a trader, stockbroker, technologist, and educator, Eddie has built his career around one mission: helping traders cut through noise, avoid expensive mistakes, and get the tools they need to stay competitive in a fast-moving market. Eddie breaks down the specs that actually matter when building a trading setup, from RAM to CPUs to data feeds, and exposes which so-called “upgrades” are nothing more than overpriced fluff. We also dig into the rise of AI-powered trading platforms and bots, and what traders can do today to prepare their machines for the next wave. As Eddie points out, a lagging system or a missed feed isn’t just an inconvenience—it can be the difference between a profitable trade and a costly loss. Beyond the hardware, we explore the broader picture. Rising tariffs and global supply chain disruptions are already reshaping the way traders access technology, and Eddie shares practical steps to avoid being caught short. He also explains why many experienced traders overlook their machines as a “secret weapon” and how quick, targeted fixes can transform reliability and performance in under an hour. This conversation goes deeper than specs and gadgets. Eddie opens up about the philosophy behind the EZ-Factor, his unique approach that blends decades of Wall Street expertise with cutting-edge technology to simplify trading and help people succeed. We talk about his ventures, including EZ Trading Computers, trusted by over 12,000 traders, and EZBreakouts, which delivers actionable daily and weekly picks backed by years of experience. For traders looking to level up—whether you’re just starting out or managing multiple screens in a professional setting—this episode is packed with insights that can help you sharpen your edge. Eddie’s perspective is clear: the right machine, the right mindset, and the right knowledge can make trading not only more profitable, but, as he likes to put it, as “EZ” as possible. ********* Visit the Sponsor of Tech Talks Network: Land your first job  in tech in 6 months as a Software QA Engineering Bootcamp with Careerist https://crst.co/OGCLA

    38 мин.

  4. -3 ДН.

    GoTo on Making AI Practical for Small and Mid Sized Businesses

    Most conversations about AI are still caught up in the spectacle. We see demos, marvel at copilots, and argue about the latest big model. But what happens when you strip away the hype and focus on AI that simply works? That is exactly the perspective Olga Lagunova brings to this episode. As Chief Product and Technology Officer at GoTo, she has one goal in mind: make AI useful, practical, and almost invisible. Olga believes the real test of AI is whether it integrates seamlessly into workflows. In her view, the most powerful AI is the kind that feels almost boring because it is just part of how work gets done. During our conversation she explains how GoTo is embedding AI into its platform so that small and midsize businesses can benefit without needing data scientists on staff or large budgets to experiment. We explore the difference between AI for SMBs and AI for enterprises, and why simplicity and trust matter more than shiny features. Our discussion also goes deeper into agentic AI, where tools are no longer just assistants but are taking on tasks in the background. Olga highlights how GoTo balances this shift with guardrails, governance, and human-in-the-loop oversight to ensure that efficiency never comes at the cost of security. We also unpack the classic build versus buy dilemma, why shadow AI is becoming a real risk for companies, and how leaders can measure ROI in a way that proves value both immediately and over time. If you are tired of the hype and want to understand how AI is quietly reshaping the backbone of business operations, this episode with Olga Lagunova will give you a grounded and forward-looking perspective.

    42 мин.

  5. -4 ДН.

    AI and Data-Driven Manufacturing with IDA Ireland and Eli Lilly and Company

    I wanted this conversation to do two things at once. First, ground the hype in real practice. Second, show how a small country can punch well above its weight by connecting industry, academia, and government with purpose. With Chantelle Kiernan from IDA Ireland and Stephen Flanagan from Eli Lilly and Company, we explored what digital transformation really looks like on the factory floor in Ireland, why talent is the engine behind it, and how cross-sector collaboration is turning ideas into measurable outcomes. Ireland’s manufacturing base employs hundreds of thousands and fuels exports, yet what stands out is the shared mindset. The shift toward Industry 5.0 puts people at the center while using digital, disruptive, and sustainable technologies to rethink production. Eli Lilly’s experience shows how a digital-first culture changes everything. New sites start paperless by default. Established plants raise their game through micro-learning, data-driven problem solving, and champions who model the behavior. The message is simple. Technology only sticks when people see clear value and have the skills to act on it. From pilots to site-wide change Here’s the thing. The strongest wins come from a strategic, site-wide approach rather than isolated pilots. Maturity assessments across pharma sites in Ireland revealed common patterns, shared bottlenecks, and repeatable opportunities. That insight helps teams justify investment, sharpen ROI arguments, and accelerate adoption without slowing production. Reinvestment in legacy facilities becomes a long-term advantage when you connect equipment, data, and people with a clear plan. This is where Ireland’s ecosystem shows its class. Purpose-built centers like Digital Manufacturing Ireland, NIBRT, IMR, and I-FORM give teams a place to test before they invest. Indigenous tech SMEs sit at the same table as global pharma leaders and large tech firms, which means collaboration moves faster. When 50 percent or more of new R&D projects cite academic partnerships, you know something healthy is happening. Skills, STEM, and the mindset shift Upskilling came through as the decisive enabler. IDA Ireland supports companies with skills needs analysis and access to training. Universities co-create relevant courses. Micro-credentials and immersive apprenticeships build confidence on the shop floor. Stephen’s point about micro-learning hit home. People learn best when they can apply knowledge to a problem they care about, right now. That keeps momentum high and spreads digital competence across teams without waiting on giant projects. Barriers still exist. Defining ROI, coping with regulatory complexity, and balancing change with daily production are real challenges. Culture is the swing factor. Leaders who set the tone, create space for experiments, and reward progress see faster results. GenAI is already shifting attitudes by improving personal productivity, which naturally opens minds to operational use cases like predictive maintenance, knowledge capture, and quality improvements. What comes next If the last decade was about connecting machines, the next decade will be about connecting knowledge. Expect smarter, greener, and more multidisciplinary manufacturing. AI will sit alongside advanced materials and sustainable design. The most resilient sites will combine agile infrastructure with strong learning cultures, so they can absorb change rather than resist it. Ireland’s model of collaboration gives a useful signal. When industry, government, and academia align around shared outcomes, the runway gets longer and the takeoff gets smoother. This episode is about the practical choices that make transformation real. Strategic assessments. Shared R&D spaces. Cohorts of digital champions. And a relentless commitment to skills. It is a story of steady progress that scales, and a reminder that the future belongs to teams who can learn faster together. ********* Visit the Sponsor of Tech Talks Network: Land your first job  in tech in 6 months as a Software QA Engineering Bootcamp with Careerist https://crst.co/OGCLA

    31 мин.

  6. -5 ДН.

    Broadridge AI, NYFIX, and the New Data Strategy for Financial Services

    What does it really mean to future-proof financial data? That’s the question at the heart of my conversation with George Rosenberger, General Manager of NYFIX at Broadridge. George has spent his career moving through every corner of the capital markets, from trading desks to broker-dealers, and now into the software side where he oversees order routing, post-trade matching, and the adoption of new AI tools. His perspective is uniquely positioned between the history of financial markets and their rapidly accelerating future. This discussion takes inspiration from Broadridge’s fifth annual Digital Transformation and Next Gen Technology study, which collected insights from more than five hundred technology and operations leaders across financial services. The survey highlights both the progress and the pressure points facing the industry. Forty-one percent of leaders still cite data security as a major hurdle, and while cloud, AI, and cybersecurity dominate the technology stack, a third of firms still lack security built into their core systems. George explains why this gap persists, how legacy platforms complicate modernization, and what steps firms can take to extract value from old infrastructure while preparing for what’s next. We also explore the irony that many organizations overestimate their digital maturity. Generative AI adoption has surged from forty to seventy-two percent in a year, but governance, compliance, and data quality concerns remain. George stresses the importance of measuring outcomes, not just intentions, and shares how Broadridge is approaching AI responsibly through initiatives like its Algo Copilot, which helps traders make sharper decisions. If you’re curious about how financial services can strengthen cybersecurity, reduce technical debt, and rethink data strategy as a true engine of innovation, this episode offers both a candid reality check and a roadmap. The speed of change is staggering, but with the right strategy, leaders can build resilience and stay ahead in a digital-first world.

    22 мин.

  7. -6 ДН.

    How Credit Karma Scales GenAI to Power 60 Billion Predictions a Day

    What does it take to deliver personalized financial guidance to more than 140 million people every single day? That is the question I put to Wan Agus, Head of Engineering at Intuit Credit Karma, in this episode of Tech Talks Daily. Most of us open the Credit Karma app to check our credit score, look at a loan option, or browse for a better credit card. What we rarely consider is the technology running behind the curtain. Wan revealed that his teams are powering more than 60 billion daily AI predictions to understand members’ needs, protect their privacy, and guide them toward the right financial choices. He explained why accuracy is everything in fintech. A misplaced recommendation can mean more than a poor customer experience; it can damage someone’s credit score and hold back their progress. Our conversation also looked at what happened after Intuit acquired Credit Karma. Two very different tech stacks had to be brought together, and identity systems had to be unified so members could move seamlessly between Credit Karma and products like TurboTax. Wan compared the process to playing two complex board games at once, where success depends on strategy and collaboration. We also explored how Credit Karma is blending traditional AI with generative AI. From early chatbot experiments to today’s Wallet Analyzer and Tax Advisor, Wan shared how his teams decide when to push forward with new tools and when to slow down to ensure safety and trust. He also gave us a glimpse into the future, where agent-to-agent technology could bring open banking-style transparency to the U.S. So how do you scale personalization without losing trust? And what can every business leader learn from Credit Karma’s balance between speed, culture, and responsibility? I would love to hear your thoughts after listening.

    42 мин.

  8. 22 СЕНТ.

    Building Trust in AI: Hitachi Vantara’s Vision for Governance

    AI is quickly moving from boardroom buzzword to boardroom headache. Enterprises are waking up to the fact that bringing large language models in-house is not just about performance or cost, but about control, accountability, and trust. In this episode of Tech Talks Daily, I sit down with Octavian Tanase, Chief Product Officer at Hitachi Vantara, to unpack what this shift really means for business and technology leaders. Octavian explains why governance has become the defining challenge of the AI era. Companies are under pressure not only to innovate but also to meet new regulatory demands and maintain trust with customers. That requires more than patching together tools or hoping for transparency from public AI providers. It means creating governance frameworks that deliver traceability, auditability, and explainability as standard practice, not as afterthoughts. We explore why vector databases may need something like a time-machine capability to document when and how information is added, giving enterprises a provable audit trail. This level of accountability supports both internal oversight and external compliance, turning abstract AI ethics debates into real operational requirements. Our conversation also turns to the role of infrastructure. Hitachi Vantara’s VSP One, with its tagline “One Data Platform, No Limits,” has been built to simplify data complexity across block, file, and object storage while providing a unified foundation for AI workloads. Octavian shares how this unified approach helps enterprises run compliant, explainable, and efficient AI across hybrid environments that span both on-premises and the cloud. This isn’t just a story about technology, but about the future of trust in digital business. If AI remains a black box, its value will always be limited. If it becomes explainable, traceable, and accountable, it can transform not only efficiency but also relationships with customers, regulators, and partners. So, how can leaders strike the right balance between governance and innovation without slowing down progress? Octavian leaves listeners with a forward-looking perspective on what the next few years of enterprise AI will demand, and why those who build on strong governance today may end up with the most resilient advantage tomorrow.   ********* Visit the Sponsor of Tech Talks Network: Land your first job  in tech in 6 months as a Software QA Engineering Bootcamp with Careerist https://crst.co/OGCLA

    23 мин.
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If every company is now a tech company and digital transformation is a journey rather than a destination, how do you keep up with the relentless pace of technological change? Every day, Tech Talks Daily brings you insights from the brightest minds in tech, business, and innovation, breaking down complex ideas into clear, actionable takeaways. Hosted by Neil C. Hughes, Tech Talks Daily explores how emerging technologies such as AI, cybersecurity, cloud computing, fintech, quantum computing, Web3, and more are shaping industries and solving real-world challenges in modern businesses. Through candid conversations with industry leaders, CEOs, Fortune 500 executives, startup founders, and even the occasional celebrity, Tech Talks Daily uncovers the trends driving digital transformation and the strategies behind successful tech adoption. But this isn't just about buzzwords. We go beyond the hype to demystify the biggest tech trends and determine their real-world impact. From cybersecurity and blockchain to AI sovereignty, robotics, and post-quantum cryptography, we explore the measurable difference these innovations can make. Whether improving security, enhancing customer experiences, or driving business growth, we also investigate the ROI of cutting-edge tech projects, asking the tough questions about what works, what doesn't, and how businesses can maximize their investments. Whether you're a business leader, IT professional, or simply curious about technology's role in our lives, you'll find engaging discussions that challenge perspectives, share diverse viewpoints, and spark new ideas. New episodes are released daily, 365 days a year, breaking down complex ideas into clear, actionable takeaways around technology and the future of business.

Информация

  • Канал
    Tech Talks Network
  • Автор
    Neil C. Hughes
  • Годы выхода
    2015 - 2025
  • Выпуски
    100
  • Ограничения
    Без ненормативной лексики
  • Авторские права
    © Neil C. Hughes - Tech Talks Daily 2015
  • Сайт подкаста
    Tech Talks Daily

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