Tech Threads: Weaving the Intelligent Future

This podcast hosted by Baya Systems explores the cutting edge of technology, from AI acceleration to data movement and chiplet innovation. Each episode dives into groundbreaking advancements shaping the future of computing, featuring insights from industry experts on the trends and challenges defining the tech landscape. Tune in to stay ahead in the rapidly evolving world of technology.

Tech Threads: Weaving the Intelligent Future is a news podcast hosted by Unknown Host, with 14 episodes on record and a Required Pod Score of 80.

Unknown Host hosts Tech Threads: Weaving the Intelligent Future, a news show with 14 episodes published.

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  Episode #114

  Scaling Custom Silicon in China: Technology Is Only the Beginning

  Sep 24, 202644 minS1

  In this episode of Tech Threads: Weaving the Intelligent Future, Baya Systems Founder and CEO Sailesh Kumar joins AdoreSys Founder and CEO KengSu Teoh to discuss the companies’ new partnership and what it means for semiconductor customers across China and the broader Asia-Pacific region. Hosted by Nandan Nayampally, the conversation explores the rapid growth of custom silicon, the increasing importance of data movement and interconnect technology, and how Baya and AdoreSys are combining complementary strengths to support complex SoC and chiplet designs. From Technology Adoption to Implementation Sailesh and KengSu discuss how Baya and AdoreSys can combine their complementary strengths to support customers across the design journey, from evaluating advanced interconnect technology to silicon implementation. Inside the Conversation • Why data movement and connectivity are becoming defining challenges in modern computing systems • How the shift toward custom silicon is changing customer requirements and development models • Why chiplet architectures create new opportunities and new connectivity challenges • What semiconductor design teams in China value when evaluating and adopting technology • How local engineering relationships can accelerate technical engagement and customer support • What Baya Systems and AdoreSys hope to accomplish through their partnership

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  Episode #113

  The Memory Maze: Copper, Optics, and the Future of AI Data Movement

  Aug 18, 202644 minS1

  As AI models grow larger and more autonomous, every query requires extraordinary volumes of data to move quickly between memory and compute, making data movement one of the defining challenges for next-generation AI infrastructure. In this episode of Tech Threads, Nandan Nayampally speaks with Srujan Linga, CEO and co-founder of Kandou AI, about why the industry’s so-called “memory wall” is actually a multidimensional “memory maze,” shaped by different requirements for bandwidth, latency and capacity. They explore the limitations of relying exclusively on high-bandwidth memory, the untapped potential of copper interconnects, and how technologies such as Chord Signaling and Copper MIMO can increase bandwidth while reducing power and extending reach. The conversation also examines where copper and optics can complement one another, how advanced interconnects could turn an entire PCB into a larger multi-chip system, and why the economics and scalability of AI infrastructure must be considered alongside raw performance. The result is a system-level perspective on what it will take to build more efficient, scalable and accessible AI infrastructure.

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  Episode #111

  Breaking the Memory Wall: How New Memory Architectures are Reshaping AI Inference

  Jun 16, 202639 minS1

  In this episode of Tech Threads: Weaving the Intelligent Future, Baya Systems’ Nandan Nayampally sits down with Charlie Cheng, founder and CEO of TC Lab, for an in-depth conversation on the memory wall and why it has become one of the defining bottlenecks in AI infrastructure. While memory constraints have existed for decades, AI inference is bringing the issue into sharper focus by turning memory bandwidth into a direct driver of user experience, system performance, and data center economics. Charlie shares his perspective on the industry’s shift toward alternative AI architectures, from high-bandwidth memory and SRAM-based approaches to emerging 3D memory technologies and hybrid-bonded architectures that bring memory much closer to compute. He explains why inference workloads, especially token generation and KV cache access, can quickly become bandwidth-bound, and why solving that challenge requires rethinking the relationship between compute, memory, packaging, and on-chip data movement. The discussion also explores what happens when memory bottlenecks are reduced or removed. As more bandwidth becomes available to AI accelerators, the pressure shifts to the rest of the system, including networks-on-chip, chiplet fabrics, and data movement architectures. For companies building next-generation AI chips, hyperscale infrastructure, autonomous systems, and edge inference platforms, this creates both a challenge and an opportunity: the need for more flexible, scalable, and software-defined approaches to moving data efficiently across increasingly complex systems. Tune in for an expert look at why the future of AI performance depends as much on memory innovation and data movement as it does on compute, and how new architectures could help unlock faster, more efficient, and more scalable AI systems.

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  Episode #10

  Beyond the CPU vs GPU War: Rethinking AI Compute at the System Level

  Apr 28, 202649 minS1

  In this episode of Tech Threads, Nandan Nayampally, Baya Systems CCO, sits down with Ian Ferguson, Vice President of Vertical Markets and Business Development at SiFive, to unpack one of the most important shifts happening in modern computing: AI is no longer just about scaling compute, it’s about orchestrating complexity.<br /><br />As architectures fragment across accelerators, chiplets, and custom silicon, the real challenge is no longer building faster chips. it’s turning all of these elements into a cohesive, high-performance system.<br /><br />This conversation explores why the industry is moving beyond the traditional “CPU vs GPU” narrative and towa...

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  Episode #109

  Inside the AI Bottleneck: Data Movement, Chiplets, and System Scaling

  Mar 27, 202654 minS1

  For the last decade AI has been driven by one thing, more compute: bigger models, more accelerators, higher throughput.<br /><br />But as NVIDIA’s Jensen Huang recently highlighted at GTC, the industry is hitting a different kind of wall, one that hasn’t received nearly as much attention.<br /><br />The real constraint is no longer just compute. It’s data movement.<br /><br />To its credit, Nvidia has pushed this frontier with innovations like NVLink Fusion, and continued investment in connectivity AI dataflow architectures. But the challenge is bigger than any one company.<br /><br />As AI systems scale...

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