Castuner

EE Times Current

EE Times On Air

EE Times Current provides a deep dive into the most compelling stories in the electronics industry. Tune in to keep yourself current on what matters to design engineers and other tech industry professionals

Сайт подкаста

Слушайте в своём приложении

Эпизоды

281 эпизод

  1. Smarter Power Sequencing with GreenPAK 21:11
  2. Integrating Interface Memristors in the Back End of Line
  3. Integrating Interface Memristors in the Back End of Line 42:16
  4. Beyond PPA: How Foundation IP Enables Predictable Execution and Lower TCO for AI-Era SoCs 24:03
  5. Why Computing With Time Gives Neuromorphic AI an Edge 57:03
  6. Where Software Meets Silicon: A Digital Twin Playbook 23:46
  7. Trust at Scale: The Next Challenge for AI-Driven Semiconductor Development 24:13
  8. Do Spikes Need Common Language for Sensing and Learning? 1:00:49
  9. Designing the AI Factory from the Rack Up 18:22
  10. Beyond Automation: Self-Verifying AI Agents for Semiconductor and PCB Design 23:24
  11. Can Great Sky’s Light-Connected AI Enable Bigger Brains? 58:17
  12. Under the Hood of Intelligent Systems 32:28
  13. Will Photonics Loosen the Bottlenecks in Neural Systems? 46:46
  14. When AI Gets a Body: Physical AI, Humanoids and the Future of Silicon 41:52
  15. Zonal Power: 48V Architectures for the Software Defined Vehicle 34:32
  16. Fixing AI’s Bottlenecks: Memory, Scale, and Sparsity 58:39
  17. Can the Nvidia Monopoly on AI Chips Be Broken? 49:00
  18. Automated Multiphysics for 3D IC Success 28:42
  19. Neuromorphic Spikes Unify Control and Decision Making 56:54
  20. Chips at the Edge: Innovation for AI at Edge and Automotive 25:47
  21. Green Always-On Sensing with Neuronova’s Sub-μwatt Chip? 47:29
  22. An Architecture for Building Brains from Top to Bottom? 55:10
  23. Tracking & Locationing Technologies from Renesas 21:55
  24. The State of Multi-Die: Insights and Customer Requirements 20:20
  25. Artificial Hearing: From Ear Drums to Tuning Forks 51:50
  26. Calibre Directions in Artificial Intelligence 21:26
  27. A Theoretical Framework for Neuromorphic Technology? 55:28
  28. Neurons Close the Loop from Insect Perception to Action 44:15
  29. Accelerating Complex Analog IC Design: The Power of Early Reliability Verification 18:46
  30. Can Neuromorphic Be Low-Power, Reconfigurable, and Scalable? 50:31
  31. Event-Driven E-Skins Protect Both Robots and Humans 47:38
  32. Event-Driven E-Skins Protect Both Robots and Humans 47:38
  33. Digital Prototypes May Enable Analog Neuromorphic Chips 52:44
  34. The State of Multi-Die Testing: Essential Insights for Designers 26:05
  35. IBM Used Mathematics as Compass on Journey to NorthPole 49:59
  36. Rippling Signals May Provide Working Memory in the Brain 51:14
  37. Making Analog Chip Designs Without Analog Designers 48:21
  38. BrainChip’s IP for Targeting AI Applications at the Edge 47:02
  39. Robots Need Physical, Not Just Artificial, Intelligence 48:36
  40. A Shift Left Strategy Addresses IC Design Challenges Through Design-Stage Verification 27:42
  41. Embracing the Efficiency of the Neuromorphic Hairball 47:50
  42. Chip Combines Analog and Digital Neurons for Sensor Data 48:44
  43. Get Powered by Renesas: Leading Solutions in Automotive and Industrial Applications 18:58
  44. Carver Mead Says Neuromorphic Efficiency Can Help AI 1:05:53
  45. How AI is Changing Every Aspect of EDA 31:17
  46. Leveraging Safety Processor Expertise to Develop RISC-V Based Automotive Implementations 13:02
  47. Next-Gen Neuromorphic Researchers Look to Future 52:53
  48. Preparing for CRA and Open-Source Silicon Security 33:12
  49. SynSense Research Head Talks Combined Sensing, Processing 46:16
  50. AI inferencing, Software Ecosystems and Trends in Industrial Automation 28:52