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EE Times Current

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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

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Episódios

281 episódios

  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