NXP EdgeVerse Techcast

NXP Dating Game: Guess the SoC Behind the Blinky (with PhyTec i.MX 8MP)
On the EdgeVerse Tech Cast, co-hosts Kyle Dando and Bridgette Stone run a throwback "Dating Game" with PhyTec, where three mystery computing platforms demo "Hello World" via blinking LEDs and Kyle must guess the NXP SoC behind each door.
Door #1 uses VS Code, a SEGGER J-Link probe, and GDB to blink an LED with simple firmware
Door #2 blinks LEDs from a Linux console using /sys/class/leds
Door #3 runs Linux LEDs while also using remoteproc to start microcontroller firmware so both Linux- and MCU-domain LEDs blink simultaneously.
PhyTec applications engineer True Loan reveals all the platforms are the same i.MX 8MP SOM and explains the industry trend toward consolidating MCU and MPU workloads on one chip to simplify maintenance, team collaboration, and long-term product support.
Getting started resources:
PhyCore i.MX 8MP dev kit
JTAG expansion board
PhyTec's developer wiki
More About i.MX 8MP SOM
00:00 Welcome and Setup
01:15 Door Three Hybrid Demo
01:54 Dating Game Rules
02:31 Door One Blinky MCU
04:18 Door Two Linux Console
06:06 Final Guesses and Reveal
07:30 Meet True from PhyTec
08:51 Why MCU Plus MPU
11:33 Getting Started Resources
12:19 Key Takeaways and Wrap

MCUXpresso SDK Updates & Roadmap | EdgeVerse Techcast
In this EdgeVerse Techcast episode recorded during an MCUXpresso SDK leadership workshop in San Jose, Kyle and Bridgette speak with Petr Lukas (Middleware/NPI) and Jerry Zeng (Drivers/NPI) about recent SDK progress and what's next. They explain NPI as day-one software enablement—from register layers and debug files to board/peripheral readiness and optimization—and how drivers and middleware work together for customer applications.
Key SDK improvements over past 12 months:
Added "Repo Zip" packaging for smaller downloads while retaining Git/west workflows
Optimized release cadence delivers 4 major releases and 8 previews per year
Delivered 40+ new drivers and 16 new boards,
Improved Freestanding project workflow
Revamped Sphinx-based documentation
Large-scale CI provides daily and weekly test coverage
SDK Looking ahead:
Expanded static analysis
Continued Zephyr-aligned strategy
Edgefast Open BT/BLE leveraging Zephyr
Introduce MCUXpresso SDK LTS
New multimedia framework.
The episode also covered highlights in the recent SDK 26.03 release.
Episode Resources:
MCUXpresso SDK Tools for MCU Solutions
MCUXpresso SDK Documentation
Release MCUXpresso SDK 26.03.00 release (GitHub)
 
00:00 Bay Area Workshop Kickoff
00:59 Meet Petr and Jerry
02:07 SDK Leadership Roles
04:22 What NPI Means
06:19 Biggest SDK Improvements
06:32 Repo Zip Packaging
07:50 Release Model and Docs
09:57 CI Coverage and Quality
11:04 Next Year Roadmap
11:59 Zephyr and Connectivity Plans
13:34 LTS and Multimedia Framework
15:33 SDK 26.03 Release Highlights
16:56 Middleware and Security Updates
17:58 NPI Preview and Ethernet
18:33 Wrap Up and Subscribe

Agentic AI at the Edge: Bringing Model Context Protocol (MCP) to Microcontrollers with Zephyr
In this episode, NXP Systems Enablement Engineer David Piskula talks about Agentic AI at the edge and the Model Context Protocol (MCP), and how NXP is bringing MCP down to the microcontroller level using Zephyr. The discussion covers why edge computing matters (security, confidentiality, low latency), how MCP standardizes JSON message exchanges between clients and servers, and how self-describing "tools" enable plug-and-play device integration. Critical in scenarios like smart homes and factory automation. David shares the challenge of implementing MCP on resource-constrained MCUs. He highlights the benefits of Zephyr providing a hardware agnostic path for evaluation. The NXP solution is available now to evaluate with an LED-control demo using NXP's eIQ Agentic AI framework.
Other episode resources:
LED-Control Demo project (GitHub repo)
Zephyr Upstream mcp_server contributed by NXP 
www.nxp.com/zephyr 
00:00 Welcome to EdgeVerse
01:07 Meet David Piskula
01:47 What Systems Enablement Does
03:09 Why Edge AI Matters
04:15 MCP Explained
04:56 How MCP Works
05:45 Smart Home Example
06:45 Factory Automation Use Case
07:26 MCP on Microcontrollers
08:32 Biggest Engineering Challenges
09:31 Plug and Play LED Demo
11:11 How to Get Started
12:22 Wrap Up and Next Steps

Go Long Range with Sub-GHz UBX100 Projects on NXP Application Code Hub
In this NXP EdgeVerse TechCast episode, NXP Systems Engineer Tony Trujillo covers sub-GHz wireless connectivity and new Application Code Hub projects for evaluating and integrating the NXP UBX100 transceiver. Tony explains where sub-GHz appears in everyday life and why it's chosen for long range, better signal penetration, lower energy consumption, and reduced interference versus 2.4 GHz. The discussion highlights four radio-modem-path resources now available: the UBX100 SDK (including the Host Radio Modem Library), a Flash Loader Demo for programming an unprogrammed UBX100 using a FRDM MCX N947 board, an RF Toolbox for lab testing and certification, and a FreeMASTER Lite web-based Evaluation GUI for out-of-box configuration and testing (including TX/RX, range tests with packet error rates, and a simplified Wireless M-Bus sniffer). They also cover preset PHY configurations for Wireless M-Bus and Wi-SUN, field upgradability via boot/flash loader, and upcoming Sigfox modem support.
Episode Resources:
UBX100 Application Code Hub Examples
UBX100 Product Details
OM-UBX100 Breakout Board: Expansion Board Hub
Wireless M-Bus Stack Partner: STACKFORCE
SigFox Build website
00:00 Welcome and episode focus
01:14 Meet Tony Trujillo
02:45 Sub GHz explained
04:40 Why sub GHz matters
05:36 UBX100 and use cases
05:55 Code Hub project overview
07:02 SDK and flash loader
08:32 RF toolbox and FreeMASTER GUI
09:29 FreeMASTER Light walkthrough
12:23 What makes UBX100 special
13:55 Custom stacks and Sigfox path
15:53 More resources to get started
17:20 Wrap up and next steps

Physical AI & Humanoid Robotics: NXP + NVIDIA Holoscan Sensor Bridge Reference Designs
In this EdgeVerse TechCast episode, hosts Kyle Dando and Bridgette Stone speak with NXP's Altaf Hussain about Physical AI and a new NXP–NVIDIA collaboration delivering integrated, real-time robot body solutions built around NVIDIA's Holoscan Sensor Bridge (HSB). They explain how Physical AI differs from cloud AI by requiring deterministic sensing, decision, and actuation under strict latency and safety constraints, and how NXP's real-time control and networking complements NVIDIA's AI compute. The collaboration launches with two HSB-ready reference designs targeting the hardest robotics problems: perception and motion—an i.MX 95 machine vision design with 10Gb low-latency data paths to the NVIDIA pipeline, and an i.MX RT 1180 distributed motor control design supporting EtherCAT and TSN for synchronized control. Reference software will be published on GitHub.
Episode Resources:
https://www.nxp.com/hsb-solutions
https://www.nvidia.com/en-us/technologies/holoscan-sensor-bridge/
https://docs.nvidia.com/holoscan/sensor-bridge/latest/introduction.html
00:00 Welcome and Topic Setup
00:39 Why Physical AI Is Hard
01:03 NXP and NVIDIA Collaboration
01:59 Defining Physical AI
03:20 Holoscan Sensor Bridge at the Edge 
05:27 Two Reference Designs
07:00 Machine Vision i.MX 95 
07:43 Motor Control i.MX RT1180
09:19 Software Enablement and Roadmap
10:53 GitHub Access and Wrap Up
11:48 Final Thanks and Next Steps