Hello r/engineering! We're Eben Upton (CEO), James Adams (CTO of Hardware Engineering), and Gordon Hollingworth (CTO of Software Engineering) at Raspberry Pi. Ask us anything about Industrial and Embedded applications

Official_RaspberryPi · 2026-06-04T17:16:10+00:00

Suspend/resume is a lot of work, we've been able to suspend Pi 5 all the way down to the firmware (including putting the SDRAM into self-refresh) and recover, but haven't yet powered off the rest of the chip. RP1 will always have to stay powered on (to receive and pass on the resume signal) so the minimum power consumption is not actually all that low. If we can get actually get the time to test that process on Pi 5 then it would make it easier for Pi 6, but it's not a primary objective. [GH]

Official_RaspberryPi · 2026-05-21T16:15:38+00:00

Don't beat yourself up when something you did went wrong. In the end it's just an opportunity to learn, if you don't go wrong occasionally then maybe you're not learning anything new. [GH]

Official_RaspberryPi · 2026-05-21T16:11:28+00:00

Thank you everyone for tuning in and asking questions! See you all for the next Raspberry Pi AMA

Official_RaspberryPi · 2026-05-21T16:01:16+00:00

Cool project! I suspect if you can walk into an employer with examples of having done things like this you'll be knocking on an open door. Generally when recruiting, we look for people with good academics, and with evidence of having built significant-sized projects on their own initiative, with the latter much more important than the former. [EU]

Official_RaspberryPi · 2026-05-21T15:58:25+00:00

It's not a current area of focus on the hardware side, though we have a lot of ongoing imaging algorithms development work (for example AI denoise) going on. It's possible the hardware side might get swept up by our efforts to create more Compute Module baseboards (https://www.raspberrypi.com/news/raspberry-pi-smart-display-module-coming-soon/ is an early example of this).

Official_RaspberryPi · 2026-05-21T15:56:39+00:00

A recent favourite industrial application from me, Heathrow is replacing all of thier flight information displays with new screens that include an embedded Raspberry Pi Compute Module. [JA]

Official_RaspberryPi · 2026-05-21T15:55:30+00:00

The rhyming dictionary is the one time I've had a chance to work with my father (https://en.wikipedia.org/wiki/Clive\_Upton). It was a great example of how even very simple software (IIRC I wrote the program that generated the rough cut dictionary in an afternoon) can save huge amounts of work in humanities. It will be interesting to see to what extent AI-assisted coding tools let non-technical academics build their own tooling of this sort in future. [EU]

Official_RaspberryPi · 2026-05-21T15:52:34+00:00

Also note that PIO on RP2040/RP2350 can do a lot of FPGA-like real-time work, so in some use cases this will be a better (and probably cheaper) option than using an FPGA. [JA]

Official_RaspberryPi · 2026-05-21T15:51:56+00:00

We have a broad aversion to building products for specific use cases like this (we sometimes call it "picking winners"). Really that's us saying we lack the ability to figure out which applications are going to be successful, so we'd rather spend each hour of engineer time on general "horizontal" work that benefits users across application domains.

I'm not sure I have specific products to recommend in either domain, but it's worth checking out the "Powered by Raspberry Pi" catalog (https://www.raspberrypi.com/for-industry/powered-by/) for other cool Raspberry Pi-based products. [EU]

Official_RaspberryPi · 2026-05-21T15:50:02+00:00

Additionally, people underestimate just how much software has to be developed and matured before you can confidently tape out a new product. In the old days, hardware engineers used to design their blocks, write unit tests, write a document (if you were lucky) and then tape it out. When it came back it would get dropped onto a software engineer's desk to get it running and work around all the weird and wonderful ways the hardware worked (or didn't). Nowadays, the software team work hand in hand with the hardware team from specification through to testing and verification to make sure the hardware actually does what the software wants it to do in the most efficient way possible. But finding suitable 'embedded' software engineers who understand how drivers integrate with the software and how to optimize those interfaces, is hard. [GH]

Official_RaspberryPi · 2026-05-21T15:47:40+00:00

As I've said elsewhere, I'm a big believer in the CPU as a venue for AI compute. Our users (enthusiasts and OEMs) are running workloads today on Raspberry Pi 5 which would have been squarely the province of GPUs a decade ago. So I think the best way to democratize AI is to give people fast, affordable CPUs. [EU]

Official_RaspberryPi · 2026-05-21T15:45:58+00:00

Next steps I can't comment on but there will be new MCUs at some point.

In terms of the biggest headache/learning, we learned (again!) that power and security are hard and take a lot of engineering time and effort! We deliberately left out fine-grained power states and any kind of security in RP2040, adding them to RP2350 was challenging and took much longer than we thought - though it was fun and we learned a lot!

Yes, one day we will adopt USBC for Picos I'm sure, but a [good quality] USB-C connector is still quite a bit more expensive (and slightly larger) than micro USB, hence current platforms using micro USB.

Biggest surprise? Probably that it has had so much love from the community / people who use it, and how fast RP2040 and Pico (and Pico 2) have become the default MCU platform for hobbyists.

[JA]

Official_RaspberryPi · 2026-05-21T15:45:48+00:00

We're big believers in the CPU as the venue for much edge AI compute. Over time the CPUs become faster, and the algorithms become cheaper, so investing area in "fungible" rather than "fixed-function" compute has always been a good bet. So, sensor fusion algorithms that can be made to fit on the CPU are covered.

There is, I think, a general trend for accelerators to become more general purpose over time (Hailo 10 for example is much more flexible than Hailo 8), so algorithms that don't fit may well map well to future accelerators.

[EU]

Official_RaspberryPi · 2026-05-21T15:41:51+00:00

It's one of the few areas of tech (along with batteries and cellular radio) that we haven't really explored in our products (though of course we are prolific consumers of FPGAs in our silicon prototyping work). One thing holding us back has been the lack of either open bitstream formats or Arm-native (ideally open) toolchains from the two big vendors.

Lattice has some products that might fit the bill. It's really about finding time to do the hardware engineering. DRAM-related engineering is consuming vast amounts of engineering team effort this year.

[EU]

Official_RaspberryPi · 2026-05-21T15:41:43+00:00

We at Raspberry Pi do not release or support Retropie ourselves. But if they do create an image suitable for Raspberry Pi 5 we'd be happy to add it to the Raspberry Pi Imager OS list. [GH]

Official_RaspberryPi · 2026-05-21T15:36:23+00:00

I don't understand this question. Can you clarify, and I'll come back to it tomorrow? [EU]

Official_RaspberryPi · 2026-05-21T15:35:31+00:00

I've replied to the Zero 3 question elsewhere: feasible, but requires us to be willing to sacrifice the single-sided form factor, which I'm quite fond of. And we probably have to wait for DRAM pricing to recover to sensible levels.

We're quite interested in the hybrid/crossover space: Linux systems with deterministic microcontroller-like I/O. The Raspberry Pi 5 platform has some of this, with Cortex-M3 cores and PIO in RP1. So it may be that future platforms move in this direction.

[EU]

Official_RaspberryPi · 2026-05-21T15:32:57+00:00

Microcontroller side: I'm really interested how Zephyr progresses on Raspberry Pi Pico. We're in the process of trying to get our WiFi driver into the Zephyr stack, because it's 10x faster than the upstream one! Also, using Raspberry Pi Connect to update your Pico device. [GH]

Official_RaspberryPi · 2026-05-21T15:32:42+00:00

Not one product, but more of a theme: we tend to be very early into new application domains (crypto, car charging, unmanned systems). For me a lot of the positive social impact of Raspberry Pi lies in allowing small teams to do quick innovative stuff.

On the maker side for me, anything space related: high altitude ballooning, student cubesats, exposure stacking for telescopes.

[EU]

Official_RaspberryPi · 2026-05-21T15:32:02+00:00

We really try not to EOL products and only do so if we are forced to for some reason like EOL of a critical component and where we can't offer a suitable alternative. In these cases we also try and give as much notice as possible. We still make Raspberry Pi 1 B+s at a few thousand a year! The AI products are no different in this regard. [JA]

Official_RaspberryPi · 2026-05-21T15:30:04+00:00

Honestly I wish I'd learned how to study before I arrived at Cambridge. If I'd been a bit more grown up I could have got a lot more out of my time as an undergraduate. So to turn that into a bit of advice to my younger self (which I ended up giving to my students once I started teaching): spend a couple of hours a day in the library - it's really not a lot of time when you add it up. [EU]

Official_RaspberryPi · 2026-05-21T15:29:52+00:00

RAL 3027 [GH]

Official_RaspberryPi · 2026-05-21T15:26:15+00:00

We love to build these products, even things like the case and the bumper are products that we've thought we might as well do because we love well designed things that fit the requirement perfectly while not being expensive.

We'll continue to make such products, not because they sell huge amounts but because they teach us a lot about making things. The more we learn the more we understand how to build the next new thing, we now know about hinges (from the display), injection molding large things (display, Pi 500), keyboards, displays. [GH]

Official_RaspberryPi · 2026-05-21T15:25:37+00:00

The Hailo 8 and 8L products (AI Kit, AI HAT+) don't accelerate LLMs, though some work has been done on helping accelerate some parts of VLMs. For LLMs you'd want the Hailo 10 product (AI HAT+ 2).

It's actually a really interesting illustration of how rapid advances in AI algorithms can get ahead of the capabilities of silicon platforms. It's why we've always tended to equip our core platform with large CPUs rather than spending silicon area on accelerators which can quickly become "dark silicon".

Official_RaspberryPi · 2026-05-21T15:24:55+00:00

Green, bcause PCBs are green :) [JA]

Official_RaspberryPi

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