NotebookLM

Google has this AI-supported Notebook system where you can upload sources in various forms (link to a website and PDF upload probably the most useful in the embedded context). I just tried it out by using it to explore the CH32 family, which is notorious for having lots of information in Chinese only. I started picking a random CH32 (happened to be CH32V003) on LCSC and downloaded its datasheet. As expected it comes up in Chinese.

I upload this PDF into a new NotebookLM notebook. The usefulness is obvious immediately. NotebookLM can read Chinese of course and I can immediately ask it questions like what variants exist, have it generate a table of variants with pin count and flash and SRAM size,...

Next I wanted to know about other CH32 models not described in this datasheet.

Unfortunately a big limitation of NotebookLM is that it cannot go google by itself. So I had to navigate to the WCH.CN website myself to find the list of WCH32 models.

Next I hit one of the curses of the modern internet: The table is purely Javascript-generated. So giving the URL to NotebookLM doesn't work, nor can you save the page or print it to PDF easily. JavaScript is a curse. Maybe the advent of AI will be able to do what disability advocates did not manage to achieve and bring back server-generated HTML.

Anyway, I managed to get the table out by using Print to PDF with a trick. I picked the largest page size available (A0). That fit the whole table. Apparently Chrome runs the JavaScript of the website again for the appropriate page size, so that I actually got more information on the page rather than getting the limited part visible on my screen fit into an A0 page.

I uploaded the PDF with the table to NotebookLM and at that point I was able to query about the whole range of CH32 models. I discovered that they have really small (20 pins) parts that can still do USB host. I decided to dive deeper.

Having identified a suitable model (CH32L103) I again had to manually go to the WCH.CN website to locate the link to the reference manual. This is one of the biggest limitations of NotebookLM right now. I can google "CH32L103 reference manual" and the first hit will be a page with a download link to the PDF. I really hope they teach NotebookLM to do that for me so that it can add sources automatically.

Anyway, I just added the download link (right click, copy link location, paste into NotebookLM's source window) to the reference manual.

Next I asked the AI to give me a short rundown about how to implement USB host support and it gave me a step-by-step with the registers and what values to write into them, complete with the sections in the reference manual that it extracted that data from, so that it's easy to check the actual RM (which is English, btw, so WCH does provide English documents even if LCSC may not have the English versions linked in its shop).

Next I explored the clock configuration, because USB needs a precise clock. I asked about how to provide the 48MHz clock with the least amount of pins. In particular whether I can use a Bypass-clock so I have 1 more pin for GPIO. NotebookLM suggested to use the internal HSI instead, because the manual says it can be scaled up to 48MHz. And that would not use any pin.

I like to point out that my question was specifically about Bypass clock vs crystal oscillator. I had mentioned to the AI that my goal was to save pins. But the AI brought up the idea of using the internal HSI only on its own. Pretty cool.

Of course I was skeptical, so I asked "The internal HSI is precise enough for USB host?" because it would be really unusual to be able to do USB host without an external clock.

NotebookLM provided a really good answer. Here's a direct quote:

HSI Precision

Source 6 describes the internal HSI characteristics. The typical frequency of the HSI >is 8MHz, with an accuracy of -1.8% to 1.8% after calibration at temperatures between >0°C and 70°C. This accuracy range translates to a possible frequency deviation of >±144kHz from the nominal 8MHz.

USB Clock Requirements

The USB 2.0 specification mandates a precise 48MHz clock for full-speed operation. >While the specification does not explicitly state a tolerance for this clock, it is >generally understood that a tight tolerance is required for reliable communication. >Typical tolerances for USB clocks are in the range of ±50ppm (±2.4kHz at 48MHz).

Analysis

The HSI's accuracy of ±144kHz falls far outside the typical tolerance range for USB >clocks. Therefore, directly using the HSI for USB host functionality would likely >result in unreliable communication.

I haven't verified the numbers, but that's not so important. The important thing is that I did not add the USB spec to my resources and I don't think the reference manual would have mentioned these requirements, so it seems that the training data of NotebookLM already includes some tech stuff like the USB standard.

So we settled on using the Bypass-clock option (which NotebookLM tells me exists) because it needs only 1 pin.

Next I asked "Does the MCU have an internal bootloader for flashing or do I have to use SWD?"

It replied with detailed info with references to the manual and the following conclusion:

The CH32L103 series offers the flexibility of using either the internal bootloader or an SWD programmer for flashing the device. The bootloader provides a convenient and > pin-efficient option for programming and updating the device's firmware.

Note that the AI has remembered my desire to keep pin usage low and refers to this requirement in its answer without me specifying this in the question.

At this point I stopped with my test. I didn't check if and how well NotebookLM can write code. I would assume it can do that since ChatGPT can do it. But I'm sure you can tell NotebookLM to write you a USB host driver in C based on the reference manual and it'll produce something which may be useful for some people. Personally I only use AI code generation for small Python scripts.

In any case, even if you use none of the other features like writing and organizing your own notes in the notebook, the feature of uploading your sources and talking to the AI about them is already good enough to make this extremely useful.

Finally, after the useful features, I tried out the silly bullshit: NotebookLM can generate a podcast based on the sources. As I'm writing this I'm listening to 17 minutes of Generic-Female-Podcast-Host talking to Generic-Male-Podcast-Host talking about microcontrollers, how they are useful in the real world, how the CH32L103 specifically is useful to build a battery powered weather station because it requires so little power and has the feature to wake up from a variety of wake sources and bla bla bla. It's bizarre!

It’s been months and we all know NotebookLM is google’s best contribution to the AI marketplace. But still no app. No one cares about their other AI apps or Gemini. We all want the NotebookLM app.