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While watching a YouTube video I saw an advert for the Plaud AI Note Taker [1]. The Plaud device looks pretty good for what it does, taking notes and managing them, using some sort of LLM function to manage the notes. The devices all cost about $300 which is an amount that doesn’t seem unreasonable for someone who’s in a lot of meetings. One of the models is the “NotePin” that seems comparable to the Humane AI Pin I previously blogged about [2].
The business model for Plaud is based on only allowing 5 hours per month of free transcriptions, then charging $16.25/month for 20 hours per month and $33.33/month for unlimited use. That’s quite expensive for any serious use.
The number of people in the market for an audio recording system that automatically transcribes things may be greater than the number of people in the market for all the stuff that the Humane AI Pin did, but it still may not be enough to run a profitable business when competing with apps on mobile phones.
While the product does look decent it seems that they are making the same mistakes as the original Humane developers did, of wanting to lock it down as a subscription based service which reduces the usability of the device. If they had sold an Android hand-held computer with their own app pre-loaded and allowed the user to install a different app then it would have been much more usable. If they had sold Android devices designed for the note taking market and allowed people to choose their own apps to install then their products would have a much longer life expectancy.
The majority of Android devices in use are probably out of support but still working while the Humane AI pin can’t be used any more and at some time in the not too distant future the Plaud devices will also become unusable. People who buy devices like the Plaud seem to be unaware of the history of such things and the expected future for them. But possibly some people just consider $300 for a year of use to be an acceptable price. If someone wanted to purchase a new high end phone every year and sell their previous one they would probably have a net cost of about $500/year.
Maybe I should look for work with a company with an implausible AI based business plan. It would be fun developing such a device if you weren’t emotionally invested in the project. Just develop new technology, earn a heap of money, play with fun computers, and move on to the next thing when it collapses. Just like all the Internet companies about 25 years ago.
Related posts:
After getting a HP Z4 G4 tower server/workstation to house my Intel Battlemage GPU [1] I’ve been playing around with some GPU stuff. For years I’ve been just buying GPUs based on the resolution and price and not bothering about anything else due to lack of ability to measure what cards are doing. The nvidia-smi program is really good for NVidia/CUDA setups but I hadn’t been aware of anything similar for AMD cards. As I prefer AMD cards for my workstations due to driver issues with NVidia that was a problem for me.
I’ve recently discovered that the program nvtop (Debian package nvtop) shows the GPU use of multiple GPU types, for me it’s worked on AMD and Intel discrete GPUs and shows some information on Intel integrated GPUs, I don’t have others convenient for testing at the moment. Currently BOINC has the Einstein@Home [2] project running on the HP Z4 G4 and it’s using between 66% and 100% of GPU compute power and 1.6G of GPU RAM. Using 100% GPU compute power allegedly takes 62W of power out of the 190W quoted TDP. I presume that the power use reported by nvtop is very inaccurate.
A friend installed a LLM on that system and the libraries used for the LLM were sufficient that BOINC just started using the GPU.
On my workstation running an AMD “[Radeon RX 460/560D / Pro 450/455/460/555/555X/560/560X]” (actually R560) with 4G of GPU RAM I have mpv taking 1G of GPU RAM to play a FullHD video expanded to a full screen window on my 5120*2160 display. I also have about 2G used by the kwin_wayland process (the Wayland server for KDE). That doesn’t leave enough GPU RAM to allow Einstein@Home to use the GPU. When playing the FullHD video in question (which is 1.2G for 42 minutes – about 500KB/s) at 1.5* speed (a common playback speed I use) that takes about 30% of the compute power on my GPU.
I had installed the rocm-opencl-icd package on my workstation (with a 5120*2160 monitor) and restarted boinc-client.service which is all that’s needed to allow BOINC to use an AMD GPU. Then the screen started flickering as the Einstein process repeatedly core dumped which I initially assumed to be it’s reaction to not having enough GPU RAM available. On every core dump the screen flickered so it went through a process of dozens of screen flickers until it had caused a sufficient number of core dumps and BOINC gave up running that job.
Another annoyance is that the boincmgr program (the graphical program for managing BOINC systems) launches two webkit processes that each use about 400M of GPU RAM, so even if other things weren’t using all my GPU RAM the boincmgr process would stop the BOINC jobs from using the GPU. I shut down some of the programs that were using GPU RAM until there was 2G free and the BOINC process kept crashing so it seems that there is some other issue.
On another system with a 4K monitor there were Chrome and Chromium GPU process taking 1.1G and 500M of GPU RAM respectively and the KWin Wayland process was taking 1G of GPU RAM. So that’s well over half the GPU RAM for just browsers and Wayland. With programs like Kitty (terminal emulator) and Nheko (Matrix client) taking over 100M of GPU RAM it seems that 4G is the bare minimum for GPU RAM with modern software and a 4K or similar display.
I also noticed the kscreenlocker_greet process taking 440M of GPU RAM. I wonder if a hostile web server could make a web browser take more GPU RAM and starve the screenlocker of GPU RAM, could that allow forcing a screen lock operation to fail?
It seems that 4G is the minimum for modern systems, which isn’t necessarily a problem as GPUs that are capable of driving 4K displays tend to have no less than 4G. My local computer store has new GPUs with 4G starting at $120 but 12G seems to be the next option up which starts at about $400.
Ebay currently has a selection of AMD GPUs with 8G of RAM under $200. I’ve had some problems with the GPU in my workstation crashing as described in my previous post where I thought it was driver issues [3]. I now believe that there are hardware issues and will look into buying one of the cards with 8G.
I need to determine which of the AMD GPUs that are currently going cheap on ebay are best. While my current PC has support for 150W PCIe power I’d rather something less power hungry than that. I have occasional issues of mpv reporting that my system is too slow for a video so slightly more compute power on the GPU would be good, but I think that every available option has significantly more compute power.
I need to find out what the relationship is between screen resolution and GPU memory. If I get an 8K display or an array of 4*4K displays (which is quite plausible as 27″ 4K displays go for $230 each) will I find 16G of GPU RAM as limiting as I find 4G now?
The nvtop program tracks PCIe data transfers for AMD GPUs, I haven’t yet seen more than 25MB/s and I need to do more tests to see what the maximum is. Running on an Intel Battlemage card nvtop doesn’t report PCIe data transfer speed which is a missing feature in either the driver or the program. I need to find out where the problem is and report a bug if someone hasn’t already done so.
The GPU RAM use of some applications seems excessive. 440M for a lockscreen? 100M+ for a terminal emulator? 320M for Thunderbird?
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I previously wrote about the upcoming UEFI CA rollover. Well, it's happened now - the old Microsoft UEFI CA from 2011 expired yesterday:
Third Party Marketplace Root (used for signing option ROMs and other software)
Log in
Subject: C=US, ST=Washington, L=Redmond, O=Microsoft Corporation, CN=Microsoft Corporation UEFI CA 2011
Validity
Not Before: Jun 27 21:22:45 2011 GMT
Not After : Jun 27 21:32:45 2026 GMT
It's dead - it's not coming back...
The world doesn't seem to have ended yesterday, so I guess we did ok? :-)
After a lot of prodding behind the scenes, Debian and many other distributions managed to get new shim binaries dual-signed with both the old and new CAs. The members of the shim-review team did a sterling job with reviews in the last few weeks. Since I started pushing people in May, we've had 21 reviews accepted successfully - see here for the list. Great stuff! Microsoft have also been working quickly - many of those shim submissions were accepted and signed by Microsoft very quickly too, with a turnaround time of less than 1 day in some cases.
Not all of those signed shims have been published and used by the distros involved yet, but expect to see them in the wild in the coming weeks and months.
These binaries should be good for people to use for the foreseeable future, until either we need to do another CA rollover or (sadly, more likely) we find an issue in shim that necessitates a new release.
We already have one of our new dual-signed shim
binaries in place in Debian, in unstable and testing (Forky) right
now. In a couple of weeks from now, we'll be rolling out very similar
new dual-signed shim binaries in the next point releases for Debian 12
(bookworm) and Debian 13 (trixie). We'll also be
upgrading fwupd in both those point releases, to make DB
and KEK updates work better.
For more information about these updates, see https://wiki.debian.org/SecureBoot/CAChanges. For your own safety, validate that your systems are updated when possible. If you don't, they may fail to boot in future.
