[HN Gopher] Why TinyML is still so hard to get excited about
___________________________________________________________________
Why TinyML is still so hard to get excited about
Author : mariuz
Score : 109 points
Date : 2023-04-04 13:34 UTC (9 hours ago)
(HTM) web link (staceyoniot.com)
(TXT) w3m dump (staceyoniot.com)
| m3kw9 wrote:
| Prob now you got GPT and there is a new baseline they have to
| live up to
| Buttons840 wrote:
| I've been learning how transformers work, and also reading about
| RNNs.
|
| It seems that transformers have succeeded because they can be
| parallelized, and solve many of the problems that RNNs have. This
| has lead to the advancements we've seen recently with GTP. Big
| companies are able to throw their data centers at the problem and
| train impressive and massive models.
|
| Part of me hopes that a non-parallelizable AI architecture might
| be discovered which performs even better. Perhaps the problems
| with RNNs could be solved in a way that doesn't parallelize? We
| would be so fortunate if a desktop computer could run an AI
| that's half as good as Microsoft's or Amazon's best AI. I would
| love to see the advantage of the data center removed.
|
| Philosophically, this does make some sense. The wisdom behind
| sayings such as "adding more people makes the project even later"
| exist because the greatest intellects we're aware of (ourselves)
| do not parallelize well.
| brrrrrm wrote:
| ML is still in a compute hungry growth phase. Every exciting new
| achievement in accuracy requires more compute than before. It
| makes sense that tinyML, which has less compute, would always
| have lagging modeling support and be a bit less interesting.
|
| TinyML does result in much cheaper products, though.
| bambax wrote:
| I'm sure there are lots of fun things to do with an Arduino that
| could recognize gestures; I'm very surprised nobody's "excited"
| by this?
|
| For example, I made a photobooth simple device based on a Pi and
| a regular DSLR; the person takes a photo by pressing a button,
| then the Pi checks the camera and sends the latest image in a web
| gallery somewhere. The problem is the button: it needs a remote.
| If wired, it risks destroying the whole apparatus if someone
| pulls on the cord; if wireless, it risks being lost.
|
| A gesture-based trigger would be super cool; but having it run on
| the Pi through the DSLR risks damaging the camera, so it should
| run on a different device, cheap and not too power hungry, such
| as an Arduino.
|
| What about some kind of MIDI-controller based on an Arduino that
| could recognize gestures?
|
| I also made a webapp to learn sight-reading (babeloop.com) but it
| requires users clicking or tapping on the screen, which is not
| natural.
|
| It would be cool to be able to listen to users reading notes out
| loud and detect if they're right or wrong, on the fly, locally in
| a browser or on a phone. A light general speech recognition model
| such as VOSK is 40Mb and is able to recognize most phonemes; but
| for music sight reading, there are only 7 syllabes, so one should
| be able to make a much smaller model? I don't know how hard it
| would be though to train my own model...?
| JohnFen wrote:
| > I'm sure there are lots of fun things to do with an Arduino
| that could recognize gestures
|
| Arduinos can recognize gestures, faces, etc. right now with
| well-established tech, no servers needed. I've had a couple of
| robots running around my place that do this sort of thing for a
| number of years now.
| tiedieconderoga wrote:
| Embedded platforms generally have very little memory and very
| few hardware threads.
|
| Tiny SoCs will likely need accelerators to run more interesting
| models. For example, ARM is working on a ML coprocessor to pair
| with their Cortex-M chips.
|
| https://www.arm.com/products/silicon-ip-cpu/ethos/ethos-u55
| bob1029 wrote:
| After the initial obsession with Jupiter-scale models, we quickly
| discovered that very small models can perform _even better_ if
| you reorganize your problem.
|
| Last week, we were trying to fine tune a 175b parameter model to
| take a natural language prompt with hopes of directly-outputting
| correct, domain-specific SQL. Now that reality has passed, we are
| looking at different paths.
|
| As of this week, we are trying to hit everything with the binary
| classification hammer. Turns out you can train a model to output
| 1 of 2 possible tokens with exponentially fewer parameters,
| training items, machine hours, etc. The statistics available in
| binary classification are also incredibly powerful and the
| results are trivial to reason with.
|
| Even if you need _thousands_ of binary classifiers, their scale
| and granularity makes this a non-event or potentially an
| advantage.
|
| The real integration magic with AI/ML is starting to look like a
| weird form of set theory. At this level of complexity, detecting
| (and potentially confirming) the user's intention is way more
| important than trying to draw a direct map from input to
| destination.
| cxie wrote:
| TinyML would depend on the breakthrough in Edge/embed AI chips,
| which doesn't seem to come in the near future...
| jononor wrote:
| Why do you say that? There are microcontrollers announced with
| neural network accelerators integrated, and low power FPGAs
| with accelerators on the market, along with many chip startups
| aiming to provide milliwatt scale dedicated neural chips.
| svantana wrote:
| I'm very into TinyML - not because of IoT but because small and
| fast models work well in (clientside) webpages, in realtime
| systems and pretty much everywhere. All while consuming less
| resources, which should be celebrated. Also, it's more democratic
| - anyone can compete in this field, supercomputer not needed.
|
| IMO, what is needed is a larger focus on resource consumption in
| competitions, benchmarks and rankings. For example, I like that
| you can rank some lists on paperswithcode by number of parameters
| [1].
|
| [1] https://paperswithcode.com/sota/image-classification-on-
| imag...
| reisender wrote:
| It seems like many of the TinyML use cases are hidden or somewhat
| dull, making it difficult to get people excited about it. Do you
| think there are ways to make TinyML more exciting and appealing
| to a wider audience? How can we better showcase the potential of
| TinyML and its ability to bring more privacy to IoT and give
| everyday products superpowers?
| hosh wrote:
| How about just being able to run a home assistant with AI
| support to reprogram the home assistant, without having to
| spend a lot more electricity? They don't have to have
| superpowers to be useful.
| marcosdumay wrote:
| I expect tinyML to be way too tiny for that.
|
| The clear use-case for it is mechanical control and feedback.
| But it seems that every robot has enough tiny problems that
| you can justify a larger CPU anyway. I too am having a hard
| time being excited about it.
| STM32F030R8 wrote:
| My home assistant runs on 5-10W power. Nothing it does
| requires a lot more electricity than a light bulb.
| hosh wrote:
| Does that home assistant have a self-hosted LLM interface
| that helps you with configuration and setup?
| hosh wrote:
| That's weird. Being able to use AI without being beholden to Big
| Tech seems like a huge win to me. Especially when I want to
| ensure that the AI is making best effort for my local community's
| best interest, and not the best interest of a large corp.
| mirker wrote:
| Even so, you can run models on a private cloud. No need to do
| anything but sense on an embedded device.
| alex_sf wrote:
| 'private' cloud.
| mirker wrote:
| 1 GPU in a NAS server is all you need. Pretty simple.
| alex_sf wrote:
| I agree, but that's colo/on-prem. Not a private cloud,
| which is typically just some allocation of dedicated
| resources from a public cloud.
| JohnFen wrote:
| Huh. I always thought of "private cloud" as meaning "my
| own server", not a carveout on a public cloud. I learned
| something new today.
|
| How does such a "private cloud" differ from using the
| "public cloud"? The two seem identical to me.
| JohnFen wrote:
| A device that doesn't need a network connection to work beats
| a device that does every time.
| hosh wrote:
| That's a huge burden on the natural resources (electricity).
|
| Beyond local control, I gave other examples of embedded AI in
| other comments -- or more specifically, what you can do with
| an embedded LLM. Namely, being able to have a better human
| interface for complex settings, and being able to reprogram
| protocols (or anything that is "software-defined") for
| future-proofing.
| mirker wrote:
| Integrating an accelerator into a dishwasher is also
| expensive. How many inferences are you going to get out of
| it before the hardware is outdated? Once a day for 5 years
| may not be enough to justify the cost. Compare that to
| having a single GPU in a server in your house that services
| all your IoT devices, which can be readily upgraded and
| requires no special software. The is no benefit to doing
| inference on device unless you are in the business of
| selling said devices.
| hosh wrote:
| A big part of TinyML is finding alternate paths for
| implementing AI in resource-constrained space.
|
| We already have SoC that is functionally not so much
| different from modern microcontrollers. Depending on
| economics of scale, it isn't that big of a leap of
| imagination to see a microcontroller which includes 4-bit
| vector ops like a GPU.
| STM32F030R8 wrote:
| >huge burden on natural resources
|
| Can you explain? I don't see how sending data to the cloud
| is a huge burden compared to say an EV or your AC unit.
| hosh wrote:
| If by "private cloud", we mean carving out something from
| a public cloud, I'm still not sure I'd want something as
| important and private as AI to be in a cloud facility.
|
| Even if you put together a private cloud in a data
| center, it's still going to use up a lot more electrical
| resources compared to say, an iphone-sized usage, much
| less in a low-powered, embedded application.
|
| Also, there's a tendency for our civilization, when we
| make efficiency gains with breakthrough technologies, to
| then expand our usage. We don't do a great job of
| actually reducing overall energy expenditure.
| hgsgm wrote:
| The article is about a consumer's perspective on uninspiring
| proprietary products being offered by Big Tech.
|
| If you build the thing you are talking about, you will create
| the excitement currently missing.
| hosh wrote:
| Sure, because Big Tech is trying to retain control of the
| market via subscriptions and rent-seeking.
| vlovich123 wrote:
| > So instead, Warden's company is releasing a new sensor that can
| scan a QR code. The idea behind this $6 sensor is that appliance
| makers can put it inside their products as a method of getting
| devices onto Wi-Fi easier. A user could simply show their Wi-Fi
| QR code (I find mine in my router app) to the sensor and get
| their, say, fridge or washer online. I think it could be neat as
| a way to transfer a recipe to an oven, or specific washing
| instructions to a washing machine for particular items of
| clothing. Unfortunately, unlike scanning a new shirt and getting
| the machine to change its parameters to provide the best wash,
| many of the use cases for TinyML are going to be kind of boring.
|
| Sorry. What's the ML piece here? QR codes are from the 90s and
| don't use any ML I'm aware of...
|
| > However, at the conference Warden told me that, while he'd
| quickly discovered that the model worked, educating people about
| new gestures was tough. "No one knows that these gestures are
| available," he said. This makes sense. If you remember back to
| the launch of the first iPhone and its touchscreen, the first ads
| and demonstrations focused on things like taps and pinch-to-zoom.
| Those weren't intuitive; they were taught.
|
| And if that were true, that's solvable just like with the iPhone
| by having tutorials when you boot your TV. I think what's
| actually the case that the CEO doesn't want to admit is that he's
| having trouble convincing TV makers this is a useful model when
| they're all going into voice-operated UIs. That and the BOM cost
| makes it unappealing.
| vlovich123 wrote:
| > Elsewhere at the event, HP showed off two TinyML
| implementations with ST Micro that are embedded in new laptops.
| The first TinyML model uses a gyroscope to detect if a laptop
| has been placed in a bag or taken out of a bag. The idea behind
| the implementation is that the laptop will start booting up
| when it's taken out of a bag in preparation for its owner to
| use it. If the model detects the laptop has been placed in a
| bag, it will change heating and cooling parameters to make sure
| the laptop doesn't overheat.
|
| And when the model gets it wrong (which it invariably does)
| you've got a laptop that failed to be in sleep in a bag (maybe
| you fallback to more primitive models that are foolproof like
| increased temp + lid closed = in bag). But seriously. If you go
| to sleep on lid close, putting it in a bag doesn't really
| change your thermal envelope (should have happened on lid
| closed). And booting before your lid opens seems silly when
| Apple shows that it can be done near instantaneously. In other
| words, this seems like a PM developed feature for promo instead
| of good engineering being done.
|
| > The second use case also helps with thermal management. In
| that use case, the laptop detects when it is on a hard or soft
| surface. If it's on a soft surface, like a bed or a person's
| lap, it will try to run cooler so as to avoid overheating.
|
| Ok. Maybe this is interesting. But do you actually need ML or
| is it enough to define a thermal budget and recognize a solid
| surface can probably dissipate heat more quickly and anything
| beyond that doesn't buy you all that much.
| digging wrote:
| All of these use cases seem like AI will only do a worse job
| of solving the problem.
| nelgaard wrote:
| Yes, with these kind of issues you need to keep it very
| simple.
|
| I have an old Chromebook that runs Linux. I did have the
| problem that it would sometimes wake up in my backpack and
| run very hot. Eventually I found out that the plastic lid
| was soft enough that it would bend and let the screen touch
| the touchpad which would wake up the Chromebook. It was
| possible to disable this behavior but it was not simple
| enought.
| Xelynega wrote:
| This is giving blockchain/cryptocurrency ptsd. "We are
| early, it's just not there yet"
| marcosdumay wrote:
| How dare you? AI pioneered that kind of empty promises
| _decades_ before blockchain was even a thing!
|
| But, seriously, this is just a "look at me!" scream to
| get customers or investors. People do that with every
| single thing (doesn't even need to be an actual thing),
| and it's no fault of the thing at all. It's not a matter
| of being there yet or anything, it's just dishonest
| people.
| Joker_vD wrote:
| > I think it could be neat as a way to transfer a recipe to an
| oven, or specific washing instructions to a washing machine for
| particular items of clothing.
|
| ...is there also a neat way to _remotely_ transfer the recipe
| 's ingredients to an oven or load clothes into a washing
| machine?
|
| One of my buddies once joked about the smart homes that they
| allow you to unlock your front door while being anywhere in the
| world -- but sadly, there is almost never a useful reason to
| unlock your house's front door from 2000 km away.
| rcme wrote:
| If you ever have serious work done on your house, it requires
| letting contracts in for weeks. If you're not home, you need
| to leave them a key outside where dozens of people likely
| have access to it. I always change my locks afterwards, but a
| digital solution would be pretty nice.
| JohnFen wrote:
| I don't know. I think a lockbox would be a cheaper and
| easier solution for that use case.
| rcme wrote:
| How would that solve the problem? Any of the workers
| could take a picture of your key and recreate it later.
| JohnFen wrote:
| Perhaps I misunderstood the problem you were talking
| about. I thought it was leaving a key unprotected. A
| lockbox resolves that, by restricting access to the key
| to people who know the lockbox combination.
|
| You mentioned rekeying the lock after the work, so I
| assumed that key copying wasn't the issue as you found a
| solution for that.
| throwaway1777 wrote:
| Airbnb is about the only one.
| zmix wrote:
| Or your children lost/forgot the key and nobody is at home.
| cossatot wrote:
| Or letting someone in to feed your cat.
| throwaway1777 wrote:
| Housesitting is a good one
| vlovich123 wrote:
| What about when you're at work and want to let the repair
| person in? Or you run an Airbnb and want to let in your
| guests without having to worry about keys and lockboxes. Or
| you want to let in a family member. I think there are valid
| reasons for that.
| JohnFen wrote:
| I'm guessing that the existence of edge cases like that are
| why Joker_vD included the "almost" qualifier.
| ipaddr wrote:
| You would let a repairman in without someone present?
| bckr wrote:
| Well you forgot about my micro drone that follows them
| around filming their every move.
|
| ... except unironically
| vlovich123 wrote:
| Sure. In such a scenario I could have cameras in place if
| I'm super paranoid. In my experience repair people have
| been extremely professional and have a reputation to
| uphold, so if I can't be at home and a repair needs to
| happen, I don't see a problem if that convenience is
| important to me.
| justrealist wrote:
| Yeah, this reminds me of the other article on the
| frontpage, about Google not understanding why anyone needs
| 5m files in Drive. Well, maybe _you_ don 't.
|
| Maybe it's not something that affects you, or 80% of
| people, 80% of the time... that doesn't make it useless.
| Try to step outside your own life even a few steps...
| burlesona wrote:
| True, but it's pretty awesome being able to check if you
| forgot to lock the back door, and then lock it, as your
| flight is landing 2000km away.
| Dalewyn wrote:
| >Sorry. What's the ML piece here? QR codes are from the 90s and
| don't use any ML I'm aware of...
|
| You must have missed the memo, _everything_ is AI now.
|
| Your toaster? It toasts your bread with AI.
|
| Your microwave? It heats your food with AI.
|
| (Yes this is sarcasm. "AI" has become a meaningless buzzword
| thanks to marketing and the media. Same goes for "machine
| learning".)
| neodypsis wrote:
| > Sorry. What's the ML piece here? QR codes are from the 90s
| and don't use any ML I'm aware of...
|
| Presumably they are using object detection to recognize where
| the QR codes are located in the image? Which they then feed to
| the standard QR decoding algorithms.
| vlovich123 wrote:
| Yeah I note that down below in my response:
|
| > That being said, it's possible the ML piece is about
| reading multiple QR codes at once in different angles. I
| could see that requiring some ML. But still. It feels like a
| solution in search of a problem since they seem to be taking
| the "throw spaghetti at the wall and see what sticks"
| approach to building products.
|
| What I'm saying is that washing clothes doesn't seem to
| benefit from any QR codes. And the cooking example is even
| more confusing because presumably you'd have one for the
| recipe, not per ingredient
| neodypsis wrote:
| I can see how it could be useful to have such an input
| method in an embedded system for some configuration options
| like WiFi credentials.
|
| > What I'm saying is that washing clothes doesn't seem to
| benefit from any QR codes. And the cooking example is even
| more confusing because presumably you'd have one for the
| recipe, not per ingredient
|
| Well, we are in the age of IoT. Every appliance now wants
| to be connected to the Internet.
| sleepybrett wrote:
| Given that this stuff was built into the original and revised
| kinect software on the xbox (360 and one) and no-one really
| knew or cared. I believe that the initial setup stuff on the
| xbox one covered the voice commands / gesture commands. I have
| a feeling they were soon forgotten. Unfortunate given how
| powerful the kinect, especially version 2, is. When it comes
| down to it, gesture control is often fiddly and obscure (there
| is no button on the screen to push to remind you the function
| exists, you just have to know 'if i wave at it, it will
| probably turn on'). Both of those downsides turn it into a non
| starter for most users.
| __MatrixMan__ wrote:
| Probably you're washing more than one shirt at a time, so the
| optimal washing parameters for the whole load is going to be
| some not-quite-average of the the data on all of the input QR
| codes, combined with whatever the machine sensors learn. Seems
| pretty ML to me, though the writing could use work.
| vlovich123 wrote:
| At which point the user can pick the optimal parameters
| anyway (and likely do a reasonable enough job) without fancy
| ML. Fancy ML would be things like "take out items xyz" to
| wash just whites.
|
| That being said, it's possible the ML piece is about reading
| multiple QR codes at once in different angles. I could see
| that requiring some ML. But still. It feels like a solution
| in search of a problem since they seem to be taking the
| "throw spaghetti at the wall and see what sticks" approach to
| building products.
| nelgaard wrote:
| Yeah, about 15 years ago when there were companies planning
| to replace barcodes with RFID tags on all products, a big
| selling point was that washing machines could detect red
| socks in a white wash.
|
| Someone did make such a washing machine, from 2012:
| https://www.appliancesonline.com.au/academy/appliance-
| news/s...
|
| Note the caption: "The washing machine's brains do the
| thinking for us".
| __MatrixMan__ wrote:
| I can't be bothered to go through the tags and think about
| settings. If the laundry destroys it I'll just stop buying
| things like that going forward. Probably there are people
| as lazy as me, but with a better eye for fashion. Maybe
| they would care?
| JohnFen wrote:
| Is this an actual problem that needs solving?
| __MatrixMan__ wrote:
| I wouldn't know, I wear the same thing every day, it all
| goes in the same load at the end of each month(ish).
|
| But I could be convinced that our clothes would wear more
| slowly if the machines had more data about what they were
| washing.
| JohnFen wrote:
| I don't think that's likely to be true. However, there is
| an easy way to reduce the damage to your clothing that
| washing causes:
|
| 1) Wash in cold water 2) Use less detergent 3) Set your
| dryer on the "low heat" setting.
| otabdeveloper4 wrote:
| > get their, say, fridge or washer online
|
| Yeah, no thanks.
| justaregulardev wrote:
| The ability to have models that can run on resource-constrained
| devices does feel like a strong direction for ML to go in and
| could lead to greater user privacy. However, I'm unconvinced by
| the IoT-aspect of this tech. In many ways, it feels like IoT has
| "failed" to be as popular with consumers as expected and feels
| overhyped. Will adding ML to IoT devices really make a
| difference?
| hosh wrote:
| Adding an embedded LLM as a human interface for every appliance
| is a huge win-- for consumers at least.
|
| For example, I have a dishwasher with a bunch of settings, can
| sense load, etc. It's got a touch interface that works with wet
| hands. Or I can tell it to start with the usual settings, or
| that a particular load is a bit different. Same with the
| laundry, the pressure cooker.
|
| It is less mind bandwidth when you got kids.
|
| What I don't want, is for my appliances to do is to phone home
| to the makers.
|
| LLMs (if you don't somehow trigger its insanity) can be far
| more capable than Siri. How do you get that into something more
| energy efficient than a high end gaming rig?
|
| Something more hidden is using LLMs to reprogram machine-to-
| machine protocols. That might extend the lifetime of machines
| that have to talk with other machines, but it breaks planned
| obsolescence.
|
| There are plenty of exciting product ideas. Whether they are
| exciting revenue generators are another thing entirely.
| calibas wrote:
| Adding hardware capable of running an LLM would significantly
| increase the price of appliances, not sure that's a win for
| consumers.
|
| In the context of the article, an LLM is kind of the opposite
| of "TinyML" and not something most IoT devices could even
| handle.
| hosh wrote:
| Not if you can condense the LLM into being able to run on
| the embedded hardware.
|
| Article aside, reducing energy use for models is one of the
| research areas for TinyML.
| calibas wrote:
| I'm skeptical that an LLM with billions of parameters can
| be compressed down into something that runs on embedded
| hardware and still remain useful.
| bckr wrote:
| Skeptical you should be, but I'm optimistic. We have
| papers showing that knowledge in these models can be
| edited and deleted. Sam Altman makes the point that too
| much compute is being spent on using the LLM as a
| database.
|
| Thinking about how few things any of these CUIs need to
| know about, I'm optimistic that we can distill them down
| to a workable size while maintaining the LLM magic.
|
| "Fridge, what is the meaning of life?"
|
| 'Sorry, I don't know about that. Ask me something about
| what's in your fridge.'
|
| "Okay how many eggs do I have."
|
| "I see 3 eggs."
|
| When I can have that conversation by proxy through my
| phone's onboard CUI while at the store, I'm going to get
| a lot of value out of that.
| JohnFen wrote:
| > It is less mind bandwidth when you got kids.
|
| If it works like ChatGPT does, then I would find it a greater
| mental burden. You'd have to carefully craft what you're
| telling it, or engage in a conversation of some sort, instead
| of just hitting a couple of buttons or turning a dial.
| marcosdumay wrote:
| > Adding an embedded LLM as a human interface for every
| appliance is a huge win-- for consumers at least.
|
| So, appliances get even harder to understand settings, that
| are actually illogical, instead of just having hidden logic?
| That's not a clear win.
| bckr wrote:
| No, there's an underlying logic and underlying settings
| that are still accessible.
|
| But transparently wrapped around that there's a "good
| Clippy" who can teach, interpret, and orchestrate those
| settings with a CUI (conversational UI, pronounced "koo-
| ee").
| marcosdumay wrote:
| Oh, a settings assistant is much easier to get right.
|
| It is just completely against the modernly accepted "best
| practices" for devices and interface development. So I
| don't see how we can get it. But yeah, it could be good.
| [deleted]
| eschneider wrote:
| ML has been on IoT devices for years. Heck, there are embedded
| arm SOCs with built in CNN coprocessors that will run your
| tensorflow models as-is. Again, they've been shipping in volume
| IoT products for years.
|
| If ML is a win for an IoT device, the hardware's been there for
| a while, though I'm sure yet-cheaper hardware might unlock a
| few more applications, it doesn't feel like much of a game
| changer.
| lamuswawir wrote:
| IoT sensors powered by ML may not provide good use cases for
| consumers, mostly because all things they can do can be done by
| a large model in the cloud, plus a phone. It will get
| interesting when we ask what use cases can't be solved by
| phone+cloud combo.
|
| Such things as air quality management are good use cases. You
| can't use your phone to do that.
| digging wrote:
| > Such things as air quality management are good use cases.
| You can't use your phone to do that.
|
| Why not? I am strictly against IoT in my household so I may
| be way off base, but why can't your phone control your air
| purifier?
| mirker wrote:
| Privacy doesn't matter unless the IoT devices are secure. Often
| times, they're not.
| RugnirViking wrote:
| From my work in AI & robotics, its generally finnicky and a bit
| crap even when a ton of work goes into it with a lot more compute
| (jetson nano or higher). I feel like trying to optimise those
| kinds of models is a bit niche/premature
| steve_adams_86 wrote:
| As a hobbyist that has been my perception of the situation as
| well, though I wasn't sure if I was just missing something.
|
| The potential is immense and exciting, but try as I might, I
| can't seem to make even fairly simple things work reliably as I
| want them to.
|
| One thing I love about embedded projects is that you can
| achieve pretty incredible reliability because everything can be
| so dialed in and isolated from points of failure in, say, an
| operating system. Trying to use ML for simple tasks felt like
| it eliminated that and introduced seemingly arbitrary failure
| into projects I really needed to work perfectly.
|
| Again, just a hobbyist, so I can't make any broad statements.
| It seems to align with what you're saying though. Once we get
| past this hump and have more powerful/effective models at a
| reasonable price point, I feel like it could be transformative.
| At the moment it's still extremely interesting and fun to
| experiment with.
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