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Apple is reportedly spending ‘millions of dollars a day’ training AI
- deleted 3y ago[deleted]
- seydor 3y agowhere are they spending it?
- outside1234 3y agoNot on Siri!
- lmedinas 3y agoWho cares ? Apple at this point as like infinite money. Plus they need to integrate more and more AI to improve their products. They already have the Hardware, now they need the SW and AI to make use of them. Same deal regarding the Apple Online Services.
- rvz 3y agoPrecisely. No idea why you are downvoted. Apple has been in the highly profitable position in the billions to be able to sit out and wait for years, rather than hastefully join in the AI race to zero. So why race when you are already at the finish line? This is Apple's case and anyone who owns the hardware that they are making or creating and releasing $0 free AI models out there. This whole article and its comments is a great big storm in a tea cup.
- felix318 3y ago[deleted]
- morkalork 3y agoA co-worker wanted to show me a specific vacation photo and just wrote what was in it and the photo came up out of the hundreds he had like magic so that was kinda nifty.
- hiidrew 3y agoI find this type of image search incredibly useful – but mostly for when I take pictures of documents and it recognizes the text on them.
- kaveet 3y agoAs you're typing in the search term, you're also given a "Name contains <term>" option in the dropdown if you're strictly searching by filename
- felix318 3y agoSure but why not give me file name matches first instead of random pictures, since I started the search from Finder itself? Why try to outsmart the user? I have no problem with searching pictures using keywords if it’s limited to the Photos app.
- aikinai 3y agoSpotlight’s ordering is asinine but that doesn’t mean AI features can’t be very useful.
- wkat4242 3y agoYeah spotlight is so bad now. It's weird because when it first came out (tiger?) it was really good and fast. Now it sucks and it's slow.
- kalleboo 3y agoIt's still super fast for me, but now I have about 10x more internal storage in my machine than in the Tiger days (which is filled with random downloaded PDF files and other crap), so there are way more results, requiring a much more intelligent sorting algorithm than it ever did when it was new.
- spandrew 3y ago[flagged]
- angarg12 3y agoMy team does ML for a Big Tech co. Considering how much we spend on hardware, and multiplied by all the teams doing ML in the company, we are easily spending millions a day training AI just on business as usual. This seems reasonable for any big tech. This sounds like non-news to me. Maybe a fluff piece for Apple?
- goodbyesf 3y ago'Millions of dollars per day' is about $1 billion a year? Considering Apple's annual revenue is about $400 billion and its net income is about $100 billion, it's more than reasonable for apple to spend millions per day beefing up their AI. I guess 'millions of dollars per day' gets more clicks than 'apple spends less than .25% of its revenue on AI'.
- TuringNYC 3y agoThis seems like rounding error and a nothing-burger story given - size of apple - size of apple r&d - size of near future opportunity and value that might be gained
- bunabhucan 3y agoApple FY2022 R&D was $26.251B or $72m/day (of 365) "Millions" just means AI is more than 3% of R&D.
- verve_rat 3y agoThis does have one interesting consequence though. If Apple spends millions a day on AI training, then only similar mega-corps will be able to complete. AI is not a democratising force, it is a capital concentrator.
- outside1234 3y agoOnly millions?
- TacticalCoder 3y agoYup. It makes zero sense. Even at tens of millions a day, it'd still be pocket change for Apple. They're making $350 billions in yearly revenues. They're not taking AI seriously.
- cellis 3y agoEven if they spent 100 million per day it could arguably be money well spent and they would still be the 3rd or 4th most profitable company in the world.
- syntaxing 3y agoI think it was hacker news that compared voice assistants. It was Google assistant > Alexa > dog shit > Siri. Siri is such a joke that I do stuff physically instead. But on the flip side, how often do people choose a phone based on the quality of the voice assistant?
- doublerabbit 3y ago> how often do people choose a phone based on the quality of the voice assistant? Must be a fair few for the amount of money Apple makes on every new release.
- ekanes 3y agoWe don't choose it based on that only because it doesn't work very well. Some technologies have to be magical and great to really take off. For example, imagine if self-driving was everything that was ever promised. Sales of cars without it would plummet.
- byw 3y agoI'm honestly not sure why Siri sucks so much. Apple could probably hire 10,000 employees to manually train for various scenarios brute-force (10,000 x $200K (salary + admin) = $2B), and it would still be chump change to them.
- checkyoursudo 3y agoI use Siri to set timers, like for the pasta that I am cooking. It does pretty well with that. Every once in a while I get a 30 minute timer instead of a 13 minute timer.
- eli 3y ago"Millions a day" and a headcount of 16 doesn't actually sound like a huge investment?
- throwaway2990 3y agoWow the anti apple crowd out in full force today! “Wah Siri sucks” “wahh 5 years” The iPhone was in development for like 8 years before it saw the light of day and everyone shat all over it and it still redefined mobile phones. Apples Silicon was in development for like 15 years and now laptop makers don’t even have a leg to stand on. Apple isn’t going to release a half cocked ai project to the world. Apple isn’t Google who hasn’t released anything of note in like 10+ years. They aren’t Meta pouring billions into a metaverse no one wants.
- dalyons 3y agoSiri does absolutely suck though. There’s not really any credible defense at this point.
- throwaway2990 3y agoSure there is. Y’all talking about Siri when Apple hasn’t even released anything yet.
- o1y32 3y ago"Apple isn't going to release a half cooked ai project to the world" Sorry what again? What is Siri then? That's even less than a half cooked product
- throwaway2990 3y agoWhen Siri came out it was better than Google and Microsoft offering. So you point is invalid. While I agree it hasn’t improved over the years. Doesn’t change The fact it was good when it came out.
- wkat4242 3y agoReleasing something top-notch and then letting it whither away is a sad Apple tradition indeed. They've done this with the Mac pro multiple times. First the trash can, then the cheese grater. At least Google kills something when they lose interest.
- rvz 3y agoApple can afford to experiment and waste their money in the millions, because they are profitable in the billions. AI doesn't affect Apple's core central products at all. It's complementary. Unlike the majority of so-called ChatGPT-wrapper and VC fuelled LLM companies burning millions a day on training and scrambling to compete with $0 on-device AI models. Apple does not need to compete with OpenAI (Although Apple has the hardware and software to do so) and can do so at any time. Google is the one that needs to. So all of the "But but but Siri", "Siri is garbage", "Apple isn't doing anything with Siri", etc isn't even the point. On-device LLMs or AI is the thing that matters to Apple and Siri will likely transition to a hybrid offline / online system eventually. Apple is in no rush to compete.
- jeremiahbuckley 3y agoApple has a huge opportunity for AI + personal privacy if they can get an LLM on the phone that doesn’t need a cel connection to be good and they can somehow promise won’t phone home your info. I would recommend they spend more than this.
- late25 3y ago>It’s helmed by John Giannandrea, Apple’s head of AI, who was hired in 2018 to help improve Siri. I’m sure he’s a smart man, but considering where Siri is, and the fact he’s been there for 5 years, I’m not holding my breath.
- mhss 3y agoIndeed. Same thoughts. I think you need business & product smarts here not raw engineering smarts.
- TX81Z 3y agoEh, who knows really? Having something in the lab that works and getting a product team to understand how to make it useful to customers aren’t the same problem. In some sense I’ve always thought Apple is focused so much on reliability and deterministic approaches that wrapping their heads around probabilistic outcomes is harder than for other companies.
- sargun 3y agoAt a big company, unless you have some serious lubrication, the first 12-18 months are spent landing. Usually you have to land your big changes in a planning cycle which are usually 6-12 months. This often means, for your first ~2 years, you're not able to do much. That, plus the lost years of productivity during COVID -- I'd say it's okay to forgive for not turning the ship.
- hn_throwaway_99 3y agoWe are talking about 5 years, which is longer than the average tenure at most tech companies. I also don't buy any Covid-related excuse with this one. If anything, I personally saw at least a couple companies make good use of the "never let a good crisis go to waste" mantra, using the general chaos of the early months of Covid to make some long-standing necessary-yet-painful changes - that is, changes that pretty much everyone knew were the way forward in the long term, but had risk of hits to revenue or much higher expenses in the short term. Using the pandemic as an excuse to go all-in on AI/Siri (e.g. "People are spending more time at home/on screens and we need a better voice interface") would have been the perfect approach IMO.
- incahoots 3y agoHow much does a typical Apple programmer make a month? Salary no doubt, but I’m not aware that a team is operating at a million+ a day. Red Bulls don’t cost that much, and I doubt any of them are taking yoga classes during their shift lol
- TX81Z 3y agoI suspect most of that figure is in machine time, but otherwise they pay engineers a lot and Apple likewise occupies a non-trivial % of all the commercial real estate in Cupertino, employees security guards, other staff, etc. These numbers seem right to me.
- Firmwarrior 3y agoApple pulls in hundreds of millions per day, I'd think that a lot of them should be going to AI if they want to remain relevant.. it's not hard to imagine Google, Facebook, or maybe even a seriously retooled Microsoft coming out with an earbud that acts as a smart assistant and pretty much replaces the modern smartphone
- TX81Z 3y agoGoogle keeps demoing vapor ware at I/O to that effect but have yet to deliver. Honestly think Apple will go to market first.
- incahoots 3y agoMachine time was a metric that never made any sense to me. I should’ve lead off with machine time excluded that millions a day statement seems hyper inflated.
- late25 3y agoI suspects it’s hardware costs not personnel (or RedBull :) ) costs.
- incahoots 3y ago
- ALoverOfLats 3y ago> helmed by John Giannandrea, Apple’s head of AI, who was hired in 2018 to help improve Siri. In the age of ChatGPT, Siri not only hasn’t been improved but has been getting even dumber lately with no significant announcements towards its improvements of understanding and doing more tasks in any WWDC recently. I would take what he does with a grain of salt.
- sho_hn 3y agoIt feels like it's the economics holding it back at this point. I cobbled together my own smart home voice assistant on a weekend a few weeks ago, sitting on top of the OpenAI APIs (Whisper, GPT-4), and of course using porcupine for wake word detection. It can do things I could never get the commercial products to do properly, for example I gave it a memory: When a user command comes in, I have GPT-4 evaluate whether it can be executed immediately or requires later follow-up. When a sensor event happens, the machinery re-prompts GPT-4 with the user command backlog, the sensor backlog and the current state, and it figures things out. That way, things like "Please turn of the lights after I leave the room" now work just fine, and all it takes is an afternoon of hacking and a PIR sensor on my little DIY Homebrew-lexa wood boxes. And of course it's also much better at interpreting natural language commands "in spirit" or "creatively". I'm sure Amazon, Google & Apple have made all of these tinkering experiments, too, but deploying LLM-backed voice services to tens of millions just isn't affordable yet, especially when you factor in risk and liability.
- brainbag 3y agoI've been thinking about making a smart home voice assistant, can you say more about your set up?
- sho_hn 3y agoI bought little wooden boxes with a hinged lid, stained them in a lovely walnut color, put ReSpeaker 2.0 USB mic arrays under round speaker grilles on top of the lids, two 3w/8ohm speakers into the sides of the box, and a RasPi4 with a WM8960 sound card / speaker driver on the inside. The boards are raised off the wood surfaces by PCB spacers (I embedded M2.5 threaded sockets into the wood) and I bought speaker grilles that bulge out a little at edge of the cylinder, so that the 4-mic array would remain fully exposed also laterally. I covered the side speakers and the mic array speaker grille with acoustic textile. The onboard code is written in very pedestrian Python and uses porcupine and the OpenAI APIs. It roughly works like this: 1. Capture audio frames and run overlapping frames by porcupine to perform hot word detection (overlapping avoids the problem of the hotword falling inbetween frames, at a cost to latency) 2. Once the hot word has been detected, buffer all audio frames into a command buffer until silence is detected as a stop (detecting "silence" is a bit involved, taking noise levels into account, and a few other tricks, more below) 3. The command buffer is sent to Whisper for transcription 4. GPT-4 is prompted with a system message steering it's behavior, the user command transcription and a JSON print out of the state of all devices (e.g. lights and Sonos speakers) in the home, grouped by rooms 5. Following the system message, GPT-4 replies with a JSON structure of changes it would like to make to the device state, omitting unchanged bits from the original 6. Add the sensor event and memory system described above There's a few other tricks. To improve the audio capture, I take note of spatially where the hot word is detected (i.e. which mic in the array gets the best signal) and then capture the rest & perform the silence detection with a corresponding bias. This is actually done in a distributed fashion over the network, so if two of the AI speakers hear the same command, only one of them will end up processing it. They end up making mainly HTTP calls to APIs that already exist around my house. I have a second RasPi in my LED shelf (another old project, https://github.com/eikehein/hyelicht/ https://github.com/eikehein/hyelicht/) that doubles as a Philips Hue bridge with a zigbee dongle. That's what the DIY AI speakers interact with when making changes to the lighting. I will say: Depending on the user command and the weather in the cloud, it's pretty slow. I've tried my best to optimize the client side for perceived user latency, but there's no way around the GPT-4 API just being pretty slow, even if it's amazingly low-friction and reliable otherwise. And 3.5-turbo just doesn't cut it for what I'm trying to do. I'd like to get all of this out of the cloud entirely. I predict the next generation of my home NAS will have a GPU in it and try to run things like fine-tuned llama2 for the home.