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Unsurprising. It's a hype bubble; it seems like only VCs and executives haven't realized that yet. It has however become a very good metric for spotting low qu
by ashtonkem 6y ago
Unsurprising. It's a hype bubble; it seems like only VCs and executives haven't realized that yet.
It has however become a very good metric for spotting low quality technical leadership. If an executive or similar is talking about "AI" or "Machine Learning" without the ability to identify specific use cases that they're hoping to implement, then that is a huge red flag. AI, as much as it actually exists, is a tool to be applied to an end, not magic pixie dust to be sprinkled onto your product to make it more profitable.
- ponker 6y agoLike all hype bubbles except blockchain, AI will be big in 10 years, it’s just hype because it’s too early. Web 2.0, e-commerce, mobile, etc all grew into their hype.
- icoder 6y agoFunny thing I: I added some AI to my CS curriculum in Uni. They said back then: "20 years ago, they made a lot of AI predictions, but they obviously did not happen, but 20 years from _now_ : oh boy". That was 20 years ago, and well, history seems to repeat itself. We'll see. Maybe with Moore's law alikes pushing the processing capacities and a separate 10x improvement in the mechanics (ie 'how' AI learns).
- ivalm 6y agoMachine translation, search, recommendation, face/object detection, image processing are just a subset of very real technologies broadly deployed today that benefit from machine learning (a subset of AI).
- acdha 6y agoAI does suffer from the problem where the term seems to be defined as “what we can't do now”. That said, I think those are also good examples of why it's important to be realistic – good translation has been significant, especially for travelers, but search, recommendations, face detection, etc. have been modest incremental improvements. That's great to have but a lot of people aren't content with that billing and create problems by overselling it as game-changing.
- csours 6y agoExactly. - "In my experience and opinion, as soon as something is well defined it becomes Artificial Narrow Intelligence - Vision systems, Natural Language Processing, Machine Learning, Neural Networks - it loses the name "AI" and gets its own specific name." https://news.ycombinator.com/item?id=24767341 https://news.ycombinator.com/item?id=24767341
- ponker 6y agoFace detection is really valuable to me. I have cameras on the front of my house and I get an alert on my phone when someone unrecognized comes up to the house. It sometimes false triggers on me and my wife but it let us know 1) when a package is delivered 2) when our kids wander out to the front yard 3) hasn't happened yet, but if a sketchy person came onto our property.
- acdha 6y agoYes, and it's gotten better than the older CV approaches. My point is that it's nice but it didn't significantly transform your life the same way, say, a smartphone did.
- amznthrwaway 6y agoI've worked on very real problems where AI provided an improvement over alternatives. That said, 90+% of AI products have AI because it sells well, not because it's better than alternatives.
- jonny_eh 6y ago> Like all hype bubbles except blockchain And VR.
- delecti 6y agoVR isn't a hype bubble at all though. It's just that graphics tech has only recently gotten powerful enough to pull it off, but it's still expensive. It'll come down in price and get better in quality, while probably staying relatively small due to the setups needed. It's just like any high-end gaming setups. Most people are fine with simple gaming on their phone (Angry Birds or whatever is popular these days), some want consoles, some want powerful PCs, some are satisfied with Oculus Quest type VR devices, and some want quite powerful PCs for VR. VR is growing way too slowly and steadily to really characterize as "hype".
- sudosysgen 6y agoI've been playing "VTOL VR", and it's really showcasing the potential of VR for things like training. Whats more, it's one of those games that could conceivably run on a very cheap VR headset in the next few years.
- ponker 6y agoVR is already widely used in industrial training. Send a forklift driver through VR training and the safety lessons might stick a little bit better, so your insurance company will cut you a discount and it can pay for itself.
- sudosysgen 6y agoIndeed. That being said, I think it has even more potential in making more adaptable simulators of things that we couldn't simulate well or dynamically enough before.
- jcims 6y agoGames are huge and, as a result, VR as a vehicle for delivering games will be huge. IMHO the world-changer is going to be AR, and the two will likely retain many complementary objectives in hardware/software/skillsets.
- fakedang 6y agoIt's funny how people attributed a ton of value to block chains and crypto currency, when most of crypto's value as an alternative to government fiat only came about because of its ability to mask illicit payments for drugs, weapons and contract killings. People went all in on Bitcoin in 2017, when the FBI had shut down Silk Road, the main Bitcoin mover for a long time, in 2014.
- at-fates-hands 6y agoTwo years ago all I heard in the health care industry was how awesome blockchain would be for our industry. Lots of presentations by big knockers in the company, big time investments and initiatives like our company was going to be the "tech leader" in the space, blah blah blah. Two years on and you can't find any mention of it on any of the internal websites, all the PPT's and videos have been scrubbed from the NAS drives they were once promoting people to go watch and learn from. All the supposed "partnerships" have been dissolved, or never took off in the first place. Two years later and blockchain is nothing but a memory at the company I work at. Just as fast as it arrived, it disappeared without so much as a trace of it ever existing in the first place.
- sjg007 6y agoBlockchain is a triple ledger so the question is, "Does this problem require a triple ledger?" I could see the triple ledger being promising in freight for example.
- rsynnott 6y agoI think you're being selective in what hype you remember, here...
- ashtonkem 6y agoSurvivorship bias.
- yters 6y agoUnless you are Sam Altman creating AGI which is the lightcone of the future and the final invention.
- oarabbus_ 6y agoDon't hold your breath.
- rvba 6y agoThe VC business model seems to be mostly be "finding the greater fool during IPO", they probably know very well that most of those things are buzzwords.
- code4tee 6y agoThis 100x.
- mhh__ 6y agoi.e. Dominic Cummings
- nickysielicki 6y agoI agree with this at face value, but I want to push back a bit so that I can sharpen my own argument. How can I argue that "AI" is a hype bubble to a layman while simultaneously acknowledging that we've seen the development of self-driving cars, music identification, Siri and Google Assistant, search by image, etc.? Obviously this isn't all "AI" in the historical CS sense of the word. It's a mix of progress in things like signal processing, computer vision, NLP, neural nets and transformers, and the raw computer engineering that has made all of that practical on modern hardware. Are you and I sticks-in-the-mud for not just going along with calling this "AI"? Is there actual worthwhile nuance by calling things their proper names rather than just kowtowing to the word that normal people have latched onto?
- whichquestion 6y agoIt seems to me the hype bubble is centered around things that require GAI to solve. Progress in more general methods for weak AIs has led to confusion about what is possible with current methods. In the traditional CS sense, the things you mention could all be considered weak AI. I predict as we continue to transition to stronger AIs with more advanced capabilities we will continue to see a shift in what people think of as “AI”. [1]https://en.m.wikipedia.org/wiki/Artificial_general_intelligence https://en.m.wikipedia.org/wiki/Artificial_general_intellige... [2]https://en.m.wikipedia.org/wiki/Weak_AI https://en.m.wikipedia.org/wiki/Weak_AI
- antipaul 6y agoI like the point you make. I think there are the AI leaders, and then there is everyone else. What is the difference? The leaders are mostly big tech, who have driven the step-change advances you describe. This, IMHO, was due to their pre-existing mastery of data. They already had a ton of well-organized data, because they were engineering cultures, and data was the lifeblood of their business (ads, search, shopping). Once ML/AI came into the picture, it was full steam ahead. Most others are (blind) followers, and cannot tease apart the engineering bit from the (data) science hype. They get fixated on the latter (data science and ML/AI) and forget the engineering, or "scale" part. The first question should not be about AI/ML, but on the other hand, do you have solid (data) engineering where your data is easily accessible to any data scientist? By now it should be apparent that "data is the new oil" and will be useful even if you don't plan to do deep learning. If you don't have solid (data) engineering and "data at scale" for anyone, anywhere, then your ML/AI efforts are doomed. Data first, only then ML/AI. See "Data Science Hierarchy of Needs": https://hackernoon.com/the-ai-hierarchy-of-needs-18f111fcc007 https://hackernoon.com/the-ai-hierarchy-of-needs-18f111fcc00...
- unemphysbro 6y agoThis is sort of like all new tech and domain application. The application tree first grows in breadth, then depth. I'm guessing real use cases will take 5-20 years to settle.
- ashtonkem 6y agoIt’s like all new tech, if you fall into the survivorship bias trap and only look at the ones that have survived. Personally I think this will be another “AI winter”, where we will gain some improvements in narrow domains but fall far short of what was promised, leading to disillusionment and a reduction in research budgets.
- AndrewKemendo 6y agoSorry but it's just wrong to call it a hype bubble because there are real and tangible uses of ML in production today on massive scaled systems that give extreme outsized results. All of GAAFM rely on ML at scale at this point for a large subset of their products. It's just that these results are also EXTREMELY unevenly distributed - and good luck breaking into anything that can use applied ML and not get crushed by GAAFM. However I agree with your point here: >If an executive or similar is talking about "AI" or "Machine Learning" without the ability to identify specific use cases that they're hoping to implement, then that is a huge red flag. So it's not as simple as "AI is Hype" - it's not hype - it's just that most organizations will struggle to actually implement it because all the data/talent/compute etc... sits in GAAFM.
- jskdvsksnb 6y agoEven for the behemoth companies that are able to harness AI, it seems like the domains are a) heavily constrained b) fault tolerant. For example, voice assistants - they have very limited capabilities and consumers will accept pretty poor performance. Look at the errors in Google's attempts to automatically answer questions in searches. Do you have any examples of domains where a FAANG has operationalized AI/ML outside of consumer products?
- AndrewKemendo 6y agoData Center optimization: "DeepMind AI Reduces Google Data Centre Cooling Bill by 40%" https://deepmind.com/blog/article/deepmind-ai-reduces-google-data-centre-cooling-bill-40 https://deepmind.com/blog/article/deepmind-ai-reduces-google...