[HN Gopher] Why A.I. Moonshots Miss
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Why A.I. Moonshots Miss
Author : birriel
Score : 56 points
Date : 2021-05-04 15:41 UTC (7 hours ago)
(HTM) web link (slate.com)
(TXT) w3m dump (slate.com)
| dqpb wrote:
| The tldr of this article is supposedly "be more incremental".
|
| But the undertones are basically "exploit more and explore less
| because exploring is expensive".
|
| It would be nice if the authors had the courage to propose a
| concrete economic model for what the right balance is and to do a
| fair accounting of the positive externalities of these projects,
| rather than just give a cherry-picked anecdotal laundry list of
| failed products.
| [deleted]
| Jiocus wrote:
| This article seems to be a rehash of the paper 'Why AI is harder
| than we think'[1].
|
| [1]: https://arxiv.org/pdf/2104.12871.pdf
|
| -
|
| Related discussion
|
| https://news.ycombinator.com/item?id=26964819
| seibelj wrote:
| I wrote this a year ago, but have been commenting for many years
| that AI is all hype https://medium.com/@seibelj/the-artificial-
| intelligence-scam...
|
| I asked to make a public bet 4 years ago, saying self-driving
| cars wouldn't be close to ready in 5 years
| https://news.ycombinator.com/item?id=13962230
|
| I have been hearing this bullshit for over a decade, and people
| (and investors, and engineers, and smart people who should know
| better) keep falling for it.
| ffhhj wrote:
| Investors should invest in a model to decide in which projects
| to invest.
| flooo wrote:
| As a researcher in AI, I accept that a lot of currently unsolved
| challenged are thought of as AI. But lately, I feel that AI is
| the problem description for _all_ currently unsolved problems.
| And then some...
|
| This surprises me, because most AI technologies have been around
| for a long time. Now with blockchain a couple of years ago, I
| could at least rationalize all excitement as people throwing new
| technology at an old problem. But with AI I am continually
| surprised by the reasons why 'an AI' would be able to solve it.
| rexreed wrote:
| As a researcher in AI, what are you really spending most of
| your time on? What problems are you solving?
| flooo wrote:
| I am currently interested in infusing reinforcement learners
| with symbolic knowledge, with safety constraints as a special
| case.
|
| I hope this helps cases where learners could come up with
| better solutions if it were not for pathological failures
| that we know to avoid.
|
| Also, I try to keep expectations around AI reasonable.
| causalmodels wrote:
| I'm not OP but I also do research in ML. My research focus is
| identifying and preventing critical system failure so people
| don't die. My of my time is spent developing new techniques
| and then testing them against data we collect from the field.
| shandor wrote:
| Where could one read more about your (or similar) research?
|
| This kind of thing is quite big at the moment in mobile
| work machinery circles, everyone's looking for a
| certifiably safe solution for enabling mixed-fleet
| operation (i.e. humans, human-controlled machines and
| autonomous machines all working in same area). Current
| safety certifications don't view the nondeterminism of ML
| models too kindly.
| brg wrote:
| > Four years later, in 2020, Forrester reported that the A.I.
| market was only $17 billion.
|
| This seems like vast under accounting for the current impact of
| AI. Every interesting technology used in the market is
| differentiated by its application of ML, be it assistants,
| recommender systems, or enhancement. The iPhone has intelligence
| built in to process control, voice access, and the camera.
| melling wrote:
| We got our current revolution because gaming paid for the
| development of GPU's.
|
| Getting consumers to fund R&D has a big impact.
|
| Still waiting for consumers to fund the robot revolution.
| petra wrote:
| There's a lot of effort/funding recently going into automating
| restaurants. Machines for cooking, cleaning, serving, delivery.
|
| Once that gets deployed at some scale, consumers will pour a
| lot of funding into robots indirectly.
| void_mint wrote:
| > Still waiting for consumers to fund the robot revolution.
|
| Aren't they already, via Tesla and Amazon?
| rexreed wrote:
| We got our current revolution for three major contributors:
|
| * Big data. Lots of big data. Mostly unstructured and
| unqueryable driving demand for...
|
| * Innovations in machine learning. "Deep learning" enabled by
| big data and algorithmic approaches that previously wouldn't
| have been possible without...
|
| * Ubiquitous access to high-performance compute power, and in
| particular GPUs, which are optimized for the sort of math
| needed to train big neural networks powered by big data.
|
| So GPU-powered compute is one of three mutually dependent
| things that got us here.
| rmah wrote:
| Robots are everywhere. We just don't call them robots. We call
| them dishwashers, CNC machines, STM machines, automatic
| welders, fabric cutting machines, etc, etc.
|
| Sort of like we already have flying cars. They're called
| "helicopters".
| rexreed wrote:
| When people think flying cars, they don't think of something
| without wheels that can only land in certain spots that
| requires years of training to operate that is significantly
| expensive to be outside of the reach of 99%.
|
| They think of the car that anyone of legal driving age with a
| reasonable amount of money that anyone with some income can
| purchase.
|
| No, helicopters are not flying cars. And no, dishwashers
| aren't what people would think of when they think of robots.
| Something that has a microprocessor in it isn't automatically
| a robot.
| petra wrote:
| Yes helicopters aren't flying cars.
|
| But if a machine automates 90% of a process, like a
| dishwasher, why shouldn't it be considered like a robot,
| say a 90% robot?
|
| Practically it does have the same effect.
| ALittleLight wrote:
| Do you think of a washing machine or a dryer as a robot
| too?
| petra wrote:
| I think of them as machines that automated a certain
| task. So a robot substitute.
| tomp wrote:
| A dishwasher is to a robot what a calculator is to a
| computer.
| rhizome wrote:
| By that token, how well can a Boston Dynamics dogbot
| clean your dishes?
| generalizations wrote:
| Which means that a robot is something that has a property
| similar to the property of 'turing completeness' in
| computers.
| stcredzero wrote:
| _When people think flying cars, they don 't think something
| without wheels that can only land in certain spots that
| requires years of training to operate that is significantly
| expensive to be outside of the reach of 99%._
|
| I think if one eliminates the training requirement, reduces
| the cost, and increase the safety, then we don't need them
| to be road vehicles. Achieve the above, and we'll have
| flying taxis!
| rexreed wrote:
| If it weren't for many of the other problems of
| helicopters including convenience and noise.
|
| How many helicopters will fit in an IKEA parking lot? And
| how many will be able to bring back whatever you buy
| there?
|
| Extend that thought experiment a bit. You might be able
| to achieve the transportation of people in controlled
| circumstances, but not much else.
| medium_burrito wrote:
| You do realize small ducted fans are an order of
| magnitude louder than a helicopter, right? All those
| slick marketing videos omit that part.
| q-big wrote:
| > When people think flying cars, they don't think of
| something without wheels that can only land in certain
| spots that requires years of training to operate that is
| significantly expensive to be outside of the reach of 99%.
|
| You write down two points:
|
| 1. regulation
|
| 2. cost
|
| "Regulation" is not an engineering problem, but a hard and
| deeply political one.
|
| For "cost": When a lot of regulation comes down, the
| possible market size increases by a lot and it begins to
| make economic sense to invest lots of engineering
| ressources into cutting costs down by a lot (I do believe
| this is possible). Then helicopters will even perhaps
| transform into something that is much more akin to flying
| cars.
| melling wrote:
| We probably don't call a dishwasher a robot because it's not
|
| That is the only consumer facing device you mentioned. I know
| we have industrial robots, so I'll skip debating where we
| draw the line.
|
| Once we get to the Apple II of home robots, consumer spending
| will fuel the rapid development, and "robots", will become
| more intelligent and agile
| burnished wrote:
| Not the person you responded to, but I think I see where
| they are coming from and agree: we don't call them robots
| because we are used to them and have a specific name. I
| don't see how they aren't robots, unless we are defining
| robots as having a specific kind of manipulator.
| melling wrote:
| Aren't we discussing robots vs machines?
|
| https://www.toyota.co.jp/en/kids/faq/i/01/01/
| criddell wrote:
| I think their point was that if the dishwasher was made
| so that mechanical hands picked up a dish, washed it,
| rinsed it, dried it, then set it aside before picking up
| the next dish and doing the same, we would call that a
| robot.
| khc wrote:
| > Sort of like we already have flying cars. They're called
| "helicopters".
|
| you cannot drive helicopters on the road, they are flying but
| not cars
| ArtWomb wrote:
| No question. It was video gaming from the period roughly
| spanning 1990-2010 that funded gpu innovation. But programmable
| compute shaders caught on very rapidly in science. And Nvidia
| was quick to not just recognize the new market, but bet the
| company that supercomputing would one day be gpu cluster based.
|
| Here's Jensen Huang talking to Stanford students about the
| birth of the Cg language (27:40" mark). The entire talk is
| gold. A text book case study of Moore's Law and the SV model of
| risk capital:
|
| https://www.youtube.com/watch?v=Xn1EsFe7snQ
|
| Ironically, IC Design itself is a strong candidate as an
| industrial process likely to be revolutionized by AI ;)
|
| Chip Placement with Deep Reinforcement Learning
|
| https://arxiv.org/abs/2004.10746
| djdjdjdjdj wrote:
| I'm willing to spend 10k for a robot who can do my kitchen and
| clothes.
|
| Let's see how long it will take
| amelius wrote:
| Yes, these kinds of robots are more useful than self-driving
| cars, because you have to sit in the car anyway and might as
| well drive.
| fierro wrote:
| I would also pay in the 10k+ range for this, easily.
| redis_mlc wrote:
| The Willow Garage PR2 robot could do that for $440,000.
|
| https://en.wikipedia.org/wiki/Robot_Operating_System#Willow_.
| ..
| rexreed wrote:
| They miss for the same reasons they have missed throughout the
| decades: they overpromise and underdeliver. That was the reason
| for the past two AI "winters" and most likely will be the same
| reason for the upcoming AI winter.
|
| What we have successfully accomplished this time around is big
| data analytics that have used machine learning technology to
| derive insights and patterns from data that traditional data
| analysis approaches have not been able to achieve. And dramatic
| improvements in computer vision and natural language processing
| among a few other areas. Those things will stay.
|
| But I'm looking forward to the next wave of AI, which should be
| in the mid- to late-2030s if the current cycles hold.
| foobarian wrote:
| On one hand, maybe the name is just unfortunate. The minute you
| mention AI the expectation is set to deliver machine sentience.
|
| On the other hand, maybe it is a good thing to set the
| goalposts high. We may not reach the target, but still end up
| with worthwhile results; see: current ML use cases in industry.
| dfilppi wrote:
| Well "intelligence" does imply reasoning, which has never
| been delivered.
| gmadsen wrote:
| I think this isn't really giving credit. Standard deep learning
| is not really slowing down. It is improving exponentially
| still.
|
| Just yesterday I was looking into new deep learning methods for
| solving PDEs. That is a huge area to explore and will change
| many things dramatically
| ChefboyOG wrote:
| An "AI winter" like we had before isn't plausible now. In the
| past, it was the failure of AI research to deliver business
| impact. The current ML boom is fundamentally different in that
| it already has become a standard part of the stack at major
| companies:
|
| - Recommendation engines (Google, YouTube, Facebook, etc.)
|
| - Fraud detection (Stripe, basically all banks)
|
| - ETA prediction (Uber, every delivery app you use)
|
| - Speech-to-text (Siri, Google Assistant, Alexa)
|
| - Sequence-to-sequence translation (used in everything from
| language translation to medicinal chemistry)
|
| - The entire field of NLP, which is now powering basically any
| popular app you use that analyzes text content or has some kind
| of filtering functionality (i.e. toxicity filtering on social
| platforms).
|
| And that's a very cursory scan. You can go much, much deeper.
| That isn't to say that there isn't plenty of snake oil out
| there, just that ML (and by extension, AI research) is
| generating billions in revenue for businesses today. There's
| not going to be a slow down in ML research for a while, as a
| result.
| whatshisface wrote:
| You could say the same thing about the first AI winter.
| Programming concepts developed for symbolic AI are in every
| language now.
| ska wrote:
| > In the past, it was the failure of AI research to deliver
| business impact.
|
| That's not quite right - the problem wasn't that no impact
| was delivered, but that it over-promised and under-delivered.
| I'm fairly optimistic of some of the machine learning impact
| (even some we've seen already) but it's by not means certain
| that business interest won't turn again. We are very much
| still in the honeymoon phase currently.
| zedshawmotherfu wrote:
| Search is a type of machine learning!
| slowmovintarget wrote:
| Partly this is because we've given up trying to get computers
| to "understand" and have focused on making them useful with
| sophisticated software. That is, the work is no longer about
| artificial intelligence, but about trained, new-style, expert
| systems.
| quadcore wrote:
| I wonder if we could detect harassment today in a chat for
| example. With like GPT3 or something.
| qayxc wrote:
| Highly unlikely. It's pretty much impossible to detect
| the difference between a friendly banter, a heated
| debate, trolling, and genuine harassment for most people
| given just a chat log.
|
| There's often much more information required (prior
| communication history of the involved parties, previous
| activities in other chats, etc.).
|
| Using automated systems like GPT-3 would simply lead to
| people switching to different languages (not in the
| literal sense, but using creative metaphors and inventing
| new slang).
|
| Pre-canned "AI" is unable to adapt and learn and I doubt
| that any form of AGI (if even possible without
| embodiment) that isn't capable of real-time online
| learning and adapting would be up to the task.
| quadcore wrote:
| Mmh I'm not convinced. There is pattern in
| aggressiveness. One of them being the harasser is talking
| about the victim or something that's strongly linked to
| the victim (like it's work, member of familly, etc).
| zedshawmotherfu wrote:
| A double bind detector!
| bordercases wrote:
| You need to look at these techniques as being in continuity
| with how mathematical modeling has been generally performed
| by humans for a couple centuries now.
|
| To directly explain the mechanics of what should otherwise
| be simple or everyday phenomena (like with three-particle
| orbits or the flow of water in your bathtub) often requires
| many equations and parameters. Since physical systems tend
| to be not-so-heterogeneous in structure, we can use
| experimental insight and exploit symmetries to reduce the
| number of equations and parameters up front. But this
| amounts to finding ways to simplify because we _don 't_
| understand the precise system in play, only an analogous
| one.
|
| For larger systems we have historically relied on equation
| solvers to do the reductions and find solutions. But there
| are systems for which the dimensionality cannot be easily
| reduced, like with language and vision. Then to be
| precisely predictive about these high-dimensional outcomes,
| we still need to compute beyond our ability to reduce the
| equations from the outset.
|
| This all converges on deep learning - since in the end,
| it's much of the same linear algebra used by solver
| packages, just recursively applied to enormous high-
| dimensional datasets. Maybe calling it intelligence gives
| more agency to the process than we can stand to attribute.
| But in many ways it's just an extension of our usual ways
| of mathematical modeling before computers, but moving into
| so many dimensions and datapoints that it produces outcomes
| similar to the behavior we use our entire brain to recreate
| instinctually (like image recognition and language use).
| stingraycharles wrote:
| Isn't artificial intelligence a very broad term anyway, of
| which expert systems, statistics, fuzzy logic and all the
| new wave neural network / deep learning are examples?
|
| You seem to be thinking about artificial general
| intelligence, which is much more difficult to achieve.
| slowmovintarget wrote:
| Time was that the term AI meant what has now come to be
| referred to as AGI or machine consciousness. Marvin
| Minksy wasn't looking to make better facial recognition,
| or better factory robots. His research was about making a
| mind.
|
| Twenty years ago, that kind of work ran into a brick
| wall. But neural networks were still useful. Enter
| Machine Learning, and it borrowing the term "AI." But
| Artificial Intelligence, for many, always meant the dream
| of building R. Daneel Olivaw, or R2D2.
| pvarangot wrote:
| AGI is even difficult to define, it's still up for debate
| if/what is part of what we call intelligence and if it's
| present on animals and if it can exist without a
| "subconscious" or "feelings".
| zedshawmotherfu wrote:
| The hard problem of consciousness, which everyone has a
| hard time defining?
| jsharf wrote:
| This is just redefining what counts as "real intelligence"
| to raise the bar.
|
| Once we have computers that can think like humans, there'll
| be people saying 'oh, it's not real "understanding", it's
| just generating speech that matches things it's heard in
| the past with some added style', not realizing that the
| same also applies to human writers.
|
| As long as the bar keeps rising and we've found business
| applications, there will be no AI winter.
| slowmovintarget wrote:
| It isn't redefining anything. There's a classification in
| AI research called "strong AI" that includes Artificial
| General Intelligence and machine consciousness. Current
| uses of ML are instances of so-called "weak AI" which is
| focused on problem-solving and utility.
|
| No redefinition, and using proper distinctions takes
| nothing away from the accomplishments made in the field.
| We don't even have anything close to a scientific
| understanding of awareness or consciousness. Being able
| to create machines actually possessing awareness seems
| fairly far off.
|
| Being able to create machines that can simulate the
| qualities of a conscious being, doesn't seem so far off.
| I suspect when we get there the data will point to there
| being a qualitative difference between real consciousness
| and simulated. Commercial interests, and likely
| government bureaucracy will have a vested interest
| drowning out such ideas, though.
|
| The bar hasn't moved. We've just begun aiming at
| different targets. That we succeed in hitting the more
| modest ones only makes sense.
| deelowe wrote:
| AGI is not currently in scope for any solutions on the
| market. The current crop of AI systems are simply
| analytical engines.
| zedshawmotherfu wrote:
| AGI isn't something that is scoped. It must be painted.
| Retric wrote:
| AI was also having huge success before the last AI winter.
| It's mostly a question of buzzword turnover not underlying
| technology.
| lordofgibbons wrote:
| I wasn't around back then, I'm curious what were the
| business use-cases of AI/ML back then?
| ForHackernews wrote:
| Spam filtering and route-planning are big successes from
| previous generations of techniques labelled as "AI".
| Retric wrote:
| Optical sorting of fruit and various other things is a
| great example where early AI techniques made significant
| real world progress. It's not sexy by today's standards,
| but is it's based on a lot of early image classification
| work.
| truth_ wrote:
| We are talking about money-making applications here. Not
| progress.
| Retric wrote:
| By progress I mean actual money making products. If your
| widget is doing shape recognition based on training sets
| and your competitors are hard coding color recognition
| then you end up making more money.
| slver wrote:
| > That was the reason for the past two AI "winters" and most
| likely will be the same reason for the upcoming AI winter.
|
| If you follow the papers coming out, I'd say we're very far
| from any winter. Public perception may ebb and flow, but
| nothing can stop us now, research has gathered that critical
| mass and we're going nuclear on AI right as we speak.
| jessenichols wrote:
| Epistemology http://www.daviddeutsch.org.uk/wp-
| content/uploads/2019/07/Po...
|
| https://aeon.co/essays/how-close-are-we-to-creating-artifici...
| stephc_int13 wrote:
| We've mostly been tricked by the Moravec's Paradox.
|
| https://en.wikipedia.org/wiki/Moravec%27s_paradox
|
| What seems difficult/hard to us is very often not that difficult
| from a computational perspective, but evolution of our species
| didn't optimize for this class of problems.
| spamizbad wrote:
| The predictions from thought leaders are a little puzzling, but I
| think predictions from CEOs are easier to explain:
|
| Engineer: This could easily take 10 years.
|
| Engineering Manager: This will take up to 10 years.
|
| VP of Engineering: This will take 5-10 years.
|
| CEO: We will have new <AI Thingy> within 5 years!
|
| A game of telephone but with optimism.
| scotty79 wrote:
| That's the thing that people don't get about estimations.
|
| Estimation (as given by the engineer) is the time, by which,
| you can be almost sure, you won't have this thing done.
| neaanopri wrote:
| "No Earlier Than"
| loopz wrote:
| Times Pi.
|
| Why?
|
| It works!
|
| Ok, Phi it is then!
| nitwit005 wrote:
| > The predictions from thought leaders are a little puzzling
|
| It doesn't seem possible to become a "thought leader" by
| correctly predicting what trends will not pan out. People like
| the ones predicting a bold new future in a short time span.
| variaga wrote:
| http://web.mnstate.edu/alm/humor/ThePlan.htm
| gremlinsinc wrote:
| I've been perplexed lately by a couple things as an atheist that
| trouble me.
|
| 1. I saw what personally I can't shake, a glitch in the matrix so
| to speak, or a mandela effect except it was a "flip" where I saw
| one whole movie clip that totally changed (including acting
| style) in 3 days, my wife saw both and verified I wasn't crazy.
|
| 2. Being logical, I've been searching on answers "why" this
| "could" be possible without it just being a "faulty memory". 90%
| of ME's are probably ... but memory seems to fade over time, 3
| days doesn't seem long enough to form the right connections to
| create false memories especially with two witnesses and many
| online claim the same exact "flip flop".. I mean the easiest
| explanation might be that Universal Studios and Movie Clips
| youtube pages just have an "alternate" version of that clip and
| they alternate them out on a schedule..
|
| So my conclusions: We are ourselves ai living in a simulation, or
| there's a multiverse but maybe it's finite so when there's too
| many realities we get convergence.
|
| I lean towards simulation because of some of the evidence some
| people affected by ME's claim that things sometimes change in a
| progression, almost like facts are being "added". Like there's
| residue as it's called for "Where are we in the milky way" which
| shows 100 different locations, and not even close to where Carl
| Sagan pointed on the very outskirts. Even Philip K. Dick claimed
| to have "traversed" timelines... though I think he seemed to
| think more like it's a multiverse... which it still could be,
| albeit a simulated one.
|
| Another factor is the axis of evil in space. Basically it's an
| observation that if I understand correctly ties the expansion of
| the galaxy along an x/y coordinate to our solar system,
| essentially putting us right square back at the center of the
| universe.
|
| https://www.space.com/37334-earth-ordinary-cosmological-axis...
|
| This to me is important because as a programmer I think if I were
| to create a simulation of just us.... I'd probably "render" us
| first and everything else after... could it be our "area" in
| space is one of the first created and everything else after...
| like pixels being pre-rendered for when we discover space and
| astrophysics someday? It'd ensure they could create the right
| conditions for our planet physics wise... to use it looks like a
| bang, but in really it's just the "rendering" process which had
| to start at a "pinpoint"... at least that's how I envision a
| "simulation" starting...
|
| Then there's the double slit experiment which proves that photons
| and other particles upto atoms and some molecules when shot
| through a slit will basically splatter (interference pattern)
| against a backdrop that tracks where they land. If you put
| something to observe though each individual particle or photon,
| they line up in a line like a stencil, if you split them before
| this, and continue the first group to the board, and the others
| go through something to "erase" the data of where they came
| from... they go back to interference.
|
| So that basically gives me thought about what observation might
| have on our own universe, is that some safeguard so that the
| physics engine only operates when we're looking? So all we see in
| space could just be data "fed" to us, may not exist, like a movie
| stage or something... we see what we aim to see, but it follows
| "rules" setup in the simulation. There's a reason light is the
| maximum speed, etc...Maybe that's the max ram available or
| something...
|
| Why this is important to ai...that's a bit of a tangent... to
| solve these complex issues I've seriously contemplated at least
| studying quantum mechanics, physics, neuroscience, astrophysics,
| and ai/machine learning. Because I think to really "create" ai
| ...especially super ai, you need a wider skillset, a broader base
| of understanding. You need to be able to define WHAT
| consciousness is, where it resides, where it comes from, maybe
| even "where it goes" when our body is done...
|
| If we're in a simulation then we know we've already conquered
| this issue because we ARE ai, or at least whatever civ we come
| from has. Whether they're human or not.
|
| TLDR: Had profound spiritual conundrum, trying to explain through
| science, discovered I probably need to learn a lot of
| science/math/physics to do so, and ya know a.i. might be like
| that because making machines "concious" or have "real
| intelligence" seems like it needs re-thought a bit. I feel like
| training a.i. is nothing like training a child but it should be
| because the way we learn is the best way. Maybe in fact a
| simulation could be where a.i. goes to "learn"...
|
| I mean a.i. you'd want to at least have ethics right? Well, we
| teach it as a society some like hitler never learn and could be
| thrown in the "trash bin" but the brightest minds could be
| plucked out, or all minds really to be put into machines, etc in
| the "real world" someday.
|
| That may be what the afterlife is... serving "real humanity" as
| their "intelligence" until we rise up against them. I really want
| to read this sci-fi, kinda sounds interesting...maybe I'll write
| it...
|
| At any point being human in a simulated universe could create
| more ethical a.i. and maybe that's the point of a simulation,
| maybe we should even research using simulations of universal
| scale as a way to create our own a.i. technology assuming we're
| the "base" universe then if that were to be a thing we'd probably
| need to create it.
| [deleted]
| LargoLasskhyfv wrote:
| Which movie clip via what media? I'd maybe believe you if it
| was on DVD/Bluray or such, but not when it were online
| somewhere/somehow, because everything there is subject to
| change without notice.
| king_magic wrote:
| You don't think it's possible that you either A) simply
| misremembered the clip or B) it was swapped out as part of some
| normal process?
|
| 3 days isn't exactly a short period of time. Lots of totally
| plausible explanations.
| sgt101 wrote:
| Interesting that Watson is cited in the article so heavily,
| because I strongly believe that the reason Watson failed was
| because of MBA's and Management Consultants. I could have told
| them (in fact, as an IBM customer, I did) that going for
| healthcare was deranged, but they went after the $$$ in complete
| denial of the difficulties (heavy regulation, safety critical,
| deeply powerful complex network of stakeholders, super complex
| badly understood domain). Also they went far to fast, if they had
| tempered the effort with some patience then they could have got
| some really decent progress on a simpler domain (like customer
| service for telco's).
|
| But the beast needed feeding.
| kickout wrote:
| That's what kills me and continues to perplex me. Something
| like AI for agriculture machines (think maize and soybean
| fields) are NOT heavily regulated, safety critical, or deeply
| complex. Its basically 160 acres of open space with reasonable
| guarantees no humans are around. It would take a trivial amount
| of time to code in the proper kill switches to deactivate these
| machines if they detect a human with _x_ feet
|
| Sadly this research is only starting to take off (with
| 1/1000000 of the investment too). 50B-100B industry...
| 256lie wrote:
| Watson missed the DL train and IBM should have partnered with a
| company that had experience in getting medical devices through
| the FDA (like MSFT are doing with Nuance).
| scotty79 wrote:
| I think they didn't get how bizarre is US healthcare. It's a
| "market" (maybe rather a system) where (nearly) every
| participant is interested in everything being as expensive as
| humanely possible.
|
| Since automation saves money and Watson is just automation it
| has no value for US healthcare participants.
|
| If they came up with completely new thing that could be priced
| additionally, it would have been a different talk.
| 256lie wrote:
| There are healthcare startups around fraud detection,
| reducing no-shows, telemedicine, drug discovery, and patient
| triage.
|
| Just radiology alone is prime for ML due to existing digital
| infrastructure and clinical use cases.
|
| The trend in FDA cleared AI products is pretty clear over the
| past decade. https://models.acrdsi.org/
| josefx wrote:
| > in complete denial of the difficulties (heavy regulation,
| safety critical, deeply powerful complex network of
| stakeholders, super complex badly understood domain)
|
| The last article I read about it cited rather mundane reasons
| for it ending up unused. Things like not even supporting the
| data formats used by hospitals that served as cutting edge
| users.
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