[HN Gopher] If it works, it's not AI: a commercial look at AI st...
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If it works, it's not AI: a commercial look at AI startups (1999)
Author : rbanffy
Score : 97 points
Date : 2025-06-07 13:52 UTC (9 hours ago)
(HTM) web link (dspace.mit.edu)
(TXT) w3m dump (dspace.mit.edu)
| clbrmbr wrote:
| Title should end (1999), as 1977 is the birth year of the author
| not the publication date.
| MontyCarloHall wrote:
| The sentiment of the title is reflected in this comment [0] from
| a few hours ago: We use so much AI in production
| every day but nobody notices because as soon as a technology
| becomes useful, we stop calling it AI. Then it's suddenly "just
| face recognition" or "just product recommendations" or "just
| [plane] autopilot" or "just adaptive cruise control" etc
|
| [0] https://news.ycombinator.com/item?id=44207603
| JimDabell wrote:
| This is known as the AI effect:
|
| https://en.wikipedia.org/wiki/AI_effect
| dunham wrote:
| I remember being taught in my late 90's AI class something
| along the lines of: "AI is anything we don't know how to
| solve, and it gets another name when we figure out how to
| solve it".
| neilv wrote:
| Same here.
|
| "AI is things we currently think are hard to do with
| computers"
|
| "AI is things that are currently easier for humans than
| computers".
| layer8 wrote:
| I don't think that's the sentiment of the title.
| MontyCarloHall wrote:
| It is exactly the sentiment of the title. From the paper's
| conclusion: Although most financiers avoided
| "artificial intelligence" firms in the early 1990s, several
| successful firms have utilized core AI technologies into
| their products. They may call them intelligence applications
| or knowledge management systems, or they may focus on the
| solution, such as customer relationship management, like
| Pegasystems, or email management, as in the case of Kana
| Communications. The former expert systems companies,
| described in Table 6.1, are mostly applying their expert
| system technology to a particular area, such as network
| management or electronic customer service. All of these firms
| today show promise in providing solutions to real problems.
|
| In other words, once a product robustly solves a real
| customer problem, it is no longer thought of as "AI," despite
| utilizing technologies commonly thought of as "artificial
| intelligence" in their contemporary eras (e.g. expert systems
| in the 80s/90s, statistical machine learning in the 2000s,
| artificial neural nets in the 2010s onwards). Today, nobody
| thinks of expert systems as AI; it's just a decision tree. A
| kernel support vector machine is just a supervised binary
| classifier. And so on.
| layer8 wrote:
| The paper is picking up a long-standing joke in its title.
| From https://www.cia.gov/readingroom/docs/CIA-
| RDP90-00965R0001002... (1987): _All these [AI] endeavors
| remain at such an experimental stage that a joke is making
| the rounds among computer scientists: "If it works, it's
| not AI."_
|
| The article is re-evaluating that prior reality, but it
| isn't making the point that successful AI stops being
| considered AI. In the part you quote, it's merely pointing
| out that AI technology isn't always marketed as such, due
| to the negative connotation "AI" had acquired.
| kevin_thibedeau wrote:
| Predicting the trajectory of a cannonball is applied
| mathematics. Aircract autopilot and cruise control are only
| slightly more elaborate. You can't label every algorithmic
| control system as "AI".
| MontyCarloHall wrote:
| I agree that aircraft autopilot/other basic applications of
| control theory are not usually considered "AI," nor were they
| ever -- control theory has its roots in mechanical governors.
|
| Certain adaptive cruise control systems certainly are
| considered AI (e.g. ones that utilize cameras for emergency
| braking or lane-keep assist).
|
| The line can be fuzzy -- for instance, are solvers of
| optimization problems in operations research "AI"? If you
| told people in the 1930s that computers would be used in a
| decade by shipping companies to optimally schedule and route
| packages or by militaries to organize wartime logistics at a
| massive scale, many would certainly have considered that some
| form of intelligence.
| jagged-chisel wrote:
| It's "AI" until it gets another name. It doesn't get that
| other name until it's been in use for a bit and users start
| understanding its use.
|
| So you're right that some of these things aren't AI now. But
| they were called that at the start of development.
| hamilyon2 wrote:
| Yes. Chess engine is clever tree search at it's core. Which
| in turn is just loops, arithmetic and updating some data
| structures.
|
| And every AI product in existence is the same. Map
| navigation, search engine ranking, even register allocation
| and query planning.
|
| Thus they are not AI, they're algorithms.
|
| The frontier is constantly moving.
| andoando wrote:
| There is a big divide between problem specific problem
| solving and general intelligence.
| behringer wrote:
| There's no g in Ai. We'll unless you spell it out but you
| know what I mean.
| paxys wrote:
| Next you'll tell me AI is just algorithms under the hood!
| tempodox wrote:
| That would be such a spoiler. I want to believe in
| miracles, oracles and omniscience!
| small_scombrus wrote:
| What's the saying?
|
| > All sciences are just highly abstracted physics
| paxys wrote:
| And physics is applied math. And math is applied logic.
| And logic is applied philosophy...
| goatlover wrote:
| Platonic forms all the way down...
| sjducb wrote:
| When algorithms improve with exposure to more data are they
| still algorithms?
|
| Where is the line where they stop being algorithms?
| adammarples wrote:
| Because they're algorithms that have an algorithm (back
| propagation) that improves the other algorithm (forward
| propagation). Very roughly speaking.
| internet_points wrote:
| And deep learning is just applied optimization and linear
| algebra (with a few clever heuristics, learnt by throwing phd
| students's at the wall and seeing what sticks).
| hliyan wrote:
| Funnily enough, this same year (1999), I wrote an essay for a
| university AI subject where I concluded "Intelligence is a
| label we apply to information processing for which we have not
| yet identified an algorithm. As soon as an algorithm is
| discovered, it ceases to be intelligence and becomes
| computation". I thought I was very clever, but later discovered
| that this thought occurs to almost everyone who thinks about
| artificial intelligence in any reasonable depth.
| MichaelZuo wrote:
| This would imply "artificial intelligence" itself is a
| nonsensical term... as in "artifical [label we apply to
| information processing for which we have not yet identified
| an algorithm]".
| kevinventullo wrote:
| I dunno, the opacity of LLM's might kind of fit the bill
| for not having an "algorithm" in the usual sense, even if
| it is possible in theory to boil them down to cathedrals of
| if-statements.
| CooCooCaCha wrote:
| I'm reminded of AI hypesters complaining that people are
| constantly moving the goalposts of AI. It's a similar effect
| and I think both have a similar reason.
|
| When people think of AI they think of robots that can think
| like us. That can solve arbitrary problems, plan for the
| future, logically reason, etc. In an autonomous fashion.
|
| That's always been true. So the goal posts haven't really
| moved, instead it's a continuous cycle of hype, understanding,
| disappointment, and acceptance. Every time a computer exhibits
| a new capability that's human-like, like recognizing faces, we
| wonder if this is what the start of AGI looks like, and
| unfortunately that's not been the case so far.
| simonw wrote:
| The term "artificial intelligence" started out in academia in
| 1956. Science fiction started using that language later.
| CooCooCaCha wrote:
| I'm not concerned with who used what and when. I'm talking
| about what people expect of AI. When you tell people that
| you're trying to create digital intelligence, they'll
| inevitably compare it to people. That's the expectation.
| neepi wrote:
| The term AI was invented because Claude Shannon was fed up
| of getting automata papers.
| simonw wrote:
| I thought it was John McCarthy trying to avoid having to
| use the term "cybernetics".
| parineum wrote:
| I think you're spot in with this. It's the enthusiasts that
| are constantly trying to move the goalposts towards them and
| then the general public puts it back where it goes once they
| catch on.
|
| AGI is what people think of when they hear AI. AI is a
| bastardized term that people use to either justify, hype
| and/or sell their research, business or products.
|
| The reason "AI" stops being AI once it becomes mainstream is
| that people figure out that it's not AI once they see the
| limitations of whatever the latest iteration is.
| jodrellblank wrote:
| This is one of my pet dislikes; so after 1950, a time when a
| computer that could win at tic-tac-toe was 'AI', nobody is ever
| allowed to talk about AI again without that whinge being
| posted? Because AI was solved then so shut up?
|
| The author of that whinge thinks that what we all wanted from
| _Artificial Intelligence_ all along was a HAAR cascade or a
| chess min-maxer, that was the dream all along? The author
| thinks that talking intelligence any more is what, "unfair"
| now? What are they even whining _about_?
|
| Because the computers of yesteryear were slow enough that
| winning a simple board game was their limit, you can't talk
| about what's next!
|
| And thats to put aside the face recognition that Google put out
| which classified dark skinned humans as gorillas, not because
| it was making a value judgement about race but because it has
| no understanding of the picture or the text label. Or the
| product recommendation engines which recommend another hundred
| refrigerators after you just bought one, and the engineers on
| the internet who defend that by saying it genuinely is the most
| effective advert to show, and calling those systems
| "intelligent" just because they are new. Putting a radar on a
| car lets it follow the car in front at a distance because there
| is a computer to connect the radar, engine, and brakes and not
| because the car has gained an understanding of what distance
| and crashing are.
| potatoman22 wrote:
| I don't think anyone is saying "you can't call facial
| recognition AI." I think their point is that laypeople tend
| to move the goalpost of what's considered AI.
| jodrellblank wrote:
| And my point is: _so what_? [edit: missed a bit; it 's not
| 'moving the goalposts' because those things were never _the
| goal_ of Artificial Intelligence!].
|
| A hundred years ago tap water was a luxury. Fifty years ago
| drinkable tap water was a luxury. Do we constantly have to
| keep hearing that we can't call anything today a "luxury"
| because in the past "luxury" was achieved already?
| mjevans wrote:
| How about: We can call it 'AI' when it should have the same
| rights as any other intelligence. Human, or otherwise?
| goatlover wrote:
| Laypeople have always had in mind Data or Skynet for what's
| considered genuine AI. Spielberg's AI movie in 2001
| involved androids where the main character was a robot
| child given the ability to form an emotional bond to a
| human mother, resulting in him wanting to become a real
| boy.
|
| The moving goalposts come from those hyping up each phase
| of AI as AGI being right around the corner, and then they
| get pushback on that.
| zahlman wrote:
| I have always considered that the term AI was inaccurate
| and didn't describe an actual form of intelligence,
| regardless of the problem it was solving. It's great that
| we're now solving problems with computer algorithms that we
| used to think required actual intelligence. But that
| doesn't mean we're moving the goalposts on what
| intelligence is; it means we're admitting we're wrong about
| what can be achieved without it.
|
| An "artificial intelligence" is no more intelligent than an
| "artificial flower" is a flower. Making it into a more
| convincing simulacrum, or expanding the range of roles
| where it can adequately substitute for the real thing (or
| even vastly outperform the real thing), is not reifying it.
| Thankfully, we don't make the same linguistic mistake with
| "artificial sweeteners"; they do in fact sweeten, but I
| would have the same complaint if we said "artificial
| sugars" instead.
|
| The point of the Turing test and all the other contemporary
| discourse was never to establish a standard to determine
| whether a computing system could "think" or be
| "intelligent"; it was to establish that this is the wrong
| question. Intelligence is tightly coupled to volition and
| self-awareness (and expressing self-awareness in text does
| not demonstrate self-awareness; a book titled "I Am A Book"
| is not self-aware).
|
| No, I cannot rigorously prove that humans (or other life)
| are intelligent by this standard. It's an axiom that
| emerges from my own _experience of observing_ my thoughts.
| I think, therefore I think.
| AIPedant wrote:
| What this really reflects is that before these problems were
| solved it was assumed (without any real evidence) the solutions
| required something like intelligence. But that turned out to
| not be the case, and "AI" is the wrong term to use.
|
| There's also the effect of "machine learning" being used
| imprecisely so it inhabits a squishy middle between
| "computational statistics" and "AI."
| alkonaut wrote:
| I don't know, isn't "AI" more a family of technologies like
| neural networks etc? Facial recognition using such tech is and
| was always AI, while adaptive cruise control using a single
| distance sensor and PID regulation is just normalcontrol" and
| not AI?
|
| I never heard about AI being used in plane autopilots, no
| matter how clever.
| clbrmbr wrote:
| Fascinating reading the section about why the 1980s AI industry
| stumbled. The Moore's law reasoning is that the early AI machines
| used custom processors which were commoditized. This time around
| we really are using general purpose compute though. Maybe there's
| an analogy to open weight models but it's a stretch.
|
| Also the section on hype is informative, but I really see (ofc
| writing this from peak hype) a difference this time around. I
| fund $1000 in Claude Code Opus 4 for my top developers over the
| course of this month, and I really do expect to get >$1000 worth
| of more work output. Probably scales to $1000/dev before we hit
| diminishing returns.
|
| Would be fun to write a 2029 version of this, with the assumption
| that we see a similar crash as happened in ~87 but in ~27. What
| would some possible stumbling reasons be this time around?
| klabb3 wrote:
| > I fund $1000 in Claude Code Opus 4 for my top developers over
| the course of this month, and I really do expect to get >$1000
| worth of more work output. Probably scales to $1000/dev before
| we hit diminishing returns.
|
| Two unknowns: the true non-VC-subsidized cost and the effects
| of increasing code output and maintenance of the code
| asymptotically. There are also second order effects of
| pipelines of senior engineers drying up and costing a lot.
| Chances are if widespread longterm adoption, we'll see 90% of
| costs going to fixing 10% or 1% of problems that are expensive
| and difficult to avoid with LLMs and expensive to hire humans
| for. Theres always a new equilibrium.
| rjsw wrote:
| I was running compiled Franz Lisp on an Atari ST in 1986,
| general purpose computing processors were usable back then.
| dtagames wrote:
| This paper is far too long and poorly written, even considering
| that the topic of expert systems was once "a thing."
|
| There are three key parallels that I see applying to today's AI
| companies:
|
| 1. Tech vs. business mismatch. The author points out that AI
| companies were (and are) run by tech folks and not business
| folks. The emphasis on the glory of tech doesn't always translate
| to effective results for their businesses customers.
|
| 2. Underestimating the implementation moat. The old expert
| systems and LLMs have one thing in common: they're both a
| tremendous amount of work to integrate into an existing system.
| Putting a chat box on your app isn't AI. Real utility involves
| specialized RAG software and domain knowledge. Your customers
| have the knowledge but can they write that software? Without it,
| your LLM is just a chatbot.
|
| 3. Failing to allow for compute costs. The hardware costs to run
| expert systems were prohibitive, but LLMs invoke an entirely
| different problem. Every single interaction with them has a cost,
| both inputs and outputs. It would be easy for your flat-rate
| consumer to use a lot of LLM time that you'll be paying for. It's
| not the fixed costs amortized over the user base, like we used to
| have. Many companies' business models won't be able to adjust to
| that variation.
| rjsw wrote:
| It is a masters thesis, the length seems fine to me, spotted a
| few typos though.
| analog31 wrote:
| A hastily edited thesis is a sure sign of a student who got a
| job offer. ;-)
| api wrote:
| Something like the AI effect exists in the biological sciences
| too. You know what you call transhumanist enhancement and life
| extension tech when it actually works? Medicine.
|
| Hype is fun. When you see the limits of a technology it often
| becomes boring even if it's still amazing.
| TruffleLabs wrote:
| This is a form of machine learning and is within the realm of
| artificial intelligence. In 1961 this was definitely leading edge
| :)
|
| "Matchbox Educable Noughts and Crosses Engine" -
| https://en.wikipedia.org/wiki/Matchbox_Educable_Noughts_and_...
|
| "The Matchbox Educable Noughts and Crosses Engine (sometimes
| called the Machine Educable Noughts and Crosses Engine or MENACE)
| was a mechanical computer made from 304 matchboxes designed and
| built by artificial intelligence researcher Donald Michie in
| 1961. It was designed to play human opponents in games of noughts
| and crosses (tic-tac-toe) by returning a move for any given state
| of play and to refine its strategy through reinforcement
| learning. This was one of the first types of artificial
| intelligence."
| neilv wrote:
| Around the time of this MEng thesis, in one startup-oriented
| professor's AI-ish research group, the spinoff startups found
| that no one wanted the AI parts of the startups.
|
| But customers of the AI startups very much wanted more mundane
| solutions, which the startup would then pivot to doing.
|
| (For example, you do startup to build AI systems to do X, and a
| database system is incidental to that; turns out the B2B
| customers wanted that database system, for non-AI reasons.)
|
| So a grad student remarked about AI startups, "First thing you
| do, throw out the AI."
|
| Which was an awkward thing for students working on AI to say to
| each other.
|
| But it was a little too early for deep learning or transformers.
| And the gold rush at the time was for Web/Internet.
| ricksunny wrote:
| It's interesting to see observe how the author's career
| progressed over the 26 years following graduation with this
| thesis. Here she is just last year presenting on ML in the
| context of the LLM age:
|
| https://www.youtube.com/watch?v=p9bUuOzpBGE
| ChuckMcM wrote:
| The corollary works well too; "If it's AI, it doesn't work."
|
| That's because its the same mechanism at play. When people can't
| explain the underlying algorithm, they can't show when the
| algorithm would work and when it wouldn't. In computer systems,
| one of the truisms is that for the same inputs a known algorithm
| produces the same outputs. If you don't get the same outputs you
| don't understand all of the inputs.
|
| But that helps set your expectations for a technology.
| QuadmasterXLII wrote:
| Don't forget the contrapositive! If it's still called AI it
| doesn't work yet.
| asmor wrote:
| I wonder if LLMs will ever not be AI. Applications using LLMs
| that aren't terrible experiences are so because they replace
| large parts of things people say LLMs can do with vector
| databases, glorified if conditions and brute force retrying.
|
| I coincidentally can run local LLMs (7900 XTX, 24 GB), but I
| almost never want to because the output of raw LLMs is trash.
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