[HN Gopher] My 25-year adventure in AI and ML
___________________________________________________________________
My 25-year adventure in AI and ML
Author : ibobev
Score : 181 points
Date : 2025-01-01 22:41 UTC (1 days ago)
(HTM) web link (austinhenley.com)
(TXT) w3m dump (austinhenley.com)
| Evidlo wrote:
| I saw this guy recently left UTK, which is close to my hometown.
| He made a blog post which made me rethink going into academia
| after grad school.
| gbnwl wrote:
| Which one and in which direction did you rethink?
|
| Your comment made me curious so I looked at his posts and he
| has a one about leaving academia because he wasn't happy in
| 2022, and a more recent one about rejoining it some months ago.
|
| https://austinhenley.com/blog/leavingacademia.html
|
| https://austinhenley.com/blog/rejoiningacademia.html
| Evidlo wrote:
| I didn't see the more recent post, so thanks for the link.
|
| I should say that I'm still in grad school (nearing the end),
| so the decision hasn't been made yet. The direction I'm
| thinking is away from academia.
|
| I love the academic environment, access to university
| resources and close proximity to lots of domain experts.
| However my experience as of late has been pretty isolating,
| as my group is almost fully remote despite nearly everyone
| living in the same town making motivation difficult some
| times. I also sometimes miss exercising my practical
| engineering skills, as my current work is entirely
| analytical/simulation. Overall its been less rewarding than I
| had hoped.
| mtrovo wrote:
| > Although I was on an AI team, I often pushed back against
| applying AI unless we had a really compelling reason. What is the
| user problem we are trying to solve? Do we really need an LLM or
| could a few if statements suffice? Are we sure that natural
| language is the appropriate interface for this?
|
| This practical approach to AI feels refreshing in a field
| drowning in buzzwords. I've built tools where simple regression
| models outperformed neural networks, and convincing teams was an
| uphill battle. It's hard to not get pushback from teams for not
| going all-in on AI when it seems decisions and budgets are hype-
| driven.
| d_sem wrote:
| This is a perfect lesson in why strong communication skills are
| important in engineering organizations. It's leaderships
| responsibility to learn from engineering what is technically
| feasible but its also engineering's responsibility to
| communicate well enough to convince their organization on the
| right path forward.
| spacecadet wrote:
| For years I worked at a company doing manufacturing automation
| with a generative CAD component. People would constantly throw
| out, "use ML" "use AI", everything was just regressions and
| open cascade... and those people never understood that it
| worked just fine without buzzwords.
| BOOSTERHIDROGEN wrote:
| Could you offer more insight into how regression analysis and
| open cascade are utilized in manufacturing processes?
| extr wrote:
| I have pushed back in a similar way many times (wrt LLMs), the
| response I typically get is some combination of:
|
| - A custom/heuristic driven approach would perform better but
| will take much longer to build so would be lower ROI.
|
| - There is a strategic angle to using AI here (building
| competency). We aren't sure what new use cases will open up in
| the medium term and we need to be fluent with building AI
| products.
|
| - There is a perceptual/marketing angle to using AI here. We
| need to convince the market/investors we are on the bleeding
| edge (hype).
|
| 3 is widely mocked but is a completely rational allocation of
| resources when you need to compete in a market for funding.
| _glass wrote:
| Prolog is AI, so whenever I see such a problem, I use
| miniKanren, implementing Relational/Logic programming in a
| light-weight way. Bleeding edge AI it is.
| physicsguy wrote:
| > will take much longer to build so would be lower ROI
|
| This one is funny because my experience has been that ekeing
| out the issues in this sort of thing is enormously
| complicated and unreliable and takes an inordinate amount of
| time. Often the 'bugs' aren't trivially fixable. One we had
| was the LLM formatting URIs given in the prompt wrongly
| meaning they're no longer valid. Most of the time it works
| fine, but sometimes it doesn't, and it's not reproducible
| easily.
| extr wrote:
| It's true, it can be maddening (impossible?) to chase down
| all the edge-case failures LLMs produce. But outside of
| life/death applications with extreme accuracy requirements
| (eg: medical diagnostics) the attitude I've seen is: who
| cares? A lot of users "get" AI now and don't really expect
| it to be 100% reliable. They're satisfied with a 95%
| solution, especially if it was deployed quickly and
| produces something they can iterate on for the last 5%.
| jorblumesea wrote:
| for 1/2, surprised to hear this because debugging models is
| usually a total black box and practically impossible. for 2,
| it's a similar problem where getting performance and accuracy
| using the same model over and over again on different problem
| sets can be challenging. not an AI expert or anything this
| has been my experience on the product side.
| extr wrote:
| Responded to the same sentiment elsewhere but my general
| sense is that for many use cases users simply do not care
| about high 9s accuracy/consistency. A 95% solution using AI
| is "good enough" if you can ship it quickly and give them
| the tools to iterate on that last 5%.
| jorblumesea wrote:
| 95% solution might work for small startup X or small biz
| y but at large company scale 5% is a huge deviation to
| correct on. Maybe just depends on the client and how
| touchy they are. At my company, we measure metrics in bps
| and moving something 50 bps is a huge win. 500 bps would
| be unheard of.
| extr wrote:
| IMO it's less about the size of the company and moreso
| the nature of the integration. Users are more forgiving
| of 95% accuracy when it's used to enhance/complement an
| existing (manual?) workflow than when it's used to
| wholesale replace it. The comparison would be building an
| AI tool to make data entry easier/faster for a human
| employee (making them say, 2x as productive even at 95%)
| versus an AI tool that bills itself as a full replacement
| for hiring a data entry function at all (requiring human
| or superhuman accuracy, edge case handling, maddening LLM
| debugging, etc).
|
| In the long run the latter is of course more valuable and
| has a larger market, so it's understandable large corps
| would try to "shoot for the moon" and unlock that value,
| but for now the former is far far more practical. It's
| just a more natural way for the tech to get integrated
| and come to market, in most large corp settings per-head
| productivity is already a measurable and well understood
| metric. "Hands off" LLM workflows are totally new and are
| a much less certain value proposition, there will be some
| hesitation at adoption until solutions are proven and
| mature.
| mrieck wrote:
| You didn't list the most important reason:
|
| - Assume LLMs will be more intelligent and cheaper, and the
| cost of switching to a new LLM model is non-existent. How
| does improving the custom/heuristic compare in that future?
| extr wrote:
| That's kind of what I was getting at in point 2, about "new
| use cases" opening up, but yeah you stated it more
| directly. It's hard to argue with. With a heuristic driven
| approach we know we will need expertise, dev hours, etc to
| improve the feature. With LLMs, well, some lab out there is
| basically doing all the hard work for us, all we need to do
| is sit back and wait for a year or two and then change one
| line of code, model="gpt-4o" to model="gpt-5o" or whatever.
| cm2187 wrote:
| CV driven development!
| j45 wrote:
| It's important to consider if existing tech can do something as
| well if not better.
|
| LLMs can have have great application where existing tech can't
| reach.
|
| Too often, seeing LLMs doing something that's done better
| already by an existing tech or something it's not designed for
| seems to miss the impact being sought.
| IanCal wrote:
| I've found having a cascade of things helps. Trying to split
| things into "decision at this later, or pass on to the next"
| with increasingly complicated models/approaches.
|
| Start with ifs, then svms then something else for example.
|
| This has some technical benefits, like speed, and gives you a
| place to put important hard coded fixes for where a better
| model makes a small but key mistake. But the bigger benefit imo
| is getting something to solve the bulk of the problem quicker,
| and a organisationally it means not saying no to an approach -
| just where it fits and at what level of improvement it's worth
| it.
| frereubu wrote:
| I have a friend who was tasked by a think tank to build an AI
| model for which they'd managed to get an enormous amount of
| funding. My friend pointed out that it would be much more
| effective if they used a regression model that could be built
| in a couple of days by a junior developer. Eventually he was
| fired from the project for sticking to his guns and refusing to
| pad his time while building something worse just so they could
| say they'd used "AI".
| mlepath wrote:
| I have had a somewhat similar journey but 14 years instead of 25
| and I always wonder how it would be different today.
|
| We were lucky enough to grow up with the industry and
| progressively learn more complexity. The kids out of school today
| are faced with decades worth of complexity on day one on the job.
| fallous wrote:
| This is true for every field. Everyone has had to step into a
| field that was built upon the hard-won experience of others and
| had to get up to speed, and the easiest way to do so is to
| recognize that fact and take advantage of the wisdom of those
| who came before.
| mnky9800n wrote:
| Physicists have centuries to catch up on just to get started. I
| think they will survive. The main issue today is more the
| saturation of useless information in my opinion. There's little
| time for your own thoughts as too much time is spent sorting
| the thoughts others want you to think.
| vouaobrasil wrote:
| For a lot of people, AI is a fun journey where they create things
| that are amazing. And I agree, the results are quite amazing. But
| it's also a sad thing that the world works this way because
| scientists like this never think of the larger social
| consequences of their work. They are insulated and elevated to
| lofty social positions while their creations fundamentally alter
| the social fabric. AI is one of those things that is quite
| dangerous and the fact that large corporations attract people by
| glorifying their intellect is a recipe for disaster.
| dale_glass wrote:
| I'm not sure what this means exactly, because AI is a wide
| field that covers so much and angers a great many people for
| many different reasons.
|
| But IMO it's pointless to hope for something else. AI at its
| core turns out to be pretty simple. No matter what the best
| intentioned scientist did, somebody else would think
| differently.
|
| For example, Stable Diffusion was originally released with a
| filter that refused to generate porn. There's your scientist
| thinking of social consequences. But does anyone even still
| remember that was a thing? Because I'm pretty sure every SD UI
| in existence at this point has it disabled by default.
| vouaobrasil wrote:
| > No matter what the best intentioned scientist did, somebody
| else would think differently.
|
| This is exactly an argument that supports technological
| determinism. We simply can't decide -- we have no ability for
| oversight to stop technology from evolving. That's precisely
| why I think AI is so dangerous.
| dale_glass wrote:
| IMO, the dangers of AI are mostly overrated. AI is just a
| new fancy way of generating pictures and text. It does
| those things better in some regards, but the danger is the
| same we already had.
| vouaobrasil wrote:
| It's also a way of mechanizing even further large amounts
| of human labor and reducing the importance of art. I
| guess it depends on what you value: for you, apparently a
| world with AI is not so bad. For me, it's disgusting.
| dale_glass wrote:
| I honestly don't see it fundamentally different from most
| other code. I generated images and music (PLAY
| instruction) with GWBASIC back when I was a teenager. I
| generated text with Perl.
|
| This is just the continuation of the same old, just a bit
| fancier.
| vouaobrasil wrote:
| I don't think it is. One could say that getting hit by a
| car is the continuation of getting hit by a person, but
| one is much more powerful than another. AI allows mass
| creation of much more complicated works at a speed much
| greater than before. the PLAY instruction might create
| some music, but it won't be the sort of music that can
| compete with human-made music. AI music is very close to
| it.
|
| Speed is important, strength is important. There is no
| obvious qualitative difference, but qualitative
| differences emerge due to a massive increase in
| complexity, just like consciousness emerges in us but
| (probably) not in a bacteria due to the massive
| difference in complexity, even though we are just a
| scaling of the former.
|
| Your text generation with Perl wouldn't be able to write
| an article, but ChatGPT can, and the magnitude difference
| is precisely what we cannot handle, just like I can't be
| hit by a speeding car at 100km/h and survive but I'd
| probably walk away from being hit at 2km/h (and once this
| actually happened to me, without injury). Would you say
| there's not much difference between the two?
| _heimdall wrote:
| This is actually where the AI concern arguments seem to
| get misunderstood in my opinion.
|
| I've never heard anyone raise serious concerns over
| fancier ML and generative algorithms - maybe concerns
| over job loss but I don't think that's what you had in
| mind (correct me if I'm wrong).
|
| The more serious concerns I hear are related to actual
| artificial intelligence, something much smarter than
| humans acting on a time scale drastically different than
| humans.
|
| I'm not vouching for those concerns here, but I would say
| its more fair to keep them in the context of AI rather
| than ML, LLMs, and generative tools.
| HarHarVeryFunny wrote:
| We're only just starting to get to the point that AI, if
| unconstrained, is capable enough to be dangerous. The
| danger is getting to the point where the not-so-bright
| malevolent actor can tap into AI to get detailed
| instructions to do something highly destructive, or have
| it do it on their behalf (e.g. hack into some system),
| that they wouldn't previously have been able to figure
| out just by Googling for information and trying to piece
| it together themself.
|
| Of course not all malevolent actors are dimwits, but
| there are also many things that even a highly intelligent
| individual couldn't do on their own, such as a Stuxnet
| level attack, that AI will eventually (how soon?) be able
| to facilitate.
| _heimdall wrote:
| > For example, Stable Diffusion was originally released with
| a filter that refused to generate porn. There's your
| scientist thinking of social consequences
|
| We would have to know their internal conversations to know
| whether that filter was being driven by scientific concern
| over social consequences or any number of business
| goals/concerns. We can't assume the reasoning behind it when
| we only have the end result.
| dale_glass wrote:
| That doesn't matter for the point I'm making: which is that
| this attempt (and any other) are trivially nullified by
| those that come next. The SD devs couldn't have created a
| state of affairs in which AI never ever would generate
| porn.
|
| And transformer architecture is too low level to care about
| things like that, there was no way for the people who made
| the guts of the modern AI systems to make it so that they
| only can ever make cute fluffy kittens or give accurate
| advice.
|
| So what I'm saying is that there's no timeline in which
| socially conscious scientists would have succeeded in
| ensuring the the current gen AI landscape with its porn,
| deepfakes and propaganda didn't come to exist.
| SteveSmith16384 wrote:
| It makes such a refreshing change to have a web page not
| cluttered with adverts and popups. Just nice, clean, well-spaced-
| out text and simple organisation.
___________________________________________________________________
(page generated 2025-01-02 23:02 UTC)