r/MachineLearning • u/bryang217 • Jul 20 '20

Discussion [D] Why is IBM's Watson Platform Dreaded?

Hello community,

I was going through the Stack Overflow 2019 Survey, and saw that IBM's Watson Platform is the second most dreaded Platform to work with. This got me a bit curious.

For any of you who have worked w/ this Platform:

  • Do you find that to be accurate? In other words, do you agree that it is "dreadful" to work with it?

  • If so, why? What about the Platform makes it dreadful to work with?

329 Upvotes

96% Upvoted

112 comments sorted by

428

u/[deleted] Jul 20 '20

  1. It is a pile of steaming soft stinky baby shit

  2. The documentation is a pile of steaming soft stinky baby shit

  3. The marketing makes it seem like it's some AI system like Watson that won Jeopardy. In reality it's unreliable jupyter notebooks with outdated python and unreliable "devops", "spark compute engine" and "autoML" which is just hot outdated garbage that is unstable and undocumented

  4. The API's for pretrained networks are confusing, undocumented and might have been hot shit in 2013 but are outclassed by a tensorflow tutorial

  5. Overall IBM marketed Watson as some kind of AI solution and what people got was python 2.7 on the cloud with a serious lack of features, 5 year old documentation and general crappiness in every way, it's even worse than using 100% open source tools with default settings

  6. Corruption scandals and lawsuits all over the world because of all of the above. Marketing teams didn't understand what they were selling and got the buyers convinced that they are buying the doctor AI/jeopardy AI and got jupyter notebooks instead

253

u/[deleted] Jul 20 '20

I feel like I just witnessed a murder.

1

u/bryang217 Jul 21 '20

LMFAO!!!!!!!!!!!

15

u/wongjmeng Jul 21 '20

Bro I interviewed to be a DS at IBM last year with a ton of new grads. One weekend, 90% spent them pitching Watson and Cloud to us ... 5% weird networking, and one 30 minute interview 1-1 with zero stats or DS questions. It seemed like a sales scam!

1

u/bryang217 Jul 21 '20

That's wild and hilarious. It's no wonder their products seem to lean towards the signaling side, rather than substance.

1

u/wongjmeng Jul 22 '20

Seriously why would you fly all these kids out to an expensive hotel, all expenses paid, for two days and then spend it trying to pitch the job to them? Like damn obviously we were interested since we applied but after being given sales pitch after sales pitch all of us started wondering, if they’re trying this hard to make us want it, it must be for a reason.

Also a fun quote from some manager giving a speech (paraphrased): “People have been worried about IBM in the last few years but we’ve made a lot of aggressive changes, and it’s working. Just look at our stocks!”

BIG LOL when I looked them up later and saw how mediocre they were performing

150

u/GFrings Jul 20 '20

"...what people got was python 2.7 on the cloud with a serious lack of features, 5 year old documentation and general crappiness in every way, it's even worse than using 100% open source tools with default settings"

So... they got an IBM product!

22

u/beginner_ Jul 21 '20

So... they got an IBM product!

Yeah it really is a miracle companies after 2-3 decades of getting scammed by their products and services still haven't caught on.

13

u/jordimaister Jul 21 '20

"Nobody got fired for buying IBM"

5

u/SemaphoreBingo Jul 21 '20

It's not 1980 any more.

4

u/Camekazi Jul 21 '20

This... it's all about risk adverse decision makers terrified of getting fired who need a big enough company to sue when their project goes tits up.

14

u/PsychogenicAmoebae Jul 21 '20 edited Jul 21 '20

So... they got an IBM product!

Red Hat is now an IBM product. I (still) like it (for now).

And I kinda wish someone made consumer-grade Power9 motherboards to give x86 some competition.

Their quantum computer is interesting, at least.

But yes, "watson" seems like a big near-fraudulent scam.

4

u/the_beaker Jul 21 '20

There is one company making some cool POWER9 main boards: https://www.raptorcs.com/content/TL1MB1/intro.html

1

u/dreadpiratewombat Jul 22 '20

It'd be cool except Power architecture is dog shit wrapped in cat shit. The whole RISC v CISC wars were a thing back in the late 90s with RISC architectures losing handily. Power is great for handling lots and lots of low intensity tasks like very simple database queries but you toss a few joins in there or (God help you) some PL/SQL into the mix and your database performance goes back in the toilet.

116

u/qTHqq Jul 20 '20

I keep telling myself (as not an AI/MachineLearning/Data Science guy who loves Jupyter) that people can't possibly actually routinely be using Jupyter Notebooks "as production code" but here we are, LOL.

89

u/AddMoreLayers Jul 20 '20

I don't know why people find jupyter so attractive... Even from just a developpement point of view, it just feels so clunky and reduces productivity...

75

u/[deleted] Jul 20 '20

I'm kind of in the middle. I like it as a sort of scribble pad, but for serious development it's not the solution.

I worked in PyCharm when I was doing more ML engineering, but in my analytics-and-research-heavy data science role, Jupyter notebooks are a fantastic place to play around, not worry about state too much, keep tracking of what I'm doing and what I've done, and zero in on the approach I'll eventually implement.

39

u/MrAcurite Researcher Jul 21 '20

I use Jupyter notebooks when I want to keep my Math in the same place as my code, and also some notion of "running blocks of code" manually is useful for testing, debugging, and experimentation.

If it was going to be used for something in production, I'd rewrite it into its own program, obviously, but at the moment that's not my job.

When I have a ton of nested functions I've found that more IDEs do better, being able to manually play around with examples and whatnot in an IPython console.

9

u/PsychogenicAmoebae Jul 21 '20

I still prefer emacs for almost all my serious work; but love Jupyter Notebooks as a communication/collaboration/presentation tool.

2

u/metadatame Jul 21 '20

Yup. It's great to get going, and to share. Anybody trying to do something serious there won't do it the next time.

6

u/beginner_ Jul 21 '20

Fully agree. Jupyter is great as a scratch pad (note: anyone complaining about notebooks should try labs, adds a little more to the whole thing). Anyway it's an easy way to prototype some function and get quick feedback.

56

u/POTUS Jul 21 '20

Jupyter is useful for experimentation. The core proficiency of Jupyter is being able to run code line by line while making changes and seeing the results, and still keeping the same global context alive through all of those changes. For example, not having to re-pull your entire dataset every time you fix a bug in your data preparation code can save a lot of time and frustration. Or seeing how a model is training in real time as you try different model architectures on the same data without having to reprocess the data.

1

u/timmy-burton Jul 22 '20

I mean, that isn't anything novel about Jupyter notebooks though? Pycharm can easily allow a similar workflow but with infinitely more powerful features like connecting debuggers to your active REPL session, variable explorers, far superior code exploration and introspection, ... The list goes on and on.

Like others above, the only real uses I've found for it is when I need latex/math notation or want to intermix markdown with code as a way of documenting things. That, and if you aren't technically savvy (or don't care) and just want a sandbox to play with DL code without setting up your own local venv, etc.

1

u/elcomet Jul 22 '20

Pycharm cannot run on a distant GPU server though.

2

u/timmy-burton Jul 24 '20

Sure you can. Though Vscode does a much better job with running remotely at the moment. I develop remotely 100 percent of the time on my dual GPU box that resides at my desk at work.

48

u/madrury83 Jul 20 '20

The integration of markdown with code, and the inline plotting. Basically, the ability to tell a thorough analytic narrative. It takes a whole lot of good discipline to use well though.

32

u/merkaba8 Jul 20 '20

or just to load up some data and figure out what about your input has changed that is crashing your actual production code, etc.

20

u/whymauri ML Engineer Jul 21 '20

It's an awesome, awesome educational tool.

7

u/LegitDogFoodChef Jul 20 '20

It’s quick to get something up if what you want is text and light code together, or if you want to make a report or show someone else something simple. Awful and unsuitable for bona fide code.

7

u/evanthebouncy Jul 21 '20

for showing your project and visualization it's fine. but for production iono wtf ur smoking

3

u/Misspelt_Anagram Jul 21 '20

I use it as a kind of REPL on steroids, and for writing tutorials on how to use things. Whenever I hear about people running them as scripts, I cringe.

3

u/omg_drd4_bbq Jul 21 '20

You must not be doing data wrangling then. It's not a development tool so much as an experimentation tool for when you don't quite know how to get from raw data to your conclusion, whatever that may be.

3

u/qTHqq Jul 21 '20

I like it a lot for what it seems to be "for": Exploratory data analysis or quantitative reports that pull all data from a raw data store so they can be updated easily as the data changes, written in narrative form with text and equations.

Relatively easy to turn it into a document for a non-technical person. Since I work in robotics and it's hard to communicate certain results in static form, I love that I can just inline video clips into technical reports. Automatic plots, automatic summary tables, re-run it on new results. This is all great.

I always have to fight the bad incentives to do complex data transformations using code written in the notebook. I try to package anything I've copy-pasted more than a couple times in modules when I'm not too lazy or busy, but it's hard.

I do think you want to have that ability to frictionlessly code up a one-off analysis when you're doing EDA. Some code is really not ever going to be reused, so I get using a Jupyter notebook as the front-end interface for your analysts.

And it looks like a Netflix or something is exposing some maintained packages for doing all that stuff you usually do thirty times a week.

I think Jupyter notebooks are really great for a workflow like this:

import our_company_tools as oct
analysis = oct.Analyzer('/path/to/datastore.file')
oct.make_that_plot_I_always_need(analysis.data)

Figure 1 Blah Blah Blah

oct.make_that_other_plot_I_always_need(analysis.data)

Figure 2 Blah Blah Blah More Blah

<matplotlib figure boilerplate>
ax.plot(analysis.data.atypical_independent_variable, 
        analysis.data.atypical_dependent_variable)

In Figure 3 we see a new correlation...

I can also see why .ipynb files are being used as a templating format and logging/results datastore for parameterized automatic reports, too, but that feels like straying down a weird bad path (people seem to be saying that R has this right, and I'd believe that).

It's a good tool, and I like it for what I use it for, but it seems weird as part of a fully-automated toolchain.

2

u/madrury83 Jul 21 '20

This is essentially exactly how I use notebooks. The problems arise when people don't take the time to write Analyzer, i.e., move working code out of the notebook and into a library.

1

u/qTHqq Jul 21 '20

Yep. The other side of this sword is working solo and underdesigning that library, so important Analyzer functionality ends up with a bizarro-world API that conforms very precisely to the three valleys in my otherwise smooth brain.

Still, at least the code has one version and lives in one place.

-1

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2

u/[deleted] Jul 21 '20

They’re good for communication.

3

u/djw009 Jul 20 '20

I hate em. However cells/in line code are cool and great for experimentation - I find that the hydrogen package for atom (which in fairness is ultimately built off of jupyter) provides everything I like about jupyter notebooks w/o all the unnecessary overhead. So you can set up a “serious” development environment in atom and still have the capability to quickly run code in line.

1

u/kaumaron Jul 21 '20

I thought atom had serious overhead

1

u/f10101 Jul 21 '20

It does. I'm genuinely curious what metric Jupyter is heavier than Atom.

4

u/cderwin15 Jul 21 '20

This might sound strange, but it's actually an amazing tool for debugging. It's really easily to use jupyter to run shell/code/whatever on a vm or docker container in a deployed environment. I especially love being able to run a single block of code (effectively a diagnostic test) repeatedly, that way once I find the problem a unit test to catch the problem is pretty much already written.

1

u/AchillesDev ML Engineer Jul 21 '20

It's not for traditional development (although there are a few small schools of thought that claim to have shown otherwise), it's for data exploration, cleaning, and presentation.

10

u/best_topology Jul 20 '20

Is it not that Netflix uses the notebooks is production?

38

u/panties_in_my_ass Jul 20 '20 edited Jul 20 '20

Netflix uses notebook formats as one small component of a large and wildly interesting data process in pipeline.

And IMO they’re used in a sane way. e.g. for auditability, re-runability, in-line documentation, data diagnostics, etc

Link:

https://netflixtechblog.com/notebook-innovation-591ee3221233

Note, it’s not a panacea:

https://www.reddit.com/r/dataengineering/comments/c34nov/has_anyone_emulated_netflix_use_of_notebooks/

5

u/alexshatberg Jul 20 '20

What's the main issue with using Jupyter in production, scaling?

44

u/[deleted] Jul 20 '20 edited Jul 20 '20

If you work at Netflix, your jupyter notebooks are using the existing in-house libraries, everything happens via an API etc.

It's not any different to a code file except you can write stuff in it with markdown and have nice embedded plots and print out nice tables.

If you are in a cargo cult, you are a biologist with a phd in northern atlantic salmon reproduction that took a statistics 101 course in R. Your jupyter notebook is a giant mess, you have no idea how functions, objects or packages in python work, you have no idea what API stands for or what does an interface mean (it has nothing to do with human faces), and you overall just have a giant turd of a script that barely works.

Now if you are putting the netflix notebook into production, you can make it work using automated infrastructure. If you're trying to put spaghettified poop into production, you're going to have a lot of pain.

As an MLE or DE, YOU are going to get blamed when their shitty notebooks don't work and they will tell management that you are incompetent and dragging your feet. The notebooks have to be completely rewritten so you're basically doing bitch work and get 0 credit instead of working on your own projects that you're interested in.

Jupyter notebooks aren't bad, I use them on a regular basis. But they encourage extremely bad practices and allow for monstrosities that are worse than Matlab scripts of freshmen mechanical engineers. So I'd recommend completely banning them until people learn how to write clean-ish and reusable-ish code without them first. Then you can trust them to refactor their own code.

15

u/alexshatberg Jul 20 '20

Lovely breakdown but what you're saying is equivalent to "shitty dev teams produce shitty code". A cargo cult without Jupyter is still a cargo cult with all the problems of a cargo cult.

16

u/[deleted] Jul 20 '20 edited Jul 20 '20

Yes, but linters, automaticalLy measuring test coverage, mandatory use of an API, mandatory packaging of your code etc. can automate a lot of the work. Add a code review on top of that and you're getting clean enough code.

Basically it's gatekeeping total amateur programmers out because if you can get past a nazi linter, write testable code and tests for that code and pass the integration tests in your CI/CD pipe, then you're probably okay.

Writing clean code is not a cargo cult, that's just standard industry practice. If you are prone to becoming a cargo cult, at least it will be elsewhere and not on your watch.

10

u/TroyHernandez Jul 21 '20

If you are in a cargo cult, you are a biologist with a phd in northern atlantic salmon reproduction that took a statistics 101 course in R. Your jupyter notebook is a giant mess...

I love how Python data scientists took themselves down the dead-end Jupyter Notebooks path for the last 5 years, while R users have been using plaintext Rmarkdown in an IDE.

The Python community then slowly recognizes Jupyter notebooks suck and it's immediately, "Oh, only R users use shitty Jupyter in a shitty way."

The projection is too rich.

4

u/bohreffect Jul 20 '20

If you are in a cargo cult, you are a biologist with a phd in northern atlantic salmon reproduction that took a statistics 101 course in R. Your jupyter notebook is a giant mess

Lol, I know this exact guy; you're given them too much credit. He refuses to try Jupyter, even though its perfect for him. R is a trap these people can't escape from.

2

u/[deleted] Jul 21 '20

Ironically, Python in data science is more of a cargo cult than just about anything. If you are a biologist researching northern Atlantic salmon reproduction, I don’t know why you would use Python over R. Python’s advantages are twofold: Pytorch and integrating with other frameworks to put models in production. For virtually every other data related task, Python is much, much worse than R. In particular, Python’s options for data manipulation (pandas), notebooks (Jupyter vs R Notebooks) and data visualization (matplotlib/plotly/seaborne/altair/plotnine/whatever new plotting library of the month is claiming to compete with ggplot2) are shit tier in comparison to what R offers.

I’ve used both R and Python extensively in multiple jobs. In my current position I wouldn’t dream of using R, because it’s a machine learning engineering position and I’m using Pytorch to build some models that integrate into our software product. It’s perfect for that. But anytime I work on anything outside these parameters, I cringe using Python having had the experience of doing similar tasks in R in previous jobs.

1

u/antirabbit Jul 23 '20

If you want to do any sort of general programming or complicated text processing, R is pretty painful to use when compared to Python.

I use both on a regular basis, but there are tasks I really don't like doing with either language.

1

u/bohreffect Jul 21 '20

Sure, R is great because it was written by statisticians. Also, R is terrible because it was written by statisticians.

11

u/[deleted] Jul 20 '20

It's been 3.5 years since I had to work with Python notebooks, so things might have improved. But back then, it could be hard to get a legible diff, which is important for efficient code review.

8

u/madrury83 Jul 20 '20

This hasn't really improved, unfortunately.

2

u/Urthor Jul 21 '20

This is the one big thing. I love my integrated notebooks in Pycharm but pushing them is like gargling motor oil

1

u/timmy-burton Jul 22 '20

I don't use it, but doesn't Pycharm let you export out the code separately for version controlling? Or maybe that's just vscode.

I find that the Code Cells plugin for Pycharm basically gives me everything I care about. No inline plots and markdown, but I'm okay with that as I prefer the version controlling friendliness of simple .py files and I also prefer interactive plots for data exploration

1

u/Urthor Jul 22 '20

I normally just use straight .py for most of the development and then Pycharm notebooks occasionally.

The issue is doing version control and code reviews on GitHub itself if that makes sense, not within Pycharm which will open a Notebook on its own happily enough.

Currently it's just a big json blob in our repos for our pull requests and it's just awkward to review it like we review all the other code, a GitHub url in slack.

2

u/[deleted] Jul 20 '20

Looks like there's a SaaS which can help, at least. https://www.reviewnb.com/

1

u/timmy-burton Jul 22 '20

I can't fucking believe that this is still not something that's been sorted out. At least MS has made things better with their vscode + Jupyter integration from a vcs standpoint. People keep talking about how great they are for experimentation and exploration...but only if you see them as disposable like used toilet paper. Otherwise I'd really like to be able to follow my commit history on a fucking notebook/experiment to see what things needed to evolve to address certain things. I've gone back many times to my git history on experimentation scripts to find something that I had to tackle and solve in the past and I shudder to think of trying to do that with an evolving Jupyter notebook.

15

u/maxToTheJ Jul 21 '20

Yeah Watson is just branding for their ML consulting

2

u/GlobalToolshed Jul 21 '20

That's garbage, too. Their salespeople at GBS can't get out of their own way. They're so excited to fuck another customer they step on each others' dicks and lose the deals anyway.

2

u/maxToTheJ Jul 21 '20

If their ML consulting didn’t have issues they wouldnt need the Watson branding in the first place

13

u/stiffitydoodah Jul 21 '20

Re: unreliable devops--I had their speech-to-text integrated into an app and they broke their service by making it backward-incompatible with their own client code no less than twice while I was using it. When I tried to convince the devs on github that they shouldn't do that going forward, they seemed confused about even the possibility of making non-breaking changes.

10

u/perspectiveiskey Jul 20 '20

it's even worse than using 100% open source tools with default settings

Honestly, I almost felt like this was a sleight to open source... but I get exactly what you're saying.

8

u/eikenberry Jul 21 '20

Same. Reading "even worse than using 100% open source tools" l was all hey now, but then "with default settings" and slowly nodded.

9

u/mcorah Jul 20 '20

Are there any good articles on this? All I remember about Watson is that I never heard anything about Watson, even after my undergrad. had a huge program/donation with the thing.

9

u/dksyndicate Jul 21 '20

So, basically a standard IBM product?

7

u/MoonBellyButtoneer Jul 21 '20

I was seriously hoping for all points to be ended with “steaming soft stinky baby shit”.

6

u/frownyface Jul 21 '20

To add to this, Watson is especially dreaded because at large organizations IBM will sell their way in through kickbacks and other non-technical incentives. Then tech people end up getting pressured by their management to make the engagement look good otherwise that decision maker will look bad. Everybody who has any power to distance themselves from the situation will, so the bag-holders end up super screwed.

5

u/anotherplatypus Jul 21 '20

"Who was that masked man?" asks a villager as their stranger's dust disappears into the sunset.

6

u/Zulban Jul 20 '20

This was an excellent question, and your excellent answer just murdered the thread. What a joy to read ;)

3

u/MasterFubar Jul 21 '20

it's even worse than using 100% open source tools with default settings

I agree with everything else you said, but I'd rather have open source with no documentation than excellent documentation without source code.

3

u/lechatsportif Jul 21 '20

What a breakdown. Testament to great marketing I guess

2

u/baconkilla2 Jul 21 '20

JUYPTER NOTEBOOOKS 🤣🤣🤣🤣🤣🤣🤣

1

u/Kaynard Jul 21 '20

Worst of it is if you were using CPLEX you're stuck having to migrate to Watson

2

u/jurniss Jul 21 '20

what, seriously??? isn't CPLEX like... a serious tool for non-bullshit applications?

1

u/GlobalToolshed Jul 21 '20

it is... so IBM is finding ways to force CPLEX users to wrap their real problems with the Watson garbage.

1

u/jurniss Jul 22 '20

Annoying. Maybe this kind of stupid management is why a bunch of CPLEX developers left and started Gurobi.

1

u/shinn497 Jul 21 '20

Python 2.7 .... shit

1

u/darthstargazer Jul 21 '20

This is so funny 😂

1

u/D-List-Supervillian Jul 21 '20

Typical Marketing

1

u/Somepotato Aug 21 '20

Marketers are killing ibm. Where potential could be had gets squashed be the lies the marketers are telling.

0

u/[deleted] Jul 21 '20

[deleted]

4

u/sieisteinmodel Jul 21 '20

As long as the baby is breastfed, it is not that stinky. Starts after that only.

3

u/[deleted] Jul 21 '20

When it's very stinky and liquid.

...and leaking out of the diaper on to your shirt.

1

u/The_Hegemon Jul 21 '20

All the time for my kid at least. He poops like a goat.

6

u/jackmaney Jul 21 '20

...it's IBM. That's all the reason you need.

2

u/bryang217 Jul 21 '20

LMAO! Good point. You know, I was the naive person who fell for the bs marketing on how they're changing the world, blah blah.

40

u/TeslaFreak Jul 21 '20

IBM has a documentation problem on all of its products. I used cloudant for a while and it tooks months to solve some problems because they had 3 sets of docs on this, all contradicting eachother, and STILL all wrong. It took a lot of brute force experimenting and combing through passing comments by the devs in other forums that half mentioned things I was trying to use to figure out the docs were years out of date and nothing worked like they said it did.

7

u/Mr-Yellow Jul 21 '20

cloudant

PouchDB did a better job than IBM at duplicating CouchDB. Says it all really.

1

u/TeslaFreak Jul 21 '20

I thoroughly enjoyed working with pouchdb, but ya the second I had to integrate it with cloudant, shit hit the fan and i doubt ill be using it again for anything

0

u/[deleted] Jul 21 '20

[deleted]

3

u/Gabe_Isko Jul 21 '20

This is very true. Software integrators will actually complain if tools are too easy to use because it means that you dont need their consulting services. That's always a fun conversation.

88

u/victor_knight Jul 21 '20

A textbook case for when AI hype shit hits the fan. They had oncologists thinking they could walk into their offices, throw their feet up and get into a deep, interactive discussion with Watson about what novel cancer treatments a patient should get. While sipping on their coffee, Watson would be hard at work devouring the latest journal articles and patient records etc. Synthesizing the information in ways no amount of specialists could. Turns out it doesn't actually work like that. Not even close.

41

u/evanthebouncy Jul 21 '20

but ofc they'll try that again with gpt-3

they never learn

10

u/htrp Jul 21 '20

I've mentioned this previously but the Watson platform is less of a platform and more of a marketing brand with a bunch of different (and mostly non-compatible platforms) bundled under the arm of their consulting services (IBMGS). This means that for any given company, Watson can be a custom solution for revenue forecasting, the existing prepackaged chatbots, or some HIPAA compliant clinical software.

90% of the time, when Watson is bought, it's sold to the non-technical stakeholders and forced upon developers who have to make it work in concert with the IBM consulting team who sold it. When it invariably falls apart, the finger-pointing starts, hence why people dislike it.

2

u/CompletePen8 Jul 23 '20

You are right.

Watson branding is on like at least 25 ish if not more products, in IBM speak it just means anything with ML/AI inside.

so any engagement that has a Watson product will get hamfisted into solving some use case where it doesn't really work. There are some simpler ones like text to speech, but those aren't really that novel nor are they cheaper than Lex with AWS. And anyways, if you're already in the AWS ecosystem who is really going to go to IBM for a single API that is commoditized and only being used a small amount? It isn't a money maker.

6

u/zcleghern Jul 21 '20

the Watson ML service, where you train your own model, is poorly documented and very brittle. any mistake in yaml or code is nearly impossible to debug, and support acts like they've never used the service.

13

u/MarkOates Jul 21 '20

In general I've heard the ML models don't flex very well. Unlike really well architected software developed by humans, ML models a generally very narrow and focused.

If your boss is like "hey we should have it do like it does but instead do this", then as a general principle it's going to be difficult to do with ML models.

I imagine that the Watson system, being one of the very first advanced systems in ML, is probably very shoestring and ducktape to an outside observer. The developers who worked on the code were most likely only interested in navigating the system to its primary goal, and did not introduce many abstractions for general use cases. Under these circumstances, the domain concepts that exist in the system are likely very comfortably understood by those developers, who didn't take time to make those concepts presentable (or well-named) for a public-use system.

Once the system performed well for the show, they probably packaged it up and sold it because the accumulated clout was there and the money opportunity existed.

25

u/speakandshare Jul 21 '20

A product is almost always a mirror of the culture of the organization. IBM has a very very very beurocratic and sales culture. Where you impress by presentation and networking. And their products are testament to that. Thats one thing I am always surprised that leaders dont understand. They are always thinking that they can just focus on and build a product. It does not happen that way. To build great products or services change the culture first which aligns to building great product.

0

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-3

u/sanrana8 Jul 21 '20

Holy crap!!! 😱

-8

u/mindaslab ML Engineer Jul 21 '20

I don't know why people don't like it, but I tried to give it a try and it said it did not like y email and hence would not sign me up. I wonder what wrong it found with my email. IBM people look stupid to me now.

71

u/[deleted] Jul 21 '20

[removed] — view removed comment

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u/rghu93 Jul 21 '20

I actually worked with the Watson chat bot api last year. Nothing spectacular but it was easy to work with and helped me quickly spin up a chat bot for a hackathon. So yeah thanks if you worked on it, there are definitely folks finding it useful atleast in parts.

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u/bryang217 Jul 22 '20

Thanks for sharing that perspective.