IBM’s Watson Health is sold off in parts

This strategy makes sense if you consider that even in it's heyday Watson was 95% data science consulting firm and 5% actual valuable technology.

I really think Watson is one of the biggest tech marketing bamboozles of the 21st century. Through Jeopardy they really had a segment of the business world and the general public convinced that they had cracked AI, but behind the scenes it was all one-off custom solutions under one trademark.

What the fuck is this? A name/email for your company when trying something out is so that you can keep track of any support requests we need, not for you to sell shit to me.

Once I provided them with my e-mail, I started receiving "You must take us to your leader" messages in a tone as if I was their employee and they were commanding me to take them to my CEO. I can't imagine myself chasing the CEO in the building because some sales people in Oracle told me to do so :)

To be fair, after being in meetings with theirs sales engineers(who wore the best shirts I've ever seen) a few times I grew to respect their stubbornness and the way they structured their corporate machine. It's a valuable lesson to have an exposure to corporate dealings I believe, before that I used to do freelance stuff and had no idea how a simple webpage can cost millions and why a large corporation won't buy that easily from a small company with similar or better product at the fraction of the cost.

This sounds like the biggest power move you could ever pull.

Years ago my client wanted me to checkout out IBM mobile app builder - Worklight, The pricing wasn't available on website and so I had to contact them. Soon I was reached out by their sales department and before I could get any details on the pricing I was speaking with VP of sales.

If I remember it correctly, It was priced ~>150K USD and even after repeatedly telling the VP that I was just exploring what their product was, The VP told me he was ready to fly in to my office the same week to 'talk further'. It was weird to end that conversation with them and my client had a good laugh when I shared the experience.

I don't get why IBM finds it hard to deal with Startups, All other behemoths (MS/Amazon/Google etc.) have successfully created products for Startups often by offering generous freebies and 'Pay as you go' plans . Where as IBM still thinks they can slap Fortune 500 pricing on entry-level startups.

I guess as long as those Fortune 500 companies & even Govt. fall for that Watson type products, They don't have a reason to change.

I loved Chef Watson, am sad that it's gone, and would pay a small amount for renewed access.

It wasn't "smart", and its recommendations needed to be tempered with human understanding, but I wound up with some great recipes that I wouldn't have thought of otherwise.

I think the best was goat milk mac & cheese with radishes and red miso.

The funniest was when it told me to remove the connective tissue from tofu.

One of my favorite past-times is talking with loyal IBM employees and seeing if they can tell me what Watson is, does, or how to use it. Ginni is laughing all the way to the bank at this point so I guess the joke's on us.

There is way more real world usage of the distributed systems concepts and skills you'd learn there (especially in large tech companies) than any other flavor of the month. While ML is also commonly used in the industry, the signal:noise is really bad, because a lot of its uses are superfluous buzzword-driven development. However, many many companies rely on distributed systems to be able to operate at scale.

Joining the hypetrain is a great way to get a bigger budget to play with.

AI chatbots are all about saving money and hiding the real customer service as much as possible, it's not about creating a nice experience.

+ People care about what other people are talking about. They like to fit in, like they're part of the cutting-edge.

+ Less experienced people have less…experience with the downsides of what they're reading about.

+ CS is no longer mostly people who care about computer science, in the same way that economics isn't only for people who want the understand economics. Tech salaries — especially engineers' — are super high, like investment bankers. So people study the respective fields as a means to an end.

+ Twitter is driven by VCs, tech press, and people marketing themselves. They're work themselves into circular frenzies all the time. Little of it matters. Almost none of them have any record of predicting what's next and a long, long record of being wrong. This is true of most people! But these are the spaces many people look to to see what is "wanted".

You seem to have good instincts. Don't be distracted by peers who work at "hot" startups or big named companies. Find something you believe should actually exist in the world and work on that. It will give you an intrinsic reward that money can't buy and status can't fill.

First, I think you're getting the wrong lesson from this. The key takeaway is stay to away from IBM. Almost everyone in the field has known that Watson is a bunch of marketing hype since day one. It's no surprise that Watson Health didn't work out. That doesn't mean that everything is overhyped, and it's important to develop a good sense for what is and what isn't when deciding where to work.

Second, every technology looks stupid when it's new. Airplanes, computers, the Internet, mobile phones -- they all had drawbacks that made them vastly inferior to the alternatives for most tasks for the first years/decades of their existence. It takes a lot of iteration and improvement to make something that's useful for everyone. Chatbots will probably get there some day - but it will take some big improvements in NLP. Perhaps this is the time to be working on them since we have a good idea of what we'd like them to do, and we just need to solve the challenges to get there.

Finally, realize that you're not the typical user. I doubt if very many people take the time to go through the menus like you did.

Just find problems to solve that are interesting to you, hype is irrelevant in finding a worthwhile thing to do (i.e. that a thing is hyped does not make it worse than something else - it does not make it better, either, though).

ML and AI is used in an absurd number of places both small and large. Most aren't ones that make news stories because they just optimize an existing experience. Sometime too much but that's more of a fault of capitalism and definitely improves the profits of the parent company. Search engines including ones on websites (ie: media, ecommerce, etc.) are powered by ML at any larger company. Recommendations systems are powered by ML and exist on most media and ecommerce sites. Fraud detection of various sorts when it comes to payments and accounts. Even mundane things like internal processes within companies like predicting which columns in a data upload correspond to what.

That's because you're lucky. You have good enough sight and you can use your hands. Unfortunately, that's not the case for millions of people especially since our populations are aging more.

I once worked for a company an “AI” company that was business logic, with humans handling the hard cases. They screamed “AI! AI!”

They had a really really really good product. They’re quite successful and good at what they do. The customers are happy. They’re makings money.

So why bragging about non-existent AI?

That’s great but not representative of average customers at all.

On the cynical flipside though, you can't entirely keep "buzzwords" off your resume simply because recruiters will always squint and "find them" because there's money involved if they do. You are almost always going to get recruiters for whatever the day's buzzword is.

I have a Masters degree and Python experience, and to most AI/ML recruiters that looks like "possible AI/ML researcher". They aren't entirely wrong, I did study AI/ML in grad school. They aren't very right either, because I learned enough to be "dangerous" and came out of grad school a massive AI/ML cynic. (That the field is mostly just Sparkling Statistics and people in general are bad at statistics and easily wowed by Sparkling Statistics. That this isn't the first hype cycle in the field, and it isn't likely to be the last either; we've not really improved on the research of the AI boom in the 1960s/1970s nor the other big AI boom of the late 1980s. They had chat bots then, they had most of the algorithms figured out, including their weaknesses. This boom we've just massively increased Garbage In, Garbage Out to those algorithms and given ourselves enough blinders to pretend that everything is still under control. We haven't solved their weaknesses. We haven't actually made major conceptual leaps. We just have a lot more data and a lot more speed. Which is something the 1960s researchers both predicted and warned us about.)

So yeah, your cynicism here is very valid, at least in my opinion. There's not a lot you can do about it, especially if your aim is to outright avoid recruiters chasing you for whatever VC money is getting thrown at them. I don't have a lot of other advice here other than the only thing you can really do with such cynicism is to apply it as best as you can to improving the things that you have the power to improve.

Ironically, the main project I work on today involves a lot of AI/ML and I'm known as a bit of a wet blanket on the team trying to temper expectations and trying to keep us from doing the worst mistakes ("confidence" values do not mean what people think they mean and showing them in any UI anywhere, especially under the name "confidence" is a massive mistake; machines don't have the "ego" for "confidence", it's a poorly applied statistical term of art that people use to badly anthropomorphize the statistical models). I don't win every battle and I do my best to make it clear I come from a point of pragmatism. It's a hard balance to keep.

My impression is that accompanying a patient is super important, it helps to understand illness, to have a plan in case of more complex treatments, etc.

Then my doctor has the ability to know me and gauge my health. She's also very good at probabilities and detecting when something really goes wrong.

I'm sure that being able to do that require a lot more than numbers.

(I'm studying data sciences, I trust them, but my guts tell me that diagnosis is in a whole different ballpark)

Those are both people problems. Tech can't solve many people problems, especially something as entrenched as healthcare. Isn't it huge, something like 10% of the US economy?

It is happening. They are called physician assistants and nurse practitioners, "supervised" by a doctor. I assume going forward, they will take more and more of the usual pink eye/ear infection/flu and other common work that does not require 6 to 8 years of post bachelor education.

The private ones might the ones in the public system at least in my country need to see a patient every 10 minutes to keep their heads above water.

That sounds like a lot of professions, engineering management included :-)

I've been to private practices where every day at lunch or near end of day there would be some drug rep with food for all the staff.

And a psychiatrist that had stacks of free samples of drugs.

Even contact lenses are marketed with free samples.

Right, but there would be a lot of point in making deals with whoever builds Watson-like devices, to turn them ever-so-slightly more likely to prescribe one drug over another or make one diagnosis over another. It might even be cheaper than hiring and sending out a bunch of salespeople.

If we want to reduce costs, we need to move to lower level providers like a LPN or CRNP. Most people coming into a GP have the flu or an ear infection or .... and that can be handled by them. There will be one MD and to handle complicated cases and to supervise. We've already switched so that intake is done by CNA making $15/hour. In the US at least working at FAANG pays far more than being a GP.

Perhaps this indicates a major gap in your visibility into and understanding of modern medical practice?

> My mom worked for a GP for about 20 years, and it seemed to me that most of what made that guy a doctor was bedside manner + being able to remember a lot of things.

"being able to remember a lot of things" -- Yes, absolutely. This is an area where AI-assisted decision support (like Watson) could be, and I hope will be, extremely valuable.

OTOH, you also rightly recognize bedside manner -- as anyone who has been a patient or a patient's family caregiver will attest, this is an essential component of core, and I think likely also the healing process. We won't get this from a machine until there is a true general purpose AI, at which point I expect an AI singularity anyway.

But consider that there are other factors of the practice of general medicine that you haven't even touched upon. For example, liability: In the office you envision, where Watson/AI makes medical decisions and these are executed by other roles like nursing, where does ultimate responsibility (and legal liability) lie? Remember that Watson outputs probabilities -- suppose the following:

Chance of disease X: 89% Chance of disease Y: 10% Chance of disease Z: 1%

If disease X, intervention A has an 80% probability of success. However, if disease Y, intervention A has an 80% probability of harm.

(before you object that this is contrived, this represents a realistic situation I encountered recently, where intervention A is high dose steroids)

Now, will we put the onus on the patient to select an intervention? I don't think that would be very popular. While I certainly do not advocate paternalism, when faced with difficult decisions quite many people openly defer to their physician.

> But GPs often make astounding amounts of money

I suppose this could be true for some definitions of "astounding," but it's generally accepted that GP/"primary care physician" pay is essentially the lowest of all specialties , which is a major contributor to lack of access to primary care in industrialized countries (while you'll not have a hard time finding a private pay dermatologist, for instance)

ANd on top of this, we are posting on HN where a mid level software engineer total comp can EASILY outpace the average US primary care physician salary.

> while leaning heavily on their staff to actually handle patients and keep the business running.

Do not all professionals and business executives rely on highly trained staff as force multipliers? This is a fundamental principle of the advancement of human economies. It is grossly inefficient to operate with individuals as "jack of all trades" when they can instead each become specialized to support a bigger or broader goal.

By "leaning heavily on their staff to actually handle patients and keep the business running" are you suggesting that the primary care physician should be performing check-in, insurance verification, rooming, vitals measurement, blood draw, medication administration etc? That is a certain recipe for massively decreased throughput and shortages/decreased access to primary care.

> I thought it could help drugs get a little cheaper too, because there wouldn't be any point in the pharma companies sending out salespeople to do lunch seminars to convince the GPs to prescribe this or that drug (this still happens).

This has been massively curtailed for 20+ years, at least in the US. I am not sure about other countries. But overall I think this is a seriously minor portion of the (exorbitant) price of medications in industrialized countries.

In any case, I doubt it would make much of an impact on utilization in most contexts, as insurance/health plans/prescription benefits have already implemented fairly strict guidelines-based formularies and coverage tiers (again, at least in the US -- I can't speak to other industrialized countries, although I expect they are similar or even more strict)

(edit: another poster points out all the direct to consumder drug advertising -- I agree - this probably has a much bigger influence in 2022; ad budgets are absolutely insance)

> Maybe this will still happen, but it doesn't seem imminent anymore.

Here we agree. I am certain we'll see AI-assisted physician decision support, but (a) the physician won't go away and (b) I think it'll be an unfortunately long ways in the future.

I’ve seen this in Japan (ish), but in the Netherlands it’s definitely the GP’s doing most of the job. The assistant just does bookings and waves me in when it’s my turn.

Come up with a way for better patient outcomes to result in higher profits and you'll see advances in patient care real damn fast.

Sure, that, and recognizing patterns and adjusting medication and being able to use good judgement for when to escalate to a referral for a specialist. But that's a lot!

I actually go to a teaching hospital for my primary care. It means I get seen by residents, and almost always also by very experienced teaching doctors. It ends up meaning that I get more time and attention by people who are actively learning and trying hard to do the right thing. The trade-off is there's no long-term trust relationship, but I am OK with that. I've also experienced care from elderly family doctors who run a "one-man-band" with a nurse and a receptionist, they're nice but I think I get better care at a teaching hospital.

That’s exactly right, but there’s nothing wrong with that.

A good doctor’s memory of patients spanning decades of a career and all of the various treatments that they did or did not respond to is very valuable. It’s a good thing that they offload as much as possible to other people so they can focus on doing what they do best.

Listen up Accenture, I will drink expensive champagne when you go bust, or get bought.

Watson Health seems to have been focused on selling the narrative of AI in healthcare, even though the technology wasn’t there.

The divestiture is only for IP also, and it seems most people in the group will be laid off.

I think somebody thought if they "humanized" AI by making it seem like it was a character, it would make AI seem all that much more closer to the dream.

On the face of it, not a horrible idea, but applied to what was essentially a bunch of separate algorithms.. pretty misleading, but that's just an opinion.

Sounds like another health care company where the exec just got convicted.

Was it the orange ties?

Medical diagnosis is a trivial problem for machine learning to beat humans. Humans are terrible at this.

The problem is there is not even the concept of high frequency medical data. Imagine machine learning in quant stock trading with samples once a year. Of course it isn't going to work.

The problem is all in the externalities. Doctors don't want AI. They can see the automation path and their bank account change down the line quite clearly. Not to mention most doctors don't know anything about data science so how can you have any faith in the algorithm prediction? No one wants to be the test case and then get a law suit. "I was just following what the computer said was correct". Wrong answer, pay up.

The real irony to me is in a 100 years people look at the current medical system as complete quakery. Literally have everything right now to build medical super intelligence but stuck with the human doctors doing the exact same things from 50 years ago.

Guessing "what are trousers" for king of Egypt isn't in itself an indicator the whole Watson system is flawed. Although you're right: it's an indicator the intelligence is non human-like.

Just like, from Watson's perspective, a human named John making hilariously bad guesses related to coin flips isn't in itself an indicator that John isn't intelligent either.

Just that there are some categories of knowledge or application of that knowledge that some systems are bad at handling.

"The plane lands safely 99% of the time" is an impressive demonstration and a completely worthless product, but if that's all you have then what can you do other than launch it?

https://en.wikipedia.org/wiki/AI_winter

This was supposed to be solved by rule-based/expert systems in the 1980s AI bubble.

The whole rest of the universe needs software too. Most companies are grossly incompetent to develop it themselves. Most are things that SWEs of the type which visit HN would never, ever want to work on. IBM does that adequately well. That's "services."

If I need a tool built which will manage workflow at a management consulting firm, a custom tool for managing cases at a law firm, or some custom supply chain kludge -- the 99% of other "boring" software -- and I happen to know nothing about technology, who do I turn to?

IBM isn't a bad choice. It's a major step up from Indian firms in terms of both price and quality. It has significant in-house technology to leverage. It's a safe choice. It will usually do better than in-house IT.

I recently evaluated the business of a company which builds ships. They developed software in-house with an IT staff who weren't qualified to tie their own shoelaces. They had huge military contracts. They didn't subcontract to IBM, but it wouldn't have been a bad choice.

They had apparently been doing some "cleanup" and somehow our site number got on to a list. All our servers, attached volumes, subnets, load-balancers were deleted.

My boss and I spent the next 30 hours applying terraform and rebuilding anything not automated.

Would not recommend IBM Cloud. We are moving off in next 6 months.

Marketing aside. Lets not forget how cool that was. It was a great public demonstation that AI / ML is possible now.

https://www.ibm.com/investor/att/pdf/IBM-2Q-Earnings-Press-R...

But when I left to go back to school "global services" a business to business consulting division was the big up and coming division. It seems that division is where IBM decided to go. Honestly they'll just sell to some big businesses so likely you'll never hear about what they're doing.

I'll agree they seem to have lost their way. Its a shame really. They did some good things: I remember a lot of the engineers there would travel to schools and promote engineering careers.

They still do stuff but it's hard research and niche so business wise it won't make them short term success. You mention power but they also have a good hand in Quantum Computing.

They make money on those who have more than they know what to do with.

Case in point: I spent six months in a project, which at its peak had about forty people working on it. Eventually it was scrapped and replaced with a solution from IBM, which in turn ended up... not being used at all.

Overall it was a hilarious waste of everyone's time, but somehow that was okay.

I understand why you're saying this. I have no idea either. However, open their 10-K and you'll find out how they make money. In fact, while their revenue and profits are declining, they still make more than $70B in revenue a year with a profit of about $4-5B, so their ability to stay in business is higher than many tech companies that are not profitable.

Extremely reliable, and extremely good at what they do. They sure are expensive.

A lot more companies should adopt them.

Yet its going the way.

They run at scale at a lot of companies.

AS/400 / iSeries was awesome at least in the beginning.

I think it may be discontinued now.

Those machines were extremely reliable and well made.

Often companies who had bought one had no idea where it was. Someone had set it up for them 7 years ago and after that nobody paid attention.

Some places were better and did proper backups. Which means stuff the right tape of a rotation into the slot.

They would also call home to tell IBM of a proper that is developing and they would send a tech out to switch the parts prior to anyone using it had any problem.

(and that is when the machines were sometimes hard to find. One was buried in a closet, with tons of paper cases, paper archives. stack buttom up to the floor.

IBM is a sale driven organization. I.e. sale first - tech after. so it cannot be judged as an high tech company, I.e. on the tech.

A point of reference is SUN - which was tech first - sale after.

Another point of reference is HP. HP was tech first, but turned into sales first.

There's your answer.

I know they bought Red Hat but I didn't hear that they gutted it. Can you expand on that?

The kinds of places where HN devs would say your career goes to die, along with your soul.

They will do the stuff the internal teams at those companies pass on.

They probably could just run much of the business just on the licencing fees they get. If you think they are not doing anything you're likely not their target customer.

I don't think they do either, judging by my experience working there as an upper-level-support technician 15 years ago.

It seemed like the organization was book-ended with decent brains: engineers and front-line managers were decent to fantastic, and the upper-management seemed to be decent at the time. However, both ends seemed to be choking to death on a hundred layers of middle management. 7 years after Office Space was released and I actually had three(3) managers. Three! I had a technical manager with whom I had bi-weekly meetings where we talked about nothing, a non-technical manager with whom I had monthly meetings where we talked about nothing, and the head of my department who was the only one who meaningfully managed me in any way. (And he was absolutely fantastic.)

For example— they made some big announcements about their impending migration from windows to linux for everybody from admin assistants to sales to developers. Exciting! I loved that linux was getting more professional credibility, and my product ran on Solaris, so having a local UNIX environment would reduce some of the cognitive load for networking, scripting, etc. etc. There was no internal mandate to start the migration yet, but I was too eager to wait. I found the official image on the intranet and started writing documentation for my coworkers. It was pretty smooth! The complex GUI apps like the Lotus suite worked great! Well, as great as they did on windows, anyway. The installer was quite polished! I was excited!

I had one more thing to install— the ancient, internal defect and ticket tracking clients used by every technical worker, product designer, all of their managers, etc. Neither the intranet page for the clients nor the Linux image docs had any info. Hours later, I found a months-old internal note EoLing the Linux port, directing people to use the obtuse CLI instead. No problem— we're all technical people here, right? Problem. The API used by the GUI client supported necessary functionality the CLI didn't. That alone rendered the Linux initiative dead-in-the-water for most technical workers who'd benefit most.

I'm sure the manager who canned the Linux client was solving a very real problem, but a) a decision directly affecting company-wide strategy getting lost in the ether, and b) nobody checking to see if these big overtures were even basically feasible, embodies their organizational shortcomings. (I might have gotten some of the details wrong— it was a long time ago— but you get the gist.)

That's almost certainly why they're getting sued for purportedly blatant age discrimination, too. Managers in the middle with too much sway to have that little top-level visibility solving their problems using means that end up screwing lots of people.

That they style themselves as a technology-focused business consulting company rather than just a tech company is pretty rich.

Thinkpads were a great example of this. Laptops which promised decent quality and support for a high price. When the laptop market was demystified and commodified, IBM correctly got out of it - for a decent price.

If some random start-up, or even Google, had built Watson, it would have correctly been seen as a gimmick. Instead it sold literally billions of software consulting to people who thought they needed AI but actually just needed a search box with dynamic autosuggestion. Would you rather get some junior guy to hack something together using open source tools, or would you rather pay IBM 50 times as much? If you chose the former, you're simply not in the target market.

The hybrid cloud is exactly the same game - as is made quite clear in that ad, it's pitched at middle management who don't want to look like chumps for ignoring the cloud, but don't want to fuck up by moving to it.

Reputation is a difficult asset to monetize - effectively you make money from it by degrading and then destroying it. After all, if you carry living up to your good reputation, you're not extracting any advantage from it. IBM can't sell their reputation or their name to the highest bidder. All they can do is keep trawling for business lines where it gives them a comparative advantage.

It's easy to see this as unscrupulous - but their customers genuinely do get a benefit from the confidence they have in IBM.

https://www.protocol.com/enterprise/ibm-lost-public-cloud

Source: I was part of "GC" in that article.

[0]: [Why Cities Keep on Growing, Corporations Always Die, and Life Gets Faster] https://www.youtube.com/watch?v=jOnWowd-7HQ

Intimately knowing the non-profit side of the healthcare system as well as the construction and operation of data science systems, I wholeheartedly disagree with your assertion and your conclusion as being a general takeaway.

I could see them making a comeback with crypto but not the way we think about it today. Instead, inter-enterprise operations infrastructure.