It's interesting to talk about what "IBM" has been doing, because after all the A&M IBM has done this last decade, they've actually got plenty of "activity" to their name. Just, activity that was previously known under the names of Softlayer, Cognos, Redhat...
IBM itself is just a consulting "solution provider" company that provides "solutions" in terms of the products and services of its subsidiaries. They're never going to look like they're on the cutting edge of some space, unless that's what one of their (equally-stodgy) enterprise clients wants to pay them to do. (And even then, why build when you can buy? IMHO IBM would only ever build a new technology at this point if there was no existing company out there in the market, with that tech IP, that they could just acquire.)
Certainly, there's the Watson AI lab, though I don't think anyone's expecting much of it at this point; nor, importantly, was anyone inside IBM ever expecting much of it. Watson (the lab specifically, not the brand strategy of calling all their cloud OLAP SaaS products "Watson") is more a nod to their clients to say "of course we're looking into AI", and a pool of people competent enough that they could clone the existing ML approach of one of their competitors if one of their clients demanded it.
IBM could be a really innovative company if they rearranged their talent pool, certainly. But innovation—getting ahead of the market and so needing to educate the market on the problem their products solve—hasn't been IBM's business model since the 1950s. IBM makes money by listening to clients' "unique" needs, and then meeting them with "custom" solutions at low CapEx cost, by using an ever-larger flywheel of existing solutions pre-tuned to almost fit every possible business use-case.
I suppose its worth noting that IBM folks received a record 9,262 U.S. patents in 2019 - the most patents ever awarded to a U.S. company and the 27th consecutive year of it grabbing the no.1 patent spot.
No idea how valuable or inovative any of these patents are, but I think its important to note when discussing: "They're never going to look like they're on the cutting edge of some space"
Appearing on the cutting edge to enterprise clients is important to IBM. That doesn't mean they are on the cutting edge (they might or might not be). IBM's large pool of patents is something they can advertise to clients. Most companies don't see their patents as valuable, and thus don't patent as much stuff.
I've worked with former IBM people - all (or some it seems) of them have a plaque of whatever their first patent was. When they talk about it they admit it was a trivial invention that is too specific to be of much use outside the one project (thus there is no value in keeping it from competitors). IBM encourages patenting everything and has people looking for things to patent. Most other companies only patent things that are unique and worth the costs. (keeping from competitors, licensing to competitors, or keeping competitors from patenting it and stopping your use)
I worked at IBM Research (Yorktown Hieghts, Last century, assisting infrastructure for research).
They spent 6 Billion Dollars on research that year (late 90s)
But Its true, IBM Values patents quite heavily. You can see some of them they printed as wall paper in the lobby (Along with mechanical calculators and models of some of daVinci's machines.)
But they also have "Trade Secrets" which are things they think they're competitors won't figure out and if you don't patent it you aren't telling the world how its done. I think some of the chip chemicals and processes for working with silicon wafers were to be classified as such.
They seemed always to be pushing the researchers to make something they could sell..
As an aside, IBM Yorktown is an oddly round building..
A few years ago, one of my buddies got a research scientist job at IBM T. J. Watson Research Center at Yorktown Heights and I got a friend&family pass visiting their building there - inside it's amazing, considering this was built in 1950s. I remember there was a long hallway with invention exhibits, some of the most iconic inventions in computer hardware, ICs, CPUs were on display. Pretty amazing.
The arc-shape building reminded me Apple Park in Cupertino, except TJ Watson center was built decades earlier.
I did enjoy the building. Rather a lot of interesting stuff was thought up there and it was humbling.
I like that the hallway was on the outside and hallways radiated out (and everyone had offices with frosted glass). It was a pain running pipes though as standard bend didn't quite work for that radius.
I'm really waiting for the day that software patents are finally struck down and we can stop this farce of pretending software patents are actually useful and valuable beyond being a cudgel in legal battles.
I just finished (a light) editing of an English (machine translated) version of a book for someone I have a lot of respect for who is a Japan-based mentor of mine - Hiroshi Maruyama had 26 years in IBM research, eventually as the director of IBM Tokyo Research Labs.
Some of the key points of the IP marketplace were
- fees for the licensee fee would be set upfront;
- the patentee would pay a % value to the government as a tax;
- if the patentee wanted to use the patent exclusively, a high licensing fee could be set, but that would also result in a higher tax being due to be paid.
The approach was to dis-incentivize bad actors putting monopolies on products via patents. It would also encourage higher utility value from patents under this system.
Another interesting concept Maruyama's book covered was LOT networks used to fight against Trolls.
- https://lotnet.com/
The idea with the Lot network was that if a patent did get rights to a patent from a member of the lot network, If any of the patents from members falls into the hands of a patent troll, all other members are automatically granted a free license of the patent.
The book covers themes on how to do research in corporate organizations (the audience focus remains with Japanese researchers/students) and has some interesting discussions.
I will provide a link to the book when it is available (if there is interest).
Maybe, it certainly sounds much better at a glance than the current system though there's tough stuff like how to set that value in such a way that independent inventors aren't forced to partner with a large company in order to use the patent system. I think some reforms like that combined with a much stricter definition of "patent-able" for some categories and/or better challenge mechanisms. Getting a bad patent thrown out due to prior art is still quite expensive and trying to evaluate if a patent is non-obvious is quite difficult to litigate.
Being a cudgel in legal battles is quite a lot of value though, that's basically the point and is how patents are meant to support and reward innovation.
There's a second part to the idea of patents though they protect innovations with the idea that once they expire other people can implement them and software patents fail abjectly at that second. There's no meat the the implementation, all modern software patents seem to boil down to connect a client to a server and display the results on an interface. There were some genuinely useful patents back in the 80s it looks like for stuff like MP3 encoding.
Also there should be some additional value to people not just companies for the government to be granting legal monopolies, and it should also be restricted to things that are actually implementable not extremely vague system level diagrams.
From what I understand, those sorts of vague software patents are far far harder to get today - in theory they never should have been granted. Unfortunately, mistakes were made, but in recent years the legal system is catching up to that, and hopefully as those older patents expire newer patents along those lines won't be granted
"On June 19, 2014 the United States Supreme Court ruled in Alice Corp. v. CLS Bank International that 'merely requiring generic computer implementation fails to transform [an] abstract idea into a patent-eligible invention'"
Software patents end up being so vague that basically every large company is violating some in some way. They don't get in legal battles with eachother often because the resulting legal decision will be somewhat random and risks huge retaliation in counter-suits.
It's not discontinuous - that's just the theory behind patents. Patents give inventors a legal "cudgel" as the commenter before put it, which makes innovation more profitable. Patents are just a legal construct, the idea is that having a patent on an invention gives you access to legal tools to protect a temporary monopoly which makes innovation more profitable, so you don't have to worry about investing money in innovation and then losing all of your profits because of copycats. However well that actually works and whether or not it ends up being a net positive for innovation is a different question, but all a patent is is a legal tool to stop others from using or making money off of your innovation, as enforced through lawsuits in the court system.
I'm not knocking them for their materials or process patents for some of their remaining R&D arms but the majority probably are software patents which I think are 95-99% unusable garbage outside of a legal fight. Generally software patents are too broad and don't contain enough implementation detail to actually use them once they do expire which is one of the important parts of the bargain for patent protection initially.
My guess is that these companies are a lot more aggressive internally about getting their employees to author patent submissions. They either actively screen code submissions and projects for patentable ideas, make patent authorship a condition of advancement, or otherwise tie authorship to performance reviews in a meaningful way.
Companies I've worked for have teams that facilitate employee patent submissions, and they will tell you why patenting is important to the company. They have had some kind of bonus structure so that you get rewarded if you submit a successful patent. But they pay well enough otherwise that, unless you're personally motivated to see your name attached to patents, it's just not worth the effort.
To put this another way: the patents you author as an employee of a company are probably not that valuable to you. But, because of the potential legal protections they offer, they are very valuable to your employer. I think the companies that are more successful in having high patent counts are doing more to align employee interest with corporate interest w/r/t patents.
There is a continuum. IBM patents everything. The other companies find patents less useful (for whatever reason) and so they are more careful about what they will spend money patenting. I've made several "inventions" that I'm sure any of the companies on your list would have patented, but since I don't work for them I don't have any patents.
As an ex-IBMer, I can tell you they really incentivize patents. IIRC, you get $1000+ on your first patent and pretty decent money on subsequent patents. Many employees form 4-5 person teams where each member basically work on their own patent but their name is listed on all patent applications submitted by their team. This way even if 4 out of 5 patents are rejected, team still has 1 approved patent and everyone in team wins some money.
If you listen to Lin Sun interview on Google's Kubernetes Podcast you hear that she have the title Master Inventor. Since she is interviewed under the title of Istio I was sure she invented some interesting techincal stuff in that field. You don't have to wait too long for (at least what I find as) the disappointing explanation of what does the title mean, why it exists and what the results are.
In short, there's incentive as well as assistance in filling up patents, they don't seem to discriminate on basis of usability, feasibility or anything else. They do give bigger bonuses for patents that are in one of the fields considered strategic for the company.
Listening to it was somewhere between amusing to depressing:
The CPUs that handle 86% of all credit card transactions for example (in the various mainframes IBM builds). Pretty nice modern architecture still capable of executing 60 year old code.
You might buy a POWER machine from a boutique manufacturer other than IBM but there were other major players such as Motorola, Apple, then later Nintendo: Nintendo adopted with the GameCube, then Wii, but IBM made custom chips for the XBox360 and the PS3, Nintendo still uses POWER in the Wii U.
I don't know why people overlook the progress IBM seems to have made in the quantum computing world. Perhaps not as impressive as Google's progress but impressive none the less.
For me personally, it was because even from the inside at IBM, you wouldn't hear much about what the quantum folks are doing if you were doing general tech. They really are in their own little world. I don't think they were even in the whole-IBM Slack team, though they might just have been security-compartmentalized with ACLs.
Was Watson just smoke and mirrors? Have there been other systems in the NLP space that eclipsed it? Genuinely asking because I don't know much background behind the story of Watson's rise and fall.
Watson didn't rise or fall, it was the centerpiece in IBM's marketing campaign, which worked for a while before they moved on. It never got beyond or matched the state of the art in anything, that wasn't the point, it got the name "Watson" on TV.
IBM wanted to prove that they employed smart people, so they hired some smart people and had them write a computer program to play Jeopardy. Did it matter that it had nothing to do with anything they were selling? Perhaps only IBM has those figures.
OK fine but there was _some_ non trivial technology behind the system that won the Jeopardy game. What I'm asking is whether what seemed like the state of the art NLP system at the time got eclipsed by newer and better systems or whether the whole thing was never really a state of the art NLP system to begin with.
The problem with Watson is that they don't have a business case. IBM sent salespeople to big customers with big problems and tried to find things to fix. In some cases, they did. But most of the time, the insurance companies, government agencies, etc they do business with scratched their heads and didn't do anything. Learning new things about their data might be seen as a threat to whatever enterprise bullshit they do!
The problem is you have companies like Google, Microsoft, Amazon, Apple, Facebook, etc have problems that this tech solves. It's easier to come up with a product with a problem that you understand. I can ask Google Photos or Siri to show me pictures of my dog in the snow in 2015, and they do. So I give Google & Apple money to store my crap. Google and Facebook use AI with all of the data they hoover up to peddle products to me. My grandparents get ads for depends, I get ads for drones, Google and Facebook make $.
Now, companies like Amazon, Microsoft and Google can go to companies that were prospected by IBM with solutions. Microsoft is minting money with ATP, because enterprise security teams suck. Amazon is selling creepy facial recognition to people, because people see it on TV, have a Ring doorbell, and want the capability. Google is selling GIS solutions, etc based on work done on maps.
> Learning new things about their data might be seen as a threat to whatever enterprise bullshit they do!
No, the problem was that Watson would be unable to help you learn anything new about enterprise data. IBM didn't even have a plausible, non-trivial proof of concept to trot out six years ago.
State of the art NLP system isn't a very meaningful term. You can't really say that Watson was "better" than Google's NLP systems at the time because they were solving different problems.
In general, what they did was not trivial, but it also wasn't revolutionary. Some of it was novel, but novel in the sense that it applied specifically to the problem they were trying to solve. It had little impact on the technology behind what IBM eventually tried to sell as Watson.
Anybody with a bucket of money could have built the same thing at the time. The impressive part was IBM figuring out that it would be worth spending a bucket of money on.
I think it was fantastic, modern NLP could do much more (if put together with the cleverness of the Watson pipeline) and it's a pot of gold if IBM ever stop trying to apply it in healthcare and apply their brains to how it could work in customer service (for example).
Note : I am aware that there are "Watson" products that claim to be this - but they aren't because they are MBA's ideas of what the best route to selling crap to the unwary. If IBM had appointed someone with a clue and given them 10x the R&D budget for the gameshow to deliver a decent product I reckon they'd have got (at least) 100x. But... oh no.. promise 30x for 1x and get f-all.x^2
Cliches aside, I think you are right about the poor decisionmaking: IBM decided to chase the biggest, most bureaucratic market, healthcare, rather than pick a market that would actually be somewhat receptive to black-box services.
Watson (the Jeopardy playing machine) really was an amazing demo for it's time (2010) and before the rise of neural networks in NLP it was one of the best demonstrations of a semi-practical system.
The "This is Watson" special edition journal[1] taught me more about traditional NLP pipelines than just about anything I've read before or since.
It was an amazing demo, as far as marketing was concerned. Now whether the technology behind it was as revolutionary as they made it sound, that's probably more controversial.
It was certainly a stye in the eye for Google (“organize the world's information and make it universally accessible and useful”), whether facbricated by marketing/advertising or not.
But it wasn't really putting itself out there as a Google competitor. IBM wasn't saying, "buy this to make a better search engine", so I never once drew the Watson vs Google comparison when it all went down in 2011. Watson seemed to want to market itself as tech to drive expert systems instead (though it never really panned out) and now 9 years later, Google Assistant can answer questions of astou ding complexity, so whatever research Google was embarking on in 2011 has since born much more fruit anyway.
That's somewhat narrowly defined considering they're really the only remaining producer of mainframes. I'm not sure if that's literally true but it may as well be.
There are some things that mainframes are legitimately better at, and some things that POWER is better at than x86, and so on. AMD and Intel benefit from incredible economies of scale that IBM could never dream of, and that's mostly where IBM loses -- the price is a lot higher and the volume a lot lower on the IBM side.
I wonder if we'll see IBM get into video games before too long. Or buying a lesser known streaming company like Mixer? It would seem like an odd fit, but it wouldn't be too surprising.
...and it's been integrated into a couple of MS games, too. Forza Horizons 4 has Mixer integrations, and even gives you a bonus experience multiplier for streaming or something like that.
edit: sorry. I misunderstood you. Some projects are delivered with subcontractors, of course. But I can tell you from inside that we still have a healthy GBS, GTS and Cloud Services, delivering projects.
IBM should not rebrand bad products as Red Hat (redwashing? hatwashing?). Maybe Red Hat could come up with a better public cloud than IBM but that would be a long-term project.
It doesn't seem to be very successful, which is understandable since Red Hat is historically an on-premise software company, and a very successful one too. Internally they probably view Online as a sales enablement tool.
Since Openshift is already Red Hat's big bet to keep growing, presumably if they were willing and able to make OpenShift Online a major success, they would have done it by now.
I'm really surprised IBM doesn't offer a cloud product based on LinuxONE machines. These are ridiculously fast machines that are probably cheaper to build and run that the equivalent capacity in OCP x86 "boxes". And only IBM can have them.
I can tell you it feels very fast. The 5 GHz cores and the L4 cache, combined with the offloaded IO make it compare very favorably to similarly sized (and priced) x86 and POWER machines.
It's pretty interesting to look at some of the quotes from that article now:
- "As IBM enters its second century in good health, far younger IT giants, such as Cisco Systems, Intel, Microsoft and Nokia, are grappling with market shifts that threaten to make them much less relevant."
- "By 2015 the firm wants its earnings per share almost to double, to “at least” $20." (It was actually $11, and kept falling from there)
- "given the complexity of the world and how much of it is still to be digitised, IBM's human platform looks unlikely to reach its limits soon. Perhaps not for another 100 years."
I was curious a out some of their early sort-of cloud offerings around 2013/2014, partly under the Watson brand. They had some interesting services for text analysis similar to services like AlchemyAPI (which IBM actually purchased not much later) that I wanted to check out. But they were also starting to try and offer more general purpose cloud services, albeit it beta forms, and I poked around a bit.
My recollection is that nearly all of them were attempts to back-door users into their
traditional enterprise software, not to actually offer true cloud platforms.
For example I remember an "analytics" offering that promised on demand instant analytics environments for exploring data and generating insights. I was interested! In reality, it was a thinly veiled portal into a hosted cognos environment. And if you're not familiar with cognos, let me tell you, while still entrenched in some Enterprise environments, it is an object case study in crufty klunky product design that has accreted disparate layers of functionality over decades. The Advent of Cognos 8 in 2005 simply smashed together a bunch of prior products like report net, power play,metric manager, and others that worked together poorly, if at all. I won't bore you further with the details except to say this, along with similar non-strategic product design by Business Objects, is why products like Tableau grew so fast in popularity.
So, yeah, as the cloud hit its stride in the 2012-2015 era, IBM was just trying to slap "cloud" labels on something they could use to sell the same old stagnant products.
IBM is trapped by their very wealthy legacy customers [banks, insurance companies, governments and a few fortune 100 stores]. IBM certainly has the talent to create new products, but unless they appeal to those customers, the effort is pointless. The existing customers are so wealthy that it's not worth the effort of the IBM sales machine to target anyone else.
When IBM buys a company, it's not to get new customers. It's only to get products that their legacy customers have been buying from someone else.
To be fair, it is quite OK for them to do just that. To cater exclusively to large businesses that require multi decade support and who demand specialized features. The reason those wealthy clients are still with IBM is precisely because they can trust IBM (it’s possibly the only tech company they do trust).
IBM marketing is all smoke and mirrors to convince everyone that they’re cutting edge in areas they’re not. They don’t need to be; their important customers are fine. The customers just want to feel like they’re working with an “innovative” company, and that feeling is delivered by IBM marketing and M&A.
>The customers just want to feel like they’re working with an “innovative” company
Actually this fully explains their foray into "blockchain". It's the hottest thing to happen to banking since the web, even though it may be pointless.
As someone who's built "production" software on top of IBM's "private blockchain" tech... it isn't quite pointless, but it's not far off; though that was a few years ago at this point lol
> And the big bet on a ridiculously over-hyped Watson could make sense if you saw incomplete and underperfoming products as merely the top of a consulting sales funnel
I worked on Watson Assistant for a few years and it’s not a bad product at all compared to the competitors but, sadly, I have to agree with the above assessment. It was completely overhyped.
Yes. Chatbots (or "Virtual Assistants") for handling routine customer care inquiries. IBM Watson Assistant is the leader in this increasingly crowded (Microsoft, Google, Amazon, and dozens of startups are competing with them) space. The tech-savvy may look down at the current state of "AI chatbots" but large enterprises in all industries currently spend a fortune on staffing call centers that predominantly handle questions like "I forgot my password can you reset it?", "I lost my bill, can you send me another copy?", and "I'd like to sign up/cancel/modify a service". Chatbots work well enough to handle 30-40% of these types of inquiries at a far lower cost than a human (who is mainly just reading a script anyway).
All of those 30-40% problems you cite are actually arguements for spending a bit on improved FAQ's, website processes and IVR's. Businesses are likely to react to a successful pitch for a solution in that space with a bit of cash to do it tactically. For chatbots to become a thing they will have to jointly solve problems with customers, and they can't just now...
Agree that more should be spent on better FAQs and better self-service search. But IVRs? No, just no. Most people start pounding the zero button and screaming "Agent" as soon as the IVR picks up, and if it doesn't immediately transfer them to a live agent they just hang up. It's a horrible customer experience.
There is, but it's also served by a saturated market full of startups that are far more innovative than IBM. And much more inexpensive.
My experience of IBM's software products is that they are slightly above average, comprehensively documented, but completely out of touch with market pricing. I wouldn't say they are affordable even for fairly large enterprises -- the bang for buck is extremely poor.
IBM is the choice for large, price-insensitive, risk-averse companies and bureaucracies. You can almost always do better than IBM.
I have a dumb idea. IBM should release an Echo/Alexa competitor with Watson branding. It should be brightly colored, made of metal with large-print buttons and be preprogrammed with older, male voice. Then they market it as home automation for Boomers.
Alpha looked so promising on release, but every time I've checked in on it, it just seemed like there was some tinkering around the edges and absolutely nothing fundamentally new or groundbreaking since its inception.
Since someone else addressed call centers, there's a million managers in blue collar fields that would kill for some software that can take in all their purchases and work orders (and those of everyone else who bought the software) and spit out insights like "don't piss your money away on the expensive grease Reddit told you to use, machines running the cheap stuff don't seem to cost anymore to operate". These are the kinds of things they could find out themselves if they wanted but can't justify spending the man hours.
Not really until language understanding improves substantially. All of the chatbot kits that I’m familiar with discard the bulk of the information in the user’s first utterance.
How could a revenue curve move in any other direction than to the right? A revenue curve that loops back on itself and starts moving to the left, back in time?
You can move back in time using this device we call "memory". Up and to the left - value grows as you consider earlier values. Up and to the right - value grows as you consider newer values. Yes considering newer values after older ones is a reasonable default but it's not completely redundant to specify that's what's meant.
If that's it, you just answered my (same as GP's) permanent confusion for people describing the "hockey stick" chart as "up and to the right". Why not just "up"?? Thanks for that!
The phrase "up and to the right" is common in business discussions to indicate "good metrics." It's a play on that, which similarly has "to the right" superfluously in your opinion.
"Up and to the right" is a relatively common business saying to indicate things are going well and that the chart for a metric (ex: revenue, users, etc) is going "up and to the right". The author made a play on this common business phrase by saying IBM's charts are going "down and to the right"
You are correct, it's redundant. Down and to the right sounds like the sort of thing a sell side analyst or salesperson would say. It could be that you are assuming your audience are unfamiliar with stock graphs, but more likely you are using redundancy for rhetorical effect.
In another section the author describes the performance of IBM against a benchmark as 18,736 basis points, which he calculates by taking the arithmetic difference of a positive return and a negative return (ugh). This just means underperformance of 187.36%. I suspect though once again the use of a 5 digit basis points figure is a rhetorical flourish.
These are just rhetorical nits though. I did enjoy the article, and the numbers and their sources are very clear.
I've heard this term for 20+ years and never questioned it until just now. I think the "to the right" part is meant to convey that profits going up is not just a one time thing, but something that has, or will be happening continually over a period of time.
Well, conceivably, if the total value were to drop to 0 in a very short amount of time, it would be simply “down” (and the inverse, for the far more unlikely event that it increased a few orders of magnitude all at once and then flatlined, appearing to simply go “up”).
Paying an infrastructure provider and a managed k8s / other "cloud" API vendor separately is actually very reasonable. There is no good reason those two things should be tightly coupled. Amazon should not get to charge a markup on hardware because of the software that runs on it. That's a regression not only from open source, but from shrink-wrapped proprietary software too. Putting the cloud back in shrink-wrap world could add a lot of value: buy commodity capacity, still write "cloud" applications for it, split the hardware savings with IBM.
To compete, Amazon will have to either lower its markup or innovate in proprietary hardware (as it's starting to do with Graviton2) to provide value-added services that software on commodity hardware can't effectively replicate. And IBM basically invented that game, so good luck.
Not to say IBM is capable of executing it, but it’s an interesting strategy.
They surely can. But so is true for Azure and GCP as well. Thus, I'm curious about whether it is a feasible pricing strategy for AWS, considering the fact that EKS is not much different from their competition's managed K8s offerings.
Understood. This IMO is a bit of a shaky ground, because, while still being (or being perceived as) a cloud leader - though Azure a formidable competitor across the cloud spectrum - AWS is definitely not a leader in the managed K8s area (where GCP clearly is, at least, as of now).
But can you just turn your datacenter off and not pay for it when you don't use it? Can you double the number of cores in your datacenter by running a script and waiting five minutes?
There is little point in using EC2 if you never want to do either, I agree. But it seems like many people do and are willing to pay more per core to do so.
After getting behind, why should it be assumed automatic to "just catch up" in cloud? Microsoft fell behind mobile and never caught up despite pouring billions on it. Same with Google and social networks. Oracle also got behind in the cloud race and will probably also lose it all.
The early bird gets the worm, stop blaming the CEO.
Although "Watson" seems a PHB toy to trick investors or job seekers into thinking it had magic AI.
In the 1990s and 2000s, Oracle and SAP used to win on the basis of their "fully integrated suite of business applications" that they contrasted with the "best of breed" approach that (they claimed) would cost more to integrate than they delivered in additional value. However, over the last 10 years, Oracle and SAP went on a buying spree scooping up all those best of breed enterprise applications and then failed to integrate them with their core offerings, creating the same problem they claimed to be addressing. At the same time, R&D spend on organic product innovation slumped.
Buying up the competition isn't the panacea many tech companies seem to think it is.
It sounds like it "worked" from their financial standpoint, at least for a while. You don't have to compete if you buy up competitors. Remember when MS bought FoxPro? Customer choice and prices may be a different story.
Microsoft was not "early" on cloud, and came back into relevance (perhaps more than Google, really, in this one case). The early bird (Friendster, Commodore Computing, VisiCalc) does not always get the worm.
the ratio of super-trolly-know-it-all (Red Hat is just a "proprietary Kubernetes distribution", really? do you even know what Red Hat does?) to "no 500 server error on my blog" is pretty high here
In the first-approximation analysis of stock buybacks, they keep the share price the same but reduce the market cap of the company by however much was bought. This is known and intended. If $55B of their $95B drop in market cap is simply by returning cash to the investors, that isn't such a bad thing.
That's incorrect. A company's market cap includes any cash the company has. Buying stock means spending that cash but increasing the value of the stock by an equal amount.
I don't think this is correct either. A company's cash, or other assets, are not included in its market cap. It's just share price times number of shares outstanding.
Where why_only_15 is incorrect is in saying that buybacks don't affect share price. The whole point of a buyback is to increase the share price.
Consider a company with 1T shares that's valued at $1T with $100B of cash. Presumably, $100B of that valuation is for the cash, because investors know they could give that money back through dividends or the like. Let's say the company buys back 100B shares for its $100B. Because the company no longer has the cash, the overall value decreases (to $900B) to the same degree that there are less shares on the market (100B less).
You should think of a stock buyback as another way of paying a dividend without triggering a taxable event for stockholders. The value transitions into a greater price of the now-fewer-outstanding shares.
Now think about how that "market price" of a share is determined. Surely investors will be valuing a company with $100B in cash higher than a company with $0 in cash.
No mention of their acquisition of the Weather Channel's digital properties, or any other M&A for that matter. Hard to see how this decade was lost for them, rather than a significant investment into the future.
IBM has had a continuous pipeline of acquisitions over decades, but where is the money? At some point the profit from the older acquisitions has to cancel out the cost of the newer ones and that isn't apparent for IBM.
This whole idea that stock buybacks are necessarily bad needs to die. Can they be bad? Sure. But there are valid reasons to pursue a strategy of buybacks vs. dividends.
It's really hard to decline so consistently with the same rotten management at the helm year after year. Did they hire management from Qualcomm to achieve this?
One thing IBM has been working on is trying to solve the issue of worldwide remittances and global payments by using Stellar (XLM) and their block-chain solution to bridge various assets and fiat currencies.
Softlayer was great. IBM Cloud is terrible. I tried provisioning a bare metal server a few months ago and gave up a couple hours in. Packet had me up and running in minutes.
Cover your ass. If you're in a position to spend a lot of money, and you hire IBM, and they mess it up, you get to say "Hey, I did my due diligence by hiring IBM".
Except there is now a counter-current where the project fails due to IBM and people would say “what did you expect, you hired IBM” (e.g. some huge government software projects).
well if you are a member of any of their large user groups you would be asking why has IBM forsaken them? They really went off the rails in a bad way seeming to have forgotten their hardware base in z, i, and even p, to where you had to look long and hard to find mention of any of those platforms during announcements.
Going to have to wait and see if IBM changes direction but last year wasn't fun as they began the shutdown of their developerworks wikis that had so much user contributed material and this change came out of the blue with little warning. that left even groups in IBM struggling to preserve knowledge built up over the years
LOL. This is hysterical and brilliant but not aggressive enough:
"The fund evaluates the 1000 largest US firms for the ratio of women on the board of directors and in executive positions (defined as Sr. VP or higher). Companies ranking in the top 10% in each sector are included in the portfolio, with the caveat that each firm must have at least one woman on its board or as CEO."
It should be top 5% or so. Also having a single woman on a board of directors is not aggressive enough. Hopefully the 10% or 5% limit throws out such companies.
I see you're doing the shorting yourself. Too bad that's note a purchasable fund.
Whilst I harbour significant doubt that simply shorting companies with newly appointed female CEOs would be an effective way of exploiting it, the glass cliff effect [0] is a known phenomena whereby female leaders are more likely to be appointed in times of crisis.
A "short" means opposite of "long", e.g. you bet _against_ a company as opposed to betting for _for_ a company. It is not a reference to any kind of timeframe.
I worry that addiction to stock buybacks is a terminal disease for companies like IBM. Imagine what $65B invested in R&D over the last eight years could have yielded in the future instead of being poured down a financial sewer.
Stock buybacks are yields for shareholders the same as dividends (just with different tax implications) - definitely not “down the sewer”.
Most companies have a limit to the amount of R&D they can do before running into a wall where the payback becomes unprofitable (for complicated reasons).
The money would have been returned as dividends instead. For-profit companies are not intended to exist just to spend all profits on themselves (although Amazon is one obvious counter example amongst many).
Go to https://en.wikipedia.org/wiki/List_of_mergers_and_acquisitio... and sort the table there by value, descending. "IBM" is a shorthand for more (un-dissolved!) subsidiaries at this point than GE or Samsung.
IBM itself is just a consulting "solution provider" company that provides "solutions" in terms of the products and services of its subsidiaries. They're never going to look like they're on the cutting edge of some space, unless that's what one of their (equally-stodgy) enterprise clients wants to pay them to do. (And even then, why build when you can buy? IMHO IBM would only ever build a new technology at this point if there was no existing company out there in the market, with that tech IP, that they could just acquire.)
Certainly, there's the Watson AI lab, though I don't think anyone's expecting much of it at this point; nor, importantly, was anyone inside IBM ever expecting much of it. Watson (the lab specifically, not the brand strategy of calling all their cloud OLAP SaaS products "Watson") is more a nod to their clients to say "of course we're looking into AI", and a pool of people competent enough that they could clone the existing ML approach of one of their competitors if one of their clients demanded it.
IBM could be a really innovative company if they rearranged their talent pool, certainly. But innovation—getting ahead of the market and so needing to educate the market on the problem their products solve—hasn't been IBM's business model since the 1950s. IBM makes money by listening to clients' "unique" needs, and then meeting them with "custom" solutions at low CapEx cost, by using an ever-larger flywheel of existing solutions pre-tuned to almost fit every possible business use-case.