Did IBM Watson Ask Warren Buffet about Value?
May 19, 2017
I read “$4 Billion Stock Sale Suggests Warren Buffett’s Love Affair with IBM Is Over.” The subtitle caught my eye. What would Watson think about this statement:
Berkshire Hathaway’s founder Warren Buffett has admitted that buying IBM shares was a mistake. He has sold 30 percent of his 81 million shares because the company failed to live up to the expectations it held in 2011.
If I had access to a fully functioning (already trained) IBM Watson, I would ask Watson that question directly.
Last night I was watching the NBA playoff game between the technically adept Houston team and the programming-crazed San Antonio team. There in the middle of a start and stop game was an IBM Watson commercial.
Let me tell you that the IBM Watson message nestled comfortably amidst the tats, the hysterical announcers, and the computer-literature crowd.
IBM has a knack for getting its message out to buyers with cash in their hands for a confection of open source, home brew, and acquired technology.
Why doesn’t Warren Buffet get the message?
According the the write up, Mr. Buffet explains what message he received about IBM:
… IBM “hasn’t done what, five or six years ago, I expected would happen – or what the management expected would happen, if you look back at what they were projecting, and how they thought the business would develop. “The earnings have been obviously disappointing. I mean, five or six years ago, I think they were earning $20+ billion pre-tax and maybe it’s $13 billion now, and I don’t think the quality of the earnings has improved. “It’s been a period when it’s been tougher than they thought and it’s been tougher than I thought. But I was wrong. I don’t blame them. I get paid to make my own decisions, and sometimes they’re right and sometimes they’re wrong.
Interesting but not quite as remarkable as smart software being advertised to NBA fans. Air ball.
Stephen E Arnold, May 19, 2017
Malware Infected USB Sticks on the Loose
May 18, 2017
Oops. We learn from TechRepublic that “IBM Admits it Sent Malware-Infected USB Sticks to Customers.”
The article cites the company’s support Advisory Post announcing the problem, a resource anyone who has received an IBM Storwize V3500, V3700 or V5000 USB drive should check for the models and serial numbers affected. The recommended fix—destroy the drive and, if you’d already inserted it, perform a malware purge on your computer.
Writer Conner Forrest describes:
So, what does the infected drive actually do to a system? ‘When the initialization tool is launched from the USB flash drive, the tool copies itself to a temporary folder on the hard drive of the desktop or laptop during normal operation,’ the IBM post said. Then, a malicious file is copied to a temporary folder called %TMP%\initTool on Windows or /tmp/initTool on Linux or Mac. It is important to note that, while the file is copied onto a machine, it isn’t actually executed during the initialization process, the post also said. As reported by ZDNet’s Danny Palmer, the malware was listed by Kaspersky lab as a member of the Reconyc Trojan malware family, which is primarily used in Russia and India.
It might be understandable if this were the first time this had happened, but IBM also unwittingly distributed infected USB drives back in 2010, at the AusCERT conference in Australia. Let us hope there is not a third time; customers rightly expect more vigilance from such a prominent company.
Cynthia Murrell, May 18, 2017
Passion for the Work Is Key to Watson Team HR
May 17, 2017
Have you ever wanted to be on the IBM Watson team? Business Insider shares, “An IBM Watson VP Says He’s Hired Candidates Without Even Conducting an Interview—Here’s Why He’d Hire You on the Spot.” The brief write-up introduces Watson’s VP of HR Obed Louissant, who reveals that he has offered some folks a job they weren’t actually seeking after speaking with them. Writer Áine Cain specifies:
In certain conversations, Louissant says that he’s been blown away by the passion and engagement with which some individuals speak about their work. … ‘It was more about the experience and what types of places they like to work at,’ Louissant says. If the type of workplace happens to sound just like IBM Watson, the branch of the company that focuses on the question answering computer system, then Louissant says he’s willing to make a job offer right then and there.”
So, never underestimate the power of revealing a passion for your work. It could just land you a better job someday, with Louissant or other corporate leaders who, like him, are ready to snap up enthusiastic workers as soon as they recognize them.
Cynthia Murrell, May 17, 2017
IBM Watson: A Joke?
May 10, 2017
I wanted to ask IBM Watson is it thought the article “IBM’s Watson Is a Joke, Says Social Capital CEO Palihapitiya.” No opportunity. Bummer.
I learned from the real journalism outfit CNBC, which has been known to sell advertising, that:
“Watson is a joke, just to be completely honest,” he said in an interview with “Closing Bell” on the sidelines of the Sohn Investment Conference in New York.
The Social Capital top dog added:
“I think what IBM is excellent at is using their sales and marketing infrastructure to convince people who have asymmetrically less knowledge to pay for something,” Palihapitiya added. “I put them and Oracle in somewhat of the same bucket.”
I like that “asymmetrically less knowledge.” It suggests that the PR firms, the paid consultants who flog the word “cognitive,” and the torrent of odd ball conference talks are smoke and mirrors.
Should one put one’s money into IBM? My reading of the article suggests that the CNBC expert believes that Jeff Bezos and Elon Musk are where the action is. What? No Alphabet Google thing?
Several observations:
- Describing something in marketing science fiction is fun and can be lucrative. The reality is that Lucene, home brew code, and acquired technology do not add up to a breakthrough in smart software. Sorry, cheerleaders.
- Reporting five years of declining revenue puts hyperbole in context. IBM is simply trying to hard to push Watson into everything from recipes to healthcare. The financial reports tell me that the bet is not working.
- Creating wild and crazy Super Bowl ads which suggest a maximum refund tips toward carnival marketing. Floating white cubes are just as incomprehensible to me as PT Barnum’s Feejee mermaid.
Perhaps IBM can roll out a TV spot with Mr. Barnum’s Chang and Eng as a spokes-people.
Stephen E Arnold, May 9, 2017
How to Use a Quantum Computer
April 20, 2017
It is a dream come true that quantum computers are finally here! But how are we going to use them? PC World discusses the possibilities in, “Quantum Computers Are Here—But What Are They Good For?” D-Wave and IBM both developed quantum computers and are trying to make a profit from them by commercializing their uses. Both companies agree, however, that quantum computers are not meant for everyday computer applications.
What should they be used for?
Instead, quantum systems will do things not possible on today’s computers, like discovering new drugs and building molecular structures. Today’s computers are good at finding answers by analyzing information within existing data sets, but quantum computers can get a wider range of answers by calculating and assuming new data sets. Quantum computers can be significantly faster and could eventually replace today’s PCs and servers. Quantum computing is one way to advance computing as today’s systems reach their physical and structural limits.
What is astounding about quantum computers are their storage capabilities. IBM has a 5-qubit system and D-Wave’s 2000Q has 2,000 qubit. IBM’s system is more advanced in technology, but D-Wave’s computer is more practical. NASA has deployed the D-Wave 2000Q for robotic space missions; Google will use it for search, image labeling, and voice recognition; and Volkswagen installed it to study China’s traffic patterns.
D-Wave also has plans to deploy its quantum system to the cloud. IBM’s 5-qubit computer, on the other hand, is being used for more scientific applications such as material sciences and quantum dynamics. Researchers can upload sample applications to IBM’s Quantum Experience to test them out. IBM recently launched the Q program to build a 50-qubit machine. IBM also wants to push their quantum capabilities in the financial and economic sector.
Quantum computers will be a standard tool in the future, just as the desktop PC was in the 1990s. By then, quantum computers will respond more to vocal commands than keyboard inputs.
Whitney Grace, April 20, 2017
Watson and Block: Tax Preparation and Watson
April 19, 2017
Author’s Note:
Tax season is over. I am now releasing a write up I did in the high pressure run up to tax filing day, April 18, 2017, to publish this blog post. I want to comment on one marketing play IBM used in 2016 and 2017 to make Watson its Amazon Echo or its Google Pixel. IBM has been working overtime to come up with clever, innovative, effective ways to sell Watson, a search-and-retrieval system spiced with home brew code, algorithms which make the system “smart,” acquired technology from outfits like Vivisimo, and some free and open source search software.
IBM Watson is being sold to Wall Street and stakeholders as IBM’s next, really big thing. With years of declining revenue under its belt, the marketing of Watson as “cognitive software” is different from the marketing of most other companies pitching artificial intelligence.
One unintended consequence of IBM’s saturation advertising of its Watson system is making the word “cognitive” shorthand for software magic. The primary beneficiaries of IBM’s relentless use of the word “cognitive” has been to help its competitors. IBM’s fuzziness and lack of concrete products has allowed companies with modest marketing budgets to pick up the IBM jargon and apply it to their products. Examples include the reworked Polyspot (now doing business as CustomerMatrix) and dozens of enterprise search vendors; for example, LucidWorks (Really?), Attivio, Microsoft, Sinequa, and Squirro (yep, Squirro). IBM makes it possible for competitors to slap the word cognitive on their products and compete against IBM’s Watson. I am tempted to describe IBM Watson as a “straw man,” but it is a collection of components, not a product.
Big outfits like Amazon have taken a short cut to the money machine. The Echo and Dot sell millions of units and drive sales of Amazon’s music and hard goods sales. IBM bets on a future hint of payoff; for example, Watson may deliver a “maximum refund” for an H&R Block customer. That sounds pretty enticing. My accountant, beady eyed devil if there ever were one, never talks about refunds. He sticks to questions about where I got my money and what I did with it. If anything, he is a cloud of darkness, preferring to follow the IRS rules and avoid any suggestion of my getting a deal, a refund, or a free ride.
Below is the story I wrote a month ago shortly after I spent 45 minutes chatting with three folks who worked at the H&R Block office near my home in rural Kentucky. Have fun reading.
Stephen E Arnold, April 18, 2017
IBM Watson is one of Big Blue’s strategic imperatives. I have enjoyed writing about Watson, mixing up my posts with the phrase “Watson weakly” instead of “Watson weekly.” Strategic imperatives are supposed to generate new revenue to replace the loss of old revenues. The problem IBM has to figure out how to solve is pace. Will IBM Watson and other strategic imperatives generate sustainable, substantial revenue quickly enough to keep the company’s revenue healthy.
The answer seems to be, “Maybe, but not very quickly.” According to IBM’s most recent quarterly report, Big Blue has now reported declining revenues for 20 consecutive quarters. Yep, that’s five years. Some stakeholders are patient, but IBM’s competitors are thrilled with IBM’s stratgegic imperatives. For the details of the most recent IBM financials, navigate to “IBM Sticks to Its Forecast Despite Underwhlming Results.” Kicking the can down the road is fun for a short time.
The revenue problem is masked by promises about the future. Watson, the smart software, is supposed to be a billion dollar baby who will end up with a $10 billion dollar revenue stream any day now. But IBM’s stock buybacks and massive PR campaigns have helped the company sell its vision of a bright new Big Blue. But selling software and consulting is different from selling hardware. In today’s markets, services and consulting are tough businesses. Examples of companies strugglling to gain traction against outfits like Gerson Lehrman, unemployed senior executives hungry for work, and new graduates will to do MBA chores for a pittance compete with outfits like Elastic, a search vendor which sells add ons to open source software and consulting for those who need it. IBM is trying almost everything. Still those declining revenues tell a somewhat dismal tale.
I assume you have watched the Super Bowl ads if not the game. I just watched the ads. I was surprised to see a one minute, very expensive, and somewhat ill conceived commercial for IBM Watson and H&R Block, the walk in store front tax preparer.
The Watson-Block Super Bowl ad featured this interesting image: A sled going downhill. Was this a Freudian slip about declining revenues?
Does it look to you that the sled is speeding downhill. Is this a metaphor for IBM Watson’s prospects in the tax advisory business?
One of IBM’s most visible promotions of its company-saving, revenue-gushing dreams is IBM Watson. You may have seen the Super Bowl ad about Watson providing H&R Block with a sure-fire way to kill off pesky competitors. How has that worked out for H&R Block?
IBM: Recycling Old Natural Language Assertions
April 6, 2017
I have ridden the natural language processing unicycle a couple of times in the last 40 years. In fact, for a company in Europe I unearthed from my archive NLP white papers from outfits like Autonomy Software and Siderean Software among others. The message is the same: Content processing from these outfits can figure out the meaning of a document. But accuracy was a challenge. I slap the word “aboutness” on these types of assertions.
Don’t get me wrong. Progress is being made. But the advances are often incremental and delivered as the subsystem level of larger systems. A good example is the remarkable breakthrough technology of Madrid, Spain-based Bitext. The company’s Deep Linguistic Analysis Platform solves a very difficult problem when an outfit like a big online service has to figure out the who, what, when, and where in a flood of content in 10, 20, or 30 or more languages. The cost of using old-school systems is simply out of reach even for companies with billion in the bank.
I read “Your Machine Used to Crunch Numbers. Now It Can Chew over What They Mean, Too.” The write up appeared in the normally factual online publication “The Register.” The story, in my opinion, sucks in IBM marketing speak and makes some interesting assertions about what Lucene, home brew scripts, and acquired technology can deliver. In my experience, “aboutness” requires serious proprietary systems and methods. Language, no matter what one believes when Google converts 400 words of Spanish into semi-okay English.
In the article I was told:
This makes sense, because the branches of AI gaining most traction today – machine learning and deep learning – typically have non-deterministic outputs. They’re “fuzzy”, producing confidence scores relating to their inputs and outputs. This makes AI-based analytics systems good at analyzing the kind of data that has sprung up since the early 2000s; particularly social media posts.
Well, sort of. There are systems which can identify from unstructured text in many languages the actor, the action, and the outcome. In addition, these systems can apply numerical recipes to identify items of potential interest to an analyst or another software systems. The issue is error rate. Many current entity tagging systems stumble badly when it comes to accuracy.
But IBM has been nosing around NLP and smart software for a long time. Do you remember Data Fountain or Dr. Jon Kleinberg’s CLEVER system? These are important, but they too were suggestive, not definitive approaches.
The write up tells me via Debbie Landers, IBM Canada’s vice president of Cognitive Solutions:
People are constantly buying security products to fix a problem or get a patch to update something after it’s already happened, which you have to do, but that’s table stakes,” he says. Machine learning is good at spotting things as they’re happening (or in the case of predictive analytics, beforehand). Their anomaly detection can surface the ‘unknown unknowns’ – problems that haven’t been seen before, but which could pose a material threat. In short, applying this branch of AI to security analytics could help you understand where attackers are going, rather than where they’ve been. What does the future hold for analytics, as we get more adept at using them? Solutions are likely to become more predictive, because they’ll be finding patterns in empirical data that people can’t spot. They’ll also become more context-aware, using statistical modeling and neural networks to produce real-time data that correlates with specific situations.
My reaction to this write up is that IBM is “constantly” thrashing for a way to make Watson-type services a huge revenue producer for IBM. From recipes to cancer, from education to ever more spectacular assertions about what IBM technology can do—IBM is demonstrating that it cannot keep up with smart software embedded in money making products and mobile services.
Is this a promotional piece? Yep, The Reg even labels it as such with this tag:
See. A promo, not fake news exactly. It is clear that IBM is working overtime with its PR firm and writing checks to get the Watson meme in many channels, including blogs.
Beyond Search wants to do its part. However, my angle is different. Look around for innovative companies engaged in smart software and closing substantive deals. Compare the performance of these systems with that of IBM’s solutions, if you can arrange an objective demonstration. Then you will know how much of IBM’s content marketing carpet bombing falls harmlessly on deaf ears and how many payloads hit a cash register and cause it to pay out cash. (A thought: A breakthrough company in Madrid may be a touchstone for those who are looking for more than marketing chatter.)
Stephen E Arnold, April 6, 2017
The Human Effort Behind AI Successes
March 14, 2017
An article at Recode, “Watson Claims to Predict Cancer, but Who Trained It To Think,” reminds us that even the most successful AI software was trained by humans, using data collected and input by humans. We have developed high hopes for AI, expecting it to help us cure disease, make our roads safer, and put criminals behind bars, among other worthy endeavors. However, we must not overlook the datasets upon which these systems are built, and the human labor used to create them. Writer (and CEO of DaaS firm Captricity) Kuang Chen points out:
The emergence of large and highly accurate datasets have allowed deep learning to ‘train’ algorithms to recognize patterns in digital representations of sounds, images and other data that have led to remarkable breakthroughs, ones that outperform previous approaches in almost every application area. For example, self-driving cars rely on massive amounts of data collected over several years from efforts like Google’s people-powered street canvassing, which provides the ability to ‘see’ roads (and was started to power services like Google Maps). The photos we upload and collectively tag as Facebook users have led to algorithms that can ‘see’ faces. And even Google’s 411 audio directory service from a decade ago was suspected to be an effort to crowdsource data to train a computer to ‘hear’ about businesses and their locations.
Watson’s promise to help detect cancer also depends on data: decades of doctor notes containing cancer patient outcomes. However, Watson cannot read handwriting. In order to access the data trapped in the historical doctor reports, researchers must have had to employ an army of people to painstakingly type and re-type (for accuracy) the data into computers in order to train Watson.
Chen notes that more and more workers in regulated industries, like healthcare, are mining for gold in their paper archives—manually inputting the valuable data hidden among the dusty pages. That is a lot of data entry. The article closes with a call for us all to remember this caveat: when considering each new and exciting potential application of AI, ask where the training data is coming from.
Cynthia Murrell, March 14, 2017
Significant Others: Salesforce Einstein and IBM Watson
March 13, 2017
The flow of semi-smart software publicity continues. Keep in mind that most smart software is little more than search with wrappers performing special operations.
The proud parents of Einstein and Watson announced that one another’s smart software systems have become a thing. Salesforce has scripts and numerical recipes to make it easier to figure out if a particular client really wants to drop the service. Watson brings Jeopardy type question answering and lots of data training to the festive announcement party.
I enjoyed “Salesforce Will Be Using IBM Watson to Make its Einstein AI Service Even Smarter.” The write up strikes me as somewhat closer to the realities of the tie up than the inebriated best wishes emanating from many other “real” journalists. For example, the write up asserts:
By bringing its all-important Watson service to Salesforce and Einstein customers, IBM is determined to double-down on that huge Salesforce consulting market, not compete with it.
IBM cannot “become” Salesforce. But Salesforce generates a need for services in many large companies. The idea is that Einstein does its thing to help a sales professional close a deal, and IBM Watson can do its thing to make “sense” of the content related to the company paying Salesforce for an integrated sales prospecting and closing system.
My take is that this is not much more than a co-publicity set up with the hope that the ability of Salesforce to talk about its tie up with IBM will generate sales and buzz. IBM hopes that its PR capabilities will produce some mileage for the huffing and puffing Watson “solution.”
In my opinion, IBM is turning cartwheels to get substantial, evergreen revenue from the Watson thing. But IBM may be pushing another fantasy animal into the revenue race. Quantum computing as a service is the next big thing. Now is quantum computing something one can actually use?
Nah, but the point is that revenue is not news at IBM. Quantum computing gives the IBM marketers another drum to bang. Moving in with Salesforce provides a way to sell something, anything, maybe.
Stephen E Arnold, March 13, 2017
IBM Watson: Mixed Signals from the Real World and IBM Marketers
February 21, 2017
I read a write up which might be fake news for all I know. I live in rural Kentucky and the doings of folks in a big city like Houston are mysterious and far away. Out local doctor squeezes in humans after dealing with race horses and dogs.
I read in Forbes, the capitalist tool, this story: “MD Anderson Benches IBM Watson In Setback For Artificial Intelligence In Medicine.”
The main idea is easy to grasp, even for folks like me sitting near the wood stove in Harrod’s Creek. As I understand it, IBM Watson was supposed to be helping the doctors at the número uno cancer treatment center in their quest to eradicate cancer. I assume the idea was to make more time available to physicians and other health care givers because IBM Watson would have had answers about patient treatment. IBM Watson knew the Jeopardy answers, right. Dealing with cancer-related questions seems to me to be easier: More narrow domain, more consistent terminology, smart people, etc etc.
The possibly fake news write up says:
The partnership between IBM and one of the world’s top cancer research institutions is falling apart. The project is on hold, MD Anderson confirms, and has been since late last year. MD Anderson is actively requesting bids from other contractors who might replace IBM in future efforts. And a scathing report from auditors at the University of Texas says the project cost MD Anderson more than $62 million and yet did not meet its goals.
But there is good news, or at least face saving news. I like this statement in the capitalist tool:
The report, however, states: “Results stated herein should not be interpreted as an opinion on the scientific basis or functional capabilities of the system in its current state.”
The door is not locked. Perhaps IBM Watson will once again be allowed to dine in the MD Anderson cafeteria and spark the pixels on the MD Anderson computing devices. Every smart software cloud may have a silver lining. Right?
But the project seems to be on “hold.” If the news is fake, then the project is full steam ahead, but I think the truth is closer to something like this: The users found the system like other smart software. Sort of helpful sometimes. At other times, the smart software was adding work, time, and frustration to an already high pressure, high stakes environment.
The capitalist tool ventures this observation:
The disclosure comes at an uncomfortable moment for IBM. Tomorrow, the company’s chief executive, Ginni Rometty, will make a presentation to a giant health information technology conference detailing the progress Watson has made in health care, and announcing the launch of new products for managing medical images and making sure hospitals deliver value for the money, as well as new partnerships with healthcare systems. The end of the MD Anderson collaboration looks bad.
I have zero idea what giant conference is held “tomorrow.” But I did notice this write up, which may be a coincidence: “IBM Sees Watson As a Primary Care Provider’s Assistant.” This seems similar to what IBM Watson was going to do at the MD Anderson cancer center. The write up asserts:
IBM is prepping Watson to work alongside primary care physicians and streamline processes. The company also added features to its Watson-based health cloud services.
The IBM Watson system has been enhanced too. The write up reports:
That Watson-primary care provider connection is being rolled out in Central New York in a six-county region and more than 2,000 providers. Meanwhile, Atrius Health, based in Massachusetts, will embed IBM’s cognitive computing tools inside its electronic medical records workflow for primary care providers.
This sounds good. Perhaps this is the “real” IBM Watson news. Rapid adoption and new capabilities make IBM Watson a must have in the smart health care providers arsenal of disease fighting weapons.
But there is that MD Anderson situation.
What do I make of these apparently contradictory write ups, which I assume are fake news, of course?
- IBM Watson, like other end user smart software systems, is a disappointment in actual use. Humans have to learn how to use the system and then take time to figure out which of the outputs are the ones that are likely to be useful in a particular patient’s case. Instead of saving time, the smart software adds tasks to already stretched professionals.
- The marketing and sales pressure is great. As a result, the marketers’ explanations may not match up with the engineering realities of a search-based system. When the marketers have left the building, the users learn the reality. After normal bureaucratic jabbering, the users’ dissatisfaction become too much for administrators to deal with. Hasta la vista, Sr. Watson.
- IBM, like other outfits betting on smart software, continue to repeat the cycle of belief, hyperbolic marketing, and learning about the costs and problems the smart system triggers. So why did Fast Search & Transfer’s run to fame fall off a cliff? Why is Hewlett Packard annoyed with Autonomy Software? Why did Entopia fail? Why is Lexmark’s new owners trying to exit the search with smart software business? Answer: Hope does not make an end user facing smart system generate sustainable revenues.
Because this IBM Watson news is fake. Why worry? Smart software will lift IBM to heights not experienced since the mainframe was the go to solution to computing needs. If you have a z series, you can run IBM Watson on it. Now that’s something I wish I could experience. My hunch is that none of the docs at MD Anderson will buy a z series and load up Watson because it is so darned useful. Maybe that is the “real” reality?
How does IBM get this Watson thing under control and generating money and producing happy customers? Let’s ask Watson? On the other hand, I don’t think the outputs will be too helpful.
Stephen E Arnold, February 21, 2017
-
- Subscribe to Beyond Search
Feature archive
News archive
-
