IBM Watson: Cruel, Cruel Caveats
November 12, 2016
There’s nothing like a cruel caveat applied to IBM Watson. Navigate to “Cognitive Computing Applications Present New Business Challenges.” These challenges are not “new”; what’s new is that naive smart software licensees are discovering that training software is difficult, time consuming, and expensive. Best of all, the training is not forever. Smart systems need to be retrained because language and data change.
The write up reports that an executive involved in smart software at Rabobank, a Dutch outfit, offered this observation at the World of Watson conference held at the end of October 2016 :
AI is everywhere, and people think it’s so fantastic. And these companies, including IBM, come in and then you go to do a project and see that it’s not really that great yet,” Serrurier Schepper said. “You have to train a model, and it takes time.”
The story continues:
After building a centralized AI unit, teams should look for quick wins and then publicize their success, Serrurier Schepper said. Models may take a long time to train, but once they’re delivering strong results, sharing this with the rest of the company can help build support for future initiatives.
Yep, time. Time is money, which is a statement any bank professional with Excel can understand.
How does one avoid failing? That’s easy. The write up reports:
Choosing the right use cases for cognitive computing applications is also important. There is a general notion that AI software can perform just about any task. And while that may be the ultimate goal of the technology, today’s tools are a ways off from that. Enterprises need to identify business problems where the technology is competent, and that’s not always a simple proposition.
The point is that no matter how generalized the perception that smart software like Watson can be, the licensee has to figure out exactly what problem to attack. The reason is that the time and cost of creating a model and then training the smart software will put the project deep into a swamp of red, mercury tinged muck.
But be prepared to spend money. The write up quotes another Watson aware executive as saying:
“If you get too hung up on ROI, you’ll never do anything.”
I disagree. Those involved in the project may have an opportunity to look for a new job. It’s the time and cost thing that creates these new horizons for some smart software champions.
Stephen E Arnold, November 12, 2016
IBM Watson Tactic: Cherry Picking
November 10, 2016
I read “IBM Buys Watson-Based Expert Personal Shopper.” The article may reveal IBM’s plan to make Watson profitable. According to the write up:
IBM’s Interactive Experience (IBM iX) unit acquired the Expert Personal Shopper (XPS) division of Fluid, a provider of digital customer experiences.
The idea is simple. Pump money into promising Watson applications created by other companies. Then when the third party’s product begins to show signs of life, IBM steps in to buy the product. IBM sales professionals now have a real product to sell, not just consulting.
The personal shopper, according to the write up:
is a dialogue-based product-recommendation platform developed by Fluid that uses IBM’s Watson cognitive computing system to personalize the customer experience and improve product discovery. XPS uses natural language to interact with and provide personalized shopping experiences for customers.
If this sounds like the dozens of other smart chat bots, it may be. The difference is that this chatbot is an application of some of Watson’s capabilities.
Is this a quick and low cost way to convert Watson’s smoke and mirrors to cash? It depends on one’s point of view. The write up says:
In 2014, IBM invested in Fluid, drawing from a $100 million fund Big Blue had set aside to invest in Watson-based businesses and applications. Earlier that year, the IBM Watson Group made its first investment in Welltok, developers of the Watson-based CaféWell Health Optimization Platform. Fluid was among the early partners IBM trotted out to showcase how Watson had become available to developers to build apps around. IBM and Fluid worked to accelerate development of XPS at the time.
Two years later and at an undisclosed purchase price, IBM Watson has a product. From the point of view of a large company, this is definitely efficient. From the vantage point of a long suffering IBM shareholder, the time and cost are probably one more example of why IBM’s quarterly revenues have reported declines for more than four years.
Stephen E Arnold, November 10, 2016
Lucidworks Hires Watson
November 7, 2016
One of our favorite companies to track is Lucidworks, due to their commitment to open source technology and development in business enterprise systems. The San Diego Times shares that “Lucidworks Integrates IBM Watson To Fusion Enterprise Discovery Platform.” This means that Lucidworks has integrated IBM’s supercomputer into their Fusion platform to help developers create discovery applications to capture data and discover insights. In short, they have added a powerful big data algorithm.
While Lucidworks is built on open source software, adding a proprietary supercomputer will only benefit their clients. Watson has proven itself an invaluable big data tool and paired with the Fusion platform will do wonders for enterprise systems. Data is a key component to every industry, but understanding and implementing it is difficult:
Lucidworks’ Fusion is an application framework for creating powerful enterprise discovery apps that help organizations access all their information to make better, data-driven decisions. Fusion can process massive amounts of structured and multi-structured data in context, including voice, text, numerical, and spatial data. By integrating Watson’s ability to read 800 million pages per second, Fusion can deliver insights within seconds. Developers benefit from this platform by cutting down the work and time it takes to create enterprise discovery apps from months to weeks.
With the Watson upgrade to Lucidworks’ Fusion platform, users gain natural language processing and machine learning. It makes the Fusion platform act more like a Star Trek computer that can provide data analysis and even interpret results.
Whitney Grace, November 7, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Be Prepared for Foggy Computing
October 31, 2016
Cloud computing allows users to access their files or hard drive from multiple devices at multiple locations. Fog computing, on the other hand, is something else entirely. Fog computing is the latest buzzword in the tech world and pretty soon it will be in the lexicon. If you are unfamiliar with fog computing, read Forbes’s article, “What Is Fog Computing? And Why It Matters In Our Big Data And IoT World.”
According to the article, smartphones are “smart” because they receive and share information with the cloud. The biggest problem with cloud computing is bandwidth, slow Internet speeds. The United States is 35th in the world for bandwidth speed, which is contrary to the belief that it is the most advanced country in the world. Demand for faster speeds increases every day. Fog computing also known as edge computing seeks to resolve the problem by grounding data. How does one “ground” data?
What if the laptop could download software updates and then share them with the phones and tablets? Instead of using precious (and slow) bandwidth for each device to individually download the updates from the cloud, they could utilize the computing power all around us and communicate internally.
Fog computing makes accessing data faster, more efficient, and more reliably from a local area rather than routing to the cloud and back. IBM and Cisco Systems are developing projects that would push computing to more local areas, such as a router, devices, and sensors.
Considering that there are security issues with housing data on a third party’s digital storage unit, it would be better to locate a more local solution. Kind of like back in the old days, when people housed their data on CPUs.
Whitney Grace, October 31, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Wow Revelation: AI and the Proletariat
October 29, 2016
IBM’s week long Watson conference WOW marks the starting gun for end of year marketing. I read “IBM Says New Watson Data Platform Will Bring Machine Learning to the Masses.” I like the headline. It reminded me of a part time lecturer at the one horse college I attended 50 years ago. Wild eyed, the fellow was a fan of “ism”, almost any flavor was okay with him. I read the books on the reading list and dutifully took the tests. To be candid, I was delighted when the course ended.
Watson, if the headline is to be believed, may be drifting into the lingo of that now ignored adjunct lecturer. I learned:
IBM unveiled a cloud-based AI engine to help businesses harness machine learning. It aims to give everyone, from CEOs to developers, a simple platform to interpret and collaborate on data.
There we have it: An “everyone.” Really?
The write up, which I assume to be spot on, told me:
“Insight is the new currency for success,” said Bob Picciano, senior vice president at IBM Analytics. “And Watson is the supercharger for the insight economy.” Picciano, speaking at the World of Watson conference in Las Vegas on Tuesday, unveiled IBM’s Watson Data Platform, touted as the “world’s fastest data ingestion engine and machine learning as a service.” The cloud-based Watson Data Platform, will “illuminate dark data,” said Picciano, and will “change everything—absolutely everything—for everyone.”
Interesting. “Insight” is the “currency of success.” The idea is that if someone understands an issue, that mental perception is money.
I like the superlatives too. I found this statement amusing: …Watson will illuminate Dark Data” and “will change everything.”
There we have it: An “everything.” Really?
Now Watson is no longer Lucene, home brew code, and acquired technology. Watson is an enabler. The write up told me that “I haven’t made it a reality yet.” The “it” is the potential of Watson. I liked the concept that I am going to have to do more with Watson.
Okay, but we sort of like the Facebook and Google tools. The IBM approach was important when I worked in my university’s computing center as a JCL go-fer. I even embraced IBM servers for projects at outfits like Bell Communications Research. Ah, the joys of MVS/TSO.
But now the Watson categorical superlatives are noise.
I highlighted this statement attributed to an IBM wizard:
“The number of people in today’s business who have to be able to leverage data as part of their everyday lives, to make sense of it, to drive intelligent decision-making, has grown rapidly,” she said. Gunnar pointed to the need for businesses to collaborate with data across departments to make decisions. The simple interface, she said, helps give everyone, from those who are data savvy to “citizen analysts,” a chance to work with data. “The notion of being able to work on data together, to share across the business, is a huge opportunity to accelerate insights and uncover things that weren’t able to because of the silos within the organization that prevented working on common information,” she [Ritika Gunnar, VP of offering management] said.
There we have it: “everyone.” Really?
The sheer overstatement and superlative density underscore that IBM is trying hard to make Watson a success. I am reasonably certain that Watson’s all-embracing range of functions will generate revenue for Big Blue.
But compare the coverage of the IBM Wow conference with the hooting and hollering for the Apple event which took place during the Wow event.
And remember the proletariat. Yep, wow.
Stephen E Arnold, October 29, 2016
The IBM Watson Hype Machine Shouts Again
October 28, 2016
The IBM Watson semi news keeps on flowing. The PR firms working with IBM and the Watson team may bring back the go go days of Madison Avenue. Note, please. I wrote “may.” IBM’s approach, in my opinion, is based on the Jack Benny LSMFT formula. Say the same thing again and again and pretty soon folks will use the product. The problem is that IBM has not yet found its Jack Benny. Bob Dylan, the elusive Nobel laureate, is not exactly the magnetic figure that Mr. Benny was.
For a recent example of the IBM Watson buzz-o-rama, navigate to “IBM Watson: Not So Elementary.” I know the story is important. Here’s the splash page for the write up:
I will definitely be able to spot this wizard if I bump into him in Harrod’s Creek, Kentucky. I wonder what the Watson expert is looking at or for. Could it be competitors like Facebook or outfits in the same game in China and Russia?
The write up begins with an old chestnut: IBM’s victory on Jeopardy. No more games. I learned:
IBM’s cognitive computing system is through playing games. It’s now a hired gun for thousands of companies in at least 20 industries.
I like the “hired” because it implies that IBM is raking in the dough from 20 different industry sectors. IBM, it seems, is back in the saddle. That is a nifty idea but for the fact that IBM reported its 18th consecutive quarter of revenue declines. The “what if” question I have is, “If Watson were generating truly big bucks, wouldn’t that quarterly report reflect a tilt toward positive revenue growth?” Bad question obviously. The Fortune real journalist did not bring it up.
The write up is an interview. I did highlight three gems, and I invite—nay, I implore—you to read and memorize every delicious word about IBM Watson. Let’s look at the three comments I circled with my big blue marker.
Augmented Intelligence
at IBM, we tend to say, in many cases, that it’s not artificial as much as it’s augmented. So it’s a system between machine computing and humans interpreting, and we call those machine-human interactions cognitive systems. That’s kind of how it layers up….it’s beginning to learn on its own—that is moving more in the direction of what some consider true artificial intelligence, or even AGI: artificial general intelligence.
Yikes, Sky Net on a mainframe, think I.
Training Watson
there isn’t a single Watson. There’s Watson for oncology. There’s Watson for radiology. There’s Watson for endocrinology…for law…for tax code…for customer service.
I say to myself, “Wow, the costs of making each independent Watson smart must be high. What if I need to ask a question and want to get answers from each individual Watson? How does that work? How long does it take to receive a consolidated answer? What if the customer service Watson gets a question about weather germane to an insurance claim in South Carolina?”
The Competition
The distinctness of the Watson approach has been to create software that you can embed in other people’s applications, and these are especially used by the companies that don’t feel comfortable putting their data into a single learning system—particularly one that’s connected to a search engine—because in effect that commoditizes their intellectual property and their cumulative knowledge. So our approach has been to create AI for private or sensitive data that is best reserved for the entities that own it and isn’t necessarily ever going to be published on the public Internet.
I ponder this question, “Will IBM become the background system for the competition?” My hunch is that Facebook, Google, Microsoft, Amazon, and a handful of outfits in backwaters like Beijing and Moscow will think about non IBM options. Odd that the international competition did not come up in the Fortune interview with the IBM wizard.
End Game
these systems will predict disease progression in time to actually take preventive action, which I think is better for everybody.
“Amazing, Watson will intervene in a person’s life,” blurt my Sky Net sensitive self.
Please, keep in mind that this is an IBM Watson cheer which is about 4,000 words in length. As you work through the original Fortune article, keep in mind:
- The time and cost of tuning a Watson may cost more than a McDonald’s fish sandwich
- The use of “augmented intelligence” is a buzzword embraced by a number of outfits, including Palantir Technologies, a competitor to IBM in the law enforcement and intelligence community. Some of IBM’s tools are ones which the critics of the Distributed Common Ground System suggest are difficult to learn, maintain, and use. User friendly is not the term which comes to mind when I think of IBM. Did you configure a mainframe or try to get a device driver for OS/2 to work? There you go.
- The head of IBM Watson is not an IBM direct hire who rose through the ranks. Watson is being guided by a person from the Weather Channel acquisition.
How does Watson integrate that weather data into queries? How can a smart system schedule surgeries when the snow storm has caused traffic jams. Some folks may use an iPhone or Pixel or use common sense.
Stephen E Arnold, October 28, 2016
IBM: Financial Report Keeps Up with Its Predecessors
October 25, 2016
IBM’s financial results for 2015-2015 third quarter kept up with their predecessors.
The Wall Street Journal, October 18, 2016, said “IBM Profit, Sales Slip But New Units Grow.” (See page B1 in the Harrod’s Creek edition of the venerable business newspaper.) I noted this passage:
The Armonk, NY Company said Monday that third quarter revenue was $19.23 billion, down 0.3%…Big Blue said its profit fell 4% to $2.9 billion during the quarter ended in September amid weakness in its systems segment, which includes mainframe computer hardware and operating system software.
According to “Barclays Says IBM’s Q3 Not Much to Get Excited About”:
Going by the weakness in third quarter margins, Barclays said it’s led into believing that the company’s cloud business doesn’t have the scale to achieve margin at or above the corporate average. The firm termed it as not good, as the company’s strategic imperatives, including cloud, are starting to reaccelerate.
Here in Harrod’s Creek, the fans of blue chip stocks are wondering when IBM will reverse its 18th consecutive quarters of revenue decline.
I suggested to the folks hanging out at the local car repair shop that they should ask Watson. Their response:
What’s Watson. Ain’t he the guy who lives in the next town over?
I was going to explain but decided to put oil in my old car. It is getting old. I don’t think it can hang on much longer. I call it “Big Blue 2 too.” That sounds like blue tutu, doesn’t it?
Stephen E Arnold, October 25, 2016
Rocket Software: Video Marketing Moment
October 23, 2016
0I did a quick, routine check of Rocket Software’s search and text analytics Web page at this link. I saw a snippet of text and then a link to a new video:
Rocket is a player in the five day IBM Watson conference later this month. What’s interesting about the WOW 2016 event is that no list of participating companies is available via a search on IBM.com or via public Web search systems. Interesting. A five day event with many luminaries I surmise.
Stephen E Arnold, October 23, 2016
IBM Watson Is Just More of Everything Except Revenue
October 11, 2016
I read “IBM Watson’s CMO Predicts the Future of Data and AI.” I thought that the article would report what IBM Watson had to say about this question: “What is the future of data and AI, Watson?” Wrong. The article presents IBM’s current thinking about what its humanoids desperately want IBM Watson to become.
There was one startling omission in the article, but I will save that until the final paragraph of this mini report.
I noted several points of interest to me in the write up which is essentially an IBM wizard answering some slightly worn questions about the sprawling brand known as Watson. (Keep in mind that I know Watson as Lucene, home brew code, and acquired technologies.)
Point One: Watson understands human language. So Watson is like the film “2001” and HAL? No, here’s what the write up says Watson is:
It’s not speech recognition like Siri, not speech synthesis like Alexa, but actually understanding human languages…
Point Two: Why use IBM Watson and not some other smart system? Answer:
We’ve invested $6 billion in our idea, a third of that is dedicated to cognitive.
Point Three: IBM made a big deal about Twitter in 2014. IBM’s position:
Twitter specifically, is interesting.
You get the idea. Superficial generalizations about how capable IBM Watson is.
What’s the big omission? Revenue. Not a peep about how IBM Watson is going to generate sustainable revenue this quarter. What’s frightening to me is that the humanoid answers about Watson are sketchy. Since Watson did not answer the questions or address the topics in the title of the source article, I conclude that IBM Watson’s answers are even more sketchy.
I love that multi billion investment, however. Now about the financial payoff. Watson, any answers?
Stephen E Arnold, October 11, 2016
HonkinNews for October 11, 2016 Now Available
October 10, 2016
The most recent HonkinNews video is now available at this link. Stories include Yahoo’s most recent adventure: A purple light Y-Mart discount of $1 billion dollars on the Verizon purchase offer. Learn how Google Translate handles a Chinese poem about ospreys, not government administration. Included in the seven minute program is information about IBM Watson in the third grade and Bing’s secret to revenue success. These stories and more like the diffusion of the idea of “good enough” search. Direct from Harrod’s Creek in rural Kentucky… HonkinNews for the week ending October 11, 2016.
Stephen E Arnold, October 10, 2016
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