Cognos: Now Transforming Business After Only 50 Years
May 3, 2019
It is 1969, and Cognos officially opened for business. That was a half century ago. Over the years, Cognos in its 50 years of “transformation” has absorbed a number of other technologies. Anyone remember Databeacon, the mid market analytics outfit. Cognos strikes me as an umbrella brand. According to CIO’s article “5 Ways IBM Cognos Analytics Is Transforming Business,” IBM’s Cognos Analytics has integrated the artificial intelligence capabilities of IBM Watson Analytics.
Okay, 50 years, much thrashing, and IBM is not on a part with the zippier outfits like DataRobot’s Eureqa. The idea of transforming is interesting, but I am not sure I buy into what looks to me like an example IBM marketing and PR. Sorry, CIO. I am just as suspicious as my neighbors here in Harrod’s Creek.
Here are the transforming things:
- Maximizing charitable donations (No, I am not kidding.)
- Optimizing retail operations with purchasing analytics. (What about Amazon’s data for merchants?)
- Leveraging data to maximize fan engagement. (No, I am not making this up.)
- Predicting audience viewing preferences.
- Deploying data science to keep salmon healthy. (Watson may not be a winner in the cancer thing, but it appears to work on fish.)
After 50 years, the write up points to these examples or use cases as transformational. Amazing.
Eureka may not capture what Cognos with Watson can deliver. The experience, however, could cause DataRobot’s phone to ring.
PS. What’s even more amazing, one of the DarkCyber team had to register to read what is marketing collateral. Interesting.
Stephen E Arnold, May 3, 2019
IBM Revenue by Country
May 1, 2019
DarkCyber spotted an interesting graph generated by DazeInfo. “IBM Revenue by Country” illustrates some of the economic consequences of IBM’s billion dollar bets. First, the US accounted for 37 percent of IBM’s revenue. Surprisingly, Japan generated about 11 percent of the company’s 2018 revenue. In 2004 IBM’s revenue from Japan amount to $12.3 billion. At the end of 2018, revenue from Japan was about $8.5 billion. International revenue in the last three years is also stagnant or declining. Watson, what can be done to remediate these declines? Watson, Watson, are you there? Can you hear me? Are you in a meeting with James Holzhauer, the professional sports gambler, who is winning on Jeopardy. You won once too. Do you remember Charles Van Doren?
Stephen E Arnold, May 1, 2019
IBM: Drugs, Web Pages, and Watson
April 22, 2019
I read “Watson For Drug Discovery”. I don’t pay much attention to IBM’s assertions about its IBM Watson technology. The Jeopardy thing, the HRBlock thing, and the froth whipped up about smart software bored me.
This story was a bit different because, if it is accurate, it reveals a lack of coordination within a company which once was reasonably well organized. I worked on indexing the content of the IBM technical libraries and oversaw the leasing of certain data sets to Big Blue for a number of years. That IBM — despite the J1, J2, and J3 charging mechanism — was a good customer and probably could have made New York commuter trains run on time. (Well, maybe not.)
The Science Magazine story focuses on IBM pulling out of selling Watson to invent drugs. I mean if anyone took a look at the recipes Watson cooked up and memorialized in the IBM cook book, drugs seemed to be a stretch. Would you like tamarind for your cancer treatment? No, possibly another spice?
The factoid I noted in the article is that even though the drug thing is history, IBM keeps or kept its Web pages touting the Watson thing. I snapped this screen shot at 641 am US Eastern time on April 22, 2019. Here it is:
The Science Magazine write up (which I assume is not channeling its inner Saturday Night Live) states:
The idea was that it [Watson} would go ripping through the medical literature, genomics databases, and your in-house data collection, finding correlations and clues that humans had missed. There’s nothing wrong with that as an aspirational goal. In fact, that’s what people eventually expect out of machine learning approaches, but a key word in that sentence is “eventually”. IBM, though, specifically sold the system as being ready to use for target identification, pathway elucidation, prediction of gene and protein function and regulation, drug repurposing, and so on. And it just wasn’t ready for those challenges, especially as early as they were announcing that they were.
Failure I understand. The inability to manage the Web site is a bit like screwing up Job Control Language instructions. When I worked in the university computer lab, that was a minimum wage student job, dead easy, and only required basic organizational and coordination skills.
IBM seems to have lost something just as it did when it allegedly fired old timers to become the “new” IBM. Maybe the old IBM has something today’s IBM lacks?
Stephen E Arnold, April 22, 2019
IEEE Spectrum Embraces Business Analysis: IBM Watson and Health
April 8, 2019
I spotted a link to “How IBM Watson Overpromised and Under delivered on AI Healthcare.” I read the article and found it reasonably balanced. What surprised me was the fact that the editors of IEEE Spectrum believed that this particularly collection of information should be published for the magazine’s and online audience. My suspicion is that IBM was promoting its technology in a manner that was egregious. IEEE was reminding its readers about veering from technical facts into the wild and crazy world of toothpaste and dandruff shampoo marketing. Then I realized the IEEE Spectrum was explaining an example digital snake oil:
I circled in Big Blue marker this passage:
Outside of corporate headquarters, however, IBM has discovered that its powerful technology is no match for the messy reality of today’s health care system. And in trying to apply Watson to cancer treatment, one of medicine’s biggest challenges, IBM encountered a fundamental mismatch between the way machines learn and the way doctors work.
Translation: Reality is different from a demo. When demos are built on software which has proven problematic for decades, one wonders how the square peg in the round hole gets funded.
I circled this statement:
… Even today’s best AI struggles to make sense of complex medical information. And encoding a human doctor’s expertise in software turns out to be a very tricky proposition. IBM has learned these painful lessons in the marketplace, as the world watched. While the company isn’t giving up on its moon shot, its launch failures have shown technologists and physicians alike just how difficult it is to build an AI doctor.
IEEE Spectrum does not use the word “desperation” but it applies. The reality, from my point of view, is that finding information and answering questions is difficult. Google pulls off a version of question answering by hooking relevance to behavior and possibly relevant advertisements. Precision and recall are not part of Google or other commercial search vendors’ vocabulary today.
But answering questions doesn’t work all that well today. Sorry Google.
“Regular” search— particularly search based on open source software, some home brew code, and acquired technology — is difficult to make work across different types of content and use cases. The dust up between HP and Autonomy is one example of what happens when “logical” explanations don’t apply to search and retrieval. There are other examples too. Just ask a Fast Search & Transfer executive who skirted serious jail time.
IEEE Spectrum’s article drives home failure this way:
In a final blow to the dream of an AI super doctor, researchers realized that Watson can’t compare a new patient with the universe of cancer patients who have come before to discover hidden patterns.
Translation: Watson doesn’t work. But the article finds some sparkles in the mine tailings. Note: A few sparkles.
The print version of the article is titled, “Watson, Heal Thyself.”
The title should be: “IBM: Stick with What Works”. The mainframes are okay. The i2 and Cybertap technology is pretty good.
The Watson thing. Wow, pretty crazy expensive and sufficiently off the rails to motivate IEEE Spectrum to embrace the baloney making methods of the Harvard Business Review.
My take on the essay? IEEE Spectrum is saying, “EEs, don’t do this hyperbole charged approach when pushing your technology toys.” News flash: The EEs will ignore this plea when big money is on the table.
Stephen E Arnold, April 8, 2019
IBM and Oldsters
March 29, 2019
I can hear the question posed to IBM Watson now, “Watson, is it okay to fire older employees in order the make room for younger, less expensive workers?”
I even can anticipate the IBM Watson answer, “Yes.”
IBM Watson is smart software, but it does not do as well providing human resource outputs as it does with generating recipes which require tamarind.
How do I know?
I read “IBM Sued By Former Employees For Alleged Illegal Firing.” I learned from the article:
IBM is being sued by a group of its former employees for allegedly laying them off for their age.
The write up added what seems obvious to a human like me but probably a nuance unnoticed by IBM’s Watson:
The lawyers of the complainants added that their main case against IBM would be a major age-discrimination lawsuit. They said that top executives of the company “took the calculated risk of openly breaking the law” in order to cover up substantial, targeted layoffs of its older workers.
IBM Watson may need a bit more training, particularly information related to employment laws and regulations.
Stephen E Arnold, March 29, 2019
RedMonk and Its Assessment of IBM as an Open Source Leader
March 24, 2019
I read “The RedMonk Programming Language Rankings: January 2019.” The analysis was interesting and contained one remarkable assertion and one probably understandable omission. The guts of the report boiled down, in my opinion, to a reminder to job hunters. If you want to increase your chances of getting hired, know:
1 JavaScript
2 Java
3 Python
4 PHP
5 C#
But the surprising statement in the write up was this one:
IBM remains at the forefront of open source innovation.
Now the omission. If IBM is in the forefront, where is Amazon? The company has made an effort to support most of the widely used open source software. Plus, the company appears to be taking tactical steps to close or capture open source.
From my vantage point, Amazon is taking a more “innovative” approach to open source. Granted Amazon’s “approach” may be a milestone in the company’s enhanced walled garden approach to core software systems. IBM’s approach seems little more than Big Blue’s attempt to give back and convince the open source community that it is not the IBM of its mainframe heritage.
Stephen E Arnold, March 24, 2019
New CIA Chief Information Officer: Watson, Who Is It?
March 19, 2019
The answer comes not from IBM Watson. “CIA Announces New Chief Information Officer” reveals that Juliane Gallina, an IBM professional has landed the job. DarkCyber finds this interesting for three reasons.
Aurora, which means dawn and $500 million for one system, may be a new technology the CIA explores.
First, Amazon’s policeware found some traction in that government agency. IBM covets US government work. Amazon may find that Gallina may ask different questions in her tenure.
Second, IBM Federal Systems is the poster child for old-school government contracting. The idea within some sectors of the US government is to find a new-school approach. Gallina may have some interesting ideas about how next-generation systems are selected, shaken down, and made operational.
Third, Gallina has intelligence sector experience. Presumably that experience will make it easier to determine which units can best be served by specific technologies. Will that insight match the diverse community of interests within the CIA?
The appointment is going be one closely watched by those within and outside the Beltway. Perhaps there will be a new technology dawn at the agency. Aurora, it’s called.
Stephen E Arnold, March 19, 2019
IBM and Its Farm Team Model
March 6, 2019
IBM and SUNY Poly have pooled their talents to create an innovating institute: a brand new artificial intelligence lab in Albany, New York. Times Union has the details in the article, “IBM, SUNY Poly Creating An Artificial Intelligence Center In Albany.” The new AI lab is only one part of a $2 billion commitment IBM has made to New York University.
The deal outlines that Empire State Development will provide SUNY with a $300 million grant over five years for the AI Hardware Center. As a trade, IBM will remain at SUNY Poly’s Center for Semiconductor Research until 2023. IBM’s spending over the period will amount to $2 billion and will make New York one of the top places for AI.
We learned:
“ ‘New York has always been at the forefront of emerging industries, and this private sector investment to create a hub for artificial intelligence research will attract world-class minds and drive economic growth in the region,’ Gov. Andrew M. Cuomo said in a statement. “Artificial intelligence has the potential to transform how we live and how businesses operate, and this partnership with IBM will help New York stay on the cutting edge developing innovative technologies.’”
The AI Hardware Center is only one of many AI institutes, among them are Rensselaer Polytechnic Institute, Applied Materials, and Tokyo Electron. IBM will also spend $30 million on AI programs at SUNY schools, while SUNY will contribute $25 million as well. SUNY wants all of its schools to have closer collaboration and it will be part of a new education model.
Is this a “farm to table” approach to innovation? Watson, what’s the answer?
Whitney Grace, March 6, 2019
IBM: Excited about the Press Coverage of Think
March 5, 2019
Interesting back patting in this IBM publicity about IBM getting publicity. You can find the happy happy information in “How Press Reacted to the Data and AI News from Think 2019.” DarkCyber was disappointed in the coverage of the Watson vs human debate. Unlike Jeopardy, post production was not available. The human judges decided the human beat IBM Watson.
However, DarkCyber provided an analysis of the debate. The human judges were like the three stooges. The debate should have been judged by artificial intelligence systems from Google, Amazon, and Microsoft. The final tally would have fallen to Facebook’s system.
If you missed our analysis, you can find it at this link.
Stephen E Arnold, March 5, 2019
Oldster Teaches Young Dogs Some Tricks
March 1, 2019
It can be easy to forget just how long IBM has been around compared to other huge tech companies, but that venerable giant was incorporated in 1911. An article at The Conversation examines “Lessons from IBM for Google, Amazon and Facebook.” Writer and former IBM employee James Cortada, author of the recently published book, IBM: The Rise and Fall and Reinvention of a Global Icon, shares his observations. He observes:
“There is a difference between individual products – successive models of PCs or typewriters – and the underlying technologies that make them work. Over 130 years, IBM released well over 3,600 hardware products and nearly a similar amount of software. But all those items and services were based on just a handful of real technological advances, such as shifting from mechanical machines to those that relied on computer chips and software, and later to networks like the internet. The transitions between those advances took place far more slowly than the steady stream of new products might suggest. These transitions from the mechanical, to the digital, and now to the networked reflected an ever-growing ability to collect and use greater amounts of information easily and quickly. IBM moved from manipulating statistical data to using technologies that teach themselves what people want and are interested in seeing.”
The write-up goes into more depth on the progression of IBM advances, emphasizing that the company’s success comes more from developing technologies over time than from sudden breakthroughs. Cortada notes that, unlike IBM, Microsoft, and Apple, Amazon, Google, and Facebook have yet to evolve away from their original functions. Those internet-born companies, he advises, can last out the century if, and only if, they adapt to evolving technologies as IBM has done.
Cynthia Murrell, March 1, 2019
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