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
Watson Weakly: Recruitment the Smart Way
February 26, 2019
IBM is working overtime to become the cloud alternative to Amazon. IBM Watson is back to recipes, health care, and background noise. IBM, however, knows how to capture the attention of the DarkCyber and Beyond Search team in rural Kentucky.
We noted an article in the Register, an online publication, with the interesting title “IBM So Very, Very Sorry after Jobs Page Casually Asks Hopefuls: Are You White, Black… or Yellow?”
The Register asserts:
IBM has apologized after its recruitment web pages asked applicants whether their ethnicity was, among other options, the racial slurs Yellow and Mulatto.
The article describes the wording as a “baffling error.” My hunch is that either IBM Watson or one of his acolytes consumed outputs with the diligence once expects of millennials and smart software, possibly working in tandem.
An IBM professional is quoted as telling the Register:
“Those questions were removed immediately when we became aware of the issue and we apologize. IBM hiring is based on skills and qualifications. We do not use race or ethnicity in the hiring process and any responses we received to those questions will be deleted. IBM has long rejected all forms of racial discrimination and we are taking appropriate steps to make sure this does not happen again.”
Watson? What about that cancer diagnosis? What about inappropriate questions? What about those old people who used to work in personnel?
Stephen E Arnold, February 26, 2019
IBM Debate Contest: Human Judges Are Unintelligent
February 12, 2019
I was a high school debater. I was a college debater. I did extemp. I did an event called readings. I won many cheesey medals and trophies. Also, I have a number of recollections about judges who shafted me and my team mate or just hapless, young me.
I learned:
Human judges mean human biases.
When I learned that the audience voted a human the victor over the Jeopardy-winning, subject matter expert sucking, and recipe writing IBM Watson, I knew the human penchant for distortion, prejudice, and foul play made an objective, scientific assessment impossible.
Humans may not be qualified to judge state of the art artificial intelligence from sophisticated organizations like IBM.
The rundown and the video of the 25 minute travesty is on display via Engadget with a non argumentative explanation in words in the write up “IBM AI Fails to Beat Human Debating Champion.” The real news report asserts:
The face-off was the latest event in IBM’s “grand challenge” series pitting humans against its intelligent machines. In 1996, its computer system beat chess grandmaster Garry Kasparov, though the Russian later accused the IBM team of cheating, something that the company denies to this day — he later retracted some of his allegations. Then, in 2011, its Watson supercomputer trounced two record-winning Jeopardy! contestants.
Yes, past victories.
Now what about the debate and human judges.
My thought is that the dust up should have been judged by a panel of digital devastators; specifically:
- Google DeepMind. DeepMind trashed a human Go player and understands the problems humanoids have being smart and proud
- Amazon SageMaker. This is a system tuned with work for a certain three letter agency and, therefore, has a Deep Lens eye to spot the truth
- Microsoft Brainwave (remember that?). This is a system which was the first hardware accelerated model to make Clippy the most intelligent “bot” on the planet. Clippy, come back.
Here’s how this judging should have worked.
- Each system “learns” what it takes to win a debate, including voice tone, rapport with the judges and audience, and physical gestures (presence)
- Each system processes the video, audio, and sentiment expressed when the people in attendance clap, whistle, laugh, sub vocalize “What a load of horse feathers,” etc.
- Each system generates a score with 0.000001 the low and 0.999999 the high
- The final tally would be calculated by Facebook FAIR (Facebook AI Research). The reason? Facebook is among the most trusted, socially responsible smart software companies.
The notion of a human judging a machine is what I call “deep stupid.” I am working on a short post about this important idea.
A human judged by humans is neither just nor impartial. Not Facebook FAIR.
An also participated award goes to IBM marketing.
IBM snagged an also participated medal. Well done.
Stephen E Arnold, February 13, 2019
With Q, Whither Watson?
January 20, 2019
It was a trying summer for IBM’s Watson as its Oncology software received some harsh criticism. Will new leadership improve the program? We learn IBM replaced Watson Health’s former head, Deborah DiSanzo, with John Kelly, previously their senior V.P. of Cognitive Solutions and Research, from Computerworld’s article, “Did IBM Overhype Watson Health’s AI Promise?” We would say the answer to that rhetorical question is, you bet!
Writer Lucas Mearian describes the troublesome July report published in Stat News. That report revealed that Watson Oncology, which is being used in several real-life healthcare facilities, had recommended “unsafe and incorrect” treatments for hypothetical patients. The Computerworld article touches on the company’s defense (or denial, depending on who you listen to), as well as covering some early problems that plagued the program. See the piece for those details. We are reminded that it takes time to fully train machine learning software, and told the AI has simply not had enough time or quality data to meet the hype generated by the sales team. Not yet.
The article closes with a look ahead, citing IBM’s relatively recent purchases of healthcare data analytics-firm Explorys, patient communications company Phytel, and Truven Health Analytics. Quoting Cynthia Burghard of IDC Health Insights, Mearian writes:
Upon completing all three acquisitions, IBM boasted its Watson Health Cloud housed “one of the world’s largest and most diverse collections of health-related data, representing an aggregate of approximately 300 million patient lives acquired from three companies. They all in their own right, before they were acquired, were very successful companies and had good, strong, loyal client bases and were plugging along.”… In late October, IBM announced plans to seed its new hybrid cloud model for Watson by first moving data from insurance payer systems. For that, Truven will be key. Once payer data is moved to the hybrid cloud, the electronic medical records (EMRs) acquired through the Explorys acquisition will follow, Kelly said.
IBM is not the first company to have its sales team outrun its developers, with an IBM quantum computer ready for prime time, what happens when one combines the two?
One possible answer is more marketing.
Cynthia Murrell, January 20, 2019
IBM Shares Big Data Analytics Test Results
January 12, 2019
Big data, big data, big data! Why does everyone assume that big data analytics is going to save the world? There are limited to big data’s power and most related projects have an 85% failure rate, according to Gartner. One reason is that few people know how to correctly implement big data projects, including vendors. There is hope on the horizon for big data companies, because IBM is making itself a guinea pig.
According to the Silicon Angle’s article, “IBM Is Its Own AI Guinea Pig, Shares Successes From The Test Results.” IBM’s Big Blue has tested big data businesses and it has recorded its failures and successes in tools, technologies, and working methods. IBM is packaging what Big Blue has learned and selling it to customers.
“ ‘What we can do is pull together the right breadth and depth of IBM resources, deploy it and customize it to customer needs and really hopefully accelerate and apply a lot of what we’ve learned, a lot of what our clients have learned to accelerate their own artificial intelligence transformation journey,’ said Caitlin Halferty (pictured, left), client engagement executive, global chief data office at IBM.”
IBM’s big data secret is metadata, because to have the right data governance plan you need to have the right metadata. IBM has a tool for that:
“IBM showcased its automated metadata generation tool at the summit. It leverages automation and AI to slice through some dense metadata-curation blocks. It shortens the often tedious, manual process of data labeling, she said. This helps data officers begin a project with clean, labeled data from the get-go.”
IBM’s key for big data success is buying their big data package and automated metadata tool. How much are the price tags on those? Also even if you do cough up the greenbacks for them do you actually know how to use the data?
Whitney Grace, November 22, 2018
The First Home Quantum Computer?
January 9, 2019
I read “IBM Unveils Its First Commercial Quantum Computer.” The write up stated with no trace of sarcasm:
we’re not quite there yet, but the company also notes that these systems are upgradable (and easy to maintain).
Gentle reader, do you know how to maintain a cryogenic system? No background in low temperature physics? No experience working with super cooled fluids? Hey, no problemo. IBM offers services too.
The write up points out that IBM wants the quantum computer to be a work of art. How about delivering useful computing capability?
Imagine this in your WeWork space:
It’s a nine-foot-tall and nine-foot-wide airtight box, with the quantum computing chandelier hanging in the middle, with all of the parts neatly hidden away.
What is more interesting is that IBM rolled out this product at the consumer electronics show.
Quick buy IBM stock. This practical device will deliver:
Games? No.
Applications? No.
Visualizations? No.
Er, PR? Yes.
Stephen E Arnold, January 9, 2019
IBM at the Consumer Electronic Show
January 6, 2019
Yep, IBM is a consumer product company. I know this because I read “LA Sues Weather Channel App Over Stealthy Data Collection.” Consumer centric outfits like Facebook and Google may operate this way. If IBM is indeed sucking and selling data from is Weather Channel App, it too must be a consumer products’ company.
I noted “Struggling IBM Uses CES to Reinvent Itself.” I assumed that that reinvention was selling data. But, no, once again I was incorrect, a common failing.
I learned from the write up:
At CES, Rometty is expected to emphasize IBM’s (NYSE: IBM) undisputed AI chops along with its aggressive moves into the hybrid cloud market and quantum computing. But the underlying theme will be what the company characterizes as “new data,” and using AI and cloud platforms to “refine” data into something useful.
I thought it was a somewhat squishy marketing opportunity, a way to disappoint stakeholders, and a cloud of fog generated about mainframes actually selling.
No CES for me. My hunch is that those seeking gadgets will have a tough time hauling away Watson on a laptop or a desktop IBM quantum computer.
See, IBM does do consumer products as long as one defines consumer in a somewhat narrow sense.
But that sneaky app thing is promising. Isn’t the former head of the Weather Channel now head of Watson. The IBM revolving door makes me dizzy.
Stephen E Arnold, January 6, 2019
IBM: Sharing Wisdom
January 3, 2019
Apparently, it does not take just one white paper to convince people that IBM is number one—it takes 10. That is the number of publications the company shares on its AI Research page, “The New Frontiers of AI: Selected IBM Research AI Publications from 2018.” The introduction to the collection reads:
“Much of the recent progress in AI has relied on data-driven techniques like deep learning and artificial neural networks. Given sufficiently large labeled training data sets and enough computation, these approaches are achieving unprecedented results. As a result, there has been a rapid gain on ‘narrow AI’ – tasks in areas such as computer vision, speech recognition, and language translation. However, a broader set of AI capabilities is needed to progress AI towards solving real-world challenges. In practice, AI systems need to learn effectively and efficiently without large amounts of data. They need to be robust, fair and explainable. They need to integrate knowledge and reasoning together with learning to improve performance and enable more sophisticated capabilities.
We also noted:
“Where are we in this evolution? While ‘general AI’ – AI that can truly think, learn, and reason like a human- is still within the realm of science fiction, ‘broad AI’ that can learn more generally and work across different disciplines is within our reach. IBM Research is driving this evolution. We have been a pioneer of artificial intelligence since the inception of the field, and we continue to expand its frontiers through our portfolio of research focused on three areas: Advancing AI, Scaling AI, and Trusting AI.”
As the echoes of IBM tooting its own horn linger, one can glean some interesting information from the documents presented. The papers are broken into color-coded categories—Advancing AI, Scaling AI, and Trusting AI. A couple of the simpler titles include “Listening Comprehension over Argumentative Content” and “Training Deep Neural Networks with 8-bit Floating Point Numbers.” Navigate to the post for all the (very) technical wisdom.
Cynthia Murrell, January 3, 2019
Apple and IBM Try to Defy Gravity
December 21, 2018
We find it a bit brazen for IBM to be pontificating about trust after Watson Health’s recent marketing missteps. Still, on her recent visit to Brussels, that company’s CEO joined the chorus criticizing certain other tech giants for violating users’ privacy. Fortune reports, “A ‘Trust Crisis:’ IBM CEO Ginni Rometty Joins Apple’s Tim Cook in Slamming Tech Abuse of User Data.” She even went so far as to suggest the EU strengthen its laws to hold companies responsible for all content that crosses their platforms. We are informed:
“Without naming company names, Rometty pointed to the ‘irresponsible handling of personal data by a few dominant consumer-facing platform companies’ as the cause of a ‘trust crisis’ between users and tech companies, according to an advanced copy of her remarks. Rometty’s comments, given at a Brussels event with top EU officials Monday, echoed recent statements by Apple CEO Tim Coo, who in October slammed Silicon Valley rivals over their use of data, equating their services to ‘surveillance.’…
We also noted this statement:
“Seeking to separate IBM—which operates primarily at a business-to-business level—from the troubled tech companies, Rometty said governments should target regulation at consumer-facing web platforms, like social media firms and search engines.”
Certainly, IBM executives and shareholders would be quite pleased to see regulations focus on consumer-facing companies and away from B2B entities like them. Rometty offers this statement to support her position:
“The power dynamic is very different in the business-to-business markets. Tackling the real problem means using a regulatory scalpel, not a sledgehammer, to avoid collateral damage that would hurt the wider, productive, and more responsible parts of the digital economy.”
Interesting perspective. Cook’s similar criticisms were also made in Brussels, in October. Does he hope to divert attention from Apple app store monopoly concerns? To be sure, throwing shade at the competition can redirect consumer, and regulatory, fury. The pot will always call the kettle black, it seems.
Cynthia Murrell, December 21, 2018
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