IBM and Investor Patience
April 18, 2018
Why have investors apparently lost patience with IBM?
Many reasons. We suggest that Watson and its smart software hyperbole may be contributing factors. To cite one example:
It appears Watson is like a Barbie doll. Barbie is notorious for her numerous careers and varied skilled set from working on the space shuttle to expert fashionista to a school teacher. Watson has a similar career trajectory, simply inject glitter and pink into its motherboard. Watson has now entered the VR/AR game word, says The Next Web in the article, “IBM And Unity Are Teaming Up To Bring Watson’s AI To VR And AR Games.”
IBM and Unity have teamed up to bring Watson’s AI capabilities to the popular gaming engine. Unity is mostly known for Pokemon Go and Star Trek Bridge Crew, but now developers will be able to download the IBM Watson Unity SDK for free. The IBM Watson Unity SDK gives users free access to Watson’s AI suite. The biggest problem with Unity based games is that other than Pokemon Go and Star Trek Bridge Crew most of them have not broken into the mainstream, but Watson’s AI suite could change that.
The potential Watson’s AI brings to Unity goes beyond basic augmented and virtual reality gaming:
“…practicing surgeon could stay immersed in a surgery simulator by using voice control. It’s an immersion breaker for a user to have to turn and either wait for menu popups or stop what they’re doing and grab a game pad to access menus and change ‘tools’ during an exercise.With Watson on board the same hypothetical surgery simulator would function much more like the real world. The user could simply say “Hand me a sponge” and the game engine could process that command using Watson’s speech processing ability.Watson’s voice recognition, speech-to-text, and image recognition features make for a promising addition to the Unity game engine and will, hopefully, propel VR/AR into the mainstream.”
Will this type of assertion get IBM back in the good graces of stakeholders? Watson might or could deliver better games, but revenue, not marketing, is the measure of success.
No success, no patience.
Whitney Grace, April 18, 2018
IBM: Can It Revivify Itself?
April 9, 2018
IBM has been struggling to keep up in a fight with Microsoft, Amazon, Google and other tech giants more suited for twenty-first century commerce. Another bold move by the company recently got it into a ton of hot water, as we discovered from a recent 24/7 Wall Street story, “IBM Hit With Massive Age Discrimination Charges, Undermining CEO Rometty.”
According to the story:
“The news once again will raise the question about the tenure of CEO Ginni Rometty, who has presided over the demise of IBM. The company has suffered quarter after quarter of falling revenue. She has tried unsuccessfully to make IBM a leader in cloud computing. In the meantime, its older software, services and hardware businesses have suffered.”
This is a major setback for IBM atop some other unsavory setbacks. A recent story said that as the company aims to positing its enterprise search for the future, it is acting as its own worst enemy in the planning stages. That seems to be the case we see over and over with IBM, they can’t seem to get out of their own way with this disgraceful age discrimination case or with the general day-to-day, it does not seem unlikely that the behemoth will someday get absorbed into a larger competitor. But who remains a question.
Perhaps IBM can pose that question to Watson? Well, maybe not?
Speeding Up Search: The Challenge of Multiple Bottlenecks
March 29, 2018
I read “Search at Scale Shows ~30,000X Speed Up.” I have been down this asphalt road before, many times in fact. The problem with search and retrieval is that numerous bottlenecks exist; for example, dealing with exceptions (content which the content processing system cannot manipulate).
Those who want relevant information or those who prefer superficial descriptions of search speed focus on a nice, easy-to-grasp metric; for example, how quickly do results display.
May I suggest you read the source document, work through the rat’s nest of acronyms, and swing your mental machete against the “metrics” in the write up?
Once you have taken these necessary steps, consider this statement from the write up:
These results suggest that we could use the high-quality matches of the RWMD to query — in sub-second time — at least 100 million documents using only a modest computational infrastructure.
The path to responsive search and retrieval is littered with multiple speed bumps. Hit any one when going to fast can break the search low rider.
I wish to list some of the speed bumps which the write does not adequately address or, in some cases, acknowledge:
- Content flows are often in the terabit or petabit range for certain filtering and query operations., One hundred million won’t ring the bell.
- This is the transform in ETL operations. Normalizing content takes some time, particularly when the historical on disc content from multiple outputs and real-time flows from systems ranging from Cisco Systems intercept devices are large. Please, think in terms of gigabytes per second and petabytes of archived data parked on servers in some countries’ government storage systems.
- Populating an index structure with new items also consumes time. If an object is not in an index of some sort, it is tough to find.
- Shaping the data set over time. Content has a weird property. It evolves. Lowly chat messages can contain a wide range of objects. Jump to today’s big light bulb which illuminates some blockchains’ ability house executables, videos, off color images, etc.
- Because IBM inevitably drags Watson to the party, keep in mind that Watson still requires humans to perform gorilla style grooming before it’s show time at the circus. Questions have to be considered. Content sources selected. The training wheels bolted to the bus. Then trials have to be launched. What good is a system which returns off point answers?
I think you get the idea.
IBM Lawyers-Up and Other Tech Giants Shiver
March 6, 2018
IBM has not exactly been on the bleeding edge of tomorrow for some years. Still massively important in the tech world, its products just aren’t as sexy as they used to be. Or are they? Turns out some big names have been stealing from Big Blue and that’s about to end, according to a recent GeekWire piece, “IBM Sues Expedia, Alleging Online Travel Giant Built Its Business on Big Blue’s Patents.”
While the title is pretty self-explanatory, here are some important takeaways:
IBM alleges Expedia’s infringements all fall under the umbrella of how online content is delivered, including aspects like ad technology, sign on processes, tracking previous communications with users and more. The lawsuit includes Expedia’s website and mobile apps, as well as its subsidiaries HomeAway, Hotels.com, Hotwire and Orbitz.
IBM is seeking an injunction against Expedia and its subsidiaries from using the patented technology, as well as up to triple the amount of damages awarded in a jury trial. IBM also “seeks royalties on the billions of dollars in revenue that defendants have received based on their infringement of IBM’s patented technology,” according to the lawsuit.
This is not the only iron IBM has in the patent fire. They also recently settled with Priceline for using the patented material. Looks like IBM might be a little more relevant than we gave them credit. It’ll be interesting to see if they can turn this momentum into new activity in 2018. We doubt it.
Patrick Roland, March 6, 2018
IBM Wants Executives to Be Disruptors
March 2, 2018
I read “IBM Tells CIOs to Become Disruptors, Touts Cognitive Services Platform.” Now that’s pretty spectacular advice from IBM. I learned from an IBM executive named Luis Pineda:
We’re provoking them really to act now, before it’s too late, maybe to optimize and increase the agility of their data and cloud infrastructure to create an insight-driven organization. We’re doing this because we believe that only by radically re-imagining their roles as CIO will they become the disruptors, and not be the disrupted. And by doing so they will be able to drive meaningful innovation that will truly transform their business and organization.
Not surprisingly, the suggestion is that IBM Watson is the system which will disrupt.
So far IBM Watson has provided me with some laughs. For IBM it has generated revenues which did not meet the lofty revenue forecasts in the heady days of winning Jeopardy. For employees who have been RIFed, IBM has disrupted—thousands of lives.
What’s fascinating is that jargon and inability to leverage what IBM does that customers want seem to trip over one another. No mention about HAL going back into space, however.
Stephen E Arnold, March 2, 2018
IBM Watson: Just When I Thought Big Blue Was Going to Sell Mainframes
March 2, 2018
I read and marveled at the report called “IBM Watson Is Heading to Space in an 11-Pound Smiling Orb Called CIMON.” I thought IBM went to space with HAL almost 50 years ago. Like IBM’s use of Charlie Chaplin, IBM dips into the past for its new ideas.
I learned:
The orb, dubbed CIMON, short for Crew Interactive Mobile Companion, will be taken to the ISS in June by German astronaut and scientist Alexander Gerst. It has been designed as an experimental assistance system to support astronauts in performing routine work.
Okay, none of that HAL stuff this time around. At least, that’s my assumption.
The write up added:
Manfred Jaumann, head of microgravity payloads at Airbus SE, which designed the hardware, said that “CIMON will be the first AI-based mission and flight assistance system,” a sort of “free flyer, a kind of flying brain” that will interact with, aid and learn from astronauts.
From Jeopardy to cancer to an astronaut’s digital Friday. Amazing.
As the song lyrics say:
You’ll take the lead on each trip we take
Then if I don’t do well
I will permit you to use the brake.
For me, I would pull the plug. Just as Dave did 50 years ago.
Stephen E Arnold, March 2, 2018
IBM Management: The Buffalo Chicken Wing Delivery Method
February 26, 2018
I love IBM. I miss my three IBM PC 704 servers which ran the Threat Open Source Intelligence Gateway for years. Toasty puppies were they. I wondered about IBM’s ability to management development projects when I tried to figure out how Serveraid could lose data so reliably. Oh, well.
I read “IBM Buffalo Billion Project Fails to Deliver.” I know. The association with chicken wings that fail to arrive was not the best metaphor. Perhaps it was the lake effect?
The article’s main idea struck me as IBM’s selling a project and then running into itself. The project was a state funded deal. The idea was to create jobs in booming Buffalo. The article points out:
The company would set up an office downtown, Cuomo announced, with $55 million in state funding for computer equipment and renovations to office space in Key Center at Fountain Plaza. In exchange, IBM promised to create 500 jobs over five years; these positions, one state memo noted, would pay, on average, $70,000 a year. Nothing in IBM’s agreement with the state, however, requires the company to create any particular kind of jobs or specifies how much they will pay.
A former employee described as a “permatemp” without benefits observed:
“‘Y’all know we got bamboozled, right?’”
IBM was to provide services like a customer call center or help desk. The training program reminded me of the IBM documentation to the quad core PC 704s; for example, the article points out:
Their training mostly involved watching PowerPoint presentations. One mislabeled the state Department of Environmental Conservation, calling it the Department of Energy Conservation. Some slides noted that IBM was “still waiting on more information.” Others outlined state programs, only to add “the IBM service desk does not have access to this tool.” Other training sessions took place over speakerphone, sometimes with more than 70 people huddled together, trying to keep quiet so everyone could hear, some taking notes with pen and paper because they were still waiting for their computers.
I noted this interesting factoid in the write up, which, I assume, is actual factual:
The deal with IBM was brokered by former SUNY Polytechnic President Alain Kaloyeros, before his arrest on federal and state corruption charges in late 2016.
Ah, IBM. Let’s ask Watson what’s going on. On second thought, let’s not.
Stephen E Arnold, February 26, 2018
IBM Watson Marketing Breakthrough: Cognitive Solutioning
February 19, 2018
I don’t pay much attention to IBM Watson. I admit that for a while I found the wild and crazy marketing amusing. I do want to point to “If You Don’t Like What IBM Is Pitching, Blame Watson: It’s Generating Sales ‘Solutions’ Now.” The write up allegedly recycles some confidential IBM information. I pulled this item out for future reference:
Internal documents seen by The Register reveal the tech goliath has developed something it calls “cognitive solutioning,” to be deployed when Big Blue is asked to do a job that can’t easily be scoped from its service catalogue.
I solution, you solution, IBM solutions. See the noun works as a “verb.” Amazing.
I am not sure what this passage means, but I circled it in red. It seems to suggest yet another massive achievement by Watson:
One document, which explains “cognitive solutioning” to IBM’s staff, says Big Blue has big plans for the Watson-fuelled service in 2018 and expects it to soon enable “real-time co-creation of solutions with clients” and do so at such speed that IBM services gains an advantage over its rivals. A roadmap for the service calls for a “cognitive solutions designer” to be hard at work in the second half of 2018, fuelled by 10,000 knowledge base articles.
Doesn’t Microsoft have a knowledgebase with lots KB articles, some of which do nifty things with a mouse click. Imagine an IBM KB system operating on global banking installations. Mouth watering solutioning ahead.
Stephen E Arnold, February 19, 2018
IBM Releases Power9 AI and Machine Learning Chip
February 12, 2018
Make no mistake, the new AI processor from IBM has Watson written all over it—but it does move the software into new territory. We get a glimpse from the brief write-up, “IBM Has a New Chip for AI and Machine Learning” at IT Pro Portal. The new chip, dubbed Power9, is now available through IBM’s cloud portal and through third-party vendors and is built into the new AC9222 platform. (See here for a more detailed discussion of both Power9 and AC9222.) Writer Sead Fadilpaši? quotes market analyst Patrick Moorhead, who states:
Power9 is a chip which has a new systems architecture that is optimized for accelerators used in machine learning. Intel makes Xeon CPUs and Nervana accelerators and NVIDIA makes Tesla accelerators. IBM’s Power9 is literally the Swiss Army knife of ML acceleration as it supports an astronomical amount of IO and bandwidth, 10X of anything that’s out there today.
That is strong praise. Fadilpaši? also quotes IBM’s Brad McCredie, who observes:
Modern workloads are becoming accelerated and the Nvidia GPU is a common accelerator. We have seen this trend coming. We built a deep relationship with them and a partnership between the Power system and the GPU. We have a unique bus that runs between the processor and the GPU and has 10x peak bandwidth over competitive systems.
Will the Power9 live up to its expectations? We suspect IBM has reason to hope for success here.
Cynthia Murrell, February 12, 2018
IBM and Algorithmic Bias
January 25, 2018
I read “Unexplainable Algos? Get Off the Market, Says IBM Chief Ginni Rometty.” The idea is in line with Weapons of Math Destruction and the apparent interest in “black box” solutions. If you are old enough, you will remember the Autonomy IDOL system. It featured a “black box” which licensees used without the ability to alter how the system operated. You may also recall that the first Google Search Appliances locked users out as well. One installed the GSA and it just worked—at least, in theory.
This article includes information derived from the IBM content output for the World Economic Forum where it helps to have one’s own helicopter for transportation.
I noted this statement:
“When it comes to the new capabilities of artificial intelligence, we must be transparent about when and how it is being applied and about who trained it, with what data, and how,” the IBM chairman, president and CEO wrote.
I don’t want to be too picky but IBM owns the i2 Analyst Notebook system. If you are not familiar with this platform, it provides law enforcement and intelligence professionals with tools to organize, analyze, and marshal information for an investigation. As a former consultant to i2, I am not sure if the plumbing developed by i2 is public. In fact, IBM and Palantir jousted in court when IBM sued Palantir for improper use of its intellectual property; that is a fancy way of saying, “Palantir engineers tried to figure out how i2 worked.” The case settled out of court and many of the documents are sealed because no one party to the case wanted certain information exposed to bright sunlight.
IBM operates a number of cybersecurity services. One of these has the ability to intercept a voice call and map that call to email and other types of communications. The last time I received some information about this service I had to sign a bundle of documents. The idea, of course, is that much of the technology was, from my point of view, a “black box.”
So what?
The statement by IBM’s CEO is important because it is, in my opi9nion, hand waving. IBM deals in systems which are neither fully understood by some of the IBM experts selling these solutions, and some of the engineers who may know more about the inner working of secret or confidential systems and methods are not talking. An expert knows stuff others do not; therefore, why talk and devalue one’s expertise.
To sum up, talk about making math centric systems and procedures transparent is just noise. The number of people who can explain how systems which emerged from Cambridge University like Autonomy’s Neurolinguistic System or i2’s Analyst Notebook are in short supply.
How can one who does not understand explain how a complex system works. Black boxes exist to keep those which thumbs for fingers from breaking what works.
Talk doesn’t do much to deal with the algorithmic basics:
- Some mathematical procedures in wide use are not easily explained or reverse engineered; hence, the IBM charge that Palantir tried a short cut through the words to the cookie jar
- Most next generation systems are built on a handful of algorithms. I have identified 10 which I explain in my lectures about the flaws embedded in “smart” systems. Each of the most widely used algorithms can be manipulated in a number of ways. Some require humans to fiddle; other fiddle when receiving inputs from other systems.
- Explainable systems are based on rules. By definition, one assumes the rules work as the authors intended. News flash. Rule based systems can behave in unpredictable, often inexplicable ways. A fun example is for you, gentle reader, to try and get the default numbering system in Microsoft Word to perform consistently with regard to left justification of numbered lists.
- Chain a series of algorithms together in a work flow. Add real time data to update thresholds. Watch the outputs. Now explain what happened. Good luck with that.
I love IBM. Always marketing.
Stephen E Arnold, January 25, 2018
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