Artificial Intelligence and the New Normal: Over Promising and Under Delivering

June 15, 2018

IBM has the world’s fastest computer. That’s intriguing. Now Watson can output more “answers” in less time. Pity the poor user who has to figure out what’s right and what’s no so right. Progress.

Perhaps a wave of reason is about to hit the AI field. Blogger Filip Piekniewski forecasts, “AI Winter is Well on its Way.” While the neural-networking approach behind deep learning has been promising, it may fall short of the hype some companies have broadcast. Piekniewski writes:

“Many bets were made in 2014, 2015 and 2016 when still new boundaries were pushed, such as the Alpha Go etc. Companies such as Tesla were announcing through the mouths of their CEO’s that fully self-driving car was very close, to the point that Tesla even started selling that option to customers [to be enabled by future software update]. We have now mid 2018 and things have changed. Not on the surface yet, NIPS conference is still oversold, the corporate PR still has AI all over its press releases, Elon Musk still keeps promising self driving cars and Google CEO keeps repeating Andrew Ng’s slogan that AI is bigger than electricity. But this narrative begins to crack. And as I predicted in my older post, the place where the cracks are most visible is autonomous driving – an actual application of the technology in the real world.”

This post documents a certain waning of interest in deep learning, and notes an apparently unforeseen limit to its scale. Most concerning so far, of course, are the accidents that have involved self-driving cars; Piekniewski examines that problem from a technical perspective, so see the article for those details. Whether the AI field will experience a “collapse,” as this post foresees, or we will simply adapt to more realistic expectations, we cannot predict.

Cynthia Murrell, June 15, 2018

IBM: Watson Wizards Available for a New Job?

May 28, 2018

I know that newspapers do real “news.” I know I worked for a reasonably good newspaper. I, therefore, assume that the information is true in the story “Some IBM Watson Employees Said They Were Laid Off Thursday.” The Thursday for those who have been on a “faire le pont” is May 24, 2018.

The write up states:

IBM told some employees in the United States and other countries on Thursday that they were being laid off. The news was reported on websites, which cited social media and Internet posts by IBM employees.

IBM also seems to be taking the reduction in force approach to success by nuking some of the Big Blue team in its health unit. (See “‘Ugly Day:’ IBM Laying Off Workers in Watson Health Group, Including Triangle.”)

I noted this statement in the Cleveland write up:

Since 2012, the Cleveland Clinic has collaborated with IBM on electronic medical records and other tools employing Watson, IBM’s supercomputer. The Clinic and IBM Watson Health have worked together to identify new cancer treatments, improve electronic medical records and medical student education, and look at the adoption of genomic-based medicine.

The issue may relate to several facets of Watson:

  1. Partners do not have a good grasp of the time and effort required to create questions which Watson is expected to answer. High powered smart people are okay with five minute conversations with an IBM Watson engineer, but extend those chats to a couple of hours over weeks, then the Watson thing is not the time saver some hoped
  2. Watson, like other smart systems, works within a tightly bounded domain. As new issues arise, questions by users cannot be answered in a way that is “spontaneously helpful.” The reason is that Watson and similar systems are just processing queries. if one does not know what one does not know, asking and answering questions can range from general to naive to dead wrong in my experience
  3. Watson and similar systems are inevitably compared to Google’s ability to locate a pizza restaurant as one drives a van in an unfamiliar locale. Watson does not work like Google.

Toss in the efficiency of using one’s experience or asking a colleague, and Watson gets in the way. Like many smart systems, users do not want to become expert Watson or similar system users. The smart system is supposed to or is expected to provide answers a person can use.

The problem with the Watson approach is that it is old fashioned search. A user has to figure out from a list of results or outputs what’s what. Contrast that to next generation information access systems which provide an answer.

IBM owns technology which performs in a more intelligent and useful way than the Watson solution.

Why IBM chased the same dream that cratered many firms with key word search technology has intrigued me. Was it the crazy idea that marketing would make search work? IBM Watson seems to be to be a potpourri of home brew code, acquired metasearch technology like Vivisimio, and jacking in open source software.

What distinguished it was the hope that marketing would make Watson into a billion dollar business.

It seems as if that dream has suffered a setback. One weird consequence is the use of the word “cognitive.” Vendors worldwide describe their systems as “cognitive search.”

From my point of view, search and retrieval is a utility. One cannot perform digital work without finding a file, content, or some other digital artifact.

No matter how many “governance” experts, how many “search” experts, how many MBAs, how many content management experts, how many information professionals want search to be the next big thing—search is still a utility. Forget this when one dreams of billions in revenue, and there is a disconnect between dreams and reality.

Effective “search” is not a single method or system. Effective search is not just smart software. Effective search is not a buzzword like “cognitive” or “artificial intelligence.”

Finding information and getting useful “answers” requires multiple tools and considerable thought.

My hunch is that the apparent problems with Watson “health” foreshadow even more severe changes for the game show winners, its true believers, and the floundering experts who chant “cognitive” at every opportunity.

Search is difficult, and in my decades of work in information access, I have not found the promised land. Silver bullets, digital bags of garlic, and unicorn dreams have not made information access a walk in the park.

Cognitive? Baloney. Remember. Television programs like Jeopardy do what’s called post production. A flawed cancer treatment may not afford this luxury. Winning a game show is TV. Sorry, IBM. Watson’s business is reality which may make a great business school case study.

Stephen E Arnold, May 28, 2018

IBM and Distancing: New Collar Jobs in France

May 23, 2018

I have zero idea if the information in the article “Exclusive: IBM bringing 1,800 AI jobs to France.” The story caught my attention because I had read “Macron Vowed to Make France a ‘Start-Up Nation.’ Is It Getting There?” You can find the story online at this link, although I read a version of the story in my dead tree edition of the real “news” paper at breakfast this morning (May 23, 2018).

Perhaps IBM recognizes that the “culture” of France makes it difficult for startups to get funding without the French management flair. Consequently a bold and surgical move to use IBM management expertise could make blockchain, AI, and Watson sing Johnny Hallyday’s Johnny, reviens ! Les Rocks les plus terribles and shoot to the top of YouTube views.

On the other hand, the play may be a long shot.

What I did find interesting in the write up was this statement:

IBM continues to make moves aimed at distancing itself from peers.

That is fascinating. IBM has faced a bit of pushback as it made some personnel decisions which annoyed some IBMers. One former IBM senior manager just shook his head and grimaced when I mentioned the floundering of the Watson billion dollar bet. I dared not bring up riffing workers over 55. That’s a sore subject for some Big Blue bleeders.

I also liked the “New Collar” buzzword.

To sum up, I assume that IBM will bring the New Collar fashion wave to the stylish world of French technology.

Let’s ask Watson. No, bad idea. Let’s not. I don’t have the time to train Watson to make sense of questions about French finance, technology, wine, cheese, schools, family history, and knowledge of Molière.

Stephen E Arnold, May 23, 2018

IBM: Just When You Thought Crazy Stuff Was Dwindling

May 19, 2018

How has IBM marketing reacted to the company’s Watson and other assorted technologies? Consider IBM and quantum computing. That’s the next big thing, just as soon as the systems become scalable. And the problem of programming? No big deal. What about applications? Hey, what is this a reality roll call?

Answer: Yes, plus another example of IBM predicting the future.

Navigate to “IBM Warns of Instant Breaking of Encryption by Quantum Computers: ‘Move Your Data Today’.”

I like that “warning.” I like that “instant breaking of encryption.” I like that command: “Move your data today.”


hog in mud

IBM’s quantum computing can solve encryption problems instantly. Can this technology wash this hog? The answer is that solving encryption instantly and cleaning this dirty beast remain highly improbably. To verify this hunch, let’s ask Watson.

The write up states with considerable aplomb:

“Anyone that wants to make sure that their data is protected for longer than 10 years should move to alternate forms of encryption now,” said Arvind Krishna, director of IBM Research.

So, let me get this straight. Quantum computing can break encryption instantly. I am supposed to move to an alternate form of encryption. But if encryption can be broken instantly, why bother?

That strikes me as a bit of the good old tautological reasoning which leads exactly to nowhere. Perhaps I don’t understand.

I learned:

The IBM Q is an attempt to build a commercial system, and IBM has allowed more than 80,000 developers run applications through a cloud-based interface. Not all types of applications will benefit from quantum computers. The best suited are problems that can be broken up into parallel processes. It requires different coding techniques. “We still don’t know which applications will be best to run on quantum computers,” Krishna said. “We need a lot of new algorithms.”

No kidding. Now we need numerical recipes, and researchers have to figure out what types of problems quantum computing can solve?

We have some dirty hogs in Harrod’s Creek, Kentucky. Perhaps IBM’s quantum cloud computing thing which needs algorithms can earn some extra money. You know that farmers in Kentucky pay pretty well for hog washing.

Stephen E Arnold, May 19, 2018

IBM Watson: Did You Generate These AI Requirements Answers?

May 16, 2018

I read a darned remarkable write up called “The 5 Attributes Of Useful AI, According To IBM.” IBM, of course, has Watson, the billion dollar bet that continues to chase other horses in the artificial intelligence derby. What Facebook and Google lack in marketing, IBM has that facet of grooming expensive horses nailed tighter than a stall barn door.

Let me run through the five attributes of “useful AI” which are explained in the write up:

  1. Managed. I think this means one pays a big outfit to do the engineering, tuning, and servicing of the useful AI. Billability seems to lurk around the edges of this seemingly innocuous term.
  2. Resilient. My hunch is that when the AI goes off the rails and generates nonsense or dead wrong outputs, the useful AI is going to fix itself. See item number 1. If the AI is resilient, why do we need the “managed” approach?
  3. Performant. I first encountered this word in Norway when a person who taught English to hearty Norwegians used it when communication with me. I think it means “works” or “performs in an acceptable manner.” The idea is that the AI system delivers a useful output. Keep in mind the “managed” and “billability” angles, please.
  4. Measureable. I like this idea almost as much as I like precision and recall. However, when one asks Watson how to treat a cancer, it seems to me that the treatment should nuke the cancer. I am on board with statistical analyses, but in the case of a doctor depending on AI for a treatment, the operative number is one and the key value is 100 percent. Your mileage may differ unless you have life threatening cancer.
  5. Continuous. I loop back to “managed” and the notion of “billability.” I like the notion that smart software should operate continuously, but there are challenges associated with “drift” as new content enters the system, the cost of processing real time or near real time flows of information which has a tendency to expand over time, and built in algorithmic biases. Few want to talk about how popular numerical recipes output junk unless tweaked, retrained, tuned, and enhanced. This work is obviously “billable.”

I would point out that one attribute important to me is that the useful AI should generate a beneficial financial positive for the customer. I understand the revenue upside for an outfit like IBM, but AI has an interesting characteristic: The smart software becomes increasingly expensive to maintain and operate in a “useful” manner over time.

If I look at “useful” from IBM’s perspective, the task for the stalwarts in Big Blue is making money from this “useful” software. Seems like it has been slow going.

Stephen E Arnold, May 16, 2018

Amazon: Why Support Blockchain? To Chase IBM? Wrong.

April 30, 2018

In June 2018, I will describe Amazon’s lynch pin approach to intelligence analysis. The “play” has been ignored or overlooked by those who monitor the next generation information access market. At the Telestrategies ISS conference, I will report the DarkCyber and Beyond Search analysts’ assessment of this important Amazon service. The audience for the Telestrategies ISS programs are law enforcement and intelligence professionals. We have developed a for fee webinar which provides details of the Amazon “swing for the fences” approach to a number of intelligence-related services. Personally I was surprised by the audaciousness of the Amazon approach.

In this context, I noted a report in “Amazon’s New Blockchain Service Could Hurt IBM” which misses the main point of the Amazon “invention.” Yes, there is a patent as well as publicly accessible data about this data management play.

The write up explains that Amazon is offering BaaS or Blockchain as a Service. The spin in the write up is the threat which Amazon poses to IBM. From my analysts’ viewpoint, this is just a tiny piece of a much larger story.

What if Amazon is interested in a far larger market than one envisioned by IBM with its arm waving?

Assessing Amazon’s “invention” on the basis of this type of data might be misleading:

Amazon’s decision to launch both the Ethereum and Hyperledger Fabric services means that it wants to straddle the public and private cloud markets with its blockchain services. IBM has a firm grasp of the private on-premise cloud market, but AWS has been gaining ground with Virtual Private Cloud (VPC) services, which isolate sections of AWS’ public cloud for private use. The CIA, for example, already uses a “secret region” of AWS to host its classified data. Therefore, deploying Fabric on AWS’ VPCs could counter IBM’s deployment of Fabric on its on-premise private clouds.

Hmm. Quite a mishmash of assertions and services.

For a different point of view, catch my sessions at the Prague Telestrategies ISS program in Prague. If you want the information now, write benkent2020 at and request information about our online webinar. Coincident with my presentation, my team will release a story in Beyond Search, and we will post a brief video highlighting some of the main points of my presentation.

Oh, with regard to IBM, that company hired an Amazon executive to help IBM catch up. That’s more than worry. That’s reaction to a system which has been under construction since 2011. With a seven year head start, big time vendors involved, and contracts in negotiation, IBM has to do more than poach a manager.

Amazon sells books, right?

Stephen E Arnold, April 30, 2018

IBM at Bat with Blockchain

April 25, 2018

What’s the difference between innovation and desperation?

About a month ago, I read “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.”

Is the idea is that old timers are not able to deliver the zip zip ideas that IBM needs? One of the Beyond Search team said at lunch that management has delivered another setback for IBM. 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.

I noticed a story this morning which illustrates another home run swing for Big Blue. “Blockchain Gets Real? IBM Advances Projects With Walmart & Others” explains that:

IBM has been working on blockchain technology for about three years, and it officially launched a blockchain business about 16 months ago, Gopinath [a vice president of blockchain solutions and research at IBM] says. About 1,500 IBMers are now working on blockchain products and consulting services, he says. Big Blue has developed a blockchain software platform built on open-source Hyperledger software from the Linux Foundation; IBM also helps clients set up and manage their blockchain systems. Thus far, IBM has worked on 400-plus blockchain projects spanning retail, financial services, healthcare, media, the supply chain, and more.

Watson was supposed to be a revenue game changer at IBM. Now IBM is beating the blockchain drum. Can IBM leverage open source technology to make the company a revenue and earnings engine? Let’s ask Watson. Who’s on first?

Patrick Roland, April 25, 2018

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?

Patrick Roland, April 9, 2018

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.

Image result for speed bump

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.

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