August 28, 2016
Confused about the jargon marketing professionals hose at you? No need. Navigate to “AI vs Deep Learning vs Machine Learning.” The truth is revealed. Here’s what my take on the definitions is:
- Artificial intelligence is an umbrella term. One can use it for almost any sales pitch.
- Deep learning. This is pattern recognition with human inputs.
- Machine learning is pretty much like deep learning.
There are some other concepts may be found in search and content processing vendors’ slideshows, sale pitches, and marketing collateral; for example:
- Cognitive computing
- Natural language processing.
What do these terms mean? I have no idea. I understand counting entities and using methods to perform query expansion. On a good day, I can name a couple of ways to perform clustering.
This buzzword blizzard just confuses me. Most Star Trek systems require rules and human crafted training. Then every once in a while one has to retrain the smart software. Progress in marketing is outpacing progress in some of the technology described by marketers.
Stephen E Arnold, August 28, 2016
August 17, 2016
I have been compiling publicly available information about Palantir Technologies, the former $20 billion unicorn. One of the factoids I located in my research was Palantir’s use of the notion intelligence augmentation. Palantir tries to make clear that humans are needed to get the most from the Gotham and Metropolitan products. This idea is somewhat old fashioned. There are some firms who explain that their content processing systems are intelligent, automatic, and really smart. As you may know, I think that marketers who suggest a new magic world of software is here and now are full of baloney. For some reason, when I describe a product or service as baloney, the wizards responsible for the product get really annoyed.
Augmented intelligence is a popular phrase. A quick check of my files related to search and content processing, turned up a number of prior uses of the phrase. These range from MondoBrain which offers “the most powerful simplest decision making and problem solving solution” to the slightly more modest write up by Matteo Pasquinelli.
In the intelligence niche, Palantir has been one of the companies bandying about the phrase “augmented intelligence” as a way to make clear that trained personnel are essential to the effective use of the Palantir framework. I like this aspect of Palantir because humans really are needed and many companies downplay that fact.
I read “IBM: AI Should Stand For ‘Augmented Intelligence’.” I love the parental “should” too. IBM, which owns the Palantir precursor and rival Analyst’s Notebook system wants to use the phrase too. Now the world of government intelligence is a relatively small group when compared to the users of Pokémon Go.
IBM, via what seems to be some content marketing, takes this position:
IBM says it is focused on augmented intelligence, systems that enhance human capabilities, rather than systems that aspire to replicate the full scope of human intelligence.
I am okay with this approach to smart software.
The write up adds this onion to the goulash:
IBM also acknowledges that AI must be trustworthy. The company argues that people will develop trust as they interact with AI systems over time, as they have done with ATMs. The key, the company suggests, will be ensuring that systems behave as we expect them to.
I check ATMs to make certain there is no false swiper technology attached to the user friendly gizmo, however.
The write up adds:
AI, IBM concludes, represents a partnership between people and machines, one that may alter the job landscape without eliminating jobs overall. The partnership comes with risks, the company says, but contends that the risks can be managed and mitigated.
My hunch is that IBM’s use of augmented intelligence may be a gentle poke at Palantir. Imagine a presentation before a group of US Army procurement professionals. IBM is pitching IBM Watson, a system consisting of open source software, home brew code, and technologies acquired by acquisition as the next big thing. IBM then tosses in the AI as augmented intelligence bedrock.
Palantir has made a similar presentation and presented Gotham and its integrated software system as an augmented intelligence framework.
How does a savvy US Army procurement professional determine how alike or dissimilar are the IBM and Palantir systems.
My thought about this semantic muddle is that both Palantir and IBM need to use language which makes the system differences more distinctive the way Endeca did. As you may know, Endeca in the late 1990s described its presentation of related content via links as “Guided Navigation.” The company then complained when another firm used its phrase. I think more about Endeca’s policing of this phrase as an innovation than I do Endeca’s computationally intensive approach to content processing.
I know I don’t use “Guided Navigation” when I am rested and talking about facets.
If I were IBM, I would search for lingo that makes sense. If I were Palantir, I would find a way to communicate the Gotham benefits in a distinctive manner.
There are significant differences between IBM Analyst’s Notebook and Palantir Gotham. Using the same phrase to describe each confuses me. I am pretty confident government procurement officials are not confused too much. Is it possible that IBM is having some fun with the AI definition as “augmented intelligence”?
Stephen E Arnold, August 17, 2016
August 16, 2016
We know you want to know everything about Watson. Well, almost everything because you are, gentle reader, a “smart person.” You can get IBM’s collection of information you and other “smart people” definitely want to know. Navigate to this Cubic Zirconia gem of a content marketing “news” story: “IBM Watson: The Smart Person’s Guide.”
What does a “smart person” want to know? The write up answers that question for you. Here’s a run down of the article and its content about Watson:
- Four TechRepublic stories about the origins of Watson, a case study, machine learning for a “smart person”, and a peep into the future
- Five TechRepublic stories about case studies of Watson in action, a write up about what companies do with Watson, photos of products with Watson inside, a glossary of Watson speak, and an answer to the question “What Is Watson?”
- Five TechRepublic and ZDNet stories about IBM declaring a “new era,” the Watson Health medical image initiative, Watson in Cisco routers, an apology for slow revenue growth, and Watson in robot restaurants
- Six articles about the “affect” of Watson including how Watson detects early stage dementia, Watson and health analytics, Watson as a short cut to treating cancer, a partnership with the American Diabetes Association, how Watson delivers personalized customer experiences, and some objective information that says 63 percent of business will benefit from artificial intelligence, recently renamed by IBM to augmented intelligence
- The timeline for all things Watson; for example, seven articles about autonomous vehicles, Cisco again but this time with WebEx, eight universities on the Watson bandwagon, the “saving Macy’s” application of Watson, digital wellness [wait, shouldn’t that article have been in the health care group?], Watson delivering cloud based cyber security, and Watson helping a Spanish bank
- How to license Watson is easy with these articles: Six lessons from an early adopter [Isn’t that a how to?], the Watson ecosystem, the Watson developer cloud, Watson health [wait, doesn’t that belong in the health care dot point too?], Watson university programs [wait, wait, don’t tell me that belongs with the earlier reference to universities on the bandwagon].
All in all the write up is an amazing illustration of how much content marketing IBM is pumping through the TechRepublic channel. That’s good for TechRepublic. How good is this investment for IBM? Who knows.
What is clear is that some more logical clustering of Watson marketing collateral seems to be needed. A question: What if this categorization of items you as a smart person need to know was performed by Watson? Hmm. There are some rough edges. Perhaps the subject matter expert providing the “augmentation” did not focus on his or her job. If fully automated, how accurate is this Watson technology?
Sorry, smart person, I have no answers. That’s because I am not a smart person and I did not read this cornucopia of marketing collateral. You will, right?
Stephen E Arnold, August 16, 2016
August 12, 2016
Star Trek technology was/is designed by prop masters and special effects artists based on preconceived notations of the time. The original Trek series ran on analog, while the franchise reboot has holograms and streamlined ships free of the 1960s “groovy” design. Google wants to make Star Trek technology a reality and in manner ways they have with a search engine and a digital assistant that responds to vocal commands. Is Google getting too big for its britches, however? STAT asked the question in its story, “’Silicon Valley Arrogance’? Google Misfires As It Strives To Turn Star Trek Fiction Into Reality.”
Google wanted to create the Star Trek tricorder, a handheld computer that records, scans, and processes any type of data from soil samples to medical information. Google created a biotech venture, Verily Life Sciences, to invent a cancer scanning tricorder, but the project is not doing so well. The cancer tricorder is only one example of Google’s misfire in medical technology. Verily appears to be working on projects that are more in the realm of science fantasy and are used as marketing devices to promote Google as the “technology company of the future.”
Google wants to maker new scientific inroads in medical technology, pulling on their expertise with big data and their initiative:
“’Part of the Silicon Valley ethos is about changing the world, about disruptive technology, about ignoring existing business models,’ and ‘taking on grand challenges,’ …
‘That’s admirable,’…but in Verily’s case, ‘it also feels pretty quixotic.’”
Fantasy drives innovation, which is why science fiction series like Star Trek are inspiration. Much of the technology from the original Trek series and later installations are available now, but we are still far from making everything from the show a reality. We should not halt experimentation on new technology, but big claims like Google’s are probably best kept silent until there is a working prototype.
There is a Louisville, Kentucky Hidden /Dark Web meet up on August 23, 2016.
Information is at this link: https://www.meetup.com/Louisville-Hidden-Dark-Web-Meetup/events/233019199/
August 10, 2016
WCC is a specialist search and content processing company. The firm maintains a low profile, which sparks my interest. I noted that WCC is hosting an Elm programming language meet up. What’s interesting is the write up announcing this initiative. I have reproduced some of the lingo used to make this meet up known to the fans of WCC and, of course, Elm:
WCC is excited to host this meetup at her headquarter. Being very interested in the latests software development technology and the advancement of knowledge, we are happy to facilitate this meetup at our offices. Elm is a functional programming language for declaratively creating web browser-based graphical user interfaces.
Anyone can misspell a word. But I particularly liked “her headquarter.” I was expecting “the company’s headquarters.”
Stephen E Arnold, August 10, 2016
August 2, 2016
Have you ever wondered if the data resting on your hard drive is safe while you are away from your computer? Have you ever worried that a hacker could sneak into your system and steal everything even when the data is resting (not actively being used)? It is a worry that most computer users experience as the traverse the Internet and possibly leaving themselves exposed. Network World describes how a potential upgrade could protect data in databases, “ A New Update To The NoSQL Database Adds Cryptsoft Technology.”
MarkLogic’s NoSQL database version nine will be released later in 2016 with an added security update that includes Cryptsoft’s KMIP (Key Management Interoperability Protocol). MarkLogic’s upgrade will use the flexibility, scalability, and agility of NoSQL with enterprise features, government-grade security, and high availability. Along with the basic upgrades, there will also be stronger augmentations to security, manageability, and data integration. MarkLogic is betting that companies will be integrating more data into their systems from dispersed silos. Data integration has its own series of security problems, but there are more solutions to protect data in transition than at rest, which is where the Cryptsoft KMIP enters:
“Data is frequently protected while in transit between consumers and businesses, MarkLogic notes, but the same isn’t always true when data is at rest within the business because of a variety of challenges associated with that task. That’s where Cryptsoft’s technology could make a difference. Rather than grappling with multiple key management tools, MarkLogic 9 users will be able to tap Cryptsoft’s embedded Key Management SDKs to manage data security from across the enterprise using a comprehensive, standards-compliant KMIP toolkit.”
Protecting data at rest is just as important as securing transitioning data. This reminds me of Oracle’s secure enterprise search angle that came out a few years ago. Is it a coincidence?
July 31, 2016
Hyperbole? Nah, just another fascinating chunk of content marketing by IBM, the proud owner of Watson. You know Watson. The “system” consisting of goodies from open source, acquisitions, and home brew IBM code.
Navigate to “It’s Elementary, Says (IBM) Watson!” The write up shouts:
Given such abilities, the possibilities of what IBM Watson can do in every industry, are limitless!
The possibilities, enumerated below, contain hashtags to make certain that the word diffuses through hashtaggy social media channels. I bet those Pokémon Go players are thrilled to get these items in their “news” stream too. The possibilities are:
- Send Watson to school. This is a nice way of saying that one must create valid training sets. Then the training sets are provided to the content processing system, the results verified, and then the intake process tuned. Does this sound like Autonomy IDOL’s method? It sure does. Plus, it is an expensive and time consuming process when done with rigor. Take a short cut and the system goes off the rails.
- Oversee Watson’s study. Yep, this is fine tuning, and it involves humans, who want money, time off, benefits, and managerial love. Is this expensive? Yep.
- Getting a grip on things. Now this is a possibility which makes the others in this list appear to be semi coherent. Watson uses “artificial intelligence” to “understand” what’s being said in text entering the system. Okay, I think this means Watson is now indexing content in a useful manner. Isn’t that what IBM iPhrase purported to do a decade ago?
- Solve complex problems in a real world. Okay, now we are getting something. What does Watson suggest to IBM, a company which has reported more than four years of declining revenue? What? I did not hear the answer.
- Learning from experience. I think this means that as Watson solves real world problems like IBM’s declining revenues, Watson bets “better.” How long will stakeholders wait? Yahoo’s stakeholders became unsettled and look what happened? Fire sale at a fraction of what Microsoft offered a few years ago.
I am not convinced about the logic of the write up nor about the “endless possibilities” Watson creates. I am more inclined to think about Amazon, Facebook, and Google as big companies likely to deliver results from smart software. What’s not to like about Amazon drones in the UK, Facebook filtering Wikipedia content, and Google solving death. Smart stuff is everywhere. One doesn’t need Sherlock Holmes to figure this out.
Stephen E Arnold, July 31, 2016
Stephen E Arnold,
July 25, 2016
Sinequa, a French search vendor, is hunting for partners in the US. The news appears in “Sinequa Partner Advantage Program Empowers the Channel to Capitalize on Leading Cognitive Search & Analytics Technology.” If you liked the title of this article, you will love the subtitle:
Company Launches New Partner Program to Drive Cross-Industry Adoption of Cognitive Search & Analytics and Address Growing Customer Demands
Keywords galore. What I noted was the euphony of “leading cognitive search and analytics technology.” A number of outfits are chasing the “cognitive search” pot of gold. Competitors include the champion in declining quarterly revenue IBM. Then there are the assorted machine learning folks at the Alphabet Google thing. Plus there are various and sundry deep learning initiatives appearing on a daily basis from the money crucible in Sillycon Valley; for example, Indico, MetaMind, Ripjar, Synapsify, and, my favorite, Idibon. I just love “idibon.” So many associations from ichibon to bon bon. Good, right?
Partners flock like Zika bearing mosquitoes when there is big money in a reseller/OEM/integrator tie up.
I learned from the Sinequa write up about Sinequa:
Sinequa continues to grow its partnerships with leading global systems integrators and value-add resellers (VARs) as well vendors of enterprise application, cloud and Big Data. In an effort to address rising customer demands from Global Fortune 2000 organizations for turning data into actionable insights, Sinequa extends its worldwide network with partners seeking to enrich their Big Data/analytics offerings in key strategic markets such as banking, defense and security, life sciences, manufacturing, utilities and government. The Sinequa Partner Advantage Program enables channel and service partners to quickly capitalize on the high growth opportunity in cognitive search and analytics. Designed to empower partners with certification programs, technical support and world-class training, Sinequa also offers partners performance-based incentives and marketing support programs…Certified partners access the recently introduced Sinequa ES Version 10. Powered by Machine Learning capabilities at its core, this ground breaking version helps deliver deep analytics of contents and user behavior, offering information with continually improving relevance to users in their work environments.
A point I think is important: Sinequa was founded in 2002. That makes the company 14 years young. Not quite a start up but agile enough when it comes to cognitive technology.
I assume that in today’s economic environment, potential partners will be swarming like the Zika bearing mosquitoes in the river marsh near my home in Harrod’s Creek, Kentucky. These critters seem to fancy my chubby, 72 year old body.
I have noted, however, that some vendors of search are having to work extra hard to close deals. Examples range from Big Blue in Union Square to SLI Systems in New Zealand and parts in between.
The idea of partnering is a good one. Endeca rose to its legitimate $100 million plus in search revenue with its carefully crafted partnering program. On the other hand, the Google Search Appliance partners continue to regroup because the wiser minds at Mother Google killed off the pricey Google Search Appliance. I treasure my print out of the GSA schedule with the five and six digit license fees for the wonderful GB 7007 and 9009 models. Imagine a locked down appliance for the price of a pre acquisition Autonomy IDOL license. Then when the document capacity of the search appliance was reached, a customer could license more Google Search Appliances. I found this business model interesting because taxi meter pricing is often an issue for chief financial officers who want to budget for certain products and services.
The upside of partnerships is that, as Endeca learned, unusual opportunities can be discovered. Once the deal is closed, the lucky partner has an opportunity to tailor the search system to meet the needs of the customer. Once up and running, life is good. Renewals, customization, consulting, maintenance fees, and other oddments make a search vendor’s life one of comfort and joy. The downsides include lawsuits, squabbles, and disruptions from competitors.
Worth watching how Sinequa maneuvers in the US market. Other French search vendors have found the costs and cultural issues a bit of a headache. Examples range from Antidot, Pertimm, and Exalead among others. Do you use Qwant?
Stephen E Arnold, July 25, 2016
July 25, 2016
For anyone following the development of artificial intelligence, I recommend checking out the article, “How Google Plans to Solve Artificial Intelligence” at MIT Technology Review. The article delves into Google’s DeepMind project, an object of renewed curiosity after its AlphaGo software bested the human world champion of the ancient game Go in March.
This Go victory is significant, because it marks progress beyond the strategy of calculating different moves’ possible outcomes; the game is too complex for that established approach (though such calculations did allow IBM’s DeepBlue to triumph over the world chess champion in 1997). The ability to master Go has some speaking of “intuition” over calculation. Just how do you give software an approximation of human intuition? Writer Tom Simonite tells us:
“Hassabis believes the reinforcement learning approach is the key to getting machine-learning software to do much more complex things than the tricks it performs for us today, such as transcribing our words, or understanding the content of photos. ‘We don’t think just observing is enough for intelligence, you also have to act,’ he says. ‘Ultimately that’s the only way you can really understand the world.’”
“DeepMind’s 3-D environment Labyrinth, built on an open-source clone of the first-person-shooter Quake, is designed to provide the next steps in proving that idea. The company has already used it to challenge agents with a game in which they must explore randomly generated mazes for 60 seconds, winning points for collecting apples or finding an exit…. Future challenges might require more complex planning—for example, learning that keys can be used to open doors. The company will also test software in other ways, and is considering taking on the video game Starcraft and even poker. But posing harder and harder challenges inside Labyrinth will be a major thread of research for some time, says Hassabis. “It should be good for the next couple of years,” he says.”
The article has a video of DeepMind’s virtual labyrinth you can check out, if you’re curious. (It looks very much like an old Windows screen saver some readers may recall.) Simonite tells us that AI firms across the industry are watching this project carefully. He also points to some ways DeepMind is already helping with real-world problems, like developing training software with the U.K.’s National Health Service to help medical personnel recognize commonly missed signs of kidney problems.
See the article for much more about Google’s hopes and plans for DeepMind. Simonite concludes by acknowledging the larger philosophical and ethical concerns around artificial intelligence. We’re told DeepMind has its own “internal ethics board of philosophers, lawyers, and businesspeople.” I think it is no exaggeration to say these folks, whom Google indicates it will name someday soon, could have great influence over the nature of our future technology. Let us hope Google chooses wisely.
Cynthia Murrell, July 25, 2016
There is a Louisville, Kentucky Hidden Web/Dark Web meet up on July 26, 2016. Information is at this link: http://bit.ly/29tVKpx.
July 15, 2016
The article on Matthias Kirschner’s blog titled US Government Commits to Publish Publicly Financed Software Under Free Software Licenses relates the initiative in the draft policy involving governmental support for increased access to tailored software code built for the Federal Government. Kirschner is the President of the Free Software Foundation Europe, and thereby is interested in promoting the United States’ new policy in the European Union. The article explains,
“The Source Code Policy is intended for efficient use of US taxpayers’ money and reuse of existing custom-made software across the public sector. It is said to reduce vendor lock-in of the public sector, and decrease duplicate costs for the same code which in return will increase transparency of public agencies. The custom-build software will also be published to the general public either as public domain, or as Free Software so others can improve and reuse the software.”
Kirschner believes in empowering people by providing this sort of software, and the US government appears to be equally enthusiastic about promoting innovation rather than redundant software purchases. There are also examples of how non-techy people can use open source resources on the White House article about the draft policy. That article lists tools like free housing counselors, sexual assault data, and even college research through College Scorecard. All in all, this seems like a no-brainer.
Chelsea Kerwin, July 15, 2016
There is a Louisville, Kentucky Hidden Web/Dark
Web meet up on July 26, 2016.
Information is at this link: http://bit.ly/29tVKpx.