Bottlenose: Not a Dolphin, Another Intelligence Vendor
December 15, 2014
Last week, maybe two weeks ago, I learned that KPMG invested in Bottlenose. The company say that the cash will “take trend intelligence global.” The company asserts here:
We organize the world’s attention and emotion.
I am, as you may know, am interested in what I call NGIA systems. These are next generation information access systems. Instead of dumping a list of Google-style search results in front of me, NGIA systems provide a range of tools to use information in ways that do not require me to formulate a query, open and browse possibly relevant documents, and either output a report or pipe the results into another system. For example, in one application of NGIA system functions, the data from a predictive system can be fed directly into the autonomous component of a drone. The purpose is to eliminate the time delay between an action that triggers a flag in a smart system and taking immediate action to neutralize a threat. NGIA is not your mother’s search engine, although I suppose one could use this type of output input operation to identify a pizza joint.
I scanned the Bottlenose Web site, trying to determine if the claims of global intelligence and organizing the world’s attention and emotion was an NGIA technology or another social media monitoring service. The company asserts that it monitors “the stream.” The idea is that real-time information is flowing through the firm’s monitoring nodes. The content is obviously processed. The outputs are made available to those interested in the marketing.
The company states:
Our Trend Intelligence solutions will take in all forms of stream data, internal and external, for a master, cross-correlated view of actionable trends in all the real-time forces affecting your business.
The key phrase for me is “all forms” of data, “internal and external.” The result will be “a master, cross-correlated view of actionable trends in all the real time forces affecting your business.” Will Bottlenose deliver this type of output to its customers? See “Leaked Emails Reveal MPAA Plans to Pay Elected Officials to Attack Google.” Sure, but only after the fact. If the information is available via a service like Bottlenose there may be some legal consequences in my view.
By my count, there are a couple of “alls” in this description. A bit of reflection reveals that if Bottlenose is to deliver, the company has to have collection methods that work like those associated with law enforcement and intelligence agencies. A number of analysts have noted that the UK’s efforts to intercept data flowing through a Belgian telecommunications company’s servers is interesting.
Is it possible that a commercial operation, with or without KPMG’s investment, is about to deliver this type of comprehensive collection to marketers? Based on what the company’s Web site asserts, I come away with the impression that Bottlenose is similar to the governmental services that are leading to political inquiries and aggressive filtering of information on networks. China is one country which is not shy about its efforts to prevent certain information from reaching its citizens.
Bottlenose says:
Bottlenose Nerve Center™ spots real-time trends, tracks interests, measures conversations, analyzes keywords and identifies influencers. As we expand our library of data sources and aggregate the content, people, thinking and emotion of humanity’s connected communications, Bottlenose will map, reflect and explore the evolving global mind. We aim to continuously show what humanity is thinking and feeling, now.
I can interpret this passage as suggesting that a commercial company will deliver “all” information to a customer via its “nerve center.” Relationships between and among entities can be discerned; for example:
This is the type of diagram that some of the specialized law enforcement and intelligence systems generate for authorized users. The idea is that a connection can be spotted without having to do any of the Google-style querying-scanning-copying-thinking type work.
My view of Bottlenose and other company’s rushing to emulate the features and functio0ns of the highly specialized and reasonably tightly controlled systems in use by law enforcement and intelligence agencies may be creating some unrealistically high expectations.
The reality of many commercial services, which may or may not apply to Bottlenose, is that:
- The systems use information on RSS feeds, the public information available from Twitter and Facebook, and changes to Web pages. These systems do not and cannot due to the cost perform comprehensive collection of high-interest data. The impression is that something is being done which is probably not actually taking place.
- The consequence of processing a subset of information is that the outputs may be dead wrong at worst and misleading at best. Numerical processes can identify that Lady Gaga’s popularity is declining relative to Taylor Swift’s. But this is a function that has been widely available from dozens of vendors for many years. Are the users of these systems aware of the potential flaws in the outputs? In my experience, nope.
- The same marketing tendencies that have contributed to the implosion of the commercial enterprise search sector are now evident in the explanation of what can be done with historical and predictive math. The hype may attract a great deal of money. But it appears that generating and sustaining revenue is a challenge few companies in this sector have been able to achieve.
My suggestion is that Bottlenose may not be a “first mover.” Bottlenose is a company that is following in the more than 15 year old footsteps of companies like Autonomy, developers of the DRE, and i2 Ltd. Both of these are Cambridge University alumni innovations. Some researchers push the origins of this type of information analysis back to the early 1970s. For me, the commercialization of the Bayesian and graph methods in the late 1990s is a useful take off point.
What is happening is that lower computing costs and cheaper storage have blended with mathematical procedures taught in most universities. Add in the Silicon Valley sauce, and we have a number of start ups that want to ride the growing interest in systems that are not forcing Google style interactions on users.
The problem is that it is far easier to paint a word picture than come to grips with the inherent difficulties in using the word “all.” That kills credibility in my book. For a company to deliver an NGIA solution, a number of software functions must be integrated into a functioning solution. The flame out of Fast Search & Transfer teaches a useful lesson. Will the lessons of Fast Search apply to Bottlenose? It will be interesting to watch the story unfold.
Stephen E Arnold, December 15, 2014
Artificial Intelligence: Duh? What?
December 13, 2014
I have been following the “AI will kill us”, the landscape of machine intelligence craziness, and “Artificial Intelligence Isn’t a Threat—Yet.”
The most recent big thinking on this subject appears in the Wall Street Journal, an organization in need of any type of intelligence: Machine, managerial, fiscal, online, and sci-fi.
Harsh? Hmm. The Wall Street Journal has been running full page ads for Factiva. If you are not familiar with this for fee service, think 1981. The system gathers “high value” content and makes it available to humans clever enough to guess the keywords that unlock, not answers, but a list of documents presumably germane to the keyword query. There are wrappers that make Factiva more fetching. But NGIA systems (what I call next generation information access systems) use the Factiva methods perfected 40 years ago as a utility.
These are Cheetos. nutritious, right? Will your smart kitchen let you eat these when it knows you are 30 pounds overweight, have consumed a quart of alcohol infused beverages, and ate a Snickers for lunch? Duh? What?
NGIA systems are sort of intelligent. The most interesting systems recurse through the previous indexes as the content processing system ingests data from users happily clicking, real time content streaming to the collection service, and threshold adjustments made either by savvy 18 year olds or some numerical recipes documented by Google’s Dr. Norvig in his standard text Artificial Intelligence.
So should be looking forward to the outputs of a predictive system pumping directly into an autonomous unmanned aerial vehicle? Will a nifty laser weapon find and do whatever the nifty gizmo does to a target? Will the money machine figure out why I need $300 for concrete repairs and decline to give it to me because the ATM “knows” the King of Concrete could not lay down in a feather bed. Forget real concrete.
The Wall Street Journal write up offers up this titbit:
Machine Intelligence on One Big Poster
December 12, 2014
I need this in my office. I will dump my early 1940s French posters and go for logos.
Navigate to this link: http://bit.ly/1sdmBL0. You will be able to download a copy of an infographic (poster) that summarizes “The Current State of Machine Intelligence.” There are some interesting editorial decisions; for example, the cheery Google logo turns up in deep learning, predictive APIs, automotive, and personal assistant. I quite liked the inclusion of IBM Watson in artificial intelligence—recipes with tamarind and post-video editing game show champion. I found the listing of Palantir as one of the “intelligence tools” outfits. Three observations:
- I am not sure if the landscape captures what machine intelligence is
- The categories, while brightly colored, do not make clear how a core technology can be speech recognition but not part of the “rethinking industries” category
- Shouldn’t Google be in every category?
I am confident that mid tier consultants and reputation surfers like Dave Schubmehl will find the chart a source of inspiration. Does Digital Reasoning actually have a product? The company did not make the cut for the top 60 companies in NGIA systems. Hmmm. Live and learn.
Stephen E Arnold, December 12, 2014
Two Companies Offering Unified Search
December 9, 2014
I am confused. What exactly differentiates some of the vendors offering “unified” search? Another question is, “Are these many functions explicitly designed to deliver outputs that reflect real time content analytics on collected text, images, and videos?
I noted this Sinequa diagram on Twitter (http://bit.ly/12IXmnh):
A day ago I was preparing a short report for a client and came across this diagram for the Attivio active intelligence engine which delivers unified access:
The similarities are quite interesting. What came first, keyword search or the repositioning of search as an application that performs is like a giant Microsoft Office solution?
How do these two companies compare to a next generation information access system (NGIAs)? I see three differences:
- An NGIA system makes search a utility, not a core function or a principal plank in the platform
- The outputs of an NGIA system are designed to make or to trigger a tactical or strategic decision; for example, the output of an NGIA system goes into a system controlling a manufacturing robot
- The purpose of the NGIA system is to deliver a solution that pivots on predictive analytics.
I conclude, therefore, that neither Sinequa nor Attivio are NGIA systems at this time. The companies could engineer their search oriented approach toward an NGIA approach. Attivio has new management to help facilitate this important shift. Sinequa, according to a mid tier consulting firm, is one of the Big Dogs in information processing.
It will be interesting to see how search-centric vendors adapt to the next generation information access market. In my forthcoming monograph on this topic, I explore the substantive differences between search-centric “we do it all” systems and the forward looking NGIA system vendors.
Stephen E Arnold, December 9, 2014
Another Good Enough Challenge to Proprietary Enterprise Search
December 8, 2014
The protestations of the enterprise search vendors in hock for tens of millions to venture funders will get louder. The argument is that proprietary search solutions are just better.
Navigate to “Postgres Full-Text Search Is Good Enough!” This has been the mantra of some of the European Community academics for a number of years. I gave a talk at CeBIT a couple of years ago and noted that the proprietary vendors were struggling to deliver a coherent and compelling argument. Examples of too-much-chest-beating came from speakers representing and Exalead and a handful of consultants. See, for example, http://bit.ly/1zicaGw.
The point of the “Postgres Good Enough” article strikes me as:
Search has became an important feature and we’ve seen a big increase in the popularity of tools like Elasticsearch and SOLR which are both based on Lucent. They are great tools but before going down the road of Weapons of Mass Search, maybe what you need is something a bit lighter which is simply good enough! What do you I mean by ‘good enough’? I mean a search engine with the following features: stemming, ranking/boost, multiple languages, fuzzy search, accent support. Luckily PostgreSQL supports all these features.
So not only are the proprietary systems dismissed, so are the open source solutions that are at the core of a number of commercialization ventures.
I don’t want to argue with the premise. What is important is that companies trying to market enterprise search solutions now have to convince a buyer why good enough is not good enough.
For decades, enterprise search vendors have been engaged in a Cold War style escalation. With each feature addition from one vendor (Autonomy), other vendors pile on more features (Endeca).
The result is that enterprise search tries to push value on customers, not delivering solutions that are valued by customers.
The “good enough” argument is one more example of a push back against the wild and crazy jumbles of code that most enterprise search vendors offer.
The good news is that good enough search is available, and it should be used. In fact, next generation information access solution vendors are including “good enough” search in robust enterprise applications.
What is interesting is that the venture funding firms seem content to move executives in and out of companies not hitting their numbers. Examples include Attivio and LucidWorks (really?). Other vendors are either really quiet or out of business like Dieselpoint and Hakia. I pointed out that the wild and crazy revenue targets for HP Autonomy and IBM Watson are examples of what happens when marketing takes precedent over what a system can do and how many customers are available to generate billions for these big outfits.
Attention needs to shift to “good enough” and to NGIA (next generation information access) vendors able to make sales, generate sustainable revenue, and solve problems that matter.
Displaying a results list is not high on the list of priorities for many organizations. And when search becomes job one, that is a signal the company may not have diagnosed its technological needs accurately. I know there are many mid tier consultants and unemployed webmasters who wish my statements were not accurate. Alas, reality can be a harsh task master or mistress.
Stephen E Arnold, December 8, 2014
The Future of News: Looking East
December 5, 2014
I read “Hacking Media: Al Jazeera Hackathon Imagines the Future of News.” The write up is interesting because it suggests that fresh thinking about “real” journalism does not occur in Midtown Manhattan.
The other main point I noted was:
Another of the 19 projects that were chosen for the hackathon is somewhat similar to Perspectives: called ReFrame, it would pull in related information about a major news topic but focus specifically on local perspectives on a national or international story — to try and correct some of the misunderstandings that often surface during the reporting of stories like the Ebola crisis, where journalists are often writing about places they have never been. Another valuable effort, although perhaps a difficult one to automate.
Difficult for some to automate. I can name several firms in the NGIA space with this type of function up and running. I am not surprised if you find this suggestion at odds with the article. But you don’t know what you don’t know as the saying goes.
I also circled this comment about hackathons, which some search vendors are sponsoring in a hope that it will lead to either sales or the landing of a sleek programmer halibut:
Hackathons have gotten a bad rap in some circles because they are often exercises in futility: although everyone has fun drinking coffee or Red Bull for 48 hours straight and eating bad pizza, what comes out of them tends to be goofy little apps or widgets that don’t accomplish a whole lot.
Net net: what seems to be far out innovations may be closer—much closer—than you assume.
Stephen E Arnold, December 5, 2014
Enterprise Search: Gritters Are Ready, Enterprise Info Highway Is Resistant
December 3, 2014
In UK talk, a gritter is a giant machine that dumps sand (grit) on a highway to make it less slippery. Enterprise search gritters are ready to dump sand on my forthcoming report about next generation information access.
The reason is that enterprise search is running on a slippery surface. The potential customers are coated in Teflon. The dust up between HP and Autonomy, the indictment of a former Fast Search & Transfer executive, and the dormancy of some high flying vendors (Dieselpoint, Hakia, Siderean Software, et al)—these are reasons why enterprise customers are looking for something that takes the company into information access realms that are beyond search. Here’s an example: “Accounting Differences, Not Fraud, Led to HP’s Autonomy Write Down.” True or false, the extensive coverage of the $11 billion deal and the subsequent billions in write down has not built confidence in the blandishments of the enterprise search vendors.
Image source: http://thehappyhousewife.com/homeschool/files/2013/01/salt-truck.jpg
Enter the gritters. Enterprise search vendors are prepping to dump no skid bits on their prospects. Among the non skid silica will be pages from mid tier consultants’ reports about fast movers and three legged rabbits. There will be conference talks that pummel the audience with assertions about the primacy of search. There will be recycled open source technology and “Fast” think packaged as business intelligence. There will be outfits that pine for the days of libraries with big budgets pitching rich metadata to trucking companies and small medical clinics who rightly ask, “What’s metadata?”
Enterprise Search: Fee Versus Free
November 25, 2014
I read a pretty darned amazing article “Is Free Enterprise Search a Game Changer?” My initial reaction was, “Didn’t the game change with the failures of flagship enterprise search systems?” And “Didn’t the cost and complexity of many enterprise search deployments fuel the emergence of the free and open source information retrieval systems?”
Many proprietary vendors are struggling to generate sustainable revenues and pay back increasingly impatient stakeholders. The reality is that the proprietary enterprise search “survivors” fear meeting the fate of Convera, Delphes, Entopia, Perfect Search, Siderean Software, TREX, and other proprietary vendors. These outfits went away.
Many vendors of proprietary enterprise search systems have left behind an environment in which revenues are simply not sustainable. Customers learned some painful lessons after licensing brand name enterprise search systems and discovering the reality of their costs and functionality. A happy quack to http://bit.ly/1AMHBL6 for this image of desolation.
Other vendors, faced with mounting costs and zero growth in revenues, sold their enterprise search companies. The spate of sell outs that began in the mid 2000s were stark evidence that delivering information retrieval systems to commercial and governmental organizations was difficult to make work.
Consider these milestones:
Autonomy sold to Hewlett Packard. HP promptly wrote off billions of dollars and launched a fascinating lawsuit that blamed Autonomy for the deal. HP quickly discovered that Autonomy, like other complex content processing companies, was difficult to sell, difficult to support, and difficult to turn into a billion dollar baby.
Convera, the product of Excalibur’s scanning legacy and ConQuest Software, captured some big deals in the US government and with outfits like the NBA. When the system did not perform like a circus dog, the company wound down. One upside for Convera alums was that they were able to set up a consulting firm to keep other companies from making the Convera-type mistakes. The losses were measured in the tens of millions.
Enterprise Search to Walk a Rocky Road in 2015
November 19, 2014
The Arnold IT team is working on a new report that focuses on what my team is calling Next Generation Information Access or NGIA. The Information Today column for the next issue (maybe January 2015) addresses one of the several hurdles that enterprise search vendors will have to get over in order to close some of the larger information access deals available today.
In this write up, I want to identify five other issues that bedevil enterprise search. Please, understand that I am not talking about Web search, which is essentially a different application of string matching and online advertising.
Here’s the partial list with a short comment:
- A suite of components, not a one shot system like a download of Lucene
- An architecture that allows the licensee flexibility when integrating, scaling, or modifying certain operations of the system. The black box is an intriguing notion, just unsuited to today’s working environment.
- A suite of components that have been designed to inter-operate without extensive custom scripting or silly explanations about the difficulty of making Component A work with Component B of the same vendor’s software. Incompatible Lego blocks don’t fly in kindergarten, and they certainly don’t work in high risk information settings.
- Connectors that work and support the file types commonly in use in fast moving, flexible work situations. The notion that the licensee can just code up a widget makes sense only when the vendor lacks the expertise or the resources to do this job before selling an information access system.
- Native support for languages in which the licensee’s content resides. Again, telling the licensee that he or she can just connect a system to a third party translation system is a limp wristed solution to today’s global content environment.
There are other hurdles as well. I will be identifying more and mapping out the specific differences between some of the aggressively marketed “charade” information access systems and solutions from vendors who have been operating at a different level in today’s three dimensional information chess game.
Playing checkers is not the same as 3D chess in my view.
Stephen E Arnold, November 19, 2014
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