True or False: Google and Dangerous Functionality
May 13, 2022
I want to be clear: I cannot determine if security-related announcements are PR emissions, legitimate items of data, or clickbait craziness. I am on the fence with the information is “Google Cloud Apparently Has a Security Issue Even Firewalls Can’t Stop.”
The write up presents as real news:
A misconfiguration in Google Cloud Platform has been found which could give threat actors full control over a target virtual machine (VM) endpoint…
These virtual machines are important cogs in some bad actors machinery. Sure, legitimate outfits rely on the Google for important work as well. Therefore, the announcement points some bad actors toward a new opportunity to poke around and outfits engaged in ethically informed activities to batten down their digital hatches.
The write up points out that the Google agreed that “misconfiguration could bypass firewall settings.”
And the Google, being Googley, semi-agrees. Does this mean that the Google Cloud is just semi-vulnerable?
Stephen E Arnold, May 13, 2022
AI as a Service Dominated by the Usual Science Club Members
May 12, 2022
A burgeoning AI-as-a-Service field may enable businesses of all sizes to take advantage of AI tools without the high cost of developing their own solutions in-house. So declares ReadWrite in its look at the “Growth of AI as a Service (AIaaS) Market.” Writer Neeraj Agarwal touts the purported advantages of such tools, which include NLP, robotics, machine learning, and computer vision:
“After having a view of what the future holds for you, businesses will be able to:
* Create strategies specifically for regional and country based on figures and facts.
* Identify where and when to invest.
* Outperform against key competitors using data and the drivers and trends shaping the market.
* Understand customers based on the latest market research findings.
* Grow Businesses by strategically positioning themselves in tech run.”
Sounds great. But we wonder what happens when just a few companies dominate. We are told:
“Big Companies like Microsoft, IBM, Google, and other market leaders have actively introduced AI services in their business models, increasing their reach and revenue without much time investments.”
So are smaller firms are shut out of this lucrative market? If so, does the lack of competition limit the benefits of these tools? These points are not addressed in the write-up. It does share some other information about the AIaaS arena, however, like how much, and in which directions, it has grown:
“The global AI-as-a-Service market was valued at USD 1.35 Bn in 2016 and is estimated to reach USD 43.1 Bn by 2028, at a CAGR of 46.9% during the forecast period. The base year considered for the study is 2017, while the forecast period is between 2018 and 2028. The compound annual growth rate (CAGR) forecast till 2028 of the different categories of the AI market are:
* AI Services- 22%
* AI Hardware- 20.5%
* AI platforms- 34.6%
* AI System Infrastructure Software- 14.1%
* AI Lifecycle Software- 38.9%
* AI Business Services- 21.9%
The market has been bifurcated into cloud-based and on-premises deployment models based on the deployment model.”
The piece also discusses types of applications available, segmentation of the market, and an analysis of competition among the major players. See the article for those details.
Cynthia Murrell, May 12, 2022
AT&T Innovation: I Thought Banjo Anticipated This Functionality
May 11, 2022
I read “AT&T Will Use Phone Location Data to Route 911 Calls to the Right Responders.” I thought that Banjo (now SafeXai) described a similar function. I thought I read a Banjo patent or two referencing the firm’s systems and methods. Despite this historical thought, I noted this statement in the article:
The company says it’ll be the first US carrier to “quickly and more accurately identify where a wireless 911 call is coming from using device GPS and hybrid information.” That’ll allow it to route the call to the correct 911 call center (public safety answering point or PSAP) which can then “dispatch first responders to the right location faster…
Banjo changed its name, but before its management shift, the company filed and obtained a number of forward-leaning patents. I recall that one of them provided a useful shopping list of off-the-shelf technologies used in smart software. If anyone is curious, the Banjo patents referencing what I think is a similar notion include US10585724, “Notifying entities of relevant events”, US10582343, “Validating and supplementing emergency call information,” and several others. I recall reading patents held by AT&T which reference this capability. I wonder how many firms can use mobile data to provide useful services to first responders, law enforcement, and intelligence entities. Once a system and method are disclosed, individuals can replicate or exploit some systems.
Collecting data via an app’s software is made more useful with real-time data from other collection points. The value of cross-correlation of data is quite high. I find it interesting that basic LE and intel methods continue to poke their nose through the heavy cloud cover over certain interesting systems and methods. I do long for the days when certain information was secret and kept that way.
Stephen E Arnold, May 11, 2022
Issues with the Zuckbook Smart Software: Imagine That
May 10, 2022
I was neither surprised by nor interested in “Facebook’s New AI System Has a ‘High Propensity’ for Racism and Bias.” The marketing hype encapsulated in PowerPoint decks and weaponized PDF files on Arxiv paint fantastical pictures of today’s marvel-making machine learning systems. Those who have been around smart software and really stupid software for a number of years understand two things: PR and marketing are easier than delivering high-value, high-utility systems and smart software works best when tailored and tuned to quite specific tasks. Generalized systems are not yet without a few flaws. Addressing these will take time, innovation, and money. Innovation is scarce in many high-technology companies. The time and money factors dictate that “good enough” and “close enough for horseshoes” systems and methods are pushed into products and services. “Good enough” works for search because no one knows what is in the index. Comparative evaluations of search and retrieval is tough when users (addicts) operate within a cloud of unknowing. The “close enough for horseshoes” produces applications which are sort of correct. Perfect for ad matching and suggesting what Facebook pages or Tweets would engage a person interested in tattoos or fad diets.
The cited article explains:
Facebook and its parent company, Meta, recently released a new tool that can be used to quickly develop state-of-the-art AI. But according to the company’s researchers, the system has the same problem as its predecessors: It’s extremely bad at avoiding results that reinforce racist and sexist stereotypes.
My recollection is that the Google has terminated some of its wizards and transformed these professionals into Xooglers in the blink of an eye. Why? Exposing some of the issues that continue to plague smart software.
Those interns, former college professors, and start up engineers rely on techniques used for decades. These are connected together, fed synthetic data, and bolted to an application. The outputs reflect the inherent oddities of the methods; for example, feed the system images spidered from Web sites and the system “learns” what is on the Web sites. Then generalize from the Web site images and produce synthetic data. The who process zooms along and costs less. The outputs, however, have minimal information about that which is not on a Web site; for example, positive images of a family in a township outside of Cape Town.
The write up states:
Meta researchers write that the model “has a high propensity to generate toxic language and reinforce harmful stereotypes, even when provided with a relatively innocuous prompt.” This means it’s easy to get biased and harmful results even when you’re not trying. The system is also vulnerable to “adversarial prompts,” where small, trivial changes in phrasing can be used to evade the system’s safeguards and produce toxic content.
What’s new? These issues surfaced in the automated content processing in the early versions of the Autonomy Neuro Linguistic Programming approach. The fix was to retrain the system and tune the outputs. Few licensees had the appetite to spend the money needed to perform the retraining and reindexing of the processed content when the search results drifted into weirdness.
Since the mid 1990s, have developers solved this problem?
Nope.
Has the email with this information reached the PR professionals and the art history majors with a minor in graphic design who produce PowerPoints? What about the former college professors and a bunch of interns and recent graduates?
Nope.
What’s this mean? Here’s my view:
- Narrow applications of smart software can work and be quite useful; for example, the Preligens system for aircraft identification. Broad applications have to be viewed as demonstrations or works in progress.
- The MBA craziness which wants to create world-dominating methods to control markets must be recognized and managed. I know that running wild for 25 years creates some habits which are going to be difficult to break. But change is needed. Craziness is not a viable business model in my opinion.
- The over-the-top hyperbole must be identified. This means that PowerPoint presentations should carry a warning label: Science fiction inside. The quasi-scientific papers with loads of authors who work at one firm should carry a disclaimer: Results are going to be difficult to verify.
Without some common sense, the flood of semi-functional smart software will increase. Not good. Why? The impact of erroneous outputs will cause more harm than users of the systems expect. Screwing up content filtering for a political rally is one thing; outputting an incorrect medical action is another.
Stephen E Arnold, May 10, 2022
Voyager Labs Exposed: Another NSO Group?
May 10, 2022
I read “Voyager Labs: L’Arma spuntata dell’intelienza artificiale.” I was expecting some high-flying smart software. What the article delivers is some juicy detail about intelware, conferences where quite non-public stories are told, and an alleged tie up between those fine folks at Palantir Technologies and the shadowy Israeli company. One caveat: One has to be able to read Italian or have a way to work around the limitations of online translation systems. (Good luck with finding a free to use system. I just asked my local Pizza Hut delivery person, who speaks and reads Italian like a Roma fan.)
Here are some allegedly spot on factoids from the write up:
- One of the directors of the company has a remarkably unusual career at a US government agency. The individual presided over specialized interrogation activities and allowing a person with a bomb to enter a government facility. There were a handful of deaths.
- The Voyager Labs’ cloud services are allegedly “managed globally by Palantir’s Gotham platform.
- Voyager’s Labs’ content was described at an intelligence conference owned and managed by an American in this way: “usable and previously unattainable information by analyzing and understanding huge amounts of open, deep and obscure Web data.”
- Allegations about the use of Voyager Labs’ system to influence an Italian election.
- Voyager Labs identifies for licensees people with red, orange, and green icons. Green is good; red is bad; orange is in the middle?
Interesting stuff. But the zinger is the assertion that Voyager Labs’ smart software can output either dumb or aberrant results. The whiz kids at Gartner Group concluded in 2017 that Voyager Labs was a “cool vendor.” That’s good to know. Gartner likes intelware that sort of works. Cool.
Interesting profile and there are more than 100 footnotes. I assume that the founder of Voyager Labs, the conference organizer, and assorted clients were not will to participate in an interview. This is an understandable position, particularly when an Israeli outfit could be the next in the NSO Group spotlight.
Stephen E Arnold, May 10, 2022
What Is Crazier Than Enterprise Search? Maybe Content Management Systems?
May 4, 2022
I met a content management system guru many years ago. He explained to me in a remarkably patronizing way that CMS was the future of enterprise content. The words “all” and the phrase “search is just a utility” still echo when I think of him.
He was incorrect. CMS is certainly not a replacement for an XML repository which can “point” to objects like a sales presentation which began life as a PowerPoint and then emerged as a nifty PDF for the 20 somethings in marketing.
CMS, in my view, boils down to clunky systems which allow different people with a wide range of cognitive content to create, retrieve, and do stuff with text and some art. Search remains pretty darned crazy as a market sector, but there are some open source options and a number of semi-useful cloud services. The tendency for art history majors to bandy the word “all” in chats about a CMS continues to make me laugh. Right, “all”. What about company videos on RuTube.ru? I am waiting for an answer.
There is something that CMS is quite skilled. “Vulnerable Plugins Plague the CMS Website Security Landscape” states:
According to the researchers, vulnerable plugins and extensions “account for far more website compromises than out-of-date, core CMS files,” with roughly half of website intrusions recorded by the firm’s clients occurring on a domain with an up-to-date CMS. Threat actors will often leverage legitimate — but hijacked — websites to host malware, credit card skimmers, or for the deployment of spam.
Thank goodness these CMS cannot index “all” content, which limits breach risks to some degree.
Quite an attack surface: Art history majors versus the bad actors with engineering degrees from a technical university or an enterprising coder who dropped out of school to sell his services via Aletenen.
Stephen E Arnold, May 4, 2022
Deepset: Following the Trail of DR LINK, Fast Search and Transfer, and Other Intrepid Enterprise Search Vendors
April 29, 2022
I noted a Yahooooo! news story called “Deepset Raises $14M to Help Companies Build NLP Apps.” To me the headline could mean:
Customization is our business and services revenue our monetization model
Precursor enterprise search vendors tried to get gullible prospects to believe a company could install software and employees could locate the information needed to answer a business question. STAIRS III, Personal Library Software / SMART, and the outfit with forward truncation (InQuire) among others were there to deliver.
Then reality happened. Autonomy and Verity upped the ante with assorted claims. The Golden Age of Enterprise Search was poking its rosy fingers through the cloud of darkness related to finding an answer.
Quite a ride: The buzzwords sawed through the doubt and outfits like Delphis, Entopia, Inference, and many others embraced variations on the smart software theme. Excursions into asking the system a question to get an answer gained steam. Remember the hand crafted AskJeeves or the mind boggling DR LINK; that was, document retrieval via linguistic knowledge.
Today there are many choices for enterprise search: Free Elastic, Algolia, Funnelback now the delightfully named Squiz, Fabasoft Mindbreeze, and, of course, many, many more.
Now we have Deepset, “the startup behind the open source NLP framework Haystack, not to be confused with Matt Dunie’s memorable “haystack with needles” metaphor, the intelware company Haystack, or a basic piles of dead grass.
The article states:
CEO Milos Rusic co-founded Deepset with Malte Pietsch and Timo Möller in 2018. Pietsch and Möller — who have data science backgrounds — came from Plista, an adtech startup, where they worked on products including an AI-powered ad creation tool. Haystack lets developers build pipelines for NLP use cases. Originally created for search applications, the framework can power engines that answer specific questions (e.g., “Why are startups moving to Berlin?”) or sift through documents. Haystack can also field “knowledge-based” searches that look for granular information on websites with a lot of data or internal wikis.
What strikes me? Three things:
- This is essentially a consulting and services approach
- Enterprise becomes apps for a situation, department, or specific need
- The buzzwords are interesting: NLP, semantic search, BERT, and humor.
Humor is a necessary quality which trying to make decades old technology work for distributed, heterogeneous data, email on a sales professionals mobile, videos, audio recordings, images, engineering diagrams along with the nifty datasets for the gizmos in the illustration, etc.
A question: Is $14 million enough?
Crickets.
Stephen E Arnold, April 29, 2022
Has the Softie Been Winged by EU Antitrust Regulators?
April 25, 2022
I read “ Microsoft on EU Antitrust Regulators’ Radar after Cloud Practices Complaints by Rivals.” The big outfit in Redmond has been keeping a low profile, allowing Amazon, Apple, Facebook / Zuckbook, and Google take the glow in the dark paint ball pellets. Now the Softie has been splatted in acid green polyethylene glycol. Lookin’ good in spring colors I suppose.
The write up states:
Microsoft’s rivals and customers have been served a questionnaire with various queries by EU antitrust regulators seeking information about the company’s business and licensing deals. The latest action hints at a possible formal investigation into Microsoft’s cloud business that might take place down the line.
Paint balls can sting, but direct hits are fairly safe, just messy. Take two or three in one eye, and the target might stumble around looking for a safe haven.
What competitors are not happy with Microsoft’s approach to the cloud market? The write up names NextCloud and OVHcloud, and others may have shared their thoughts.
The next volley of shots may not be from paint ball guns. More lethal weapons might be flown over the customer centric folks in Redmond. Microsoft has coughed up money in the past, and it may have to bleed some cash to make the possible legal drones stop dropping grenades from the clouds.
Stephen E Arnold, April xx, 2022
Nuclia: The Solution to the Enterprise Search Problem?
April 21, 2022
I read an interesting article called “Spanish Startup Nuclia Gets $5.4M to Advance Unstructured Data Search.” The article includes an illustration, presumably provided by Nuclia, which depicts search as a super app accessed via APIs.
Source: Silicon Angle and possibly Nuclia.com. Consult the linked story to see the red lines zip around without bottlenecks. (What? Bottlenecks in content processing, index updating, and query processing. Who ever heard of such a thing?)
Here are some of the highlights — assertions is probably a better word — about the Nuclia technology:
- The system is “AI powered.”
- Nuclia can “connect to any data source and automatically index its content regardless of what format or even language it is in.”
- The system can “discover semantic results, specific paragraphs in text and relationships between data. These capabilities can be integrated in any application with ease.”
- Nuclia can “detect images within unstructured datasets.”
- The cloud-based service can “say one video is X% similar to another one, and so on.”
What makes the Nuclia approach tick? There are two main components:
- The Nuclia vector database which is available via GitHub
- The application programming interface.
The news hook for the search story is that investors have input $5.4 million in seed funding to the company.
Algolia wants to reinvent search. Maybe Nuclia has? Google is search, but it may be intrigued with the assertions about vector embeddings and finding similarities which may be otherwise overlooked. The idea is that the ad for Liberty Mutual might be displayed in YouTube videos about seized yachts by business wizards on one or more lists of interesting individuals. Elastics may want to poke around Nuclia in a quest for adding some new functionality to its search system.
Enterprise search seems to be slightly less dormant than it has been.
Stephen E Arnold, April 21, 2022
Enterprise Search Vendors: Sure, Some Are Missing But Does Anyone Know or Care?
April 20, 2022
I came across a site called Software Suggest and its article “Coveo Enterprise Search Alternatives.” Wow. What’s a good word for bad info?
The system generated 29 vendors in addition to Coveo. The options were not in alphabetical order or any pattern I could discern. What outfits are on the list? Here are the enterprise search vendors for February 2022, the most recent incarnation of this list. My comments are included in parentheses for each system. By the way, an alternative is picking from two choices. This is more correctly labeled “options.” Just another indication of hippy dippy information about information retrieval.
AddSearch (Web site search which is not enterprise search)
Algolia (a publicly trade search company hiring to reinvent enterprise search just as Fast Search & Transfer did more than a decade ago)
Bonsai.io (another Eleasticsearch repackager)
Coveo (no info, just a plea for comments)
C Searcher(from HNsoft in Portugal. desktop search last updated in 2018 according to the firm’s Web site)
CTX Search (the expired certificate does bode well)
Datafari (maybe open source? chat service has no action since May 2021)
Expertrec Search Engine (an eCommerce solution, not an enterprise search system)
Funnelback (the name is now Squiz. The technology Australian)
Galaktic (a Web site search solution from Taglr, an eCommerce search service)
IBM Watson (yikes)
Inbenta (A Catalan outfit which shapes its message to suit the purchasing climate)
Indica Enterprise Search (based in the Netherlands but the name points to a cannabis plant)
Intrasearch (open source search repackaged with some spicy AI and other buzzwords)
Lateral (the German company with an office in Tasmania offers an interface similar to that of Babel Street and Geospark Analytics for an organization’s content)
Lookeen (desktop search for “all your data”. All?)
OnBase ECM (this is a tricky one. ISYS Search sold to Lexmark. Lexmark sold to Highland. Highland appears to be the proud possessor of ISYS Search and has grafted it to an enterprise content management system)
OpenText (the proud owner of many search systems, including Tuxedo and everyone’s fave BRS Search)
Relevancy Platform (three years ago, Searchspring Relevancy Platform was acquired by Scaleworks which looks like a financial outfit)
Sajari (smart site search for eCommerce)
SearchBox Search (Elasticsearch from the cloud)
Searchify (a replacement for Index Tank. who?)
SearchUnify (looks like a smart customer support system, a pitch used by Coveo and others in the sector)
Site Search 360 (not an enterprise search solution in my opinion)
SLI Systems (eCommerce search, not enterprise search, but I could be off base here)
Team Search (TransVault searches Azure Tenancy set ups)
Wescale (mobile eCommerce search)
Wizzy (the name is almost as interesting as the original Purple Yogi system and another eCommerce search system)
Wuha (not as good a name as Purple Yogi. A French NLP search outfit)
X1 Search (from Idea Labs, X1 is into eDiscovery and search)
This is quite an incomplete and inconsistent list from Software Suggest. It is obvious that there is considerable confusion about the meaning of “enterprise search.” I thought I provided a useful definition in my book “The Landscape of Enterprise Search,” published by Panda Press a decade ago. The book, like me, is not too popular or well known. As a result, the blundering around in eCommerce search, Web site search, application specific search, and enterprise search is painful. Who cares? No one at Software Suggest I posit.
My hunch is that this is content marketing for Coveo. Just a guess, however.
Stephen E Arnold, April xx, 2022
-
- Subscribe to Beyond Search
Feature archive
News archive
-
