Palantir Revenue: Close to $1 Billion
January 18, 2019
I read “Palantir Posted Nearly $1 Billion in 2018 Sales, Executive Says.” The write up states:
Palantir Technologies Inc., the data analytics startup co-founded by Peter Thiel, generated almost $1 billion in revenue last year, an executive said in a French television interview.
Half of that revenue came from commercial clients. The other half came from non commercial clients like government agencies and non governmental organizations.
The company’s new Foundry product contributed to a boost in revenue, which had been forecast to be $750 million.
How close to $1 billion is Palantir? It seems that Palantir is closer to $800 million in revenue which is going to be okay for financial horse shoes.
How long has it taken Palantir to reach the $800 million figure, assuming that it is accurate?
Palantir was founded in 2003. That’s close to 15 years. How long did it take Autonomy to get close to $800 million in revenue? About 14 years.
What’s Palantir’s secret sauce? Its proprietary systems and methods. What was Autonomy’s secret sauce? Its secret neuro dynamics system.
Interesting. Palantir and Autonomy share other similarities as well.
The trajectory of Palantir’s initial public offering will be an event for investors who have injected about $2 billion in the firm.
Few search centric, content processing, analytics companies have achieved this type of revenue.
Like me, stakeholders in Palantir will be anticipating a pay day. Once the dust settles, I will get more information about sustainable revenue and other tidbits about the company. Perhaps other parallels with Autonomy will become evident.
Stephen E Arnold, January 18, 2019
Deloitte and NLP: Is the Analysis On Time and Off Target?
January 18, 2019
I read “Using AI to Unleash the Power of Unstructured Government Data.” I was surprised because I thought that US government agencies were using smart software (NLP, smart ETL, digital notebooks, etc.). My recollection is that use of these types of tools began in the mid 1990s, maybe a few years earlier. i2 Ltd., a firm for which I did a few minor projects, rolled out its Analyst’s Notebook in the mid 1990s, and it gained traction in a number of government agencies a couple of years after British government units began using the software.
The write up states:
DoD’s Defense Advanced Research Projects Agency (DARPA) recently created the Deep Exploration and Filtering of Text (DEFT) program, which uses natural language processing (NLP), a form of artificial intelligence, to automatically extract relevant information and help analysts derive actionable insights from it.
My recollection is that DEFT fired up in 2010 or 2011. Once funding became available, activity picked up in 2012. That was six years ago.
However, DEFT is essentially a follow on from other initiatives which reach by to Purple Yogi (Stratify) and DR-LINK, among others.
The capabilities of NLP are presented as closely linked technical activities; for example:
- Name entity resolution
- Relationship extraction
- Sentiment analysis
- Topic modeling
- Text categorization
- Text clustering
- Information extraction
The collection of buzzwords is interesting. I would annotate each of these items to place them in the context of my research into content processing, intelware, and related topics:
Facebook User Awareness: Two Views
January 17, 2019
What happens when Silicon Valley centric “real” journalists contemplate the question, “How much do Americans know about data slurping, reusing, and monetizing.
For one view, navigate to “Most Facebook Users Still in the Dark about Its Creepy Ad Practices, Pew Finds.” The headline tells the story. I learned:
Pew found three-quarters (74%) of Facebook users did not know the social networking behemoth maintains a list of their interests and traits to target them with ads, only discovering this when researchers directed them to view their Facebook ad preferences page.
Now for another view. Navigate to “Don’t Underestimate Americans’ Knowledge of Facebook’s Business Model.” I learned from this write up:
But let’s take another look at the numbers. According to Pew, 26 percent of Americans are aware that Facebook records a list of their interests and uses it to target ads at them. There are roughly 214 million Americans with Facebook profiles. If that’s the case, then over the past decade, 55.6 million people have educated themselves about how ad targeting works. Facebook itself has played no small role in this effort, regularly describing their ad targeting system in software and marketing materials, and recently even started building pop-up events around it.
And to add beef to the argument:
Pew surveyed more than 3,400 U.S. Facebook users in May and June, and found that a whopping 44 percent of those ages 18 to 29 say they’ve deleted the app from their phone in the last year. Some of them may have reinstalled it later. Overall, 26 percent of survey respondents say they deleted the app, while 42 percent have “taken a break” for several weeks or more, and 54 percent have adjusted their privacy settings.
Nothing like interpreting data from a survey from the left coast.
Stephen E Arnold, January 17, 2019
Google Translate: A Facelift but Some Post-Op Needed
January 17, 2019
Google Translate is the go to app to figure out what people are saying in a foreign language. One of the best features is that Google Translate scans the text and can translate it, albeit a garbled version. Google Translate has gotten a makeover and Mobile Syrup spills the details: “Google Translate Web Site Gets Material Design Refresh And New Features.”
Google Translation’s face lift is part of the Material Design change. The basic design remains the same, but the text and document buttons are rounder. There are also two new blue buttons above the input box, labeled “text” and “documents.” Text is to translate the current page, while documents translated uploaded files. There is a new “History,” “Saved,” and “Community” buttons. History contains a list of previous translations, while saved opens your own custom phrasebook of saved translations. Community is for language lovers, where they can verify and view other users’ translations. However, if you have to speak two-five languages to participate.
The newest change is:
“Perhaps one of the most significant changes is a new responsive design. Adjusting the size of the window will dynamically adjust Translate’s layout. For example, if you use a smaller window, Translate will take on a more ‘mobile friendly’ layout with a vertical-oriented system. When you expand your window out, it’ll adjust back to a horizontal layout.”
The changes to Google Translate are slight, but the app could use some enhancements when handling popular words; for example, “jajillas.”
Whitney Grace, January 17, 2018
Elsevier Excitement: Not an Oxymoron
January 16, 2019
Professional publishing – the information designed for lawyers, accountants, scientists, technologists, and their ilk – is usually a quiet place. Notice that I did not say, “Dull.”
Now one of the leaders in this small club of gatekeepers has evidenced some actual management excitement at least here in Harrod’s Creek.
According to Inside Higher Education:
The entire editorial board of the Elsevier-owned Journal of Informetrics resigned Thursday in protest over high open-access fees, restricted access to citation data and commercial control of scholarly work. Today, the same team is launching a new fully open-access journal called Quantitative Science Studies.
Most of the folks outside the STEM world of publishing are unaware that many professional publishers rely on a very reliable business model. Some of its features include:
- Work with august academic institutions to make sure the paper based “publish or perish” model is required for anything close to a tenure track or a jump in pay
- Charge the authors for various things. Remember. The authors have to publish in esteemed journals which are in theory reviewed by hard working peers. The idea is to make sure those fudged data are identified and stopped before the vetted paper is published. Non reproducible results? Let’s not talk about those.
- Charge the academic institutions with the tenure track and aspiring scholars to subscribe to these peer reviewed journals.
- Recycle the content in different ways to generate downstream revenue from online databases and services.
- Work with vendors who create digital or microfilm versions of the older versions of the publications to generate royalties.
Most of these methods are little known and only partially understood by individuals who don’t pay much attention to a $2,000 for four issues paper publication.
Now the revolt is indeed exciting. The write up does the normal journalism thing. The good stuff is the business model, the somewhat generous money generating mechanisms from which the authors and the institutions are excluded, and the fact that scholarly information is only available to those with the money to pay for these documents.
Is this the beginning of the end for Elsevier-type outfits and their close cousins, the Reed Elsevier type outfits?
To me this is an interesting question.
Stephen E Arnold, January 16, 2019
Factualities for January 16, 2018
January 16, 2019
Data are everywhere. And we know that the information in nuggets is credible, accurate, and essential for making decisions quickly. What’s wrong with using factualities? Nothing. Absolutely solid gold in each item.
One hour. The lead time a pilot has when relying on IBM Watson to predict turbulence. Now for horse races. Source: Jim Harris
100,000. The number of times spyware is downloaded from the Google Play service. Source: Digit.in
$3.7 million. Amount generated by a hacking group using the Ryuk ransomware. Source: Ars Technica
100. The number of types of inappropriate content banned by Chinese authorities. Source: Financial Times with a pay wall to make the factoid more valuable.
244. Number of secret Netflix categories. Source: Netflix Codes
$11. Cost of a training program which will teach you to do well on a programming interview. Source: Next Web
$17,164 per hour. The cost to run 2.5 million AWS HPC Tasks using 40,000 EC2 Spot Instances for 8 hours. Source: Jeff Barr, Amazon guru
48 percent. In 96 months, the growth of people viewing television over-the-air. Source: Techcrunch
Ah, crunchy factualities. Good for the mobile decision maker. Tasty too.
Stephen E Arnold, January 16, 2019
Silicon Valley Gets Political
January 16, 2019
Google, Facebook, and other tech giants are no strangers to political intrigue. Recently, it’s not their products that are being used by governments. Rather, it’s the employees who are standing up to voice their opinions. And the waves are being felt, as we discovered in a recent Digital Journal story, “Google Employees Ready to Strike Over China Censorship Deal.”
According to the story:
“This is why Google’s new China venture has caused dismay among its workforce. Reported by The Intercept, Google has apparently been working on a project code-named Dragonfly. This is to build a search engine for China that would have the additional functionality to “censor broad categories of information about human rights, democracy, and peaceful protest.”
This is a big story. Not only because employees are attempting control their fate, at least in some small percentage. As we mentioned, this stand is making waves. Now, Google’s “Shadow Workforce” is also demanding management pay more attention to it. Google’s contract employees make up a huge portion of its workforce, and do not want to be trampled upon. This is an interesting moment for Google. Its employees are attempting to be stronger, but we don’t know if it will make happier employees or a bureaucratic nightmare.
Patrick Wensink, January 16, 2018
Ignoring Amazon: Risky, Short Sighted, Maybe Not an Informed Decision
January 15, 2019
I read “AWS, MongoDB, and the Economic Realities of Open Source.” The write up does a good job of explaining how convenience can generate cash for old line businesses.
The essay then runs down the features of a typical open source business model; namely, money comes from proprietary add ons, services, training, etc. Accurate and helpful is the discussion. Few people recognize the vulnerability of this type of open source model for companies not in a “winner take all position.” A good example is Elastic’s success, and the lack of success of other open source search systems which are in most cases pretty good.
The discussion of Amazon explains that Amazon is in the service business; specifically, the software-as-a-service business. That’s mostly correct. I have given two or three talks about Amazon’s use of AWS in the law enforcement and intelligence sector, and I have to be honest. Few understood what I was emphasizing. Amazon is a disruption machine. I call it the Bezos bulldozer.
The write up draws parallels with the music business case with which the Stratechery essay begins. I understand the parallel. I agree with this statement:
AWS is not selling MongoDB: what they are selling is “performance, scalability, and availability.” DocumentDB is just one particular area of many where those benefits are manifested on AWS. Make no mistake: these benefits are valuable.
The point of the write up is mostly on the money as well. I noted this statement:
…the debate on the impact of cloud services on open source has been a strident one for a while now. I think, though, that the debate gets sidetracked by (understandable) discussions about “fairness” and what AWS supposedly owes open source. Yes, companies like MongoDB Inc. and Redis Labs worked hard, and yes, AWS is largely built on open source, but the world is governed by economic realities, not subjective judgments of fairness.
There are several facets of Amazon’s system and method for competition which may be more important than the inclusion of open source software in its suite of “conveniences.”
At some point, I would welcome conference organizers, MBAs, and open source mavens to address such questions as:
- What is the ease of entry or implementation for open source services on AWS?
- What is the future of training developers to use the AWS system? Who does the training?
- What is the short term benefit to Amazon to have developers use open source and the AWS platform to create new products and services?
- What is the long term benefit to Amazon to have new products and services become successful on the AWS platform?
- What is the mid term impact on procurements for commercial and government entities?
- What is the shape of the Bezos bulldozer’s approach to lock in?
I was recently informed by a conference organizer that no one had interest in Amazon’s disruption of the policeware and intelware sector.
Do you think that the organizer’s conclusion was informed? Do you think open source is more than the digital equivalent of a gateway drug?
I do. For information about the DarkCyber briefing on Amazon’s policeware and intelware “play,” write benkent2020 at yahoo dot com.
Stephen E Arnold, January 15, 2019
Google and the Revolt of the Science Club Within
January 15, 2019
I know I said I would cover more DarkCyber topics, but I read a remarkable article called:
With a headline like this one, let’s look at a couple of the statements set forth in the write up as factualities:
The [Instagram and Twitter] campaign is another example of the growing movement of tech employees publicly critiquing industry-wide practices they say are leading to inequality in the workplace. The tech industry has for years seen abysmal diversity statistics related to employment of female and underrepresented minorities in its workforce. Supporters of the campaign say that ending forced arbitration is a key step to creating a fairer workplace culture that will help curb such disparity.
The point to note is that Google which has largely failed at social media has employees who use the services the online ad giant was unable to understand, me-to, and make successful. Interesting. A disconnect signal perhaps?
Another statement from the write up:
As part of the effort, the group organizing the campaign researched the contracts of around 30 major tech companies and 10 of the biggest suppliers of contract employees for major tech companies. Not a single tech company met their basic criteria for protecting employees’ rights to pursue legal action against their companies for workplace issues, the group said.
Hmm. The “30 major tech companies” include outfits like Boeing, Raytheon, IBM, and similar giants? I don’t know. My hypothesis is that the “major” are outfits which are in the San Francisco-San Mateo area.
What is clear, however, is that giant companies which have acted as if they were countries now have governance problems to go along with their management challenges.
I have termed the broad approach to managing Yahoo-type outfits (I use Yahoo as an archetype, not a functional company) the HSSCMM or high school science club management method. The approach operates in ways that can be baffling to those not in the science club; for example, the junior prom is stupid. Only dorks go. The notion is that by exclusion one becomes more exceptional.
Now we have a terrarium in which to watch a science club go to war with its very bright, very elite, and very sciencey members.
Exciting? Nah. Interesting? Maybe. Financially significant? Oh, yes.
Stephen E Arnold, January 15, 2019
DarkCyber for January 15, 2019, Now Available
January 15, 2019
DarkCyber for January 15, 2019, is now available at www.arnoldit.com/wordpress and on Vimeo at https://www.vimeo.com/311054042 . The program is a production of Stephen E Arnold. It is the only weekly video news shows focusing on the Dark Web, cyber crime, and lesser known Internet services.
The first story discusses Discord, an in-game and chat service. The system takes a somewhat hands-off approach to monitoring user messages. Discord features what are called “magic emojis.” These emojis, when used among those who are members of a specific social group within Discord, can convey messages. Some potential bad actors–for example, white supremacists–allegedly have been using the services as a communications channel.
The second story explores an allegation that Facebook WhatsApp makes it possible for those interested in child pornography to locate this type of content. Third party apps provide finder services. Facebook is introducing electronic payments within WhatsApp. The likelihood for bad actors to use WhatsApp as a mechanism to exchange objectionable content is high. Facebook’s content policies are likely to undergo scrutiny from government authorities in 2019.
The third story profiles Gamalon, a company which develops software for the Defense Advanced Research Projects Agency and commercial enterprises. The key to Gamalon system is that it uses advanced statistical procedures to identify and extract ideas from source content. The company’s technology makes use of Bayesian methods in order to create automatically machine learning models. The models can then create new models to deal with new ideas expressed in the source data processed by the system.
The fourth story reports on Spain’s 36 month effort to slow or halt the trade of weapons in the country via the Dark Web. Authorities have arrested more than 200 individuals and seized hand guns and automatic weapons. The investigation continues.
The final story points to a study which provides facts and figures about the hidden Internet. Some of the data in the study sponsored by a star of the hit cable television program Shark Tank is quite remarkable. To cite one example, the number of hidden sites on the Internet is 32 times the number of stars in the galaxy. That a very large number and difficult to match with DarkCyber’s research data.
Kenny Toth, January 15, 2019
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