Open Source: A New Slogan Emerges. No Poster Art Yet
October 23, 2020
I read “Huawei’s Open Source Innovation Inspired by Of All, By All, for All.” Interesting. Microsoft is interested in open source. Amazon is semi interested in open source. Google is probably still interested in open source unless the team working on open source lost interest. But Huawei? Huawei is interested in open source. The write up reports:
Huawei has acknowledged the importance of open source and the role it plays in accelerating innovation within the software industry, stating that ecosystems such as openEuler, openGauss, openLooKeng, and MindSpore have created an ecosystem of open source basic software projects….The openEuler, openGauss, openLooKeng and MindSpore open source communities are all ‘led’ by Huawei as the company seeks to lay the groundwork for full-stack hardware and software collaboration.
Does Huawei’s support of open source fit into the strategic plan for Chinese technology?
The article provides a partial answer:
Huawei Cloud & AI Open Source business general manager Du Junping says that open source enables organizations to create innovation and value in an environment that is ‘open, fair, transparent, and secure’. Huawei says it is inspired by the mindset of fostering a sustainable, open source basic software ecosystem ‘Of All, By All, For All’.
Catchy: Of all, by all, for all. Very egalitarian and kumbaya-ish. Is it similar to “Smash the gang of four” or “Have fewer children, raise more pigs”? No, of course not.
Stephen E Arnold, October 23, 2020
Buzzwords and Baloney: Insecurity Signals? No Way. Do You Like My Hair?
October 22, 2020
People like to sound smart and impressive. The belief is if they appear smart and impressive they will rub shoulders with the best of the best. The Next Web says otherwise in the article: “Using Jargon To Sound Smart? Science Says You’re Just Insecure.”
Apparently people who use too much jargon-use are insecure. Relying on a specialized vocabulary momentarily inflates their ego. This long known truth was proven by the study “Compensatory Conspicuous Communication: Low Status Increases Jargon Use.” The study found that professionals low on the corporate ladder used more acronyms in their written communication and relied on jargon usage when interacting with higher ranks.
All industries have their jargon, but it is alienating to people outside the specific industry. It is even more alienating to others within the industry, because if they are unfamiliar with the term they will not admit it.
Does this mean people on every corporate ladder rung has insecurity? Yup.
Unfortunately you cannot beat jargon users so it is better to join the herd:
“As much as it’s annoying and superfluous, jargon is unlikely to go away. So you literally have two choices: you can embrace it or ignore it. I’m of the opinion that if you can’t beat them, you join them. How? By using a technology bullsh*t generator — yes, you’ve read that correctly. This tool won’t change your life but you’ll definitely have some fun.”
Another fun thing to do with jargon enthusiasts is make up words. It takes practice, but if you speak confidently enough you will soon be “proclaving” [sic] people. Cloudify too.
Whitney Grace, October 23, 2020
Freeware Tool GT4T for Translating Text
October 20, 2020
Here is a more efficient solution for those translating from one (human) language to another. Ghacks.net suggests we “Translate Microsoft Office Documents or Text from Any Word Editor and Get Dictionary Definitions Instantly with GT4T.” Writer Ashwin explores the freeware tool and takes us along for the ride with instructions and plenty of screenshots. He writes:
“Translating is no easy task, it requires precision, and you may be constantly looking up words that you don’t know or are unsure about. Opening up the browser every few seconds isn’t going to be productive either if you are working in desktop programs, e.g. Microsoft Word. GT4T is a freeware tool that can help translate text from any word editor quickly. The name stands for Google Translate for Translators, and obviously the program requires an internet connection to work. It does support other translation services, more on this later. The application doesn’t have a GUI window to work with. Instead, it runs in the background, you can access it using a couple of keyboard shortcuts.”
The write-up walks us through setting up the app with the languages one is working with and describes how to translate text in any program. One important caveat—GT4T replaces the original text (in the document and on the clipboard) with the translation, so users will want to save the original version separately. The tool supports the following services, and provides a way to switch between them: Google Neural, Microsoft Translator, Youdao, Yandex, Google Phrase Based, DeepL Pro, Baidu, Tencent, Sogou, CloudTranslation, NiuTrans, Systran, TradooIT, and Papago.
Ashwin describes the pop-up dictionary function and tells us how to create custom profiles with specified languages for different projects. GT4T is available for Mac and Windows, though it does not have a version tailored to mobile devices. Users may notice a “Snore Toast” shortcut in Windows’ Start menu—do not be alarmed, we’re advised, that is just to display toast notifications related to the tool.
Cynthia Murrell, October 20, 2020
IBM Watson: Can AI Have Trouble Finding a True Friend?
October 19, 2020
It appears that IBM’s super computer Watson is dealing with loneliness during the global pandemic, because the Daily Mail shares: “Artificial Intelligence Can Detect How Lonely You Are With 94 Percent Accuracy Just By Analyzing Your Speech Patterns.”
Researchers at the UC San Diego School of Medicine studied the speech patterns of older adults when they discussed loneliness. Using AI that included IBM’s Watson, the researchers analyzed how participants spoke including words, phrases, and silence gaps. They discovered that AI algorithms were almost as accurate as self-reports and questionnaires.
The researchers discovered that lonely people usually have long respires when discussing loneliness and express more sadness in their responses. The problem with self-reports and questionnaires (also completed by individuals) are often biased, because of stigma associated with loneliness.
To avoid bias, the researchers used natural language processing specially designed as a quantitative assessment of expressed emotion and sentiment combined with the usual loneliness diagnostic tools. The project did the following:
“Participants were also interviewed during personal conversations, which were taped and manually transcribed. Transcripts were then examined using natural language processing tools, including IBM’s Watson Natural Language Understanding (WNLU) software, to quantify sentiment and expressed emotions. WNLU uses deep learning to extract metadata from keywords, categories, sentiment, emotion and syntax. ‘Natural language patterns and machine learning allow us to systematically examine long interviews from many individuals and explore how subtle speech features like emotions may indicate loneliness,’ said first author Varsha Badal at UCSD. ‘Similar emotion analyses by humans would be open to bias, lack consistency and require extensive training to standardize.’”
The AI predicted with 94% accuracy self-acknowledged loneliness and quantitative loneliness with 76%. In the future, mental health professionals may use AI algorithms with natural language processing to diagnosis and record loneliness. It would be more accurate without the self-bias and could lead to better treatment.
Whitney Grace, October 18, 2020
Another Crazy Enterprise Search Report
October 18, 2020
“Enterprise Search Market Investment Analysis | Dassault Systemes, Oracle, HP Autonomy, Expert System Inc.” may be a knock out report, but its presentation of the company’s nuanced understanding is like hitting an egg with a feather. The effort appears to be there, but the result is an intact egg.
You can learn about this omelet of a report at this link. The publisher is PRnewsleader, which seems to be one of the off brand SEO centric content outputters.
The first thing I noticed about this report was the list of vendors in the document; to wit:
Coveo Corp.
Dassault Systèmes
Esker Software
Expert System
HP Autonomy
IBM Corp.
Lucidworks
Marklogic
Microsoft
Oracle
Perceptive Software
Polyspot and Sinequa
SAP
What jumped out at me was the inclusion of Polyspot and Sinequa. Polyspot was acquired years ago by an outfit called oppScience. The company offers Bee4Sense and list information retrieval as a solution. As far as I know, oppScience is a company based in Paris, not on a street once known for fish sales. Sinequa is a separate company. True, it once positioned itself as an enterprise search developer. That core capability has been wrapped in buzzwordery; for example, “insight platform.” Therefore, listing two companies incorrectly as one illustrates a minor slip up.
I also noticed the inclusion of Esker Software. This company is a process automation outfit, and it says that it has an artificial intelligence capability. (Doesn’t every company today?) Esker is into the cloud, and its search technology is a bullet point, not the white paper/journal article/rah rah approach used by Lucidworks.
And what about Elasticsearch? What about Algolia (former Dassault Exalead DNA I heard)? What about Voyager Search? What about Maxxcat? And there are other vendors.
What’s amusing is that the authors of this report are able to set forth:
forecasts for Enterprise Search investments till 2029.
Okay, that’s almost a decade in the Era of the Rona. I am not sure what’s going on tomorrow. Predicting search in 2029 is Snow Crash territory. But I am confident the authors of this report are intrepid researchers who just happened to overlook the Polyspot Sinequa mistake. What else has been overlooked?
Stephen E Arnold, October 18, 2020
Amazon Policeware: Is the Online Bookseller a Corporate Nation State with Policeware?
October 12, 2020
Who knows if the statements in “Leaked: Confidential Amazon Memo Reveals New Software to Track Unions.” Would a company create policeware to spy on employees? Possibly, but DarkCyber thinks that Amazon’s policeware is simply being repurposed. The Bezos bulldozer is a digital nation state, and some governance methods embrace data gathering, analytics, and predictive outputs. The idea is to be in front of trends, actions, and groups. Nothing new about this.
The write up, however, revels in the “confidential” document and places it in a zippy socio-political context. DarkCyber noted this passage:
The new tool would also track other non-union threats to the company, like crime and weather.
The operative word is “new.” In our analysis of Amazon’s policeware and intelware innovations, the “new” mischaracterizes products, services, partnerships, and features under development for more than a decade. My Amazon policeware lectures for the 2020 National Cyber Crime Conference plus some other presentations for LE and intel professionals have walked through some of the capabilities of the AWS policeware platform. (Want to know more? Write benkent2020 at yahoo dot com. Options and prices will be provided to qualified inquirers.)
The write up reports:
The new technology system — called the geoSPatial Operating Console, or SPOC — would help the company analyze and visualize at least around 40 different data sets, the memo says. Among them are many related to unions, including “Whole Foods Market Activism/Unionization Efforts,” “union grant money flow patterns,” “and “Presence of Local Union Chapters and Alt Labor Groups.” Additionally, one of the potential use cases for the tool is described in the memo as “The Union Relationship Map,” though no other details are provided.
Snappy name but the plumbing is in operation. Here’s a test question for the intrepid “real” journalists bandying the word “new” hither and yon. “What cloud service provides the back end, content processing, and other analytic features for GeoSpark Analytics?” You have one minute to write your answer in your blue book.
And where, pray tell, is the source document?
Interesting but the Amazon policeware and intelware platform is overlooked. Why? One does not know what one does not know I presume.
Stephen E Arnold, October 12, 2020
Amazon Deals for Machine Learning
October 8, 2020
“Amazon Announces Price Cuts on GPU Instances in AWS Sagemaker” contains an interesting statement; to wit:
Amazon Web Services is cutting the price of GPU instances on Sagemaker, its fully managed machine learning service. AWS said customers will see up to 18% in price reductions on all ml.p2 and ml.p3 GPU instances. The price cuts will apply from October 1 for all SageMaker components…
Several questions come to mind:
- Are Microsoft’s sales policies becoming a problem for Amazon AWS?
- Has the JEDI generated an uptick in interest in Azure from US allies?
- Are deals like Oracle’s play to land Zoom in Big Red’s cloud sounding an alarm?
On the other hand, Amazon may be sufficiently confident to cut prices because its cloud business continues to surge.
Price wars among gasoline filling stations were common in the 1950s. Could the sales tactic find traction in 2020, which has been an interesting year.
Stephen E Arnold, October 10, 2020
The Ultimate Private Public Partnership?
October 7, 2020
It looks as though the line between the US government and Silicon Valley is being blurred into oblivion. That is the message we get as we delve into Unlimited Hangout’s report, “New Pentagon-Google Partnership Suggests AI Will Soon Be Used to Diagnose Covid-19.” Writer Whitney Webb begins by examining evidence that a joint project between the Pentagon’s young Defense Innovation Unit (DIU) and Google Cloud is poised to expand from predicting cancer cases to also forecasting the spread of COVID-19. See the involved write-up for that evidence, but we are more interested in Webb’s further conclusion—that the US military & intelligence agencies and big tech companies like Google, Amazon, Microsoft, and others are nigh inseparable. Many of their decision makers are the same, their projects do as much for companies’ bottom lines as for the public good, and they are swimming in the same pools of (citizen’) data. We learn:
“NSCAI [National Security Commission on Artificial Intelligence] unites the US intelligence community and the military, which is already collaborating on AI initiatives via the Joint Artificial Intelligence Center and Silicon Valley companies. Notably, many of those Silicon Valley companies—like Google, for instance—are not only contractors to US intelligence, the military, or both but were initially created with funding from the CIA’s In-Q-Tel, which also has a considerable presence on the NSCAI. Thus, while the line between Silicon Valley and the US national-security state has always been murky, now that line is essentially nonexistent as entities like the NSCAI, DIB [Defense Innovation Board], and DIU, among several others, clearly show. Whereas China, as Robert Work noted, has the ‘civil-military fusion’ model at its disposal, the NSCAI and the US government respond to that model by further fusing the US technology industry with the national-security state.”
Recent moves in this arena involve healthcare-related projects. They are billed as helping citizens stay healthy, and that is a welcome benefit, but there is much more to it. The key asset here, of course, is all that tasty data—real-world medical information that can be used to train and refine valuable AI algorithms. Webb writes:
“Thus, the implementation of the Predictive Health program is expected to amass troves upon troves of medical data that offer both the DIU and its partners in Silicon Valley the ‘rare opportunity’ for training new, improved AI models that can then be marketed commercially.”
Do we really want private companies generating profit from public data?
Cynthia Murrell, October 7, 2020
A Challenge for Federal Records Management
October 6, 2020
Federal agencies are facing a mandate without adequate funding. This is sure to go smoothly. GCN explains why, for these entities, “Records Management Is About to Get Harder.” The White House’s Office of Management and Budget is requiring federal agencies to completely shift to electronic recordkeeping by the end of 2022, after which the National Archives and Records Administration shall accept no new paper records. The directive presents two challenges which overlap: digitizing existing records and providing a process whereby new records are created digitally in the first place. Officials plan to begin at the intersection of those requirements, invoking a Venn diagram. They must be as efficient as they can because, we’re told, Congress is reluctant to loosen purse strings enough to sufficiently fund the project.
The article cites a recent discussion among federal records management specialists regarding the transition. Reporter Troy K. Schneider writes:
“Although agencies’ readiness levels varied widely, most participants said they were on track to meet the M-19-21 deadlines. Yet whether the available tools and resources are sufficient, however, is another matter. ‘There never are enough resources,’ one official said. ‘We’ve got great resources to the extent that we have them,’ referring to the staff and the record schedules that have been developed, but the work will outstrip them — and this year’s telework-driven embrace of collaboration tools has only increased the degree of difficulty….“Complicating that resource challenge in terms of staff and money is the rapidly growing suite of communication tools agencies use. Too often, participants said, the adoption and deployment of those tools is happening before Federal Records Act requirements are accounted for.”
SharePoint and Office 365 are but two examples of software in which agencies have invested much that may not be able to keep pace with current governance needs and a greatly increased cloud-centered user base. One suggestion is to mimic the Continuous Diagnostics and Mitigation Program now used by the Department of Homeland Security and the General Services Administration for their approved product lists, reporting requirements, and cybersecurity funding. Whatever the solution, we’re told:
“Ultimately, the group agreed, fundamentals are more important than specific technologies. ‘What I’ve seen in looking at my compatriots in other agencies is they spent incredible sums of money to deploy a technology,’ one participant said. ‘And those solutions have not been nearly as effective as they have been sold as because some of the fundamentals hadn’t been done — like understanding your record schedule and the organizational and institutional changes around processes and capabilities that really need to be in place to feed the right records.’”
Indeed, rushing to choose a solution before closely examining one’s needs is a recipe for waste and disappointment. Let us hope decision makers think things through and spend the limited funds wisely. If they do not, our nation’s records are bound to become a huge, paperless mess.
Cynthia Murrell, October 6, 2020
TikTok Measures Mark a Sharp Turn for U.S. Policy
October 5, 2020
In a severe departure from our previous course, the United States seems to be embracing data localization laws. Nextgov declares, “On TikTok, the Trump Administration is Adopting China’s Own Vision for the Internet.” Though the Administration’s opening demands on the issue have not come to pass, the compromise does mean the data of U.S. TikTok users must be stored in this country on Oracle’s servers. Writer, and GMF Digital director, Sam duPont observes that the administration’s claim it acted out of security concerns does not hold water—the privacy risks of using TikTok, though considerable, are present with many apps. Targeting one company makes little sense. It looks more like a move to assert digital sovereignty and block the free flow of data. DuPont writes:
“On the other hand, requiring domestic data storage as a solution to the risks presented by TikTok is right out of China’s own playbook for the internet, which it has been advocating around the world. Governments in Russia, Indonesia, Saudi Arabia, Turkey, Vietnam and elsewhere have imposed or considered replicating data localization requirements akin to China’s own. Until recently, the United States has been a staunch opponent of these laws. And for good reason. Data localization requirements do little to improve the privacy or security of data, but they come with significant economic costs. Data storage and processing is a scale business. When a small Korean company can take advantage of cloud computing services provided by a U.S. company with servers located in Singapore, everybody wins. But where data localization laws require redundant data storage and processing facilities in every market, the economic advantages of digitalization diminish rapidly. Like all wars, the U.S.-China digital trade war has come with casualties, and chief among them is the U.S. commitment to an open, global internet.”
We’re reminded of the administration’s “Clean Network” program, an effort to sever all cyber connections between China and the U.S. This digital isolationist posture is similar to that of China itself and, if enough countries follow suit, will endanger the free-flowing internet that connects people around the world both personally and professionally.
Cynthia Murrell, October 5, 2020
-
- Subscribe to Beyond Search
Feature archive
News archive
-
