The ownership structure is designed to make sure the “god group” has a say in things Palantirian. The term appears to be forever. That seems reasonable when climate change, financial pressure, and the Rona are rampant.
Hard Data Predicts Why Songs Are Big Hits
August 26, 2020
Hollywood has a formula system to make blockbuster films and the music industry has something similar. It is harder to predict hit music than films, but Datanami believes someone finally has the answer: “Hooktheory Uses Data To Quantify What Makes Songs ‘Great’.”
Berkeley startup Hooktheory knows that many songs have similar melodies and lyrics. Hooktheory makes software and other learning materials for songwriters and musicians. With their technology, the startup wants to prove what makes music popular is quantifiable. Hooktheory started a crowdsourced database dubbed “Theorytabs” that analyses popular songs and the plan is to make it better with machine learning.
Theorytabs is a beloved project:
“The Hooktheory analysis database began as a “labor of love” by Hooktheory co-founders Dave Carlton, Chris Anderson and Ryan Miyakawa, based on the idea that “conventional tabs and sheet music are great for showing you how to play a song, but they’re not ideal for understanding how everything fits together.” Over time, the project snowballed into a community effort that compiled tens of thousands of Theorytabs, which Hooktheory describes as “similar to a guitar tab but powered by a simple yet powerful notation that stores the chord and melody information relative to the song’s key.”
Theorytabs users can view popular songs from idol singers to videogame themes. They can play around with key changes, tempos, mixers, and loops, along with listening to piano versions and syncing the songs up with YouTube music videos.
Hooktheory owns over 20,000 well-formatted tabs for popular music. The startup is working with Carnegie Mellon University and New York University to take Theorytabs to the next level. The music community has welcomed Theorytabs and people are eager to learn about the data behind great music.
Whitney Grace, August 27, 2020
OnionFruit Revamps With New Browser Version
August 26, 2020
Remaining anonymous is impossible online, especially with all the cookies we “eat.” Instead of an all cookie diet, try using a browser made from onions and fruit! Major Geeks revealed their latest harvest with an update to their popular TOR browser: OnionFruit Connect 2020.730.0.
TOR browsers work, because they encrypt a user’s browsing data in many security layers like an onion. In order to identify the user, one has to peel back layers of encrypted data. It makes hacking someone with a Tor browser tedious and extremely difficult. TOR browsers also allow people to connect to the Dark Web that uses encrypted and random web addresses.
OnionFruit guarantees its users are protected:
“Having the ability to use a browser that you are already comfortable with makes using TOR more of a seamless process. OnionFruit Connect will initiate the TOR service and then configures your proxy settings allowing your apps to be routed through TOR’s tunnel. You will be notified that you’re protected, confirming that all your internet traffic is being passed through the TOR tunnel safely encrypted. This process ensures that every single site you visit gets routed through multiple servers to help mask your actions, making them difficult to track.”
OnionFruit is simple to set up on a computer and then access the TOR network. The best thing is that it works with favored browsers: Chrome, Firefox, Edge, Opera, and others without an extra configuration. OnionFruit updates itself, has custom landing pages, and a download speed monitor.
It is an easy way to encrypt Web browsing and also learn more about the TOR network.
Whitney Grace, August 26, 2020
Zero Search Results = Useful Information
August 26, 2020
I saw a notice for a conference called “Activate.” Zippy title. What caught my attention was the title of a talk; specifically, “Implementing a Deep Learning Search Engine.” The technology appears to be the open source Solr search system. As you know, dig into Solr and what do you find? Lucene. The hay day of enterprise search has gone. Perhaps another harvest will come? But after the implosion of the promises made by Fulcrum, Verity, Autonomy, Fast, Convera, and Entopia, I am not sure search has credibility.
Don’t get me wrong. Search is a major part of companies; for example, Salesforce bought Diffeo, which was an interesting search system. Elastic is, of course, the commercial firm selling support for the open source Elasticsearch system. There are unusual systems as well; for example, the quirky Qwant, which has some Pertimm inside.
But consider this description of the talk for the Activate conference delivered by two wizards (well, maybe apprentice wizards) from the Lucidworks outfit:
Recent advances in Deep Learning brings us the possibility to get improvements in almost any domain. Search Engines aren’t an exception. Semantic search, visual search, “zero results” queries, recommendations, chatbots etc. – this is just a shortlist of topics that can benefit from Deep Learning based algorithms. But more powerful methods are also more expensive, so they require addressing the variety of scalability challenges. In this talk, we will go through details of how we implement Deep Learning Search Engine at Lucidworks: what kind of techniques we use to train robust and efficient models as well as how we tackle scalability difficulties to get the best query time performance. We will also demo several use-cases of how we leverage semantic search capabilities to tackle such challenges as visual search and “zero results” queries in eCommerce.
Three points:
- Deep learning is one of those buzzwords that recyclers of open source technology slap on a utility function like search. What search vendor does not include smart software, semantics, and more Gartner-infused techno babble? Not many.
- Short cuts for training smart software for machine learning is indeed important. However, the approach which strikes me as interesting is the one taken by the ever-pragmatic AWS system pushed along by the Bezos bulldozer. AWS wants to make training a matter of buying commodity solutions of data off the shelf. Presumably the approach works like one of those consumer soap tablets I have seen in our local grocery store. Buy, rip, and wash. Bingo! Clean ML. Grubbing in data is time consuming, expensive, and oh-so-easy to get wrong.
- The goal of “zero results” in eCommerce or any other domain is not exactly a challenge. Zero results deliver data. I know that an objective system displays only the objects matching my query. Not any longer. Synonym expansion, predictive analytics, clustering, and other numerical processes are going to show me something. Too bad that the “something” is usually not what I want.
- For special cases like ecommerce, instead of a list of crazy options, why not ask the user, “Do you want to see what products other people purchased when searching for X?” Choice is sometimes helpful.
Is this important? To me, yes. To most others, no.
The problem with making information easy is everywhere today. From individuals who disbelieve verifiable information like the earth is spheroid to the wisdom of demanding no law enforcement. Yeah, that will work.
Some quick facts to put this Lucidworks’ assertion in perspective. The company has ingested more than $209 million since 2007. I did some advice giving to the first president of Lucidworks, then called Lucid Imagination. I did some advice giving for another semi-lucid president. None of that advice resonated because recycling jargon does not generate sustainable revenues.
The point is that jazzy words and crazy ideas like “zero results” are bad are part of the problem search vendors face. Today’s search systems have drifted from displaying results which match a user’s query to dumping baloney on the display.
It is easier to yip yap with buzzwords that deal with some of the painful realities of information retrieval. Deep learning? Yeah, that will help the person locate that PowerPoint… not.
Stephen E Arnold, August 26, 2020
Will the US Government Understand Streaming and ISPs?
August 26, 2020
There’s hope I suppose. After reading “Streaming Is Laying Bare How Big ISPs, Big Tech, and Big Media Work Together Against Users,” I am not sure the message will get through. Dark patterns can be difficult to explain. Crafty and efficient MBAs create ways to harvest money. Consumers may get the drift, but regulators and elected officials? Maybe, maybe not.
One this is certain: With appeals like this one, most will just smile and move on:
We need more choices for our ISPs, so they can’t keep charging us more for bad service. We need more choices so they can’t leverage their captive audiences for their new video services. We need net neutrality so these giant companies can’t create fiefdoms where they manipulate how we spend our time online. And we need our technology to be freed from corporate deals so we get what we paid for.
For some fun reading, check out this cost comparison chart. How’s the communication with the US government working out?
Stephen E Arnold, August 26, 2020
Gartner Group: Planning Its Next Generation of Marketing Pitches
August 25, 2020
If you are a fan of Gartner, a mid-tier consulting firm, you will want to navigate to “Gartner Hype-Cycle Adds 20+ New Technologies.” Now the “new” part interests me. Examples include:
- AI-assisted design (maybe Eli Attia’s method or Google’s approach?)
- Biodegradable sensors
- Differential privacy (like having one work mobile and one personal mobile?)
- Composable enterprise (I have zero clue what this means)
- Health passports (like a receipt for passage to Poveglia (a Plague Island in 1793?)
- Social distancing technologies.
The write up reports:
Trust models based on responsible authorities are being replaced by algorithmic trust models to ensure privacy and security of data, source of assets and identity of individuals and things. Algorithmic trust helps to ensure that organizations will not be exposed to the risk and costs of losing the trust of their customers, employees and partners. Emerging technologies tied to algorithmic trust include secure access service edge (SASE), differential privacy, authenticated provenance, bring your own identity, responsible AI and explainable AI.
When will AI create the Gartner hype cycle? Will use of that technology generate “trust”? Gobble down a biodegradable sensor and social distance. The future of consulting is … no human consultants. That might be a step forward? Come to think of it. An AI generating a hype chart might actually use numbers and data, not opinions of those good enough to work at a mid tier consulting firm.
Stephen E Arnold, August 25, 2020
Palantir: Stakeholders May Know Whom to Blame If Money Does Not Flow
August 25, 2020
Another Palantir technologies item. Is it accurate? Who knows. But I found “Palantir Targeting 3 Class Voting Structure According to Leaked S-1, Giving Founders 49.999999% Control in Perpetuity” fun reading. The write up states:
Wow, this is a really complicated ownership structure.
Okay, I understand. Just as in the Great Chain of Being, there is “god” or in this case a “god group” at the top. In the middle are the people who do knowledge work for the “god group.” At the bottom are the worker bees.
The ownership structure is designed to make sure the “god group” has a say in things Palantirian.
Observations:
- Investors know whom to invite to a meeting if the Palantirians’ numbers don’t materialize. Will the “god group” show up for that chit chat? Unlikely. Their lawyers, for sure.
- Who leaked this document? Why? Under what circumstances? Is anyone “looking” into this referenced confidential S-1 filing? Peter Thiel, a big dog, must be really thrilled with the leaker, the leaked info, and the outfit disseminating confidential information.
- Will the complicated structure work as well as Mark Zuckerberg’s set up? Mr. Zuckerberg has more customers, multiple revenue opportunities, and billions of people. So, probably not as the Palentirians hope.
It is worth monitoring the situation.
Stephen E Arnold, August 25, 2020
Students of AI Do Not Study Ethics: Who Would Have Guessed? Plato?
August 25, 2020
Philosophers have argued about what is ethical for millennia and there are some agreed upon concepts: be kind, do not harm others, seek to better humanity, etc. Isaac Asimov is credited with creating the ethics for robots with his “Three Laws of Robotics.” However much Asimov’s robotic laws apply to reality, they are still fictional and real robotic/AI students need to learn more about ethics says The Next Web article: “Study: On 18% Of Data Science Students Are Learning About AI Ethics.”
The main ethical arguments surrounding AI are racial and gender biases and companies have launched their own AI ethical initiatives to avoid future problems. These initiatives are supposedly designed to serve humanity, but many critics say “ethics washing” will be a problem.
An even bigger issue is the lack of universities teaching future AI developers and data scientists about ethics related to their fields. Software firm Anaconda surveyed 2,360 data science students, professionals, and academics to see if they are being taught AI ethics. Only 18% of the students said they learned about the subject, while 15% of teachers said they taught it. There is interest to learn more, but no one implementing any curriculum nor programs:
“Anaconda’s survey of data scientists from more than 100 countries found the ethics gap extends from academia to industry. While organizations can mitigate the problem through fairness tools and explainability solutions, neither appears to be gaining mass adoption.
Only 15% of respondents said their organization has implemented a fairness system, and just 19% reported they have an explainability tool in place.”
Without ethics the consequences will affect legal, competitive, financial, and other sectors. Understandably these will trickle down to other parts of society and could be harmful.
Ethical laws are usually not enacted until predicted consequences are on full display, but do not science fiction works like Asimov already demonstrate the possibilities?
Whitney Grace, August 25, 2020
Bringing IT Department into Analytics Decisions: Seems Reasonable
August 25, 2020
Woe to the company that implements a data analysis solution without consulting its IT department. That is the moral of the IT Brief write-up, “Extracting Insights from Data Requires More than Just a Pretty Dashboard.” A slick dashboard is nice to have, and it can offer non-technical workers the comfort of pretty graphs, projections, and generated reports. But what happens when users do not understand the data that underlies these results? Contributor Steve Singer writes:
“If you’re not sure where your data comes from, or how clean it is, you can’t trust the reports you generate from it. In some cases, if you don’t know what you have, you don’t even know how to ask the right questions. Somehow, we all have to get smarter about our approaches to all the data in our organizations and our development of the skill sets needed to capitalize on dashboard analytics. … In some businesses, decisions on dashboard purchases and deployment are made with little or no consultation with the IT department and data specialists. No one carefully considers whether the stores of data are in a suitable form or location to support the new tools. All too often they are not. Business decision-makers then find themselves disappointed when the tools fail to deliver the benefits they expected. Avoiding this scenario requires business units discuss their objectives with IT so that together they can decide on the most effective products and approaches. Data specialists must be able to assess whether tools are fit for purpose and able to be linked to the organization’s existing IT infrastructure.”
A company’s IT department is (or should be) a wealth of technical expertise at decision-makers’ fingertips. Singer offers four tips for working together to make the best choices: Begin with a clear plan that defines objectives, then decide whether infrastructure changes are needed; examine data sources and stores; establish a trust score for available data; then, and only then, select the appropriate dashboard or toolset. Though such collaboration would be a drastic change for some companies, it is well worth the effort when data projects actually product the desired results. That beats flashy but meaningless graphs any day.
Cynthia Murrell, August 25, 2020
DarkCyber for 8-25-20: Andrax Hacker Toolkit, NSO Group PR Push, Tor Under Attack, and Eagle Drone Killer
August 25, 2020
DarkCyber is a video news program produced by Stephen E Arnold, publisher of Beyond Search and DarkCyber. You can view this week’s program on YouTube or Facebook.
The program for August 25, 2020, contains four stories. The first focuses on a hacker’s toolkit called Andrax. The packager of this penetration testing bundle makes some bold claims. Security professionals who use highly-regard pentest systems from ImmunitySec are called “dumbs” and “lamers.” Clever or uninformed marketing? You have to determine the answer for yourself.
The second story summarizes highlights of Massachusetts Institute of Technology’s “Technology Review” interview with the founder of NSO Group. NSO Group–unlike most vendors of specialized software–has been the subject of media scrutiny. In the interview, the founder of NSO Group seems to suggest that he does not understand the intelware market. Even more interesting is MIT’s decision to publish the interview and give NSO Group more media exposure. DarkCyber asks a question others have not posed.
The third story reviews two surprising items of information from a Nusenu study or analysis. (Nusenu may be a security firm, a Web services vendor, or a single individual.) The first interesting revelation in the Nusenu report is that about 25 percent of Tor relay exit servers have been compromised by an unknown third party. The second juicy morsel is the identification of five Internet service providers who may be hosting Tor relay servers and other interesting services.
The final story zooms to a single eagle. The Michigan government learned that an expensive drone was destroyed by an eagle. If you want your own raptor to knock down surveillance drones, DarkCyber provides a company that will provide an organic c-UAS (counter unmanned aerial system).
Kenny Toth, August 25, 2020
Misjudging Facebook: An Insight Pandemic Blinds Pundits
August 24, 2020
The stories about Mark Zuckerberg’s TikTok activities have sparked some semi-pundits’ engines to turn over. The Wall Street Journal (a Murdoch outfit) and the Next Web (a Silicon Valley style “real” new service) are two examples. The savvy Roman emperor look alike may be the Force causing the TikTok starship to lose momentum. Definitely exciting, and, if true, Mr. Zuckerberg may have the strategic insights of Julius Caesar who smoked Vercingetorix. TikTok has been wounded, and it is a slick story about insider access, political power, and business.
However, there’s an even more interesting bit of punditry about Facebook. Navigate to “Content Regulation Lapses Cast Doubts on Facebook’s Biz Model.” The write up states:
the problem is not one of image. Repeated data and content regulation lapses on Facebook’s part have emerged, and these have rightly raised severe questions about their business model, and led to more attention, scrutiny and questioning from several governments across the world, including India.
Navigate to the source document for of this “Facebook will fail” lens.
News flash: Content moderation is holiday window dressing. Facebook provides advertisers with quite useful access to people who will purchase stuff and believe things. The anti Facebook advertising boycott went nowhere.
As long as Mr. Zuckerberg causes some information channels to believe he can influence the president of the United States to help him chop block TikTok at the knees, Facebook wins.
Clear thinking about Facebook is needed. News channels who push the Facebook influence agenda and pundits who miss the big picture are like Miracle Gro dumped on a moth orchid. Mr. Zuckerberg is able to operate in a big field just right for shaping into an extension of Mr. Caesar’s holdings.
Stephen E Arnold, August 24, 2020
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