Matroid: Not Just Math, a Reminder That Google Is Not Search
October 15, 2020
For many people Google is search. Need a pizza? Google it. But for rick media in contexts like streaming video, Google has pizza cheese on its chin.
A venture funding information service called Finsmes published “Matroid Raises $20 Million in Series B Funding.” Add to the firm’s earlier funding, the company has tallied about $33 million to fuel its innovation engine.
Founded in 2016, the company works at the intersection of machine learning (smart software) and image analysis (more smart software). The Finsmes article states:
The company plans to use the new funding to accelerate product development and go-to-market expansion in manufacturing, industrial IOT (IIOT), and video security markets. Led by Reza Zadeh, CEO and Founder, Matroid Matroid is a studio for creating and deploying detectors (computer vision models) to search visual media for people, behavior, objects, and events — no programming required. Once a detector is developed, Matroid can search any live stream or recorded video, providing real time notifications when the object of interest has been detected. Customers use it in construction, manufacturing, security, media, retail and other industries.
Real time analysis of streaming video is a very important search problem. Despite the perception that “Google is search,” the market for a solution is hefty.
Observations:
- The name of the company is borrowed from math wonks
- Law enforcement and intelligence agencies need a solution that works to deal with the video data available to investigators
- Google’s YouTube search illustrates that ad-supported, good enough methods which rely on a creator to index products or tag videos are examples of old-school thinking, maybe Internet dinosaur thinking.
The company will require additional funding. Nailing real time streaming video knowledge generation requires a large hammer.
Stephen E Arnold, October 15, 2020
GSA Government Okays These Drones
October 12, 2020
The General Services Administration has given five manufacturers its blessing to sell their small unmanned aircraft systems (sUAS) to government agencies. GCN examines the development in, “US-Made Small Drones Added to GSA Schedule.” The Defense Innovation Unit (DIU) and the Army’s Short Range Reconnaissance program (SRR) have been working toward this approval for 18 months. That joint effort has developed drones equipped with situational awareness tools that can be deployed quickly. A related DIU project, Blue sUAS, focused on non-DOD applications of drones, like safety inspections, rescue missions, and fighting forest fires. Writer Stephanie Kanowitz informs us:
“The five companies whose products will be available are Altavian, Parrot, Skydio, Teal and Vantage Robotics. … Recognizing a need for drones that government agencies, including the military, could use, Vantage applied to be part of Blue sUAS and tweaked its Vesper unmanned aerial vehicle for federal agency use. Vesper, developed for DIU, differs from Vantage’s first-generation drone, Snap, in that it is ‘substantially more advanced in just about every way,’ including sensors, flight capabilities, security and materials, said Vantage CEO Tobin Fisher. ‘To be specific, on the sensor side, we developed a camera that can see in the dark in 4K and integrated a thermal sensor as well as 18x zoom,’ Fisher said. Additionally, Vesper can fly for 50 minutes and features an extended radio range with an AES 256-encrypted 5-mile link. Vesper is made with components from trusted sources, which Fisher said includes Qualcomm for the onboard processor, Microhard for the radio and SigmaTron International for assembly.”
Impressive. It was crucial that any component that touched data in any way be from a non-Chinese source. For security reasons, the 2020 National Defense Authorization Act prohibits government agencies from purchasing or using drones made in China. The effort goes beyond government agencies, though. Those eye-popping capabilities will soon grace commercial drones, as well. The article quotes the DIU’s Chris Bonzagni:
“These companies have been able to leverage the roughly $18 million in DOD investments to develop spinoff enterprise solutions to offer secure, domestically produced options to enterprise customers worldwide, ultimately adding a much-needed boost to the U.S. sUAS industrial base.”
Ready or not, drones are here to stay and only getting more capable and numerous. Chinese drones are interesting too, but some may phone home.
Cynthia Murrell, October 12, 2020
A New Role for Facial Recognition
October 6, 2020
The travel industry is finding its way around COVID-provoked limitations. Where once travelers were promised a “seamless” experience, they are now promised a “touchless” one, we learn from PhocusWire’s piece, “Touchless Tech: The Simple—and Advanced—Ways Ground Transport Providers Are Encouraging Travel.” Some measures are low-tech, like pledges to clean thoroughly, glove and mask use, and single-passenger rides instead of traditional shuttles. However, others are more technically advanced. The role of facial recognition in “touchless tickets” caught our eye. Writer Jill Menze reports:
“On the rail front, Eurostar has tapped facial-verification technology provider iProov to enable contactless travel from United Kingdom to France. With the solution, passengers can be identified without a ticket or passport when boarding the train, as well as complete border exit processes, at St. Pancras International station without encountering people or hardware. ‘What we’re trying to facilitate for the first time ever is a seamless process of going through ticket and border exit checks contactlessly and more fluidly than it’s ever been possible before using face verification,’ iProov founder and CEO Andrew Bud says. ‘That means, instead of checking people’s ID when they arrive, you check their ID long before. The idea is that you move the process of checking IDs away from the boarding point to the booking point.’ During booking, Eurostar will offer travelers an accelerated pre-boarding option, which allows passengers to scan their identity documentation using Eurostar’s app before using iProov’s facial biometric check, which uses patented controlled illumination to authenticate the user’s identity against the ID document. After that, travelers would not have to show a ticket or passport until they reach their destination.”
Eurostar plans to enact the technology next March, and Bud says other railway entities have expressed enthusiasm. This is an interesting use of facial recognition tech. It seems getting back to business is powerful motivation to innovate.
Cynthia Murrell, October 6, 2020
Quibbling over Quibi
October 1, 2020
Yep, quick bite. Just what investors needed. An money sucking mosquito draining financial blood from clueless investors.
“Why Quibi Failed” is one of those Silicon Valley management analyses I enjoy. The write up received wider distribution by its inclusion in the MSN news channel. Yep, a Microsoft real news operation, not to be confused with Bing news, the messages displayed in Windows 10, or the razzle dazzle about Surface Duo. Hey, I know. Combine the Duo with the quick bite thing. That’s an idea: A $1400 gizmo that plays Quibi content. Winner!
The “Why Quibi Failed” explains that has failed. The write up paints a dire picture:
Since its US debut in April, Quibi seemed destined for such an ending. It badly missed subscriber and viewership targets and in June was on pace to sign up only 2 million paying subscribers by the end of the year (its goal was over 7 million). It was forced to manage reports of mass layoffs and rumors that its founder, Jeffrey Katzenberg, and its CEO, Meg Whitman, were not seeing eye to eye. And now it’s fighting a lawsuit filed by a video company alleging Quibi infringed on its patented technology (Quibi denies this).
In point of fact, the outfit is chugging along and might pull off a sale to another company looking for magic; that is, content. Sounds like Quibi needs to upgrade its public relations unit.
Why has Quibi been bitten where the sun does not shine? The write up turns to one of the wizards leading the charge to the future of entertainment, Jeffrey Katzenberg:
Katzenberg blamed everything on the coronavirus.
The article explains:
Quibi could have invested more in content from celebrities its younger audience might actually appreciate, like YouTube, Instagram, or TikTok stars. Instead, it threw lots of money at the kind of names that older executives might imagine young people enjoy—Jennifer Lopez, Idris Elba, Tyra Banks, Usher, and every teenager’s favorite actor, 53-year-old Kiefer Sutherland.
The idea is that old school Hollywood thinking is not hip to the charms of Bad Bunny or the ever delightful video style of Gamers Nexus.
Other reasons for the alleged failure of Quibi include:
- Content (wait, not a strength)
- Lack of “shareability”
- The format of quick bites; that is, 10 minute chunks of juicy digital goodness.
But wait. There’s no fix, no options, no recommendations.
That’s a bit of a problem with Silicon Valley business thinking. Imagine. Figuring out next steps.
Several observations:
- A closer look at the management track record of the Quibi leadership would be helpful. Hints about “tension” are okay, but let’s dig into the facts like disastrous deals and massive flops suggest that headwinds have been blowing for years
- Quibi’s “chunk at a time” is out of step with the type of real-time, constant-click data available to an outfit like TikTok, Amazon Twitch, and (gasp!) Facebook Instagram Reels. Mismatch? For sure.
- Some information about the production deals for the magical content. With it content is often produced, edited, and distributed from a laptop in an RV camp or from an organic vegan coffee shop; for example, the antics of Kara and Nate and their interesting videos. Quibi did it the Hollywood 1980s way. That’s a money saving idea.
- A bit of digging into the “management style” of Mr. Katzenberg and Ms. Whitman could be complemented with actual interviews of people who knew how these two brilliant leaders interacted with one another.
There is a book waiting to be written about Quibi. If there were functional universities teaching business the old fashioned way, there is at least one case study. The legal antics of Quibi investors might enliven a law review if these print centric publications are still funded.
In short, the analysis like Quibi seems oddly appropriate even with Rona ready to accept the blame. Quick bite? Nope, big chomp in tender places. One may want to consider that Quibi is “actually quite good.” But for whom?
Stephen E Arnold, October 1, 2020
Fujitsu Simplifies, Reduces Costs of Preventing Facial Authentication Fraud
September 25, 2020
Fujitsu says it has developed a cost-effective way to thwart attempts to fool facial recognition systems, we learn from IT-Online’s write-up, “Fujitsu Overcomes Facial Authentication Fraud.” The same factor that makes facial authentication systems more convenient than other verification methods, like images of fingerprints or palm veins, also makes them more vulnerable to fraud—photos of faces are easy to capture and reproduce. We’re told:
“Fujitsu Laboratories has developed a facial recognition technology that uses conventional cameras to successfully identify efforts to spoof authentication systems. This includes impersonation attempts in which a person presents a printed photograph or an image from the internet to a camera. Conventional technologies rely on expensive, dedicated devices like near-infrared cameras to identify telltale signs of forgery, or the user is required to move their face from side to side, which remains difficult to duplicate with a forgery. This leads to increased costs, however, and the need for additional user interaction slows the authentication process. To tackle these challenges, Fujitsu has developed a forgery feature extraction technology that detects the subtle differences between an authentic image and a forgery, as well as a forgery judgment technology that accounts for variations in appearance due to the capture environment. … Fujitsu believes that, by using these technologies, it becomes possible to identify counterfeits using only the information of face images taken by a general-purpose camera and to realize relatively convenient and inexpensive spoofing detection.”
We’re told the company tested the system in a real-world office/ telecommuting setting and confirmed it works as desired. Fujitsu hopes the technology will prove popular as remote work continues and, possibly, grows. The venerable global information and communication tech firm serves many prominent companies in several industries. Based in Tokyo, Fujitsu has been operating since 1935.
Cynthia Murrell, September 25, 2020
Podcast Search: Illuminating the Rich Media Darkness
September 22, 2020
Search for podcasts is broken. We learn of a possible first step toward a fix from Podnews in the brief write-up, “The Podfather Launches a New, Open Podcast Directory.” James Cridland writes:
“‘The digital ad space is watching as the bottom falls out of their data collection methods. But how exactly does Apple’s Age of Privacy impact podcasting?’ – in today’s Sounds Profitable, our new adtech newsletter, with Podsights.
“Adam Curry has launched a new, open podcast directory for app developers, working with developer Dave Jones. Speaking on a new podcast, Podcasting 2.0, Curry and Jones worry that ‘Apple is starting to tinker with their directory’, and say that the company is ‘a very centralized private entity that is controlling pretty much what everybody considers the default yellow pages for podcasting.’ His alternative, The Podcast Index, promises that the ‘core, categorized index will always be available for free, for any use’. You can sign up to be a developer on their developer portal. We support this initiative. As of today, Podnews uses The Podcast Index for our main podcast search.”
The index is a simple type-and-search format. It seems to work acceptably well on Podnews’ database, though it could use a little relevance refinement. Will the open directory attract developers and reach the larger segment? We hope this or another solution is implemented soon.
Cynthia Murrell, September 22, 2020
Facial Recognition: Who Is Against Early Diagnosis of Heart Disease?
September 3, 2020
The anti-facial recognition cohort may have a new challenge on their capable hands. Facial recognition is controversial. What if analysis of a face — for instance, in a selfie — can lead to an early diagnosis of heart disease. The person is alerted to visit a doctor. What if a life is saved? Is facial recognition granted a hall pass for a medical application?
I don’t want to dwell on fencing applications of pattern recognition. I would suggest that a quick look at “AI Expected to Detect Heart Disease via Selfies: Chinese Researchers” might be interesting. The write up states:
Facial appearance has long been identified as an indicator of cardiovascular risk. Features such as male pattern baldness, earlobe crease, xanthelasmata (yellowish deposit of fat around or on the eyelids) and skin wrinkling are the most common predictors.
And what about accuracy?
According to the results published in the European Heart Journal, the algorithm had a sensitivity of 80 percent and specificity of 54 percent, outperforming the traditional prediction model of coronary artery disease. Sensitivity refers to the algorithm’s ability to designate a patient with a disease as positive, while specificity is the test’s ability to designate a patient without disease as negative.
Interesting. How will anti-FR cohorts deal with medical technology which finds its way into different government agencies? DarkCyber does not have an answer, but perhaps pattern recognition will be banned? Perhaps not, however?
Stephen E Arnold, September 3, 2020
Maps with Blank Spots
September 2, 2020
We noted the “real” news outfit story “Blanked-Out Spots On China’s Maps Helped Us Uncover Xinjiang’s Camps.” The how to is interesting. We learned:
Our breakthrough came when we noticed that there was some sort of issue with satellite imagery tiles loading in the vicinity of one of the known camps while using the Chinese mapping platform Baidu Maps. The satellite imagery was old, but otherwise fine when zoomed out — but at a certain point, plain light gray tiles would appear over the camp location. They disappeared as you zoomed in further, while the satellite imagery was replaced by the standard gray reference tiles, which showed features such as building outlines and roads. At that time, Baidu only had satellite imagery at medium resolution in most parts of Xinjiang, which would be replaced by their general reference map tiles when you zoomed in closer. That wasn’t what was happening here — these light gray tiles at the camp location were a different color than the reference map tiles and lacked any drawn information, such as roads.
After reading the article, DarkCyber wonders what other interesting sites are missing?
Stephen E Arnold, September 2, 2010
Defeating Facial Recognition: Chasing a Ghost
August 12, 2020
The article hedges. Check the title: “This Tool could Protect Your Photos from Facial Recognition.” Notice the “could”. The main idea is that people do not want their photos analyzed and indexed with the name, location, state of mind, and other index terms. I am not so sure, but the write up explains with that “could” coloring the information:
The software is not intended to be just a one-off tool for privacy-loving individuals. If deployed across millions of images, it would be a broadside against facial recognition systems, poisoning the accuracy of the data sets they gather from the Web. <
So facial recognition = bad. Screwing up facial recognition = good.
There’s more:
“Our goal is to make Clearview go away,” said Dr Ben Zhao, a professor of computer science at the University of Chicago.
Okay, a company is a target.
How’s this work:
Fawkes converts an image — or “cloaks” it, in the researchers’ parlance — by subtly altering some of the features that facial recognition systems depend on when they construct a person’s face print.
Several observations:
- In the event of a problem like the explosion in Lebanon, maybe facial recognition can identify some of those killed.
- Law enforcement may find narrowing a pool of suspects to a smaller group may enhance an investigative process.
- Unidentified individuals who are successfully identified “could” add precision to Covid contact tracking.
- Applying the technology to differentiate “false” positives from “true”positives in some medical imaging activities may be helpful in some medical diagnoses.
My concern is that technical write ups are often little more than social polemics. Examining the upside and downside of an innovation is important. Converting a technical process into a quest to “kill” a company, a concept, or an application of technical processes is not helpful in DarkCyber’s view.
Stephen E Arnold, August 12, 2020
Visual Search Engines Provide Different POV Than the Google
July 15, 2020
Google image search is the standard visual search tool people use. It does not, however, provide the extra kick needed for deeper dives, especially with all the Pinterest results. Tech Funnel addresses how visual search engines are an advantage for businesses as well as points out nine great ones in: “Popular 9 Visual Search Engines To Know.”
There are many benefits to using visual search, such as it that it connects with younger generations because they connect with images when they use social media and apps. They are far more likely to purchase an item through these platforms than a Web site. Visual search also allows people to emotionally connect with a brand than standard text and it boosts revenue as it will be the next way people search for items along with voice search.
Popular visual search engines include Pinterest Lens that allows users to take photos of items and they can find, save, or shop for them. Fashion retailers are already using it, so Pinterest users can find clothing their models wear. Google Lens is similar to Pinterest Lens, except its applications are more diverse. It can be used for translation, searching for items, places, people, etc.
Amazon Rekognitio, Instagram Shopping, Snapchat Camera Search, and eBay powered by Cassini search engine have visual search engines dedicated to searching and locating items from photos. They each have different aspects, but all perform the same function. Bing appears to be different:
“From the viewpoint of a user, the experience gotten from Bing Visual Search is similar to other various visual search platforms. However, its feature of an extensive developer platform makes it preferable by a lot of developers.
With Bing Visual Search, developers are enabled to instruct the search engine on the particular data people can get from a specific photo. This means that if Bing Visual Search directs an individual to a certain product on your website, the developer has the ability to determine what information should be provided to the visitor.”
CamFind and EasyJet are the most original engines, because they are not associated with shopping nor Google. CamFind is the first successful mobile visual engine that uses image detection. EasyJet allows people to book flights based off photos, so now you can finally discover where you screen wallpaper is located.
Whitney Grace, July 15, 2020
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