Ever seen at a photo of a delicious looking meal on Instagram and wondered how the heck to make that? Now there’s an AI for that, kind of.
Facebook’s AI research lab has been developing a system that can analyze a photo of food and then create a recipe. So, is Facebook trying to take on all the food bloggers of the world now too?
Well, not exactly, the AI is part of an ongoing effort to teach AI how to see and then understand the visual world. Food is just a fun and challenging training exercise. They have been referring to it as “inverse cooking.”
According to Facebook, “The “inverse cooking” system uses computer vision, technology that extracts information from digital images and videos to give computers a high level of understanding of the visual world,”
The concept of computer vision isn’t new. Computer vision is the guiding force behind mobile apps that can identify something just by snapping a picture. If you’ve ever taken a photo of your credit card on an app instead of typing out all the numbers, then you’ve seen computer vision in action.
Facebook researchers insist that this is no ordinary computer vision because their system uses two networks to arrive at the solution, therefore increasing accuracy. According to Facebook research scientist Michal Drozdzal, the system works by dividing the problem into two parts. A neutral network works to identify ingredients that are visible in the image, while the second network pulls a recipe from a kind of database.
These two networks have been the key to researcher’s success with more complicated dishes where you can’t necessarily see every ingredient. Of course, the tech team hasn’t stepped foot in the kitchen yet, so the jury is still out.
This sounds neat and all, but why should you care if the computer is learning how to cook?
Research projects like this one carry AI technology a long way. As the AI gets smarter and expands its limits, researchers are able to conceptualize new ways to put the technology to use in our everyday lives. For now, AI like this is saving you the trouble of typing out your entire credit card number, but someday it could analyze images on a much grander scale.
Airbnb has blocked 50K+ bookings for being too big during COVID-19
(NEWS) Airbnb has cancelled a huge number of reservations as a security precaution during COVID-19 in the past year or so.
In the last year or so, Airbnb has purposefully prevented at least 50,000 people from making irresponsible reservations on their properties, in many cases blocking those people from the platform itself. This prevention, at least in theory, helped cut down on the number of COVID parties during the pandemic.
According to The Verge, Airbnb’s head of trust and safety communication, Ben Breit, acknowledged blocked reservations in several cities across the United States, including Dallas, San Diego, and New Orleans. Breit confirmed that this response was an attempt to prevent large gatherings and parties during the height of the COVID-19 pandemic during which many areas banned group activities involving more than a few people.
While some requests for reservations were simply denied or “redirected”, many users were blocked from using Airbnb entirely. Airbnb noted that the number of blocked requests outpaced the number of people who were blocked, signifying that some accounts attempted to make more than one reservation before being removed from the platform.
Airbnb reportedly stated that “Instituting a global ban on parties and events is in the best interest of public health” prior to enacting a total ban on rentals at the beginning of 2020, a decision that gave way to the blocks and redirections in the last 12 months.
The evaluation system used to flag problematic reservations is relatively simple, according to Breit: “If you are under the age of 25 and you don’t have a history of positive reviews, we will not allow you to book an entire home listing local to where you live.”
But Airbnb didn’t entirely remove multiple-body listings or large rentals. The Verge reports that flagged users with the aforementioned criteria were still able to book both small rentals in local locations and larger rentals in reasonably distant locations.
Regardless of the optics here, Airbnb’s policy efficacy can’t be ignored. Multiple cities reported comparatively “quiet” holiday seasons–something that may contribute to Airbnb’s decision to extend their policy through the end of this summer.
The hosting company is also offering increased security measures, such as noise detection and a 24-hour hotline, at a discounted rate to property owners.
As both the vaccine gap and the proliferation of the Delta variant of COVID-19 continue to contribute to outbreaks, one can reasonably expect Airbnb to hold to this policy.
TL;DV summarizes video meetings so folks can catch up in quickly *with* context
(TECHNOLOGY) TL;DV makes catching up on video team meetings slightly more tolerable and easily digestable.
2021 was the year of virtual meetings, and while there are some perks associated with remote collaboration (I’m looking at you, pair of work pants that I didn’t have to wear once this year), these meetings often feel exponentially more arduous than their dressed-up counterparts. TL;DV, a consolidation app for Google Meet, looks to give back a bit of your time.
TL;DV (an acronym for “Too Long; Didn’t View”) is a Google Chrome recording extension that helps users specify important sections of meetings for anyone who needs to view them asynchronously. Users can tag specific segments in Google Meet sessions, transcribe audio, and leave notes above tagged sections for timestamp purposes, and the subsequent file can be shared via a host of both Google and third-party apps.
While the extension is only available for Google Meet at the time of writing, the TL;DV team has included a link to a survey for Zoom and MS Teams users on their site, thus implying that the team is looking into expanding into those platforms in the future.
The mission behind TL;DV is, according to the website, to empower users to “control how we spend our precious time” in the interest of combatting FOMO and meeting fatigue. By dramatically shortening the amount of time one must spend perusing a meeting recording, they seem well on their way to doing so.
Of course, the issue of human oversight remains. It seems likely that meeting facilitators will drop the ball here and there while tagging sections of the recording, and employees who miss crucial information in a recorded session are sure to be frustrated in the process–just not as frustrated as they might be if they attended the entire meeting live.
The current (free) version of TL;DV is in Beta, so users will have a three-hour cap on their videos. The development team promises a professional version by the end of 2021, with the added bonus of leaving prior recordings available for free for anyone who used the Beta. This is certainly an extension to keep an eye on–whether or not you’re remaining remote in 2022, virtual conferencing is no doubt here to stay.
Hiding from facial recognition is a booming business
(TECH NEWS) ‘Cloaking’ is the new way to hide your face. Companies are making big money designing cloaking apps that thwart your features by adding a layer of make up, clothing, blurring, and even transforming you into your favorite celebrity.
Facial recognition companies and those who seek to thwart them are currently locked in a grand game of cat and mouse. Though it’s been relentlessly pursued by police, politicians, and technocrats alike, the increasing use of facial recognition technology in public spaces, workplaces, and housing complexes remains a widely unpopular phenomenon.
So it’s no surprise that there is big money to be made in the field of “cloaking,” or dodging facial recognition tech – particularly during COVID times while facial coverings are, literally, in fashion.
Take Fawkes, a cloaking app designed by researchers at the University of Chicago. It is named for Guy Fawkes, the 17th century English revolutionary whose likeness was popularized as a symbol of anonymity, and solidarity in V For Vendetta.
Fawkes works by subtly overlaying a celebrity’s facial information over your selfies at the pixel level. To your friends, the changes will go completely unnoticed, but to an artificial intelligence trying to identify your face, you’d theoretically look just like Beyonce.
Fawkes isn’t available to the general public yet, but if you’re looking for strategies to fly under the radar of facial recognition, don’t fret; it is just one example of the ways in which cloaking has entered the mainstream.
Other forms of cloaking have emerged in the forms of Tik Tok makeup trends, clothes that confuse recognition algorithms, tools that automatically blur identifying features on the face, and much more. Since effective facial recognition relies on having as much information about human faces as possible, cloaking enthusiasts like Ben Zhao, Professor of computer science at the University of Chicago and co-developer of Fawkes, hope to make facial recognition less effective against the rest of the population too. In an interview with The New York Times, Zhao asserts, “our [team’s] goal is to make Clearview [AI] go away.”
For the uninitiated, Clearview AI is a start-up that recently became infamous for scraping billions of public photos from the internet and privately using them to build the database for a law enforcement facial recognition tool.
The CEO of Clearview, Hoan Ton-That, claimed that the tool would only be improved by these workarounds and that in long run, cloaking is futile. If that sounds like supervillain talk, you might see why he’s earned himself a reputation similar to the likes of Martin Shkreli or Ajit Pai with his company’s uniquely aggressive approach to data harvesting.
It all feels like the beginning of a cyberpunk western: a story of man vs. machine. The deck is stacked, the rules are undecided, and the world is watching. But so far, you can rest assured that no algorithm has completely outsmarted our own eyeballs… yet.
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