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Favor founders’ foray into real estate tech yields serious questions

(TECH NEWS) As Favor’s founders launch Sunroom, we have unanswered questions that will reveal the company’s intentions once answered.

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sunroom real estate rentals on demand

Popular delivery startup, Favor, was acquired by Texas grocer HEB in February for an undisclosed sum, freeing up the founders Ben Doherty and Zac Maurais up for their next venture. Enter Sunroom which makes property rental tours on-demand.

Sunroom seeks to improve the property rentals process – renters can search available properties, select the addresses they’d like to tour, and then order a “tour guide,” which is a licensed Sunroom agent that is paid an average of $20 per hour, kind of like Uber for property rentals.

The company currently serves Austin but has expressed publicly that they intend to expand.

Property managers pay Sunroom if a qualified tenant is placed, and renters never pay for the app (just like apartment locators, a common practice in Texas). At launch, the company differentiated itself as a tech contender with a $1.5M round of seed funding from heavy hitters like Tim Draper of Draper Associates, and Joshua Baer of Capital Factory.

Maurais told AustinInno, “We knew we wanted to do something inside of the rental market because it’s so massive and affects a lot of people. I’ve had bad landlords in the past and have been renting for the past decade. So I understand first hand.”

He also said that renters can keep application info saved in the app for their next rental experience, “almost like you’re building out your renter’s resume.” Perhaps the long game is building an alternative credit rating for renters? Now that would actually be interesting.

Technologists are inquisitive by nature – put a bunch in a room for a weekend hackathon and with technology, they’ve solved a problem that they hadn’t even thought about prior to the weekend. Thus, the industry is prone to inherently believe they have the answers to everything, and they’re accustomed to make decisions quickly and move nimbly which is something I personally admire.

But if you go to any tech meetup (we’ve hosted one monthly for 10+ years), and mention real estate, their beautiful brains flip into action mode, and there is an instinct that they can fix real estate. As a whole. What sucks about real estate? Not sure, but they know it sucks, and they can fix it.

That combination doesn’t mean they’re stupid or evil, just that they’re fixers. But it also means that endless attempts at “disruption” come from technologists rather than industry insiders with technology experience. And most efforts inevitably fail. Or they pivot into a modified version of the traditional model they sought to innovate in the first place (like Redfin).

Speaking of Redfin, that’s what first comes to mind when we see Sunroom (regarding how they potentially pay agents). But what also comes to mind is the model the founders created with Favor (compete with a national brand locally where they have a soft spot, seek acquisition by a large company to suit their tech needs).

So the future of Sunroom relies heavily on the answers to the following questions that we have sent to them multiple times, without answer:

  1. The 8 agents you have licensed under your broker, are they the only agents on demand?
  2. Who gets the commission on the rental, and what is the split for the $20/hr agent that showed the property?
  3. Do consumers sign any locator representation agreement with you?
  4. Are the agents on salary, hourly, or commission with a bonus of hourly pay for touring properties?
  5. Ben and Zac are now licensed agents – do either of you intend on being the broker when eligible? How’d you find the current broker? What’s the plan there?
  6. Do you guys intend on expanding beyond Austin? Which cities are next, and what does the growth plan look like?
  7. Has Redfin’s model been of inspiration for your model?
  8. What am I missing in why you’re so disruptive?

Further, what does the fiduciary relationship look like? Does Sunroom represent the renter or the property manager, or are they attempting dual agency? Are the agents employees or do they remain independent contractors? See how things can get hairy?

We’ve seen a bajillion startups come and go where outsiders try to get a cut of a commission via a slick app that implies representation, and even more than that seeking to manage the contract portion of rentals, and even MORE that offer showings on demand, but where I see disruption is in the pay model for agents (and the potential to cut agents out of the rental market), but until Sunroom answers basic questions, we simply won’t know.

Stay tuned – they’re either the first exciting disruption to hit the real estate market in so many years, or they’re another group of technologists that see a profit opportunity.

Lani is the Chief Operating Officer at The American Genius - she has co-authored a book, co-founded BASHH and Austin Digital Jobs, and is a seasoned business writer and editorialist with a penchant for the irreverent.

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Career consultants help job seekers beat AI robot interviews

(TECH NEWS) With the growth of artificial intelligence conducting the job screening, consultants in South Korea have come up with an innovative response.

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job screening by robot

When it comes to resume screenings, women and people of color are regularly passed over, even if they have the exact same resume as a man. In order to give everyone a fair try, we need a system that’s less biased. With the cool, calculating depictions of artificial intelligence in modern media, it’s tempting to say that AI could help us solve our resume screening woes. After all, nothing says unbiased like a machine…right?

Wrong.

I mean, if you need an example of what can go wrong with AI, look no further than Microsoft’s Tay, which went from making banal conversation to spouting racist and misogynistic nonsense in less than 24 hours. Not exactly the ideal.

Sure, Tay was learning from Twitter, which is a hotbed of cruelty and conflict, but the thing is, professional software isn’t always much better. Google’s software has been caught offering biased translations (assuming, for example, if you wrote “engineer” you were referring to a man) and Amazon has been called out for using job screening software that was biased against women.

And that’s just part of what could go wrong with AI scanning your resume. After all, even if gender and race are accounted for (which, again, all bets are off), you’d better bet there are other things – like specific phrases – that these machines are on the lookout for.

So, how do you stand out when it’s a machine, not a human, judging your work? Consultants in South Korea have a solution: teach people how to work around the bots. This includes anything from resume work to learning what facial expressions are ideal for filmed interviews.

It helps that many companies use the same software to do screening. Instead of trying to prepare to impress a wide variety of humans, if someone knew the right tricks for handling an AI system, they could potentially put in much less work. For example, maybe one human interviewer likes big smiles, while the other is put off by them. The AI system, on the other hand, won’t waver from company to company.

Granted, this solution isn’t foolproof either. Not every business uses the same program to scan applicants, for instance. Plus, this tech is still in its relative infancy – a program could easily be in flux as requirements are tweaked. Who knows, maybe someday we’ll actually have application software that can more accurately serve as a judge of applicant quality.

In the meantime, there’s always AI interview classes.

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Google chrome: The anti-cookie monster in 2022

(TECH NEWS) If you are tired of third party cookies trying to grab every bit of data about you, google has heard and responded with their new updates.

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3rd party cookies

Google has announced the end of third-party tracking cookies on its Chrome browser within the next two years in an effort to grant users better means of security and privacy. With third-party cookies having been relied upon by advertising and social media networks, this move will undoubtedly have ramifications on the digital ad sector.

Google’s announcement was made in a blog post by Chrome engineering director, Justin Schuh. This follows Google’s Privacy Sandbox launch back in August, an initiative meant to brainstorm ideas concerning behavioral advertising online without using third-party cookies.

Chrome is currently the most popular browser, comprising of 64% of the global browser market. Additionally, Google has staked out its role as the world’s largest online ad company with countless partners and intermediaries. This change and any others made by Google will affect this army of partnerships.

This comes in the wake of rising popularity for anti-tracking features on web browsers across the board. Safari and Firefox have both launched updates (Intelligent Tracking Prevention for Safari and the Enhanced Tracking Prevention for Firefox) with Microsoft having recently released the new Edge browser which automatically utilizes tracking prevention. These changes have rocked share prices for ad tech companies since last year.

The two-year grace period before Chrome goes cookie-less has given the ad and media industries time to absorb the shock and develop plans of action. The transition has soften the blow, demonstrating Google’s willingness to keep positive working relations with ad partnerships. Although users can look forward to better privacy protection and choice over how their data is used, Google has made it clear it’s trying to keep balance in the web ecosystems which will likely mean compromises for everyone involved.

Chrome’s SameSite cookie update will launch in February, requiring publishers and ad tech vendors to label third-party cookies that can be used elsewhere on the web.

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Computer vision helps AI create a recipe from just a photo

(TECH NEWS) It’s so hard to find the right recipe for that beautiful meal you saw on tv or online. Well computer vision helps AI recreate it from a picture!

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computer vision recreates recipe

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.

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