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Copyright © 2018 Mindset Ventures. All Rights Reserved.
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Copyright © 2018 Mindset Ventures. All Rights Reserved.
Design by Eólica.

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Skyline AI raises $18M Series A for its machine learning-based real estate investment tech.

A mere four months after coming out of stealth mode with $3 million in seed funding, real estate investment startup Skyline AI announced that it has raised an $18 million Series A. The round was led by Sequoia Capital, a returning investor, and TLV Partners, with participation from JLL Spark, a division of real estate investment management firm JLL. The strategic funding will allow Skyline AI to add more asset classes to its platform, which uses data science and machine learning algorithms to help institutional investors make better decisions about properties.

Skyline AI says its technology is trained on what it claims is the most comprehensive data set in the industry, drawing from more than 100 sources, with market information covering the last 50 years. Its technology is meant to provide faster and more accurate analysis than traditional methods, so investors can react more quickly to changes in the real estate market.

Co-founder and CEO Guy Zipori told TechCrunch in an email that the startup decided to raise its Series A so soon after coming out of stealth because of positive response from investors, adding that the round was oversubscribed. “The timing of the round also worked out perfectly with our current deal flow and expansion plans. The round was significant, putting us in a great position to move forward,” he said.

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Taranis Acquires Aerial Imagery Platform Mavrx.

Israeli precision agriculture intelligence platform Taranis is acquiring the assets of Mavrx, the San Francisco-based aerial imagery platform.

Taranis will integrate Mavrx’s aircraft-based ultra-high resolution (UHR) imagery product into its AI2 product line and bring existing Mavrx customers onto the Taranis platform. Taranis is also taking on some of Mavrx’s customer-facing and sales staff as well as the team that ran flight operations.

Taranis helps farmers increase their yields and cut costs by monitoring their fields with sensors, weather data, field scouting and imagery using computer vision, data science and deep learning algorithms to detect early symptoms of weeds, uneven emergence, nutrient deficiencies, disease/insect infestations, water damage, equipment problems and more. The aim is to help farmers address issues quickly and understand the impact on yield and cost of production.

It is understood that Mavrx ran into some financial and operational difficulty in recent months and was not able to service its clients for the upcoming growing season despite providing a popular product with a 90% customer renewal rate.

“As well as adding Mavrx technology to the Taranis platform, we felt we had a moral obligation to serve Mavrx’s existing clients with our product lines, especially as we saw how much they liked the Mavrx product,” Ofir Schlam, founder and CEO of Taranis told AgFunderNews.

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Proven wants to sell AI distilled custom skincare.

YC-backed startup Proven wants to make it suck less for women to find skincare that works for them. The co-founders are taking what they describe as a “rational, logic-based” approach to figuring out which ingredients might be most appropriate for each individual.

As a TC Disrupt battlefield founder once memorably put it during her on-stage pitch, the beauty industry makes a whole lot of money from a whole lot of BS. And skincare falls squarely into the ‘full of it’ category, with its expensively marketed pseudoscientific claims touting ‘miracle’ fixes that most definitely aren’t.

Proven’s co-founders, Ming Zhao and Amy Yuan, say frustration when battling with this BS via their own skincare issues ultimately led them to found the business together. Zhao had had a stressful job in private equity which she credits with “really wrecking my skin”, while Yuan suffered adolescent skin problems and also has allergies that can affect it.

“After trying numerous products and investing — I saw it as an investment, in expensive ‘miracle’-promising products — nothing really worked for me,” says Zhao. “So I became very frustrated and I felt betrayed by our beauty industry. And eventually what actually worked for me were customized products that were made for my by a few different facialists. So that’s how the optimize idea of tailoring products to exactly someone’s situation, someone’s skin, first came to my mind numerous years ago.”

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Sepio Systems Solution to Prevent ATM Jackpotting Attacks.

“Sepio’s software suite can prevent the recent ATM Jackpotting attacks”.

“Sepio’s software suite can prevent the recent ATM Jackpotting attacks,” said Robert Bigman, a senior advisor to Sepio and the former Chief Information Security Officer for the Central Intelligence Agency. “The recent attacks are a painful demonstration of the ease of executing cyber-attack after gaining physical access to IT equipment. The current approach to ATM security is insufficient. Integrating cyber-physical security components is a necessity," added Mr. Bigman.

ATM Jackpotting attacks have been around for a while, mostly in South America and Africa. Recent developments and warnings coming from the U.S Secret Service confirm that this type of cyber-crime is now widely happening in the US as well.

The described attack goes through the process of infecting the ATM with the Ploutus.D malware, and then maintaining remote access capabilities to trigger the cash spitting. All Jackpotting attacks, require physical access to the ATM to connect USB device. Keyboard emulator, detachable media and wireless interface are used for infecting the machine.

“Sepio’s software suite prevent these attacks by blocking any malicious hardware from being connected. Our solution alerts when a new device is connected before the attack starts,” said Greg Poch, Sepio Systems Vice President of Sales. “Our clients find our solution effective and easy to maintain,” added Mr. Poch.

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Health Tech Podcast: How AI is making humans the ‘fundamental thing in the internet of things’.

GeekWire’s Health Tech Podcast goes in-depth with tech innovators bringing new ideas and ingenuity to digital health and wellness.

Twenty years ago, in 1998, you would have been hard-pressed to find a single hospital room with a personal computer in it.

Patient files were kept in filing cabinets. Prescriptions were written by hand. The Human Genome Project was still just halfway through a years-long, multi-billion-dollar effort to sequence the DNA of the human race. In short, there wasn’t a huge abundance of data on our health.

Today, electronic medical records and advanced genetic sequencing have completely changed the landscape — and brought challenges and opportunities that are almost impossible for humans to tackle on their own. That’s where artificial intelligence steps in.

AI is finding fertile ground for growth in hospitals and medical labs around the world, promising to give human health a boost as it addresses everything from preventing heart attacks to revolutionizing how we diagnose diseases. That interplay is the topic of our most recent Health Tech Podcast, and if the experts are to be believed, it’s just the beginning.

“I see this possibility of precision health, where people are the most fundamental thing in the Internet of Things,” said Peter Lee, a corporate vice president at Microsoft who leads the company’s NExT program. “When we’re looking 10 years out, that sort of precision in diagnosis and treatment, I think, can be incredibly powerful.”

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This Former White House Staffer Invented a Video Game That Could Reinvent the Hiring Process.

Founded by a former White House staffer, San Francisco-based Scoutible is using artificial intelligence to change the hiring process.

Hiring someone who turns out to be a bad fit can be costly: Unhappy employees cost the U.S. economy between $450 billion and $550 billion in lost productivity each year, according to research firm Gallup. And replacing a full-time worker can cost up to twice the employee's salary.

While working on a project at Harvard Law School, Angela Antony found herself immersed in statistics like those.

"If you look across the economy, about 46 percent of hires leave within 18 months. That's despite all the time, resources, and billions of dollars spent trying to effectively hire," Antony says. "My research was really trying to understand what that missing data set was that was preventing us from being able to accurately predict people's long-term performance in a role."

That research helped land her a job at the White House with the National Economic Council in 2015. It was there, at an entrepreneurship policy event, that she met Mark Cuban. Antony told him about her research and the book she was writing on the topic.

"Mark said, 'Don't finish that book,' " Antony says. " 'You should build the solution, and I want to fund it.' "


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