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March 25, 2019
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CoParenter helps divorced parents settle disputes using AI and human mediation

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A former judge and family law educator has teamed up with tech entrepreneurs to launch an app they hope will help divorced parents better manage their co-parenting disputes, communications, shared calendar and other decisions within a single platform. The app, called coParenter, aims to be more comprehensive than its competitors, while also leveraging a combination of AI technology and on-demand human interaction to help co-parents navigate high-conflict situations.

The idea for coParenter emerged from co-founder Hon. Sherrill A. Ellsworth’s personal experience and entrepreneur Jonathan Verk, who had been through a divorce himself.

Ellsworth had been a presiding judge of the Superior Court in Riverside County, California for 20 years and a family law educator for 10. During this time, she saw firsthand how families were destroyed by today’s legal system.

“I witnessed countless families torn apart as they slogged through the family law system. I saw how families would battle over the simplest of disagreements like where their child will go to school, what doctor they should see and what their diet should be — all matters that belong at home, not in a courtroom,” she says.

Ellsworth also notes that 80 percent of the disagreements presented in the courtroom didn’t even require legal intervention — but most of the cases she presided over involved parents asking the judge to make the co-parenting decision.

As she came to the end of her career, she began to realize the legal system just wasn’t built for these sorts of situations.

She then met Jonathan Verk, previously EVP Strategic Partnerships at Shazam and now coParenter CEO. Verk had just divorced and had an idea about how technology could help make the co-parenting process easier. He already had on board his longtime friend and serial entrepreneur Eric Weiss, now COO, to help build the system. But he needed someone with legal expertise.

That’s how coParenter was born.

The app, also built by CTO Niels Hansen, today exists alongside a whole host of other tools built for different aspects of the co-parenting process.

That includes those apps designed to document communication, like OurFamilyWizard, Talking Parents, AppClose and Divvito Messenger; those for sharing calendars, like Custody Connection, Custody X Exchange and Alimentor; and even those that offer a combination of features like WeParent, 2houses, SmartCoparent and Fayr, among others.

But the team at coParenter argues that their app covers all aspects of co-parenting, including communication, documentation, calendar and schedule sharing, location-based tools for pickup and drop-off logging, expense tracking and reimbursements, schedule change requests, tools for making decisions on day-to-day parenting choices like haircuts, diet, allowance, use of media, etc. and more.

Notably, coParenter also offers a “solo mode” — meaning you can use the app even if the other co-parent refuses to do the same. This is a key feature that many rival apps lack.

However, the biggest differentiator is how coParenter puts a mediator of sorts in your pocket.

The app begins by using AI, machine learning and sentiment analysis technology to keep conversations civil. The tech will jump in to flag curse words, inflammatory phrases and offensive names to keep a heated conversation from escalating — much like a human mediator would do when trying to calm two warring parties.

When conversations take a bad turn, the app will pop up a warning message that asks the parent if they’re sure they want to use that term, allowing them time to pause and think. (If only social media platforms had built features like this!)

 

When parents need more assistance, they can opt to use the app instead of turning to lawyers.

The company offers on-demand access to professionals as both monthly ($12.99/mo – 20 credits, or enough for two mediations) or yearly ($119.99/year – 240 credits) subscriptions. Both parents can subscribe for $199.99/year, each receiving 240 credits.

“Comparatively, an average hour with a lawyer costs between $250 and upwards of $500, just to file a single motion,” Ellsworth says.

These professionals are not mediators, but are licensed in their respective fields — typically family law attorneys, therapists, social workers or other retired bench officers with strong conflict resolution backgrounds. Ellsworth oversees the professionals to ensure they have the proper guidance.

All communication between the parent and the professional is considered confidential and not subject to admission as evidence, as the goal is to stay out of the courts. However, all the history and documentation elsewhere in the app can be used in court, if the parents do end up there.

The app has been in beta for nearly a year, and officially launched this January. To date, coParenter claims it has already helped to resolve more than 4,000 disputes and more than 2,000 co-parents have used it for scheduling. Indeed, 81 percent of the disputing parents resolved all their issues in the app, without needing a professional mediator or legal professional, the company says.

CoParenter is available on both iOS and Android.

News Source = techcrunch.com

Facebook says its new A.I. technology can detect ‘revenge porn’

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Facebook on Friday announced a new artificial intelligence powered tool that it says will help the social network detect revenge porn – the nonconsensually shared intimate images that, when posted online, can have devastating consequences for those who appear in the photos. The technology will leverage both A.I. and machine learning techniques to proactively detect near nude images or videos that are shared without permission across Facebook and Instagram.

The announcement follows on Facebook’s earlier pilot of a photo-matching technology, which had people directly submit their intimate photos and videos to Facebook. The program, which was run in partnership with victim advocate organizations, would then create a digital fingerprint of that image so Facebook could stop it from ever being shared online across its platforms. This is similar to how companies today prevent child abuse images from being posted to their sites.

The new A.I. technology for revenge porn, however, doesn’t require the victim’s involvement. This is important, Facebook explains, because victims are sometimes too afraid of retribution to report the content themselves. Other times, they’re simply unaware that the photos or videos are being shared.

While the company was short on details about how the new system itself works, it did note that it goes beyond simply “detecting nudity.”

After the system flags an image or video, a specially trained member of Facebook’s Community Operations team will review the image then remove it if it violates Facebook’s Community Standards. In most cases, the company will also disable the account, as a result. An appeals process is available if the person believes Facebook has made a mistake.

In addition to the technology and existing pilot program, Facebook says it also reviewed how its other procedures around revenge porn reporting could be improved. It found, for instance, that victims wanted faster responses following their reports and they didn’t want a robotic reply. Other victims didn’t know how to use the reporting tools or even that they existed.

Facebook noted that addressing revenge porn is critical as it can lead to mental health consequences like anxiety, depression, suicidal thoughts and sometimes even PTSD. There can also be professional consequences, like lost jobs and damaged relationships with colleagues. Plus, those in more traditional communities around the world may be shunned or exiled, persecuted or even physically harmed.

Facebook admits that it wasn’t finding a way to “acknowledge the trauma that the victims endure,” when responding to their reports. It says it’s now re-evaluating the reporting tools and process to make sure they’re more “straightforward, clear and empathetic.”

It’s also launching “Not Without My Consent,” a victim-support hub in the Facebook Safety Center that was developed in partnership with experts. The hub will offer victims access to organizations and resources that can support them, and it will detail the steps to take to report the content to Facebook.

In the months ahead, Facebook says it will also build victim support toolkits with more locally and culturally relevant info by working with partners including the Revenge Porn Helpline (UK), Cyber Civil Rights Initiative (US), Digital Rights Foundation (Pakistan), SaferNet (Brazil) and Professor Lee Ji-yeon (South Korea).

Revenge porn is one of the many issues that results from offering the world a platform for public sharing. Facebook today is beginning to own up to the failures of social media across many fronts – which also include things like data privacy violations, the spread of misinformation, and online harassment and abuse.

CEO Mark Zuckerberg recently announced a pivot to privacy, where Facebook’s products will be joined together as an encrypted, interoperable, messaging network – but the move has shaken Facebook internally, causing it to lose top execs along the way.

While changes are in line with what the public wants, many have already lost trust in Facebook. For the first time in 10 years Edison Research noted a decline in Facebook usage in the U.S., from 67 to 62 percent of Americans 12 and older. Still, Facebook still a massive platform with its over 2 billion users. Even if users themselves opt out of Facebook, that doesn’t prevent them from ever becoming a victim of revenge porn or other online abuse by those who continue to use the social network.

News Source = techcrunch.com

BMW continues to bet on the (Azure) cloud

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Earlier this week, at MWC Barcelona, BMW announced its newest in-car AI initiative: BMW Natural Interaction. The idea here is to use cameras, microphones and other sensors in the car to allow you to have more natural interactions with the car, either through voice or gestures. The marquee feature here is the ability to point at something outside the car and get more information about it or, if it’s a restaurant, have the BMW Intelligent Personal Assistant (IPA) make a reservation for you. These systems will work by combining in-car AI with cloud technologies — and for those, BMW continues to bet on Microsoft’s Azure cloud.

After the announcement, I sat down with Christoph Grote, BMW Group’s senior VP for electronics. I admit that a lot of what I saw in the demo felt a bit futuristic, but Grote noted that everything he showed off during his presentation is more or less production-ready. “I don’t think I would’ve dared to stand up there if any of the things I showed today were a utopia,” he told me. “All of this is in series production and some of it is already available as part of the BMW OS 7 release. But the major work we are doing, looking ahead to the iNext [electric SUV], is about gaze, head pose and gesture tracking and combing those with the other modalities. But everything we showed today is going to go into production.”

In practice, this means that BMW will use two cameras: a wide-angle camera behind the rear-view mirror that can track the gestures of both the driver and front-seat passenger and one behind the dashboard that only looks at the driver through the steering wheel and recognizes when their eyes blink, where their eyes look and their head pose.

As Grote noted, figuring out where you are looking is not exactly easy. The camera sees your hands in relation to the car. That’s pretty straightforward. But the car, too, is situated somewhere in space, and for this to work, that localization has to be very precise, and the digital map has to be very detailed, too. “GPS isn’t enough for this,” Grote said, and noted that the company plans to use the car’s forward-facing camera to gather additional information that helps localize the car in space based on comparing the image to the digital map. The AI smarts that power these mapping features run right in the car — and in many ways, these features also lay the groundwork for self-driving cars, which obviously need highly detailed maps, too.

In many ways, this work is a continuation of BMW’s work on its IPA in-car assistant. “There, we use Azure Cognitive Service and we plan to integrate these new modalities (like gaze and gesture tracking) with the same technology. And that’s important for these multi-modal systems. […] We have a great partnership with Microsoft and we expect that’ll continue.”

Grote also noted that BMW has a long history of working in the cloud, thanks to many years of experience in offering its connected car services. “We don’t think of the car as an isolated client that connects to some service in the cloud, but that we also see these connected cars as a swarm that has collective intelligence.”

Vehicle-to-everything (V2X) connectivity is one of the hot topics in the car industry right now — especially given the advent of 5G with its low-latency connectivity — and BMW does have its own point of view here. For Grote, V2X systems that use the cellular network and connect to the cloud have major advantages over those that try to connect cars directly. These cloud-connected systems, he argues, are easier to maintain and they are able to translate between different standards or — in the long run — integrate different generations of this system to ensure that cars from different manufacturers can talk to each other.

“A cellular-based system is forward-looking, maintainable, secure and the better foundation that guarantees future development efforts versus a standard that’s 20 years old, from a time when the carriers were not interested in machine-to-machine traffic at all.”

BMW continues to bet on the cloud for many of its newest tech developments. Among car manufacturers, it’s obviously not alone here. Daimler recently announced that it has moved its big data platform to the cloud, for example. And in many ways, that move makes sense. Running online services isn’t a core competency for many of these companies, and even if they are experienced at running their own data centers by now, this isn’t what allows them to differentiate their cars in a highly competitive market. That energy is better spent on building applications, not managing them. The large cloud providers also offer global coverage, and redundancies are hard and expensive to build.

News Source = techcrunch.com

Biotech AI startup Sight Diagnostics gets $27.8M to speed up blood tests

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Sight Diagnostics, an Israeli medical devices startup that’s using AI technology to speed up blood testing, has closed a  $27.8 million Series C funding round.

The company has built a desktop machine, called OLO, that analyzes cartridges manually loaded with drops of the patient’s blood — performing blood counts in situ.

The new funding is led by VC firm Longliv Ventures, also based in Israel, and a member of the multinational conglomerate CK Hutchison Group.

Sight Diagnostics said it was after strategic investment for the Series C — specifically investors that could contribute to its technological and commercial expansion. And on that front CK Hutchison Group’s portfolio includes more than 14,500 health and beauty stores across Europe and Asia, providing a clear go-to-market route for the company’s OLO blood testing device.

Other strategic investors in the round include Jack Nicklaus II, a healthcare philanthropist and board member of the Nicklaus Children’s Health Care Foundation; Steven Esrick, a healthcare impact investor; and a “major medical equipment manufacturer” — which they’re not naming.

Sight Diagnostics also notes that it’s seeking additional strategic partners who can help it get its device to “major markets throughout the world”.

Commenting in a statement, Yossi Pollak, co-founder and CEO, said: “We sought out groups and individuals who genuinely believe in our mission to improve health for everyone with next-generation diagnostics, and most importantly, who can add significant value beyond financial support. We are already seeing positive traction across Europe and seeking additional strategic partners who can help us deploy OLO to major markets throughout the world.”

The company says it expects that customers across “multiple countries in Europe” will have deployed OLO in actual use this year.

Existing investors OurCrowd, Go Capital, and New Alliance Capital also participated in the Series C. The medtech startup, which was founded back in 2011, has raised more than $50M to date, only disclosing its Series A and B raises last year.

The new funding will be used to further efforts to sell what it bills as its “lab-grade” point-of-care blood diagnostics system, OLO, around the world. Although its initial go-to-market push has focused on Europe — where it has obtained CE Mark registration for OLO (necessary for commercial sale within certain European countries) following a 287-person clinical trial, and went on to launch the device last summer. It’s since signed a distribution agreement for OLO in Italy.

“We have pursued several pilots with potential customers in Europe, specifically in the UK and Italy,” co-founder Danny Levner tells TechCrunch. “In Europe, it is typical for market adoption to begin with pilot studies: Small clinical evaluations that each major customers run at their own facilities, under real-world conditions. This allows users to experience the specific benefits of the technology in their own context. In typical progress, pilot studies are then followed by modest initial orders, and then by broad deployment.”

The funding will also support ongoing regulatory efforts in the U.S., where it’s been conducting a series of trials as part of FDA testing in the hopes of gaining regulatory clearance for OLO. Levner tells us it has now submitted data to the regulator and is waiting for it to be reviewed.

“In December 2018, we completed US clinical trials at three US clinical sites and we are submitting them later this month to the FDA. We are seeking 510(k) FDA clearance for use in US CLIA compliant laboratories, to be followed by a CLIA waiver application that will allow for use at any doctor’s office. We are very pleased with the results of our US trial and we hope to obtain the FDA’s 510(k) clearance within a year’s time,” he says.

“With the current funding, we’re focusing on commercialization in the European market, starting in the UK, Italy and the Nordics,” he adds. “In the US, we’re working to identify new opportunities in oncology and pediatrics.”

Funds will also go on R&D to expand the menu of diagnostic tests the company is able to offer via OLO.

The startup previously told us it envisages developing the device into a platform capable of running a portfolio of blood tests, saying each additional test would be added individually and only after “independent clinical validation”.

The initial test OLO offers is a complete blood count (CBC), with Sight Diagnostics applying machine learning and computer vision technology to digitize and analyze a high resolution photograph of a finger prick’s worth of the patient’s blood on device.

The idea is to offer an alternative to having venous blood drawn and sent away to a lab for analysis — with an OLO-based CBC billed as taking “minutes” to perform, with the startup also claiming it’s simple enough for non-professional to carry out, whereas it says a lab-based blood count can take several days to process and return a result.

On the R&D front, Levner says it sees “enormous potential” for OLO to be used to diagnose blood diseases such as leukemia and sickle cell anemia.

“Also, given the small amount of blood required and the minimally-invasive nature of the test when using finger-prick blood samples, there is an opportunity to use OLO in neonatal screening,” he says. “Accordingly, one of the most important immediate next steps is to tailor the test procedures and algorithms for neonate screening.”

Levner also told us that some of its pilot studies have looked at evaluating “improvements in operator and patient satisfaction”. “Clearly standing out in these studies is the preference for finger-prick-based testing, which OLO provides,” he claims. 

One key point to note: Sight Diagnostics has still yet to publish peer reviewed results of its clinical trials for OLO. Last July it told us it has a publication pending in a peer-reviewed journal.

“With regards to the peer-reviewed publication, we’ve decided to combine the results from the Israel clinical trials with those that we just completed in the US for a more robust publication,” the company says now. “We expect to focus on that publication after we receive FDA approval in the US.”

News Source = techcrunch.com

Databricks raises $250M at a $2.75B valuation for its analytics platform

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Databricks, the company behind the Apache Spark big data analytics engine, today announced that it has raised a $250 million Series E round led by Andreessen Horowitz. Coatue Management, Microsoft and NEA, also participated in this round, which brings the company’s total funding to $498.5 million. Microsoft’s involvement here is probably a bit of a surprise, but it’s worth noting that it also worked with Databricks on the launch of Azure Databricks as a first-party service on the platform, something that’s still a rarity in the Azure cloud.

As Databricks also today announced, its annual recurring revenue now exceeds $100 million. The company didn’t share whether it’s cash flow-positive at this point, but Databricks CEO and co-founder Ali Ghodsi shared that the company’s valuation is now $2.75 billion.

Current customers, which the company says number around 2,000, include the likes of Nielsen, Hotels.com, Overstock, Bechtel, Shell and HP.

While Databricks is obviously known for its contributions to Apache Spark, the company itself monetizes that work by offering its Unified Analytics platform on top of it. This platform allows enterprises to build their data pipelines across data storage systems and prepare data sets for data scientists and engineers. To do this, Databricks offers shared notebooks and tools for building, managing and monitoring data pipelines, and then uses that data to build machine learning models, for example. Indeed, training and deploying these models is one of the company’s focus areas these days, which makes sense, given that this is one of the main use cases for big data, after all.

On top of that, Databricks also offers a fully managed service for hosting all of these tools.

“Databricks is the clear winner in the big data platform race,” said Ben Horowitz, co-founder and general partner at Andreessen Horowitz, in today’s announcement. “In addition, they have created a new category atop their world-beating Apache Spark platform called Unified Analytics that is growing even faster. As a result, we are thrilled to invest in this round.”

Ghodsi told me that Horowitz was also instrumental in getting the company to re-focus on growth. The company was already growing fast, of course, but Horowitz asked him why Databricks wasn’t growing faster. Unsurprisingly, given that it’s an enterprise company, that means aggressively hiring a larger sales force — and that’s costly. Hence the company’s need to raise at this point.

As Ghodsi told me, one of the areas the company wants to focus on is the Asia Pacific region, where overall cloud usage is growing fast. The other area the company is focusing on is support for more verticals like mass media and entertainment, federal agencies and fintech firms, which also comes with its own cost, given that the experts there don’t come cheap.

Ghodsi likes to call this “boring AI,” since it’s not as exciting as self-driving cars. In his view, though, the enterprise companies that don’t start using machine learning now will inevitably be left behind in the long run. “If you don’t get there, there’ll be no place for you in the next 20 years,” he said.

Engineering, of course, will also get a chunk of this new funding, with an emphasis on relatively new products like MLFlow and Delta, two tools Databricks recently developed and that make it easier to manage the life cycle of machine learning models and build the necessary data pipelines to feed them.

News Source = techcrunch.com

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