Author: azeeadmin

Mike Rothenberg, infamous Silicon Valley venture capitalist and founder of Rothenberg Ventures, has been formally charged by the Securities and Exchange Commission for overcharging investors to fund personal projects.

Rothenberg had been under investigation by the SEC for quite some time. The SEC now alleges in a statement the investor and his firm had misappropriated up to $7 million dollars for personal enjoyment, meanwhile claiming the funds were from his own coffers to pay for lavish parties, hotels and sporting events.

We’ve reached out to Rothenberg for comment and are waiting to hear back.

*This post is being updated

Venezuela has just taken drastic and unprecedented steps to stabilize its currency as it grapples with hyperinflation and other economic issues. The country’s currency has not only been massively devaluated and renamed, but is now tied a state-issued cryptocurrency called the Petro, which itself fluctuates based on oil prices. Hardly anyone knows what to expect out of this.

The Petro is not new; it arrived earlier this year in the form of a stepped offering to private and then public buyers, raising more than $3 billion from foreign governments and presumably some private buyers. President Trump forbade the U.S. from taking part.

Although it is supposed to be a liquid asset reflective of the price of oil, and there is of course a whitepaper that describes the system in broad strokes, though it lacks almost any real technical detail. But the country’s own national assembly called the state-issued cryptocurrency unconstitutional, blockchain industry experts have called it a scam, and there are Russian machinations to consider as well. Bloomberg has a good roundup of official communications about the token.

The scheme originated in the administration of Venezuelan President Nicolas Maduro and seems to be an attempt to lend some credibility and stability to the country’s currency. The strong bolivar, which has lost more than 90 percent of its value over the last decade, has been renamed the sovereign bolivar and artificially returned to pre-inflation values. In practical terms that means a loaf of bread that cost 100 bolivars in 2012 and 100,000 last week will now, theoretically, cost around 100 again. Whether that will actually happen — the black market rates are probably more influential — is anyone’s guess.

In case it isn’t clear, I’m not an economist and don’t plan to become one. But this is an historic moment in the blockchain world in that it is the first time an official fiat currency has been pegged to a state-run cryptocurrency. That makes it of interest to the international community for many reasons, although obviously this is far from the ideal method by which one might want to demonstrate such a system.

Although this whole situation is nominally of interest, it seems unlikely to benefit the people on the ground in Venezuela who have no use for oil-based cryptocurrencies and just want to buy some bottled water, a package of diapers, and a train ticket out of the country. How this all plays out will no doubt be instructive but let’s not lose sight of the humanitarian crisis playing out on the streets. Here as elsewhere, donations can help.

Venezuela has just taken drastic and unprecedented steps to stabilize its currency as it grapples with hyperinflation and other economic issues. The country’s currency has not only been massively devaluated and renamed, but is now tied a state-issued cryptocurrency called the Petro, which itself fluctuates based on oil prices. Hardly anyone knows what to expect out of this.

The Petro is not new; it arrived earlier this year in the form of a stepped offering to private and then public buyers, raising more than $3 billion from foreign governments and presumably some private buyers. President Trump forbade the U.S. from taking part.

Although it is supposed to be a liquid asset reflective of the price of oil, and there is of course a whitepaper that describes the system in broad strokes, though it lacks almost any real technical detail. But the country’s own national assembly called the state-issued cryptocurrency unconstitutional, blockchain industry experts have called it a scam, and there are Russian machinations to consider as well. Bloomberg has a good roundup of official communications about the token.

The scheme originated in the administration of Venezuelan President Nicolas Maduro and seems to be an attempt to lend some credibility and stability to the country’s currency. The strong bolivar, which has lost more than 90 percent of its value over the last decade, has been renamed the sovereign bolivar and artificially returned to pre-inflation values. In practical terms that means a loaf of bread that cost 100 bolivars in 2012 and 100,000 last week will now, theoretically, cost around 100 again. Whether that will actually happen — the black market rates are probably more influential — is anyone’s guess.

In case it isn’t clear, I’m not an economist and don’t plan to become one. But this is an historic moment in the blockchain world in that it is the first time an official fiat currency has been pegged to a state-run cryptocurrency. That makes it of interest to the international community for many reasons, although obviously this is far from the ideal method by which one might want to demonstrate such a system.

Although this whole situation is nominally of interest, it seems unlikely to benefit the people on the ground in Venezuela who have no use for oil-based cryptocurrencies and just want to buy some bottled water, a package of diapers, and a train ticket out of the country. How this all plays out will no doubt be instructive but let’s not lose sight of the humanitarian crisis playing out on the streets. Here as elsewhere, donations can help.

Amazon is today rolling out a set of new features to its Echo Dot Kids Edition devices – the now $70 version of the Echo Dot smart speaker that ships with a protective case and a year’s subscription to Amazon FreeTime, normally a $2.99 per month subscription for Prime members. Now joining the Kids Edition’s parental controls and other exclusive content are new skills from Disney, Hotel Transylvania, and Pac-Man as well as a calming “Sleep Sounds” skill for bedtime.

There are now four new skills that play sounds of thunderstorms, rain, the ocean, or a babbling brook, as well as an all-encompassing “sleep sounds” skill that offers 42 different soothing options to choose from. New parents may be glad to know that this includes baby soothing sounds like cars, trains and the vacuum (don’t knock it until you try it, folks. It works.)

Amazon clarified to us that while there is a version of sleep sounds in the Skill Store today, this version launching on the Kids Edition is a different, child-directed version.

Also new to the Kids Edition is “Disney Plot Twist,” which is like a Disney version of Mad Libs where players change out words and phrases in short adventure stories. The skill features popular Disney characters like Anna, Olaf and Christoff as the narrators and is exclusive to Kids Edition devices.

The new movie “Hotel Transylvania 3: Summer Vacation” is featured in another new skill, Drac’s Pack, which includes monster stories, songs and jokes.

Meanwhile, Pac-Man Stories is a skill that includes interactive stories for the whole family, that work similar to choose-your-own-adventures – that is, the decisions you make will affect the ending.

Both of these are broadly available on Alexa, meaning they don’t require a Kids Edition device to access.

Stories, however, does appear to be one of the areas Amazon is investing in to make its Alexa-powered speakers more appealing to families with young children. The company recently decided to stop working on its chat stories app Amazon Rapids, saying it will instead continue to adapt those Amazon Rapids stories for the Alexa platform.

Amazon also tries to market the Echo Dot Kids Edition to families by making some kid-friendly content, like Disney Plot Twist, available exclusively to device owners.

For example, it already offers exclusive kid skills like Disney Stories, Loud House Challenge, No Way That’s True, Funny Fill In, Spongebob Challenge, Weird but True, Name that Animal, This or That, Word world, Ben ten, Classroom thirteen, Batman Adventures, and Climb the Beanstalk, with this device.

But the Kids Edition can also be confusing to use, because the exclusive skills come whitelisted and ready to go, while other kid-safe skills have to be manually whitelisted through a parents dashboard. And there isn’t enough instruction either from Alexa or in the Alexa app on this process, at present, we found when testing the device earlier.

Unless there’s a specific exclusive skill that parents really want their kids to have, the savings are also minimal when buying the Kids Edition Dot/FreeTime bundle, versus buying a regular Dot and adding on FreeTime separately.

Magnetic resonance imaging is an invaluable tool in the medical field, but it’s also a slow and cumbersome process. It may take fifteen minutes or an hour to complete a scan, during which time the patient, perhaps a child or someone in serious pain, must sit perfectly still. NYU has been working on a way to accelerate this process, and is now collaborating with Facebook with the goal of cutting down MRI durations by 90 percent by applying AI-based imaging tools.

It’s important at the outset to distinguish this effort from other common uses of AI in the medical imaging field. An X-ray, or indeed an MRI scan, once completed, could be inspected by an object recognition system watching for abnormalities, saving time for doctors and maybe even catching something they might have missed. This project isn’t about analyzing imagery that’s already been created, but rather expediting its creation in the first place.

The reason MRIs take so long is because the machine must create a series of 2D images or slices, many of which must be stacked up to make a 3D image. Sometimes only a handful are needed, but for full fidelity and depth — for something like a scan for a brain tumor — lots of slices are required.

The FastMRI project, begun in 2015 by NYU researchers, investigates the possibility of creating imagery of a similar quality to a traditional scan, but by collecting only a fraction of the data normally needed.

Think of it like scanning an ordinary photo. You could scan the whole thing… but if you only scanned every other line (this is called “undersampling”) and then intelligently filled in the missing pixels, it would take half as long. And machine learning systems are getting quite good at tasks like that. Our own brains do it all the time: you have blind spots with stuff in them right now that you don’t notice because your vision system is filling in the gaps — intelligently.

The data collected at left could be “undersampled” as at right, with the missing data filled in later

If an AI system could be trained to fill in the gaps from MRI scans where only the most critical data is collected, the actual time during which a patient would have to sit in the imaging tube could be reduced considerably. It’s easier on the patient, and one machine could handle far more people than it does doing a full scan every time, making scans cheaper and more easily obtainable.

The NYU School of Medicine researchers began work on this three years ago and published some early results showing that the approach was at least feasible. But like an MRI scan, this kind of work takes time.

“We and other institutions have taken some baby steps in using AI for this type of problem,” explained NYU’s Dan Sodickson, director of the Center of Advanced Imaging Innovation and Research there. “The sense is that already in the first attempts, with relatively simple methods, we can do better than other current acceleration techniques — get better image quality and maybe accelerate further by some percentage, but not by large multiples yet.”

So to give the project a boost, Sodickson and the radiologists at NYU are combining forces with the AI wonks at Facebook and its Artificial Intelligence Research group (FAIR).

NYU School of Medicine’s Department of Radiology chair Michael Recht, MD, Daniel Sodickson, MD, vice chair for research and director of the Center for Advanced Imaging Innovation and Yvonne Lui, MD, director of artificial intelligence, examine an MRI

“We have some great physicists here and even some hot-stuff mathematicians, but Facebook and FAIR have some of the leading AI scientists in the world. So it’s complementary expertise,” Sodickson said.

And while Facebook isn’t planning on starting a medical imaging arm, FAIR has a pretty broad mandate.

“We’re looking for impactful but also scientifically interesting problems,” said FAIR’s Larry Zitnick. AI-based creation or re-creation of realistic imagery (often called “hallucination”) is a major area of research, but this would be a unique application of it — not to mention one that could help some people.

With a patient’s MRI data, he explained, the generated imagery “doesn’t need to be just plausible, but it needs to retain the same flaws.” So the computer vision agent that fills in the gaps needs to be able to recognize more than just overall patterns and structure, and to be able to retain and even intelligently extend abnormalities within the image. To not do so would be a massive modification of the original data.

Fortunately it turns out that MRI machines are pretty flexible when it comes to how they produce images. If you would normally take scans from 200 different positions, for instance, it’s not hard to tell the machine to do half that, but with a higher density in one area or another. Other imagers like CT and PET scanners aren’t so docile.

Even after a couple years of work the research is still at an early stage. These things can’t be rushed, after all, and with medical data there are ethical considerations and a difficulty in procuring enough data. But the NYU researchers’ ground work has paid off with initial results and a powerful data set.

Zitnick noted that because AI agents require lots of data to train up to effective levels, it’s a major change going from a set of, say, 500 MRI scans to a set of 10,000. With the former data set you might be able to do a proof of concept, but with the latter you can make something accurate enough to actually use.

The partnership announced today is between NYU and Facebook, but both hope that others will join up.

“We’re working on this out in the open. We’re going to be open-sourcing it all,” said Zitnick. One might expect no less of academic research, but of course a great deal of AI work in particular goes on behind closed doors these days.

So the first steps as a joint venture will be to define the problem, document the data set and release it, create baselines and metrics by which to measure their success, and so on. Meanwhile, the two organizations will be meeting and swapping data regularly and running results past actual clinicians.

“We don’t know how to solve this problem,” Zitnick said. “We don’t know if we’ll succeed or not. But that’s kind of the fun of it.”

What Robinhood did to democratize buying individual stocks, Titan wants to do for investing in a managed portfolio. Instead of being restricted to rich accredited investors willing to pour $5,000 or even $500,000 into a traditional hedge fund that charges 2 percent fees and 20 percent of profits, Titan lets anyone invest as little as $1,000 for just a 1 percent fee while keeping all the profits. Titan picks the top 20 stocks based on data mined from the most prestigious hedge funds, then invests your money directly in those with personalized shorts based on your risk profile.

Titan has over $10 million under management after quietly spinning up five months ago, and this week the startup graduates from Y Combinator. Now Titan ready to give upscale millennials a more sophisticated way to play the markets.

This startup is hot. It refused to disclose its funding, likely in hopes of not tipping off competitors and incumbents to the opportunity it’s chasing. But it’s the buzz of YC, with several partners already investing their own money through Titan. When you consider Stanford-educated free stock trading app Robinhood’s stunning $5.6 billion valuation thanks to its disruption of E*Trade, it’s easy to imagine why investors are eager to back Titan’s attack on other financial vehicles.

“We’re all 28 to 30 years old, says co-founder Clayton Gardner about his team. “We want to actively invest and participate in the market but most of us who don’t have experience have no idea what we’re doing.” Most younger investors end up turning to family, friends, or Reddit for unreliable advice. But Titan lets them instantly buy the most reputable stocks without having to stay glued to market tickers, while using an app to cut out the costs of pricey brokers and Wall Street offices.

Titan co-founders (from left): Max Bernardy, Clayton Gardner, Joe Percoco

“We all came from the world of having worked at hedge funds and private equity firms like Goldman Sachs and Blackstone. We spent five years doing that and ultimately were very frustrated that the experiences and products we were building for wealthy people were completely inaccessible to people who weren’t rich or didn’t have a fancy suit” Gardner recalls. “Instead of charging high fees, we can use software to bring the products directly to consumers.”

How Titan Works

Titan wants to build BlackRock for a new generation, but its origin is much more traditional. Gardner and his co-founder Joe Percoco met on their first day of business school at UPenn’s Wharton (of course). Meanwhile, Titan’s third co-founder Max Bernardy was studying computer science at Stanford before earning a patent in hedge fund software and doing engineering at a few startups. The unfortunate fact is the world of finance is dominated by alumni from these schools. Titan will enjoy the classic privilege of industry connections as it tries to carve out a client base for a fresh product.

“We were frustrated that millenniala only have two options for investing: buying and selling stocks themselves or investing in a market weighted index” says Gardner. “We’re building the third.”

Titan’s first product isn’t technically a hedge fund but it’s built like one. It piggybacks off of the big hedgies that have to report their holdings. Titan uses its software to determine which are the top 20 stocks across these funds based on turnover, concentration, and more. All users download the Titan iOS app (no Android for now), fund their account, and are automatically invested into fractional shares of the same 20 stocks.

Titan keeps 1 percent of whatever you earn in profit. There is a minimum $1000 investment, so some younger adults may be below the bar. “We’re targeting a more premium millennial for start. A lot of our early users are in the tech field and are already investing” says Gardner.

For downside protection, Titan collects information about its users to assess their risk tolerance and hedge their investment by shorting the bottom 0 to 20 percent of the market so they’ll earn some if eveything crashes. Rather than Titan controlling the assets itself, an industry favorite custodian called Apex keeps them secure. The app uses 256bit encryption and SSL for data transfers, and funds are insured up to $500,000.

How have its bets and traction been doing? “We’ve been pleasantly surprised so far” Gardner beams, noting Titan’s thousands of clients. It claims its up 10 percent year-to-date and up 33 percent in one year compared to the S&P 500’s 2 percent year-to-date and 22 percent in one year. Charging a fee on profits rather than on how much users invest aligns Titan and its clients around success.

But beyond the demographic and business model, it’s the educational elements that set Titan apart. Users don’t have to hunt online for investment research. Titan compiles it into deep dives into top stocks like Amazon or Comcast, laying out investment theses for why your should want your money in “the everything store” or “a toll road for the Internet”. Through in-app videos, push notifications, and reports, Titan tries to make its users smarter, not just richer.

With time and funding, “Eventually we hope to launch other financial products, including crypto, bonds, international equities, etc” Percoco tells me. That could put Titan on a collision course with the Wealthfront, Coinbase, and the recently crypto-equipped Robinhood as well as direct competitors like asset managers BlackRock and JP Morgan.

“If we fast forward 10 to 20 years in the future, millennials will have inherited $10 trillion, and at this rate they’re not equipped to handle that money” says Gardner. “Financial management isn’t something taught in school.”

Worryingly, when I ask what they see as the top threats to Titan, the co-founders exhibited some Ivy League hubris with Gardner telling me “Nothing that jumps out…” Back in reality, building software that reliably prints money is no easy feat. A security failure or big drop could crater the app’s brand. And if its education materials are too frothy, they could instill blind confidence in younger investors without the cash to sustain sizable losses.

As a teenager in Nigeria, I tried to build an artificial intelligence system. I was inspired by the same dream that motivated the pioneers in the field: That we could create an intelligence of pure logic and objectivity that would free humanity from human error and human foibles.

I was working with weak computer systems and intermittent electricity, and needless to say my AI project failed. Eighteen years later—as an engineer researching artificial intelligence, privacy and machine-learning algorithms—I’m seeing that so far, the premise that AI can free us from subjectivity or bias is also disappointing. We are creating intelligence in our own image. And that’s not a compliment.

Researchers have known for awhile that purportedly neutral algorithms can mirror or even accentuate racial, gender and other biases lurking in the data they are fed. Internet searches on names that are more often identified as belonging to black people were found to prompt search engines to generate ads for bailbondsmen. Algorithms used for job-searching were more likely to suggest higher-paying jobs to male searchers than female. Algorithms used in criminal justice also displayed bias.

Five years later, expunging algorithmic bias is turning out to be a tough problem. It takes careful work to comb through millions of sub-decisions to figure out why the algorithm reached the conclusion it did. And even when that is possible, it is not always clear which sub-decisions are the culprits.

Yet applications of these powerful technologies are advancing faster than the flaws can be addressed.

Recent research underscores this machine bias, showing that commercial facial-recognition systems excel at identifying light-skinned males, with an error rate of less than 1 percent. But if you’re a dark-skinned female, the chance you’ll be misidentified rises to almost 35 percent.

AI systems are often only as intelligent—and as fair—as the data used to train them. They use the patterns in the data they have been fed and apply them consistently to make future decisions. Consider an AI tasked with sorting the best nurses for a hospital to hire. If the AI has been fed historical data—profiles of excellent nurses who have mostly been female—it will tend to judge female candidates to be better fits. Algorithms need to be carefully designed to account for historical biases.

Occasionally, AI systems get food poisoning. The most famous case was Watson, the AI that first defeated humans in 2011 on the television game show “Jeopardy.” Watson’s masters at IBM needed to teach it language, including American slang, so they fed it the contents of the online Urban Dictionary. But after ingesting that colorful linguistic meal, Watson developed a swearing habit. It began to punctuate its responses with four-letter words.

We have to be careful what we feed our algorithms. Belatedly, companies now understand that they can’t train facial-recognition technology by mainly using photos of white men. But better training data alone won’t solve the underlying problem of making algorithms achieve fairness.

Algorithms can already tell you what you might want to read, who you might want to date and where you might find work. When they are able to advise on who gets hired, who receives a loan, or the length of a prison sentence, AI will have to be made more transparent—and more accountable and respectful of society’s values and norms.

Accountability begins with human oversight when AI is making sensitive decisions. In an unusual move, Microsoft president Brad Smith recently called for the U.S. government to consider requiring human oversight of facial-recognition technologies.

The next step is to disclose when humans are subject to decisions made by AI. Top-down government regulation may not be a feasible or desirable fix for algorithmic bias. But processes can be created that would allow people to appeal machine-made decisions—by appealing to humans. The EU’s new General Data Protection Regulation establishes the right for individuals to know and challenge automated decisions.

Today people who have been misidentified—whether in an airport or an employment data base—have no recourse. They might have been knowingly photographed for a driver’s license, or covertly filmed by a surveillance camera (which has a higher error rate.) They cannot know where their image is stored, whether it has been sold or who can access it. They have no way of knowing whether they have been harmed by erroneous data or unfair decisions.

Minorities are already disadvantaged by such immature technologies, and the burden they bear for the improved security of society at large is both inequitable and uncompensated. Engineers alone will not be able to address this. An AI system is like a very smart child just beginning to understand the complexities of discrimination.

To realize the dream I had as a teenager, of an AI that can free humans from bias instead of reinforcing bias, will require a range of experts and regulators to think more deeply not only about what AI can do, but what it should do—and then teach it how. 

CBS in the beginning of the year brought its streaming service for cord cutters, CBS All Access, to Amazon’s a la carte TV service, Prime Video Channels. At the time, however, only the higher-priced, $9.99 per month commercial-free subscription was offered to Prime members. At the time, CBS said its $5.99 per month ad-supported tier would arrive in the months ahead. It’s now making good on that promise with the launch of the Limited Commercials plan option on Amazon’s Channels.

The expanded availability of the more affordable version of the streaming service could help to boost its numbers, given Amazon’s reported impact on delivering over-the-top subscribers through the Amazon Channels platform.

A report from Digiday citing TV network sources even claimed that Amazon can account for anywhere from 25 to 45 percent of a company’s direct-to-consumer subscribers. (An earlier report that Amazon Channels could deliver as many as 55 percent of subscriptions has been disputed by a couple of networks, however. They said it’s a top driver, but that figure was too high.) Regardless, Amazon Channels is one of the only ways to really pick and choose your streaming subscriptions, as most other services are focused on “skinny bundles” where a small number of channels is wrapped up for around $40 per month.

CBS today says there are over 2.5 million CBS All Access subscribers, but declined to break out how many of those have come from Amazon. However, around the time of the original announcement in January, the company had also reported having 2 million All Access subscribers. Some portion of that subscriber base likely did come from Amazon, but maybe not as many as would have signed up had the lower-cost subscription been available at launch.

CBS recently said it believes it will have 4 million All Access subscribers by next year, and 8 million by 2022.

Many of those are drawn in by its flagship program, “Star Trek: Discovery,” whose new season won’t kick off until 2019. The company will also next year premiere a reboot of “The Twilight Zone,” in association with Jordan Peele’s (“Get Out”) Monkeypaw Productions and Simon Kinberg’s Genre Films.

It more recently announced Patrick Stewart would return to star in a new “Star Trek” series as Jean-Luc Picard, as part of its larger investment in expanding the “Star Trek” universe on its service.

Audible is getting into the fitness business with a little help from Aaptiv. The Amazon-owned audiobook giant is adding content from the popular audio fitness app. There are only three guided courses to start — all firmly targeted at beginners.

There’s audio coaching to run a mile, a 5K and a guided meditation course, all with 20 sessions apiece. The service says it will be adding new courses through the year, including four workouts and a session aimed at improving sleep in the coming weeks.

The exclusive courses will be offered up for free to Audible members through September of next year — at which point, one imagines, there will be an added premium on top of the standard Audible subscription fee.

For the moment, Audible appears to just be dipping its toes in the water on this one. I wouldn’t be too nervous if I was in charge of a fitness or meditation app just yet, though its decision to move forward will almost certainly depend on how much interest this initial crop generates.

If Audible opts to keep the content free for subscriptions, however, it could certainly prove a compelling reason to make the switch.

You know that feeling when a deadline’s bearing down on you like a runaway train? If you hope to secure a spot in Startup Alley at Disrupt San Francisco 2018 — which takes place September 5-7 — you’d best get moving, because that deadline is coming at you full steam ahead. Your chance to buy a Disrupt SF Startup Alley Exhibitor Package ends on August 24.

Disrupt San Francisco 2018 will be our largest, most ambitious Disrupt event ever, with more than 10,000 attendees descending on the City by the Bay to see the best and brightest tech innovations. It’s also the only Disrupt event happening in North America this year. Those are two huge, compelling reasons to place your early-stage startup in Startup Alley.

We expect more than 1,200 exhibitors and sponsors to hold forth in the Alley as all those attendees — technologists, investors, tech journalists, founders, marketers and entrepreneurs — go searching for the best of the best. Exhibitors will be the front-and-center focus of all that Disrupt action.

Here’s what comes in a value-packed Startup Alley Exhibitor Package:

• Two Founder passes for all three days of Disrupt SF 2018
• One-day to exhibit on the Startup Alley show floor
• Use of CrunchMatch — our curated investor-to-startup matching platform
• Access to The Main Stage, The Next Stage, The Q&A Stage, The Showcase Stage
• All workshops
• Access to the attendee list; ability to message attendees with the Disrupt App
• Attend the TC After Party

Hello, what’s this? Why it’s a lovely bonus. Buy a Startup Alley Exhibitor Package and you might even be selected to participate in the Startup Battlefield competition in one of the Wild Card spots. Two startups will be selected from Startup Alley to pitch on our main stage at Disrupt SF. You could end up like our Disrupt NY 2017 Startup Battlefield winners, Recordgram, who won the Wild Card selection at Disrupt NY 2017 and went on to win the entire competition.

Disrupt San Francisco 2018 takes place September 5-7. Don’t miss out on all the possible connections, inspiration and opportunities that await you in Startup Alley. Hop on board this train for the ride of your life before the August 24 deadline. Buy your Startup Alley Exhibitor Package now.