All posts in “economy”

The canaries in a coal mine

I’ve seen startups come and go over the years and I was particularly interested to see what happened to August Smart locks today. The company originally tapped Yves Behar to make a better smart lock, one that would meld with the sensitivities of a certain kind of smart home stylist with the high-concept, high-tech design of the Nest thermostat. The products, while beautiful, were unusable in most situations that you’d want a smart lock. As Matt Burns noted, there’s a reason they were selling the locks in Best Buy and not Home Depot.

Why were they unusable? Because they essentially rethought the way locks would work. Take the deadbolt, for example. The August solution was to replace the outer lock and cylinder with their product, leaving in place the inner knob and all of the deadbolt hardware. It was the ultimate facade. This solution obviously reduced the cost and complexity but also required matching your current deadbolt to the new August actuator or buying a new deadbolt and throwing away the outside cylinder. Further, you were sunk if you wanted to put this thing onto new construction. Finally, unless you added an extra keypad, it was useless for homes with children.

While we’re throwing stones, it’s also interesting to note that the company’s latest product, a smart doorbell, could not be used in old construction. The doorbell was actually a three-by-three-inch box with a camera and button on it. This would never fit in the average home where the doorbell is a half-inch by three-inch rectangle.

In other words, the ideal August customer didn’t exist or instead existed solely in the company’s promotional photographs. They got acquired primarily for their potentially lucrative Wal-Mart contract.

If you watch startups long enough you can see interesting tells. Poor products launched haphazardly? The CEOs are focused on an acquisition or are almost out of money. Red hot hype cycle with loads of interest? Headed for a correction of Biblical proportions. Celebrity investors making the news? The company is sunk. Hot Dog costumes? You probably want to talk to your broker.

Quiet, methodical releases, year-after-year? Things are probably going OK.

In other words when you look at startups of any stripe – from social media apps to fintech to anything else – look at the products. Look at what they’re saying. Look at where they’re selling. I’ve met countless Fitbit investors who still see growth in the cards when the Venn diagram of folks who have a Fitbit has already eclipsed the circle of folks who need one. I’d wager there’s an acquisition in the future of any company that exhibits that sort of behavior. That Fitbit is still standing in a field of dead fitness bands is a testament to their previous dedication to methodical releases, year-after-year. How long that can last is anyone’s guess.

I’m not here to laugh over the corpse of August. I get no pleasure in seeing good ideas die. But it’s clear that with a little careful thought and a lot of attention you can see just where and when the next SV darling will skid off of Highway 1 and into the grass. With August it was obvious. With others – Theranos, for example – it was far less so. But the signs are there, if we heed them.

Build your own token sale with CoinLaunch’s CoinCreator

Building a token sale is at once quite simple — you build a token and sell it — and quite complex. A number of issues crop up immediately, including, but not limited to, the need for an expensive team of lawyers, marketers, social media experts and, until now, an expensive crew to build your smart contract.

CoinLaunch, a project by repeat entrepreneur Reuven Cohen, aims to reduce the complexity of at least one part of the process. His service, CoinCreator, allows non-programmers to build simple smart contracts in a few minutes.

“Early this year we began looking for an end-to-end platform that facilitated everything we needed to build, deploy and monetize compliant Initial Coin Offerings in one place,” said Cohen. “As we searched we quickly realized that nothing like this exists.”

“Today if you want to create an ICO the only real option is to hire a team of blockchain developers, lawyers and accountants, and marketing gurus or build all the smart contract components yourself. This process is time-consuming, complicated and expensive and also assumes you can even find the right people to help you, which is in itself difficult.”

The creator asks for a few basic bits if data, including the name of your coin and the total issued. Then you create a simple contract that controls the flow and usage of these tokens. Cohen claims the product is compliant with current regulations as long as you connect the token to some sort of utility and avoid selling equity.

The project is self-funded and Cohen and his partner Randy Clemens are planning their own token sale in 2018.

“CoinLaunch provides a free and easy to use Coin Creator that enables anyone with little to no experience in cryptocurrencies the ability to create their own Ethereum-based ICO (ERC20 tokens),” said Cohen. “Combined with an ICO campaign creator that allows users to create an entire ICO campaign as well as accept Ethereum-based funding from backers.”

“The platform includes an integrated compliance system that allows for any vetted ICOs to comply with various local regulations, including KYC and AML. We are also working on integrating SEC-based crowdfunding compliance, specifically Job Act Title III and Regulation A.”

Ultimately tools that reduce the complexity of token sales will take over from the jerry-built systems currently in place. Token-sales-in-a-box services exist, but they are aimed at raising massive consulting fees and basic, programmatic and regulated services just don’t exist yet. This is an interesting first step, and, according to Cohen, it’s quite popular. The project launched yesterday and so far users have generated the equivalent of about $1 billion using the service.

Two global investors will talk token sales at Disrupt Berlin

Token sales, also called ICOs, are the new normal when it comes to early stage cash. Originally envisioned as a way to create new and unique rails for payments, customer interaction, and peer-to-peer networking the token is now both an integral part of most companies and a great way to fund a great (or awful) idea.

This year at Disrupt Berlin we’ll be joined by Zoe Adamovicz of Neufund and Kavita Gupta of Consensys. Both of these folks are seasoned blockchain investors with millions at their disposal and they’ll be talking about how investors should sail the rocky shoals of regulation, how token sales are changing the way VCs interact with companies, and how these tools will change in the future.

Token sales are here to stay but they will morph. In this Disrupt panel we’ll discuss what that means to startups, investors, and most important, the world.

Get your Disrupt tickets right now to save 30 percent off of your tickets and meet luminaries in the token space. You’ll also see the Startup Battlefield competition, in which a handful of startups pitch our judges with the hopes of winning the coveted Disrupt Cup and a cash prize.

You’ll get to chat with plenty of promising startups in Startup Alley, see amazing talks on the main stage, and unwind after a long day at the show with a cocktail and some new friends at the Disrupt after party.

Do you run a startup? The Startup Alley Exhibitor Package is your best bet to get the greatest exposure by exhibiting your company or product directly on the Disrupt Berlin show floor.

ROSS Intelligence lands $8.7M Series A to speed up legal research with AI

Armed with an understanding of machine learning, ROSS Intelligence is going after LexisNexis and Thomson Reuters for ownership of legal research. The startup, founded in 2015 by Andrew Arruda, Jimoh Ovbiagele and Pargles Dall’Oglio at the University of Toronto, is announcing an $8.7 million Series A today led by iNovia Capital with participation from Comcast Ventures Catalyst Fund, Y Combinator Continuity Fund, Real Ventures, Dentons’ NextLaw Labs and angels.

At its core, ROSS is a platform that helps legal teams sort through case law to find details relevant to new cases. This process takes days and even weeks with standard keyword search, so ROSS is augmenting keyword search with machine learning to simultaneously speed up the research process and improve relevancy of items found.

“Bluehill benchmarks Lexis’s tech and they are finding 30 percent more relevant info with ROSS in less time,” Andrew Arruda, co-founder and CEO of ROSS, explained to me in an interview.

ROSS is using a combination of off the shelf and proprietary deep learning algorithms for its AI stack. The startup is using IBM Watson for at least some of its natural language processing capabilities, but the team shied away from elaborating.

Building a complete machine learning stack is expensive, so it makes sense for startups to lean on off the shelf tech early on so long as decisions are being made that ensure the scalability of the business. Much of the value wrapped up in ROSS is related to its corpus of training data. The startup is working with 20 law firms to simulate workflow examples and test results with human feedback.

“We really spent time looking at the value ROSS was delivering back to law firms,” noted Kai Bond, an investor in ROSS through Comcast Ventures. “What took a week now takes two to four hours.”

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The company’s initial plan to get to market was to sell software designed for specific domains of law to large firms like Latham & Watkins and Sidley Austin. Today ROSS offers products in both bankruptcy and intellectual property law. It is looking to expand into other types of law, like labor and employment, simultaneously moving down to serve smaller firms.

LexisNexis and Thomson Reuters are frequently on the butt end of claims made by machine learning-powered data analytics startups emerging in a potpourri of industries. A strategy favored by many of these businesses is pushing products to interns and college students for free so that they, in turn, push their advanced tools into the arms of future employers.

“The work ROSS is doing with law schools and law students is interesting,” Karam Nijjar, a partner at iNovia Capital and investor in ROSS, asserted. “As these students enter the workforce, you’re taking someone using an iPhone and handing them a BlackBerry their first day on the job.”

Prior to today’s Series A, ROSS had secured a $4.3 million seed round also led by iNovia Capital. As ROSS moves to scale it will be navigating a heavy field of mergers and acquisitions and attempts by legacy players to ensure legal tech services remain consolidated.

Deepgram opens up its machine transcription platform to everyone

Deepgram, a startup applying machine learning to audio data, is releasing its machine transcription platform this morning for free. No more will you have to pay for other services like Trint to get the dirty work of automated transcription done. Hint: it has something to do with data.

Machine transcription isn’t solved. In fact, machine anything isn’t solved. And it seems like everyone these days is making haste to build their own Fort Knox of data to solve machine everything. Deepgram’s approach is to make its transcription service free for anyone to upload their audio content and receive searchable text in return.

This approach isn’t particularly unique — as I said, everyone needs data. Don’t forget that Image Captchas are basically a means of forcing plebeians to label image data sets for training machine learning models.

Deepgram is using deep learning for its transcription tool (surprise!) — good old convolutional and recurrent neural networks. Everything is generalized in the free version, but paid offerings might include custom training on company and product names as well as terms of art in a given industry.

I uploaded an hour long interview I did about a week ago to the service to test it out. The file was recorded in a noisy restaurant and consisted of two people having a dialog. The transcription quality was far from perfect — but it wasn’t meaningfully worse than anything else on the market.

I was able to search for a specific quote I remembered and after three attempts, I found the segment of dialog. I wouldn’t be able to copy and paste it without angering the interviewee, but it would have given me the context I needed to tell my story. The search process took about five minutes and, to Deepgram’s credit, it was obvious that searches were using the sounds of words to find more matches. The thing to remember is that the service costs considerably less than more accurate human transcription and will improve with time.

“ASR is not solved,” Scott Stephenson, co-founder and CEO of Deepgram, explained to me in an interview. “It’s solved for specific data sets but with noisy accented call data, any service will do a poor job with it.”

In addition to the platform, Deepgram is also offering a mostly free API for machine transcription. If you use over a million minutes you will be charged — computation is expensive so it wouldn’t make sense to allow someone to troll the company with a 50 terabyte audio file.

While humans still reign supreme in the transcription world, it’s possible that synthesized audio could tilt the odds in the favor of the machines in the near future. Projects like WaveNet and Lyrebird, that generate speech from text, could help to augment systems with data for uncommon words that tend to be the most likely to trip up machine translation systems like Deepgram and those made by the tech giants.

Featured Image: Colin McConnell / Contributor/Getty Images