Locked Treasure Trove of Voice Data

Every year, Apple’s customer service team speaks with millions of customers to help troubleshoot devices. Uber, Lyft, and Doordash conduct millions of phone interviews to screen for new drivers. JPMorgan Chase speaks to millions of households and small businesses to help with financial planning. Collectively, enterprises converse for trillions of minutes annually. There is a treasure trove of information-rich data waiting to be unlocked from all of these conversations.

Voice is one of the biggest trends in enterprise technology. However, today’s speech recognition technology has been optimized for one-way, short-form conversations like those delivered to a virtual assistant. Unlike Siri and Alexa commands, enterprise communication is messy. Most employees aren’t speaking clearly and slowly into a high-fidelity microphone. Instead, meetings and calls usually have multiple people with different accents speaking over each other far away from the microphone.

Making sense of verbal communication for enterprises is a massive opportunity, but it’s nascent given technical challenges and prohibitive costs. Enter Deepgram.

Turning Voice into Value through Deep Learning

Advancements in natural language processing (NLP) are helping enterprises understand intention and perception from emails and other forms of written communication. However, the holy grail has been to understand verbal communication in a similar way. Deepgram has taken an entirely new approach to automatic speech recognition (ASR) by coupling robust deep learning models with specialized data infrastructure.

Through Deepgram’s API, data scientists and developers can convert messy, unstructured audio data into accurate and structured transcriptions in real-time. Deepgram builds custom end-to-end deep learning models for every customer. This architecture enables Deepgram to achieve ~95% accuracy vs. ~72% accuracy from incumbent competitors. In addition to significantly improved accuracy, Deepgram’s technology enables better pricing, higher reliability and superior performance at scale.

Inspired by Dark Matter

Deepgram’s founders are uniquely positioned to build high-performance voice infrastructure. The concept came while both founders were Ph.D. students researching the creation of dark matter two miles underground. It was after that research experiment they discovered there wasn’t a tool available that would help process recordings and pinpoint valuable timestamps. When we met Scott Stephenson and the team, we were blown away by their customer obsession, technical prowess, and commercial ambition.

Deepgram publically launched its speech engine two years ago and its customers depend on its technology for mission-critical analysis and workflow. To date, Deepgram has processed over one billion minutes of voice data. When we spoke with Deepgram’s customers, we were amazed at how thorough they had been in testing Deepgram vs. competitors. Deepgram consistently exceeded the competition across multiple performance dimensions.

Deepgram will enable a new generation of enterprise applications and services. We are just scratching the surface of what information and signals can be extracted from voice data. Deepgram is built for developers and is architected to power the full spectrum of companies ranging from a small startup to a multinational Fortune 100 company.

Wing’s Partnership with Deepgram

We are thrilled to announce that Wing has led Deepgram’s $12M Series A financing. We are proud to invest alongside our friends at NVIDIA, SAP.iO, Compound Ventures, and Y Combinator. I have joined Deepgram’s board and am excited to work with the team to help enterprises better understand and leverage their voice data.

If you would like to learn more about Deepgram, please visit the company website. Deepgram is hiring and if you are interested in working on hard problems with an incredible team, please visit Deepgram’s Careers page.

Unlocking the Largest Data Source in the Enterprise: Voice was originally published in WING VC on Medium, where people are continuing the conversation by highlighting and responding to this story.

Here is the professional breakdown of the surveyed audience:

Here are the results:

Q1: The crypto market is valued at ~$110 bn today. What is your prediction for where it ends 2019?

Q2: If you could own just one crypto asset for the next year it would be…?

Q3: Over the next 3 months, I am going to be:

Q4: Over the last 6 months, I was a:

Q5: What is your personal allocation within crypto?

Q6: On Dec 31, 2022 the price of BTC will be:

Q7: BTC has or will bottom at this price:

Q8: [Optional] What will be a potential catalyst for the crypto market to rebound?

This was an open-ended question and some of the most frequent responses were:

• Bitcoin ETF approval
• Telegram & Facebook launching crypto protocols
• Growth of Lightning Network
• Regulatory clarity
• More infrastructure build out (scalability, security, privacy)
• Improved usability and consumer-facing products

Q9: [Optional] Are you more or less confident than you were in 2017 that crypto will “win”?

42 of 59 respondents (71%) reported that they are more confident than they were in 2017 that crypto will “win”. This was an open-ended question and many respondents included commentary that the reason why they are more confident is because more smart people are entering the space and building important infrastructure and tooling.

Please email me any questions, thoughts or suggestions to zach@wing.vc or message me on Twitter @zacharydewitt. Wing is a $460M early stage venture fund founded by ex-Sequoia and Accel partners.

Crypto Sentiment Survey (February 2019) was originally published in WING VC on Medium, where people are continuing the conversation by highlighting and responding to this story.

As a follow up to our recent crypto sentiment survey that we worked on with a prominent crypto angel investor (link here), we wanted to dig deeper into the sentiment across professional cohorts. As a recap, the breakdown of the 82 people surveyed is as follows:

For this exercise and for the results below, we removed everyone from the survey who reported that they do not directly work in the crypto industry. For example, this could be someone who works at a traditional hedge fund who is very knowledgeable about crypto and who is personally invested in crypto, but the hedge fund that she works for is not fully dedicated to crypto. Consequently, n = 82 decreased to n = 58, but all of the below results are from people directly employed in the crypto industry.

Crypto Allocations

In the survey, we asked everyone about their current crypto allocations. Here is the data, by professional cohort:

From the data above, it is interesting to note that crypto hedge funds own relatively less BTC (38%) and ETH (17%) than other crypto investors and are instead, more weighted towards other liquid alts + private crypto investments. Furthermore, entrepreneurs and developers have a relatively high allocation to BTC (53%) and the relatively average allocation to ETH (24%).

Crypto Market Sentiment

In the survey, we asked everyone for their best predictions on i) what the total crypto market valuation will be at the end of 2018 and ii) what the price of BTC will be at the end of 2022. Here is the data, by professional cohort:

Hedge funds, angel investors and family offices are most bullish in the near-term (2018). They are also relatively more bullish than VCs on where the price of BTC will be in 2022.

Concluding Observations

There are a handful of interesting observations, despite the limited size of the survey (remember, n = 58). Observation #1: Crypto hedge funds are the most bullish on the crypto market (both in predicting a ~2x total market cap improvement by end of 2018 and in predicting a ~20x improvement in BTC’s price by 2022), but are allocating a relatively larger portion of their current holdings away from BTC and ETH and towards other liquid alts + private crypto deals. Observation #2: Entrepreneurs and developers hold a relatively high amount of BTC (53%) and an average amount of ETH (24%). Observation #3: Crypto-focused VCs hold the relatively highest allocation of BTC (53%), despite being relatively more conservative on BTC’s 2022 price (crypto VCs are predicting BTC multiplies~8x in price per token vs. crypto hedge funds predicting BTC multiples~20x).

Subscribe below to be emailed updates when new surveys come out:

Here is the professional breakdown of the surveyed audience:

Here are the results:

Q1: The crypto market is valued at ~$240bn today. What is your prediction for where it ends 2018?

It is worth noting that per my last crypto sentiment survey in April 2018, the median 2018 crypto market cap prediction was $750bn. Today’s median 2018 crypto market cap prediction has decreased 47% to $400bn. Over the same period, the actual total crypto market cap decreased from $300bn to $240bn, or 20%. Thus, the 2018 year end sentiment has decreased disproportionately more than the actual market cap decline over the last three months.

Q2: If you could own just one crypto asset (public or private) for the next year, what would it be (note: this was an open answer field question)?

Q3: What category of assets will get the best returns over next 3 years?

Q4: Over the next 3 months I am going to be:

Q5: Over the last 6 months I was:

Q6: What’s your personal % allocation?

Q7: On Dec 31, 2022 the price of Bitcoin (BTC, per token) will be:

Subscribe below to be emailed updates when new surveys come out:

Here are the results:

Q1: The crypto market is valued at ~$300bn today. What is your prediction for where it ends 2018?

Q2: Near-term sentiment: for Q2 2018, how are you feeling about the crypto markets?

Q3: What % of your crypto holdings is Bitcoin?

Q4: What % of your crypto holdings is Ethereum?

Q5: What cryptoasset are you most bullish on for 2018?

Q6: Which alt coin (non-BTC, BCH, ETH) are you most bullish on for 2018?

Subscribe below to be emailed updates when new surveys come out:

Please reach out with any questions or comments: zach@wing.vc

A recent study (read: Originals by Adam Grant) of some of the most influential leaders in history found that strategically procrastinating can actually lead to the best speech, presentation or idea. By taking a break, you are more likely to engage in divergent thinking and give ideas time to incubate.

Martin Luther King Jr. didn’t start writing his “I Have a Dream Speech” until 10pm the night before.

The day before The Gettysburg Address, President Lincoln had only prepared about half of his speech.

Resisting to solidify your conclusion up front keeps you open to new ideas and allows you to fully develop your thesis.

To put this into practice at work, when people say “don’t bring me problems, bring me solutions”, bring problems first and then procrastinate to brainstorm, debate and consult before settling on a solution.

In your personal life and professional life trying asking more neutral questions. You already know what you think so getting someone to agree with you isn’t as valuable as getting their unbiased opinion.

On the flip side, people with high confidence generally seek out contradictory information to their own beliefs to form an argument. Listen carefully to how people are asking you questions as it could be a signal for confidence or lack of confidence on the subject matter.

Adopt a low RC factor — Sam Walton, Founder of Walmart and Sam’s Club

The “RC” that Sam is referring to is “Resistance to Change.” When you think of Walmart, you think slow and steady. Given that a low RC factor is part of the Walmart DNA, it is no surprise that FastCompany named Walmart the 5th most innovate retail company in the world in 2014 (after Warby Parker and ahead of eBay).

The best leaders are open to constant change and are willing to re-examine every assumption, even their own. Change can be the hardest thing you have to do as a leader.

Just as trying to think up startup ideas tends to produce bad ones, working on things that could be dismissed as “toys” often produces good ones. When something is described as a toy, that means it has everything an idea needs except being important.

When I moved out to San Francisco about a year ago, we were lucky enough to meet with Biz Stone, one of the Twitter co-founders and overall great person, who gave us the same advice about building a toy when thinking about product design: something that is fun, simple and entertaining. Biz Stone introduced us to a quotation that has stuck with me. Charles Eames, one of the most influential designer and architects of the 20th century, said:

Toys are not really as innocent as they look. Toys and games are precursors to serious ideas.

Paul, Charles and Biz are on to something. When Twitter started, it was a fun toy, and now it is something a lot more important and profound. Same with Facebook. Same with Snapchat. This is true not only for the large social media companies that we use everyday, but also for many of the fastest growing companies in the world, like Uber. If you listen to Travis Kalanick speak about the founding of Uber, he consistently explains Uber started as a fun tool for him and his close friends to call a private car after dinner.

If someone tells your idea is “childish” or “not serious enough”, you may actually be on to something big.