The vast enterprise tech category is Silicon Valley’s richest, and today it’s poised to change faster than ever before. That’s probably the biggest reason to come to TechCrunch’s first-ever show focused entirely on enterprise. But here are five more reasons to commit to joining TechCrunch’s editors on September 5 at San Francisco’s Yerba Buena Center for an outstanding day (agenda here) addressing the tech tsunami sweeping through enterprise.
#1 Artificial Intelligence.
At once the most consequential and most hyped technology, no one doubts that AI will change business software and increase productivity like few if any, technologies before it. To peek ahead into that future, TechCrunch will interview Andrew Ng, arguably the world’s most experienced AI practitioner at huge companies (Baidu, Google) as well as at startups. AI will be a theme across every session, but we’ll address again it head-on in a panel with investor Jocelyn Goldfein (Zetta), founder Bindu Reddy (Reality Engines) and executive John Ball (Salesforce / Einstein).
#2. Data, The Cloud and Kubernetes.
If AI is at the dawn of tomorrow, cloud transformation is the high noon of today. 90% of the world’s data was created in the past two years, and no enterprise can keep its data hoard on-prem forever. Azure’s CTO Mark Russinovitch (CTO) will discuss Microsft’s vision for the cloud. Leaders in the open-source Kubernetes revolution, Joe Beda (VMWare) and Aparna Sinha (Google) and others will dig into what Kubernetes means to companies making the move to cloud. And last, there is the question of how to find signal in all the data – which will bring three visionary founders to the stage: Benoit Dageville (Snowflake), Ali Ghodsi (Databricks), Murli Thirumale (Portworx).
#3 Everything else on the main stage!
Let’s start with a fireside chat with SAP CEO Bill McDermott and Qualtrics Chief Experience Officer Julie Larson-Green. We have top investors talking where they are making their bets, and security experts talking data and privacy. And then there is quantum, the technology revolution waiting on the other side of AI: Jay Gambetta, the principal theoretical scientist behind IBM’s quantum computing effort, Jim Clarke, the director of quantum hardware at Intel Labs, and Krysta Svore, style="font-weight: 400;"> who leads the Microsoft’s quantum effort.
All told, there are 21 programming sessions.
#4 Network and get your questions answered.
There will be two Q&A breakout sessions with top enterprise investors for founders (and anyone else) to query investors directly. Plus, TechCrunch’s unbeatable CrunchMatch app makes it really easy to set up meetings with the other attendees, an incredible array of folks, plus the 20 early-stage startups exhibiting on the expo floor.
Enterprise giant SAP is our sponsor for the show, and they are not only bringing a squad of top executives, they are producing four parallel track sessions featuring key SAP Chief Innovation Officer Max Wessel, SAP Chief Designer and Futurist Martin Wezowski and SAP.IO’s managing director Ram Jambunathan (SAP.iO) in sessions including, how to scale-up an enterprise startup, how startups win large enterprise customers, and what the enterprise future looks like.
Check out the complete agenda. Don’t miss this show! This line-up is a view into the future like none other.
Grab your $349 tickets today, and don’t wait till the day of to book because prices go up at the door!
We still have 2 Startup Demo Tables left. Each table comes with 4 tickets and a prime location to demo your startup on the expo floor. Book your demo table now before they’re all gone!
Brooklinen, the direct-to-consumer bed sheet brand backed by investors including FirstMark, is entering the apparel space with its first line of loungewear. The company says its designs, including tops, pants, shorts and a dress, are inspired by vintage athletic clothing and made from cotton and modal blended with spandex. Prices range from $28 for a t-shirt to $75 for jogger pants.
The startup, whose investors also include NYU Innovation Venture Fund and Dorm Room Fund, has built its reputation around high-quality but affordable linens and is able to offer lower prices by controlling the design, manufacturing and logistics and fulfillment of its sheets, comforters, pillows and towels. It is primarily an e-commerce startup, but has also run pop-up shops. Brooklinen’s last round of funding was a $10 million Series A announced in 2017.
Welcome back to the transcribed edition of the popular podcast Equity. Kate Clark had the hosting reins this week and welcomed Revolution’s Clara Sieg to the studio.
They discussed the trend of investors backing companies from “second-tier” markets like Austin, Atlanta, Denver, Philadelphia, Seattle, etc. Just how do cities become tech hubs? It’s a special kind of recipe, Sieg says. A city must have a great university, or a few, nearby to provide a constant flow of talent. They need some big corporations around for the same reason. They need a healthy community of angel investors ready and willing to get things going.
Sieg: Fundamentally in these second and third tier markets, an idea on the back of a napkin doesn’t get funded, so you really have to bootstrap to a certain degree and prove out really economics before you can unlock capital. Typically the companies that we’re investing in at the Series A, Series B level are a little bit farther along than their brethren would be in the Bay Area or New York.
Valuation expectations are just lower so you own more of a company for a smaller check-in. Inherently, if it’s an exit, that is a better outcome for you and it’s just cheaper to scale companies in those markets. Employee retention is better, cost of living is lower, so the capital required to scale these companies and that’s coming in after you and diluting you is less.
Clark: So when Steve Case founded Revolution, was he coming at it from the perspective of like, “This is obviously good business?” Which it is, to invest in these companies, or was it coming from a perspective of like, “It’s not fair that companies in these areas just don’t have access to capital like we do here in the Bay Area?”
Sieg: Neither, really. I think our investing approach in the early days, and what we still focus on today is what is now commonly referred to as disruption, right? Historically, Zipcar was basically disrupting the rental car market, and it was not really thought of as a great venture-backable opportunity in the early days. That’s obviously changed now, transportation is a huge piece of what venture capitalists focus on, but from day one, we focused on sleepy, incumbent markets where technology can be an enabler of a new business model that makes it better, faster, cheaper for the consumer, or the business that it’s serving, and where you can change the margins in the business to create a market leader that incumbents then either have to own or that can be a large standalone company.
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Welcome back to this week’s transcribed edition of Equity.
This was a big week of news that the Equity duo had to cover. Kate was at the Code Conference, Fortnite maker, Epic Games bought Houseparty, and a bit more on the Bird-Scoot deal.
Then came talk of the CrowdStrike IPO, which gave way to a heated discussion about dual-class shares.
Alex Wilhelm: I think it’s honest. I think giving the public one vote per share, and giving yourself 10 so you retain greater than 50% of voting is a sop. I think it’s ridiculous. Just fly under your own flag. If you don’t want to share any control, then don’t. If you want to have a company with a functional governance, that adheres to historical norms for how this stuff works, then have votes. This 10 versus 1 thing is a fracking farce, because I can’t swear on this show, so you can fill that in yourself. If you want to look at a historical example of a company that didn’t have this setup, it was Amazon, which historically thinks far ahead, and has done fantastically well. It’s public company growing from a, I believe, under nine-figure revenue. The idea you can’t do it is trash. The idea that it always works is wrong. To me, it’s dishonest. If you’re going to sell shares, go public, and float, share the voting power with your shareholders. Don’t treat them like children, and you like a god. You’re not.
Kate Clark: Alex is getting really worked up, but I totally agree with you. That’s why I want to-
Wilhelm: I’m not worked up, I’m angry.
Clark: That’s why I wanted to talk about it though, because I think it’s important. I think what you just said is a perfect summary of why it’s messed up. The only thing I think that will really change this, is to see whether these dual-class stocks, versus single-class stocks, perform differently on the market. As far as I know, they’re not, which means that people don’t care. Or, people don’t know, I don’t know. If a company isn’t going to lose any money doing it … If they’re not going to have any consequences whatsoever, they’re not going to be up against any negative feedback from shareholders, then of course, they’re going to keep doing it. Like I said, it’s not really talked about very much.
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For the first time, Amazon today showed off its newest fully electric delivery drone at its first re:Mars conference in Las Vegas. Chances are, it neither looks nor flies like what you’d expect from a drone. It’s an ingenious hexagonal hybrid design, though, that has very few moving parts and uses the shroud that protects its blades as its wings when it transitions from vertical, helicopter-like flight at takeoff to its airplane-like mode.
These drones, Amazon says, will start making deliveries in the coming months, though it’s not yet clear where exactly that will happen.
What’s maybe even more important, though, is that the drone is chock-full of sensors and a suite of compute modules that run a variety of machine learning models to keep the drone safe. Today’s announcement marks the first time Amazon is publicly talking about those visual, thermal and ultrasonic sensors, which it designed in-house, and how the drone’s autonomous flight systems maneuver it to its landing spot. The focus here was on building a drone that is as safe as possible and able to be independently safe. Even when it’s not connected to a network and it encounters a new situation, it’ll be able to react appropriately and safely.
When you see it fly in airplane mode, it looks a little bit like a TIE fighter, where the core holds all the sensors and navigation technology, as well as the package. The new drone can fly up to 15 miles and carry packages that weigh up to five pounds.
This new design is quite a departure from earlier models. I got a chance to see it ahead of today’s announcement and I admit that I expected a far more conventional design — more like a refined version of the last, almost sled-like, design.
Besides the cool factor of the drone, though, which is probably a bit larger than you may expect, what Amazon is really emphasizing this week is the sensor suite and safety features it developed for the drone.
Ahead of today’s announcement, I sat down with Gur Kimchi, Amazon’s VP for its Prime Air program, to talk about the progress the company has made in recent years and what makes this new drone special.
“Our sense and avoid technology is what makes the drone independently safe,” he told me. “I say independently safe because that’s in contrast to other approaches where some of the safety features are off the aircraft. In our case, they are on the aircraft.”
Kimchi also stressed that Amazon designed virtually all of the drone’s software and hardware stack in-house. “We control the aircraft technologies from the raw materials to the hardware, to software, to the structures, to the factory to the supply chain and eventually to the delivery,” he said. “And finally the aircraft itself has controls and capabilities to react to the world that are unique.”
What’s clear is that the team tried to keep the actual flight surfaces as simple as possible. There are four traditional airplane control surfaces and six rotors. That’s it. The autopilot, which evaluates all of the sensor data and which Amazon also developed in-house, gives the drone six degrees of freedom to maneuver to its destination. The angled box at the center of the drone, which houses most of the drone’s smarts and the package it delivers, doesn’t pivot. It sits rigidly within the aircraft.
It’s unclear how loud the drone will be. Kimchi would only say that it’s well within established safety standards and that the profile of the noise also matters. He likened it to the difference between hearing a dentist’s drill and classical music. Either way, though, the drone is likely loud enough that it’s hard to miss when it approaches your backyard.
To see what’s happening around it, the new drone uses a number of sensors and machine learning models — all running independently — that constantly monitor the drone’s flight envelope (which, thanks to its unique shape and controls, is far more flexible than that of a regular drone) and environment. These include regular camera images and infrared cameras to get a view of its surroundings. There are multiple sensors on all sides of the aircraft so that it can spot things that are far away, like an oncoming aircraft, as well as objects that are close, when the drone is landing, for example.
The drone also uses various machine learning models to, for example, detect other air traffic around it and react accordingly, or to detect people in the landing zone or to see a line over it (which is a really hard problem to solve, given that lines tend to be rather hard to detect). To do this, the team uses photogrammetrical models, segmentation models and neural networks. “We probably have the state of the art algorithms in all of these domains,” Kimchi argued.
Whenever the drone detects an object or a person in the landing zone, it obviously aborts — or at least delays — the delivery attempt.
The team also uses a technique known as Visual Simultaneous Localization and Mapping (VSLAM), which helps the drone build a map of its current environment, even when it doesn’t have any other previous information about a location or any GPS information.
“That combination of perception and algorithmic diversity is what we think makes our system uniquely safe,” said Kimchi. As the drone makes its way to the delivery location or back to the warehouse, all of the sensors and algorithms always have to be in agreement. When one fails or detects an issue, the drone will abort the mission. “Every part of the system has to agree that it’s okay to proceed,” Kimchi said.
What Kimchi stressed throughout our conversation is that Amazon’s approach goes beyond redundancy, which is a pretty obvious concept in aviation and involves having multiple instances of the same hardware on board. Kimchi argues that having a diversity of sensors that are completely independent of each other is also important. The drone only has one angle of attack sensor, for example, but it also has a number of other ways to measure the same value.
Amazon isn’t quite ready to delve into all the details of what the actual on-board hardware looks like, though. Kimchi did tell me that the system uses more than one operating system and CPU architecture, though.
It’s the integration of all of those sensors, AI smarts and the actual design of the drone that makes the whole unit work. At some point, though, things will go wrong. The drone can easily handle a rotor that stops working, which is pretty standard these days. In some circumstances, it can even handle two failed units. And unlike most other drones, it can glide if necessary, just like any other airplane. But when it needs to find a place to land, its AI smarts kick in and the drone will try to find a safe place to land, away from people and objects — and it has to do so without having any prior knowledge of its surroundings.
To get to this point, the team actually used an AI system to evaluate more than 50,000 different configurations. Just the computational fluid dynamics simulations took up 30 million hours of AWS compute time (it’s good to own a large cloud when you want to build a novel, highly optimized drone, it seems). The team also ran millions of simulations, of course, with all of the sensors, and looked at all of the possible positions and sensor ranges — and even different lenses for the cameras — to find an optimal solution. “The optimization is what is the right, diverse set of sensors and how they are configured on the aircraft,” Kimchi noted. “You always have both redundancy and diversity, both from the physical domain — sonar versus photons — and the algorithmic domain.”
The team also ran thousands of hardware-in-the-loop simulations where all the flight services are actuating and all the sensors are perceiving the simulated environment. Here, too, Kimchi wasn’t quite ready to give away the secret sauce the team uses to make that work.
And the team obviously tested the drones in the real world to validate its models. “The analytical models, the computational models are very rich and are very deep, but they are not calibrated against the real world. The real world is the ultimate random event generator,” he said.
It remains to be seen where the new drone will make its first deliveries. That’s a secret Amazon also isn’t quite ready to reveal yet. That will happen within the next few months, though. Amazon started drone deliveries in England a while back, so that’s an obvious choice, but there’s no reason the company could opt for another country as well. The U.S. seems like an unlikely candidate, given that the regulations there are still in flux, but maybe that’s a problem that will be solved by then, too. Either way, what once looked like a bit of a Black Friday stunt may just land in your backyard sooner than you think.