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Here’s Huawei Mate 20 Pro Kirin 980 Vs iPhone XS A12 Bionic benchmarks comparison is out. Here is who comes out on top. [ Continue reading this over at RedmondPie.com ]
Here’s Huawei Mate 20 Pro Kirin 980 Vs iPhone XS A12 Bionic benchmarks comparison is out. Here is who comes out on top. [ Continue reading this over at RedmondPie.com ]
Docker, the company that did more to create today’s modern containerized computing environment than any other independent company, has raised $92 million of a targeted $192 million funding round, according to a filing with the Securities and Exchange Commission. The new funding is a signal that while Docker may have lost its race with Google’s […]
Docker, the company that did more to create today’s modern containerized computing environment than any other independent company, has raised $92 million of a targeted $192 million funding round, according to a filing with the Securities and Exchange Commission.
The new funding is a signal that while Docker may have lost its race with Google’s Kubernetes over whose toolkit would be the most widely adopted, the San Francisco-based company has become the champion for businesses that want to move to the modern hybrid application development and information technology operations model of programming.
To understand the importance of containers in modern programming it may help to explain what they are. Put simply, they’re virtual application environments that don’t require an operating system to work. In the past, this type of functionality would have been created using virtual machines, which included software and an operating system.
Containers, by contrast, are more efficient.
Because they only contain the application and the libraries, frameworks, etc. they depend on, you can put lots of them on a single host operating system. The only operating system on the server is that one host operating system and the containers talk directly to it. That keeps the containers small and the overhead extremely low.
Enterprises are quickly moving to containers as they are looking to improve how they develop and manage software — and do so faster. But they can’t do that alone and need partners like Docker to help them make that transition.
What many people miss is that Docker is far more than the container orchestration layer — Kubernetes won that war — but a full toolchain for building and managing those containers.
With every open source project, technology companies are quick to adopt (and adapt) the open source project and be well-versed with how to use it. More mainstream big businesses that aren’t quite as tech-savvy will turn to a company like Docker to help them manage projects developed with the toolkits.
It’s the natural evolution of a technology startup that serves big business customers to become uninteresting while they become more profitable. Enterprises use them. They make money. The hype is gone. Because once a company sells to a big enterprise customer, they stick with that vendor forever.
… Docker has quietly transformed into an enterprise business with explosive revenue growth and a developer community in the millions, under the leadership of our CEO, the legendary Steve Singh. Our strategy is simple: every large enterprise in the world is preparing to migrate their applications and infrastructure to the cloud, en masse. They need a solution to do so reliably and securely, without expensive code or process changes, and without locking themselves to a single operating system or cloud. Today the only solution meeting these requirements is Docker Enterprise Edition. This puts Docker at the center of a massive growth opportunity. To take advantage of this opportunity, we need a CTO by Steve’s side with decades of experience shipping and supporting software for the largest corporations in the world. So I now have a new role: to help find that ideal CTO, provide the occasional bit of advice, and get out of the team’s way as they continue to build a juggernaut of a business. As a shareholder, I couldn’t be happier to accept this role.
With the money, it’s likely that Docker will ramp up its sales and marketing staff to start generating the kind of revenue numbers it needs to go out for a public offering in 2019. The company has built up a slate of independent directors (in another clear sign that it’s trying to open a window for its exit into the public markets).
Docker is already a “unicorn” worth well over $1 billion. The last time Docker reportedly raised capital was back in late 2017, when The Wall Street Journal href="https://www.wsj.com/articles/docker-raising-75-million-1507332173">uncovered a filing document from the Securities and Exchange Commission indicating that the company had raised $60 million of a targeted $75 million round. Investors at the time included AME Cloud Ventures, Benchmark, Coatue Management, Goldman Sachs and Greylock Partners. At the time, that investment valued the company at $1.3 billion.
We’ve reached out to the company for comment and will update this post when we hear back.
Upwork, the rebranded merger of oDesk and Elance, debuted on Nasdaq this morning, after dropping its S-1 about four weeks ago. Shares opened at $23.00, which represents a 53% jump — shares were priced at $15 before the opening bell by investors, a significant uptick from the company’s revised projection of $12 to $14, which […]
Upwork, the rebranded merger of oDesk and Elance, debuted on Nasdaq this morning, after dropping its S-1 about four weeks ago. Shares opened at $23.00, which represents a 53% jump — shares were priced at $15 before the opening bell by investors, a significant uptick from the company’s revised projection of $12 to $14, which was already an increase from its original $10 to $12 target. The stock trades under the ticker UPWK, and the company will fundraise approximately $102 million of new cash for its balance sheet ($187 million total with existing shareholders).
Shares are still currently up 40% compared to their original price.
I talked with Upwork CEO Stephane Kasriel this morning about the IPO road show, in which he said he took approximately 160 meetings with investors. Investors were engaged on the “combination of the strengths of the business and the strengths of the mission,“ and he was clearly excited about the engagement the offering received.
Upwork, whose antecedent companies go back almost two decades, is a positive cash flow business, albeit one growing top line revenue only about 27.6% year over year. Kasriel said that the company should be able to “compound at that rate for decades” due to the growing number of workers who freelance around the world in order to have flexible work arrangements. “When you think about which jobs are being created in the global economy, in most countries it is these knowledge jobs,” he said.
In addition, “When you really take a long term view, what really matters is to be good stewards of capital,” Kasriel noted, and said that the company was very focused on areas like sales and marketing ROI. His goal is to continue to grow the company with limited dilution to shareholders, a message that apparently has been well-received.
As for Kasriel himself, he becomes a public company CEO. He was elevated to the CEO role in 2015 from SVP of Engineering – a somewhat unusual path, even in tech-obsessed Silicon Valley. He emphasized that “we are a tech company,” and noted that every day is a learning experience. “I was just on CNBC, and for introverts, what really scares me is to be on live broadcast TV,” he said.
A huge part of Upwork’s business today is focused on the enterprise, particularly complex workflows that require multiple types of talent. The company’s platform not only handles talent management, but the long array of tasks to manage people: HR, legal, procurement, information security, and others.
According to the company, it will host $1.5 billion worth of gross sales value across two million unique projects. The company estimates that its products are used by 30% of the Fortune 500.
Upwork, which has offices in Mountain View, San Francisco, and Chicago, has 1,500 employees – and as is to be expected – roughly 1,100 of them are freelancers. Kasriel said, “We use our own product, which we call drinking our own champagne.”
Among the major VC investors behind the company are Benchmark, which owned 15%, Sigma Partners, which owned 14.2%, and Globespan, T. Rowe Price, and FirstMark. The company is offering 6,818,181 new shares as well as 5,658,512 shares from existing shareholders. Citigroup, Jefferies, and RBC jointly led the book.
Now that the company has debuted, Upwork wants to refocus once again on its business following weeks of talking to investors. “We need to build this company for the ages,” Kasriel noted, and said that his message to employees was to “focus on the mission.”
The firm’s upcoming fund will not include longtime Benchmark general partners Mitch Lasky and Matt Cohler.
While other firms close billion-dollar venture funds despite a history of smaller fundraises, Benchmark is sticking to its guns. The firm, known for its early bets on Twitter, Uber, Snap and WeWork, hasn’t fallen victim to the SoftBank effect.
Longtime Benchmark general partners Bill Gurley and Peter Fenton are listed on the filing alongside three newer members of the partnership. Benchmark staples Mitch Lasky and Matt Cohler, who joined the firm in 2007 and 2008, respectively, are noticeably absent.
Cohler, for his part, joined Benchmark a decade ago from Facebook where he was a vice president. At Benchmark, he was responsible for investments in Dropbox, Domo, Duo Security and others.
In June 2017, he replaced Gurley on Uber’s board of directors. Gurley stepped down from the ride-hailing giant’s board following a well-publicized fight to remove founder Travis Kalanick from the c-suite.
Cohler and Lasky are expected to keep their board seats, according to Axios.
Sarah Tavel, Chetan Puttagunta and Eric Vishria will replace the pair in fund nine. Puttagunta joined the storied VC firm from NEA in July. Tavel, Benchmark’s first-ever female partner, was hired about a year ago from Greylock Partners and Vishria, the co-founder of social browsing startup Rockmelt, joined in 2014 as the fifth member of the firm’s partnership.
Despite the personnel shake-ups, Benchmark is shaping up to having a pretty stellar 2018. Two of its portfolio companies, Upwork and Elastic, submitted their S-1 registration statements to the SEC in September. Benchmark is the largest shareholder in both companies.
Huawei P20 is among 4 models from the Chinese phone company caught faking benchmark tests. Here’s everything you need to know. [ Continue reading this over at RedmondPie.com ]
In an ecosystem enthralled with private capital and delayed public debuts, Bill Gurley has been something of a maverick. The former dot-com equity analyst and long-time partner at Benchmark has pushed hard for companies to go public and “grow up,” including at his portfolio company Uber, where he was formerly a board member. Earlier this […]
In an ecosystem enthralled with private capital and delayed public debuts, Bill Gurley has been something of a maverick. The former dot-com equity analyst and long-time partner at Benchmark has pushed hard for companies to go public and “grow up,” including at his portfolio company Uber, where he was formerly a board member.
Earlier this year, he noted that “it’s cool to go public again,” and now we are starting to see the fruits of Benchmark’s labors. Over the past 24 hours, two companies – Elastic and Upwork – have submitted their S-1 registration statements to the SEC, and Benchmark is the largest shareholder in both. That follows last year’s IPO for Stitch Fix, where Gurley was the lead investor.
The story of these two public aspirants are certainly divergent. Upwork is the rebranded merger of two companies, Elance and oDesk, which merged in 2013. Benchmark got involved through oDesk, leading a Series B round of investment in the company in 2006, with founding partner Kevin Harvey joining the board. Considering oDesk was founded in 2003, and Elance in 1999, it has certainly been a circuitous route to the public markets for the company.
Elastic, on the other hand, is a relatively rare case of a company going public quite early in its evolution. The startup was founded just a few years ago in 2012 according to Crunchbase, and Benchmark’s Peter Fenton led a $10m series A into the company that same year. Only six years later, the company is heading to the public markets, with a projected unicorn valuation.
While Upwork has certainly been a journey, it’s Elastic that best exemplifies the startup trajectory that I think Gurley has been advocating for the past few years. Given its rapid revenue growth and key ownership of the search engine market, it is doubtful the company would have struggled to raise additional capital from the private markets. Indeed, six years from founding to IPO is more reminiscent of the 1990s, when the IPO was a key early milestone in the development of a startup since private investment was just not available.
The other interesting dynamic here is around capital efficiency. Elastic raised just $162 million in venture capital according to Crunchbase, a surprisingly low number considering its revenues, growth, and valuation. Enterprise startups have been raising more capital over time as sales and marketing costs have soared and the standards required to publicly debut have become more exacting. That capital efficiency is mirrored on the consumer side by Stitch Fix, which had raised just $42 million in venture capital before its IPO.
These are early data points, but it is clear that Gurley’s and Benchmark’s words around capital efficiency and public markets are influencing their advice to their startup boards and leading to very different actions from these founders. It’s a contrast to companies like Palantir and SpaceX, which have seemed to have committed to staying private for as long as possible.
Benchmark is not the only company that has had some good S-1 news this week. The lead investor in the other two prominent tech IPOs so far this season — Eventbrite and SurveyMonkey — is Tiger Global, the quiet but prolific crossover hedge fund. The fund owns 21.3% of Eventbrite and 29.3% of SurveyMonkey.
The rise of these crossover funds is driving renewed interest in early public liquidity. Unlike traditional venture firms, which typically have a decade investment horizon (plus frequent multi-year extensions), these hedge funds face greater pressure to get returns on a compressed timeline.
That’s indicative here with Tiger Global. It’s investments in Eventbrite and SurveyMonkey took place in 2013, so it is just roughly five years from investment to IPO. Certainly, the hedge fund targets growth-stage opportunities which have shorter liquidity times in general, yet, the speed of liquidity is still notable even for growth investors.
For an ecosystem that has in many ways avoided the public markets, these changing norms will not just increase the pressure to go public, but may also present challenges for boards where discordant voices may be simultaneously pushing the exec team to stay private or go public. It’s a dynamic that founders are going to have to increasingly think through as they select investors through each of their venture rounds, in order to ensure that every investor is on the same page regarding the timeline for the public markets.
Elastic, the provider of subscription-based data search software used by Dell, Netflix, The New York Times and others, has unveiled its IPO filing after confidentially submitting paperwork to the SEC in June. The company will be the latest in a line of enterprise SaaS businesses to hit the public markets in 2018. Headquartered in Mountain View, […]
Elastic, the provider of subscription-based data search software used by Dell, Netflix, The New York Times and others, has unveiled its IPO filing after confidentially submitting paperwork to the SEC in June. The company will be the latest in a line of enterprise SaaS businesses to hit the public markets in 2018.
Headquartered in Mountain View, Elastic plans to raise $100 million in its NYSE listing, though that’s likely a placeholder amount. The timing of the filing suggests the company will transition to the public markets this fall; we’ve reached out to the company for more details.
Elastic will trade under the symbol ESTC.
The business is known for its core product, an open source search tool called ElasticSearch. It also offers a range of analytics and visualization tools meant to help businesses organize large datasets, competing directly with companies like Splunk and even Amazon — a name it mentions 14 times in the filing.
“Amazon offers some of our open source features as part of its Amazon Web Services offering. As such, Amazon competes with us for potential customers, and while Amazon cannot provide our proprietary software, the pricing of Amazon’s offerings may limit our ability to adjust,” the company wrote in the filing, which also lists Endeca, FAST, Autonomy and several others as key competitors.
This is our first look at the Elastic’s financials. The company brought in $159.9 million in revenue in the 12 months ended July 30, 2018, up roughly 100% from $88.1 million the year prior. Losses are growing at about the same rate. Elastic reported a net loss of $18.5 million in the second quarter of 2018. That’s an increase from $9.9 million in the same period in 2017.
Founded in 2012, the company has raised about $100 million in venture capital funding, garnering a $700 million the last time it raised VC, which was all the way back in 2014. Its investors include Benchmark, NEA and Future Fund, which each retain a 17.8%, 10.2% and 8.2% pre-IPO stake, respectively.
A flurry of business software companies have opted to go public this year. Domo, a business analytics company based in Utah, went public in June raising $193 million in the process. On top of that, subscription biller Zuora had a positive debut in April in what was a “clear sign post on the road to SaaS maturation,” according to TechCrunch’s Ron Miller. DocuSign and Smartsheet are also recent examples of both high-profile and successful SaaS IPOs.
A group of computer vision researchers from ETH Zurich want to do their bit to enhance AI development on smartphones. To wit: They’ve created a benchmark system for assessing the performance of several major neural network architectures used for common AI tasks. They’re hoping it will be useful to other AI researchers but also to […]
A group of computer vision researchers from ETH Zurich want to do their bit to enhance AI development on smartphones. To wit: They’ve created a benchmark system for assessing the performance of several major neural network architectures used for common AI tasks.
They’re hoping it will be useful to other AI researchers but also to chipmakers (by helping them get competitive insights); Android developers (to see how fast their AI models will run on different devices); and, well, to phone nerds — such as by showing whether or not a particular device contains the necessary drivers for AI accelerators. (And, therefore, whether or not they should believe a company’s marketing messages.)
The app, called AI Benchmark, is available for download on Google Play and can run on any device with Android 4.1 or higher — generating a score the researchers describe as a “final verdict” of the device’s AI performance.
AI tasks being assessed by their benchmark system include image classification, face recognition, image deblurring, image super-resolution, photo enhancement or segmentation.
They are even testing some algorithms used in autonomous driving systems, though there’s not really any practical purpose for doing that at this point. Not yet anyway. (Looking down the road, the researchers say it’s not clear what hardware platform will be used for autonomous driving — and they suggest it’s “quite possible” mobile processors will, in future, become fast enough to be used for this task. So they’re at least prepped for that possibility.)
The app also includes visualizations of the algorithms’ output to help users assess the results and get a feel for the current state-of-the-art in various AI fields.
The researchers hope their score will become a universally accepted metric — similar to DxOMark that is used for evaluating camera performance — and all algorithms included in the benchmark are open source. The current ranking of different smartphones and mobile processors is available on the project’s webpage.
The benchmark system and app was around three months in development, says AI researcher and developer Andrey Ignatov.
He explains that the score being displayed reflects two main aspects: The SoC’s speed and available RAM.
“Let’s consider two devices: one with a score of 6000 and one with a score of 200. If some AI algorithm will run on the first device for 5 seconds, then this means that on the second device this will take about 30 times longer, i.e. almost 2.5 minutes. And if we are thinking about applications like face recognition this is not just about the speed, but about the applicability of the approach: Nobody will wait 10 seconds till their phone will be trying to recognize them.
“The same is about memory: The larger is the network/input image — the more RAM is needed to process it. If the phone has small amount of RAM that is e.g. only enough to enhance 0.3MP photo, then this enhancement will be clearly useless, but if it can do the same job for Full HD images — this opens up much wider possibilities. So, basically the higher score — the more complex algorithms can be used / larger images can be processed / it will take less time to do this.”
Discussing the idea for the benchmark, Ignatov says the lab is “tightly bound” to both research and industry — so “at some point we became curious about what are the limitations of running the recent AI algorithms on smartphones”.
“Since there was no information about this (currently, all AI algorithms are running remotely on the servers, not on your device, except for some built-in apps integrated in phone’s firmware), we decided to develop our own tool that will clearly show the performance and capabilities of each device,” he adds.
“We can say that we are quite satisfied with the obtained results — despite all current problems, the industry is clearly moving towards using AI on smartphones, and we also hope that our efforts will help to accelerate this movement and give some useful information for other members participating in this development.”
After building the benchmarking system and collating scores on a bunch of Android devices, Ignatov sums up the current situation of AI on smartphones as “both interesting and absurd”.
For example, the team found that devices running Qualcomm chips weren’t the clear winners they’d imagined — i.e. based on the company’s promotional materials about Snapdragon’s 845 AI capabilities and 8x performance acceleration.
“It turned out that this acceleration is available only for ‘quantized’ networks that currently cannot be deployed on the phones, thus for ‘normal’ networks you won’t get any acceleration at all,” he says. “The saddest thing is that actually they can theoretically provide acceleration for the latter networks too, but they just haven’t implemented the appropriated drivers yet, and the only possible way to get this acceleration now is to use Snapdragon’s proprietary SDK available for their own processors only. As a result — if you are developing an app that is using AI, you won’t get any acceleration on Snapdragon’s SoCs, unless you are developing it for their processors only.”
Whereas the researchers found that Huawei’s Kirin’s 970 CPU — which is technically even slower than Snapdragon 636 — offered a surprisingly strong performance.
“Their integrated NPU gives almost 10x acceleration for Neural Networks, and thus even the most powerful phone CPUs and GPUs can’t compete with it,” says Ignatov. “Additionally, Huawei P20/P20 Pro are the only smartphones on the market running Android 8.1 that are currently providing AI acceleration, all other phones will get this support only in Android 9 or later.”
It’s not all great news for Huawei phone owners, though, as Ignatov says the NPU doesn’t provide acceleration for ‘quantized’ networks (though he notes the company has promised to add this support by the end of this year); and also it uses its own RAM — which is “quite limited” in size, and therefore you “can’t process large images with it”…
“We would say that if they solve these two issues — most likely nobody will be able to compete with them within the following year(s),” he suggests, though he also emphasizes that this assessment only refers to the one SoC, noting that Huawei’s processors don’t have the NPU module.
For Samsung processors, the researchers flag up that all the company’s devices are still running Android 8.0 but AI acceleration is only available starting from Android 8.1 and above. Natch.
They also found CPU performance could “vary quite significantly” — up to 50% on the same Samsung device — because of throttling and power optimization logic. Which would then have a knock on impact on AI performance.
For Mediatek, the researchers found the chipmaker is providing acceleration for both ‘quantized’ and ‘normal’ networks — which means it can reach the performance of “top CPUs”.
But, on the flip side, Ignatov calls out the company’s slogan — that it’s “Leading the Edge-AI Technology Revolution” — dubbing it “nothing more than their dream”, and adding: “Even the aforementioned Samsung’s latest Exynos CPU can slightly outperform it without using any acceleration at all, not to mention Huawei with its Kirin’s 970 NPU.”
“In summary: Snapdragon — can theoretically provide good results, but are lacking the drivers; Huawei — quite outstanding results now and most probably in the nearest future; Samsung — no acceleration support now (most likely this will change soon since they are now developing their own AI Chip), but powerful CPUs; Mediatek — good results for mid-range devices, but definitely no breakthrough.”
It’s also worth noting that some of the results were obtained on prototype samples, rather than shipped smartphones, so haven’t yet been included in the benchmark table on the team’s website.
“We will wait till the devices with final firmware will come to the market since some changes might still be introduced,” he adds.
For more on the pros and cons of AI-powered smartphone features check out our article from earlier this year.