Tag Archives: startups

Investing in tech startups an act of trust for VC firms

When investing in tech startups, including BI vendors trying to get started, venture capital firms want to see more than just a good idea.

They want to see a real need for a particular product when they consider investing in tech startups, and they want to see founders who have enough management experience that they won’t ruin a company with poor decisions even if what they’re bringing to market could stand out.

There is also a litany of things they don’t want to see when they’re investing in tech startups, warnings that tell investors a particular company is a bad bet.

Vanessa Larco is a partner at New Enterprise Associates, a venture capital firm with over $20 billion in assets under management. From Salesforce and Tableau years ago to Sisu just recently, NEA has a history of investing in tech startups, and betting on BI vendors in particular. Larco, meanwhile, has a background in computer science that includes time as director of product management at Box and leading the speech recognition experience team at Xbox Kinect v1, and she leads some of NEA’s investments in tech startups and participates on deal teams led by colleagues.

Vanessa LarcoVanessa Larco

Larco recently answered a series of questions about investing in tech startups. In Part I of a two-part Q&A, she discussed what she looks for in BI startups and what stood out about Sisu. In Part II, she went into detail about what might prevent an investor from working with a company, and her process for investing in tech startups.

In a given year, how many tech startups — not only BI vendors — might NEA invest in?

Vanessa Larco: It’s anywhere from 15 to 30 new investments per year where we take a board seat — this excludes seed deals.

Meanwhile, when looking at investing in tech startups — those 15 to 30 in a given year — how many pitches do you go through before choosing who to work with?

Larco: For me individually, I invest in one or two companies a year — period. I spend 12 months just finding those one or two companies a year. But I talk to at least one or two companies a day, so I’m seeing between 600 and 1,000 companies a year and I invest in one.

So of those other 599 to 999 companies, what is it about them that eliminates them? What are some obvious warning signs and some more subtle things that stop you from investing in a tech startup?

I can think of hundreds of reasons why you shouldn’t invest, but what you’re actually thinking about is what’s that thing, what’s the spark that makes you suspend disbelief and take that leap of faith.
Vanessa LarcoPartner, NEA

Larco: By default, it’s more about what is that special thing that makes me say, ‘Yes.’ When you’re investing in a company in their early startup phase, there are a billion reasons why you shouldn’t invest. I can give you a thousand red flags — the capital-to-revenue ratio doesn’t make sense, the team isn’t experienced in the space, it’s too early for us because they’re pre-product, or it’s too late for us because they’re pre-IPO, the work that they’re going after isn’t big enough, the economics don’t really make sense, and I don’t understand how they’re going to make sense in the future. I can think of hundreds of reasons why you shouldn’t invest, but what you’re actually thinking about is what’s that thing, what’s the spark that makes you suspend disbelief and take that leap of faith, because they’re all leaps of faith.

So what gives you that faith when investing in tech startups?

Larco: On every deal, at least a dozen people are like, ‘That’s the dumbest stuff that I’ve ever seen; how did that person ever think that was a good idea?’ You have way more naysayers than you have people who think something is brilliant. That’s just the nature of investing in startups.

You’re looking for that spark when something just clicks for you about the founding team, whether it’s that they’re incredibly accomplished, or have some unique insights, or there’s something incredibly special that even if something doesn’t make sense you feel like the team will figure it out and you just really want to work with them. There’s enough stuff there that’s interesting that you believe they’ll make something work and their initial hypothesis is something I can get behind. Or it’s, ‘Holy cow, I’ve never seen such an innovative product. It meets a need that no one is paying attention to, and it leads to their vision of how they’ll become an independent company… that expand its vision.’ Or it can be that you don’t really get it, but holy smokes, look at the customers they have attracted in a short amount of time — these are hard customers and we know they don’t just buy anything, so we know something is there, and if these people see it a bunch of other people will see it and they’ll be successful.

And what’s the process – how does the relationship start and progress to the point where NEA commits capital?

Larco: It’s different for everybody. Some people are super data driven, some people are very relationship driven. I’m personally a hybrid of being space driven and relationship driven. There are some spaces I really like, data being one of them, HR tech being another. And then I want to get to know the people and find out if they’re people I’ll click with, so then we’ll just spend time together over months, and then when they’re ready I’m just like, ‘I’m here.’ We’ve done all the work, I know I want to invest. And from there you talk to your partnership and do a financial analysis and a returns analysis, and do the actual quantitative work. That’s the easier part. The harder part is to get the conviction to take a leap of faith. For me that’s about the relationship, and I really believe in the founders — I see the need.

How long might it take from the point when you first meet with someone to the point when you close the deal?

Larco: For me it’s longer than most. I like to get to know someone because ideally we’re going to spend the next 10 years of our lives working together, through the ups and the downs, so I want to get to know the founders a year before they actually want to take funding from us. And once they say they’re ready to go, it can take us two to four weeks to make the investment as a partnership.

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Differentiation key for BI startups when attracting investors

BI startups, like all companies when they’re getting started, need money to get off the ground.

BI startups need to show that they have a good idea, and are not simply repackaging analytics software platforms already on the market. They need to show that they can build a strong product, and that their founders have the expertise to build and sustain something commercially viable.

And with that, they need to attract investors to fund the company in the years it takes between the time an idea forms and a company becomes financially solvent.

Vanessa Larco is a partner at New Enterprise Associates, a venture capital firm with over $20 billion assets under management. NEA was an early investor in companies such as Tableau and Salesforce when they were tech startups, and, among many other types of companies, continues to invest in BI startups. Recently, NEA was part of an investment round in Sisu, a startup BI vendor founded in 2018 and based in San Francisco.

Vanessa LarcoVanessa Larco

Larco, meanwhile, has an extensive background in computer science, and before joining NEA was director of product management at Box. Prior to that, she worked in the gaming industry, leading the speech recognition experience team at Xbox Kinnect v1. She leads deals investing in tech companies, including BI startups, and participates in others led by colleagues.

Larco recently took time to answer questions about investing in BI startups.

In Part I of a two-part Q&A, she discusses what she looks for in a BI startup and what she loved about Sisu. In Part II, Larco talks about the process of investing in BI startups, including the warning signs that arise that may keep her from investing.

When you’re considering investing in BI startups, what are some of the characteristics you want to see in a vendor that tell you it might make a good investment?

Vanessa Larco: I think every partner has their own journey when trying to figure out where to invest. For me, I draw a lot on my experience having been a product manager. When I think about what the challenges were that I had or that my team had in building, launching, supporting, maintaining products and then when you see a solution — whether it’s in data or any other vertical — that makes sense and you can say, ‘Wow, if this had existed when I was doing things it would have made my life easier, my team’s life easier,’ it’s something that resonates right off the bat.

I think every partner has their own journey when trying to figure out where to invest. For me, I draw a lot on my experience having been a product manager.
Vanessa LarcoPartner, NEA

You then validate it against actual teams that are still building things and ask them if this would be helpful, and that validates the real need for it.

In the case of Sisu, what stood out about them and led NEA to decide it was a company worth betting on?

Larco: Every process, as much as we like it to be standardized, turns out to be its own unique snowflake, and in the case of Sisu, Pete Sonsini led the deal team and I joined the deal team, meaning I helped him evaluate the opportunity and spent time with the team. I am super excited about Sisu. I ran it by some of my portfolio companies, particularly the ones who [complain that] board meetings take forever because they show a bunch of data and people ask, ‘Well why did this happen, why did that happen?’ And to get those answers it takes at least week. So when I saw the Sisu value proposition I wondered if this will solve that problem.

Even back when I led a product team in the past and we would present to CEOs, we’d show numbers going up and down and they’d ask, ‘Well, why did that happen?’ We’d have to get back to them. It’s just super painful when you know they’re going to ask you why, and that is what takes forever. Sometimes you spend all that time trying to figure out why, and then nothing comes of it, so when I saw the Sisu value proposition I thought that if this actually works it could be game changing.

What happened after you saw Sisu’s value proposition?

Larco: I took it to a good friend at a portfolio company to kick the tires, and they were like, ‘Yes. Yes, this awesome. Thank you so much.’ They said their data person would be so happy they wouldn’t be bogged down answering some very simple questions and doing the manual work to answer why, so from that perspective it was super exciting.

Once NEA invests in BI startups, how much influence does it want going forward — does it seek a spot on the board of directors, leave the company alone or something in between?

Larco: Each case in venture is different. It’s not a high-volume type of industry — we’re not doing hundreds of deals a year — so each deal is very unique and each financing round is unique. But in general, the earlier in the company’s lifecycle you invest in, the founders want you on their board because they want the attention and support, the advice, the feedback, the connection. VCs, in most cases, have been on many boards and seen a lot of stories play out, and you have a lot of connections to potential customers, and so to be able to understand what a company’s needs are as they change is really valuable. Most of the time, both parties want a seat on the board.

But if it’s super, super early and someone else leads the financing round and you’re just participating, someone else takes the board seat. Or if it’s the late stages then the board is already pretty filled out and it has less unknowns than in the early formation years, in those cases you may not take a seat on the board. If an investor is acquiring a significant amount of equity and you’re between 15 and 30 percent, they will typically take a board seat. Anything less than that, it may not make a ton of sense to take a board seat — there’s a limit to how many board seats we can take.

Besides Sisu, who are some startups in the BI/analytics space NEA has recently invested in?

Larco: My colleague Julia Schottenstein led the investment in Metabase, which is in the data space in the open-source project world. I was on the deal team and attended the board meetings for a company called OmniSci. The real value proposition there is they do some really cool geospatial [analysis], and it’s lightning fast. If you need data and need to visualize it across any type of map, I haven’t seen anything like it. From my gaming and advertising days that would have been a massive help. It’s a category that historically if you were investors in Tableau and other data companies that have done really well — it’s a category NEA has performed really well in in the past. It’s a massive category for IT spends, so it’s an area we actively invest in year over year.

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AI vendors to watch in 2020 and beyond

There are thousands of AI startups around the world. Many aim to do similar things — create chatbots, develop hardware to better power AI models or sell platforms to automatically transcribe business meetings and phone calls.

These AI vendors, or AI-powered product vendors, have raised billions over the last decade, and will likely raise even more in the coming years. Among the thousands of startups, a few shine a little brighter than others.

To help enterprises keep an eye on some of the most promising AI startups, here is a list of those founded within the past five years. The startups listed are all independent companies, or not a subsidiary of a larger technology vendor. The chosen startups also cater to enterprises rather than consumers, and focus on explainable AI, hardware, transcription and text extraction, or virtual agents.

Explainable AI vendors and AI ethics

As the need for more explainable AI models has skyrocketed over the last couple of years and the debate over ethical AI has reached government levels, the number of vendors developing and selling products to help developers and business users understand AI models has increased dramatically. Two to keep an eye on are DarwinAI and Diveplane.

DarwinAI uses traditional machine learning to probe and understand deep learning neural networks to optimize them to run faster.

Founded in 2017 and based in Waterloo, Ontario, the startup creates mathematical models of the networks, and then uses AI to create a model that infers faster, while claiming to maintain the same general levels of accuracy. While the goal is to optimize the deep learning models, a 2018 update introduced an “explainability toolkit” that offers optimization recommendations for specific tasks. The platform then provides detailed breakdowns on how each task works, and how exactly the optimization will improve them.

Founded in 2017, Diveplane claims to create explainable AI models based on historical data observations. The startup, headquartered in Raleigh, N.C., puts its outputs through a conviction metric that ranks how likely new or changed data fits into the model. A low ranking indicates a potential anomaly. A ranking that’s too low indicates that the system is highly surprised, and that the data likely doesn’t belong in a model’s data set.

AI startups, AI vendors
There are thousands of AI startups in the world today, and it looks like there will be many more over the coming years.

In addition to the explainability product, Diveplane also sells a product that creates an anonymized digital twin of a data set. It doesn’t necessarily help with explainability, but it does help with issues around data privacy.

According to Diveplane CEO Mike Capps, Diveplane Geminai takes in data, understands it and then generates new data from it without carrying over personal data. In healthcare, for example, the product can input patient data and scrub personal information like names and locations, while keeping the patterns in the data. The outputs can then be fed into machine learning algorithms.

“It keeps the data anonymous,” Capps said.

AI hardware

To help power increasingly complex AI models, more advanced hardware — or at least hardware designed specifically for AI workloads — is needed. Major companies, including Intel and Nvidia, have quickly stepped up to the challenge, but so, too, have numerous startups. Many are doing great work, but one stands out.

Cerebras Systems, a 2016 startup based in Los Altos, Calif., made headlines around the world in 2019 when it created what it dubbed the world’s largest computer chip designed for AI workloads. The chip, about the size of a dinner plate, has some 400,000 cores and 1.2 trillion transistors. By comparison, the largest GPU has around 21.1 billion transistors.

The company has shipped a limited number of chips so far, but with a valuation expected to be well over $1 billion, Cerebras looks to be going places.

Automatic transcription companies

It’s predicted that more businesses will use natural language processing (NLP) technology in 2020 and that more BI and AI vendors will integrate natural language search functions into their platforms in the coming years.

Numerous startups sell transcription and text capturing platforms, as well as many established companies. It’s hard to judge them, as their platforms and services are generally comparable; however, two companies stand out.

Fireflies.ai sells a transcription platform that syncs with users’ calendars to automatically join and transcribe phone meetings. According to CEO and co-founder Krish Ramineni, the platform can transcribe calls with over 90% accuracy levels after weeks of training.

The startup, founded in 2016, presents transcripts within a searchable and editable platform. The transcription is automatically broken into paragraphs and includes punctuation. Fireflies.ai also automatically extracts and bullets information it deems essential. This feature does “a fairly good job,” one client said earlier this year.

The startup plans to expand that function to automatically label more types of information, including tasks and questions.

Meanwhile, Trint, founded in late 2014 by former broadcast journalist Jeff Kofman, is an automatic transcription platform designed specifically for newsrooms, although it has clients across several verticals.

The platform can connect directly with live video feeds, such as the streaming of important events or live press releases, and automatically transcribe them in real time. Transcriptions are collaborative, as well as searchable and editable, and included embedded time codes to easily go back to the video.

“It’s a software with an emotional response, because people who transcribe generally hate it,” Kofman said.

Bots and virtual agents

As companies look to cut costs and process client requests faster, the use of chatbots and virtual agents has greatly increased across numerous verticals over the last few years. While there are many startups in this field, a couple stand out.

Boost.ai, a Scandinavian startup founded in 2016, sells an advanced conversational agent that it claims is powered by a neural network. Automatic semantic understanding technology sits on top of the network, enabling the agent to read textual input word by word, and then as a whole sentence, to understand user intent.

Agents are pre-trained on one of several verticals before they are trained on the data of a new client, and the Boost.ai platform is quick to set up and has a low count of false positives, according to co-founder Henry Vaage Iversen. It can generally understand the intent of most questions within a few weeks of training, and will find a close alternative if it can’t understand it completely, he said.

The platform supports 25 languages, and pre-trained modules for a number of verticals, including banking, insurance and transportation industries.

Formed in 2018, EyeLevel.ai doesn’t create virtual agents or bots; instead, it has a platform for conversational AI marketing agents. The San Francisco-based startup has more than 1,500 chatbot publishers on its platform, including independent developers and major companies.

Eyelevel.ai is essentially a marketing platform — it advertises for numerous clients through the bots on in its marketplace. Earlier this year, Eyelevel.ai co-founder Ryan Begley offered an example.

An independent developer on its platform created a bot that quizzes users on their Game of Thrones knowledge. The bot operates on social media platforms, and, besides providing a fun game for users, it also collects marketing data on them and advertises products to them. The data it collects is fed back into the Eyelevel platform, which then uses it to promote through its other bots.

By opening the platform to independent developers, it gives individuals a chance to get their bot to a broader audience while making some extra cash. Eyelevel.ai offers tools to help new bot developers get started, too.

“Really, the key goal of the business is help them make money,” Begley said of the developers.

Startup launches continuing to surge

This list of AI-related startups represents only a small percentage of the startups out there. Many offer unique products and services to their clients, and investors have widely picked up on that.

According to the comprehensive AI Index 2019 report, a nearly 300-page report on AI trends complied by the Human-Centered Artificial Intelligence initiative at Stanford University, global private AI investment in startups reached $37 billion in 2019 as of November.

The report notes that since 2010, which saw $1.3 billion raised, investments in AI startups have increased at an average annual growth rate of over 48%.

The report, which considered only AI startups with more than $400,000 in funding, also found that more than 3,000 AI startups received funding in 2018. That number is on the rise, the report notes.

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3 networking startups rearchitect routing

Startups played a pivotal role in disrupting the business of network switching. Today, they’re on track to do the same to routing.

Software under development by upstarts Arrcus, DriveNets and Volta Networks represents a new routing architecture, industry analysts agreed. Cloud service providers, SaaS providers, telcos and the largest financial institutions are the most likely candidates for deploying the networking startups’ technology in the data center and at the edge.

The vendors’ software could also be useful for peering among internet service providers and for data center interconnects (DCIs). Colocation companies like Equinix, Digital Realty Trust and Global Switch use DCIs to connect their facilities to customer data centers.

Market research firm IDC recently named the three companies 2019 innovators for their work in decoupling routing software from its underlying hardware. Separating management, control and data planes from the device make it possible to run the software on commodity products powered by merchant silicon from companies like Broadcom and Intel.

Severing software from hardware and running it on commodity gear — a process called disaggregation — reduces operational expenses. Companies can lower labor costs by managing multiple routers at once, instead of each one separately. The architecture also adds flexibility by making it possible to distribute and manage physical and virtual routers across data centers or at the network edge.

“Effectively, you’ve got a Lego that you can mix and match based on your requirements,” said Brad Casemore, an analyst at IDC. “It leads to a standardized environment where you can run the same software across all of it.”

Disaggregation from switching to routing

Disaggregation in network switching, a nearly 10-year trend, forced incumbents Cisco and Juniper Networks to acquire startups that had developed software capable of providing centralized network management. The transition led to an overhaul in the way the companies’ products manage switching fabrics.

New technologies developed by Arrcus, DriveNets and Volta show that there’s “an evolution in disaggregation to the routing layer,” Casemore said. Each of the vendors is initially targeting their products at communication and cloud service providers.

“It’s really compelling technology,” Casemore said.

Here is a brief description of each of the networking startups, including the key differentiators and market challenges listed in the 2019 IDC Innovators report on disaggregated routing platforms:

— Arrcus built a network operating system, called ArcOS, with extensive routing protocol support. This year, for example, the vendor incorporated the Link State Vector Routing (LSVR) protocol into ArcOS for organizations running hyperscale data centers and large cloud environments.

Arrcus has built its data plane adaptation layer to separate ArcOS from the underlying hardware. ArcOS is also the first independent NOS to support devices powered by Broadcom’s Trident 3, Tomahawk 3, Jericho+ or Jericho2 network silicon. The Jericho2 platform is for 100 Gb and 400 Gb routing.

Despite its innovative technology, Arrcus still has to prove it can deliver significant cost savings and ROI. The company also has to show a simple process for buying and supporting the underlying hardware.

Arrcus, based in San Jose, Calif., has more than 60 employees and has raised $45 million in funding.

— DriveNets developed a container-based router control plane for merchant silicon-based white boxes. Hardware manufacturers bundle the software with their products and sell it under a license that is free from capacity constraints.

The architecture provides carriers with a routing model that uses a cluster of low-cost white boxes capable of scaling to any size. DriveNets based the model on the one used in hyperscale data centers.

DriveNets’ hurdles include convincing communication service providers to change how they procure, deploy and manage router infrastructure. “The adoption of the DriveNets architecture might be slowed by the need for communication service providers to redesign internal processes and management systems,” IDC said.

DriveNets, based in Ra’anana, Israel, has more than 200 employees and has raised $117 million in funding.

— Volta built a cloud-native, cloud-hosted control plane that can spin up and manage as many as 255 instances of virtual routers on a single, on-premises commodity switch. The use of switching gear provides a “significant cost advantage,” while also making Volta technology useful for provider edge routing. Volta’s technology could be helpful to carriers overhauling cell sites to support next-generation 5G wireless technology.

Volta’s technology and its subscription model that covers support, maintenance and hardware warranty could provide significantly lower capital and operational expenses. However, as a startup, in a competitive industry, it faces a “significant challenge” in winning deals over better-known competitors with more money.

Volta, based in Cambridge, Mass., has 51 employees and has raised $3.3 million in funding.

Moving toward software-based routing

Companies with hyperscale data centers, like Amazon, Facebook, Google and Microsoft, have favored disaggregated networking software on standardized hardware for years. Today, major service providers and financial institutions use the same white box switches. Users include AT&T, Comcast, Verizon, JPMorgan Chase and Fidelity Investments.

As a result, in 2018, the share of the global Ethernet data center switching market held by Cisco and Juniper fell, while that of bare-metal switching manufacturers increased, according to IDC.

Analysts believe the same dynamics will likely play out in routing. “People are now noticing and realizing that white box approaches can work. They’re mature,” said Roy Chua, a principal analyst at AvidThink.

Potentially, these companies become M&A targets if they have traction in some high-value accounts.
Brad CasemoreAnalyst, IDC

Analysts expect carriers to seriously consider white box routers as they build out their network edge to deliver 5G services.

“They’re actually trying to move away from [physical] routers and toward software-based routing,” said Lee Doyle, principal analyst at Doyle Research. “None of this has been hugely deployed yet. But I think we’re going to see significant deployments in 2020 and 2021 in the 5G market.”

Routing sales for Cisco and Juniper have been declining. However, the decrease is primarily due to carriers cutting back on spending after they found they couldn’t wring any more revenue from consumers, Casemore said.

But with 5G deployments on the horizon, incumbents like Cisco and Juniper are probably watching networking startups closely to see which ones are winning deals for routing technology.

“Potentially, these companies become M&A targets if they have traction in some high-value accounts,” Casemore said.

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Microsoft for Startups and NVIDIA Inception join forces to accelerate AI startups | Blog

Startups, especially in the AI space, have a multitude of unique, daily challenges, from selecting the right technology systems to improving their algorithms to building a robust sales pipeline.

That’s why today at Slush we announced that we are teaming with NVIDIA to give cutting-edge startups developing AI technologies fewer things to worry about by providing them preferred access to the Microsoft for Startups and NVIDIA Inception programs. Now, eligible startups active in our respective programs can receive preferred access and reciprocal benefits, including free or discounted technology, go-to-market support and access to technical experts.

NVIDIA Logo

Eligible NVIDIA Inception AI startups can access Microsoft for Startups’ premium offer, providing:

· Free access to Microsoft technologies, including up to $120k of free Azure cloud.

· Dedicated go-to-market resources to help startups sell alongside our global sales teams and partner channel.

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Eligible Microsoft for Startups AI members can access NVIDIA Inception benefits including:

· Free credits for NVIDIA Deep Learning Institute online courses, such as the Fundamentals of Deep Learning for Computer Vision, Accelerating Data Science, and Image Classification.

· Access to go-to-market NVIDIA Inception Connect events and marketing support.

· Unlimited access to DevTalk—a forum built for technical inquiries and community engagement.

· Guidance on which GPU applications and hardware are best suited for your needs.

· Discounts on NVIDIA DGX systems, NVIDIA GPU accelerators, NVIDIA Quadro pro graphics, and NVIDIA TITAN GPUs for deep learning.

This partnership will allow us to accelerate AI startups with NVIDIA’s deep technical expertise and market-leading GPU technology on Microsoft Azure, combined with both companies’ ability to connect startups with customers.

Launched in February 2018, Microsoft for Startups is a comprehensive global program designed to support startups as they build and scale their companies. Since we launched, companies active with Microsoft for Startups are on track to drive $1B in pipeline opportunity by the end of 2020. To find out more about the Microsoft for Startups and to apply for the program, click here.

NVIDIA Inception is a virtual accelerator program that supports startups harnessing GPUs for AI and data science applications during critical stages of product development, prototyping and deployment. Since its launch in 2016, the program has expanded to over 5,000 companies. To find out more about NVIDIA Inception, click here.

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Announcing Microsoft for Startups Autonomous Driving | Blog

Today, at the Frankfurt Motorshow (IAA) we announced Microsoft for Startups: Autonomous Driving (MfS – AD), an exclusive program which aims to accelerate the growth of startups working on autonomous driving (AD).

Increasingly startups have been playing a crucial role in bringing autonomous driving technology to the world. From building full-stack autonomy solutions for OEMs to opening up new business opportunities in areas like delivery, ride-sharing and long haul transit, startups have been at the forefront of technological advancement in this space. Startups also play a critical role in delivering important AD enablement technologies and solutions like simulation, data management, labeling and more.

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Cultivating a state-of-the-art, global partner ecosystem has been a focal point of our autonomous driving strategy and our startup partners have played an important part in helping our customers deliver the promise of autonomous driving at scale. For instance, Cognata is using their simulation technology to help customers like Audi AG speed up their AV development. We announced partnerships with Ascent Robotics, a Tokyo-based startup making innovative use of reinforcement learning and neuroscience to deliver complex L4 driving scenarios and Linker Networks, a startup based in Taiwan taking annotation efficiency and reliability to a whole new level through their AI-based auto-labeling technology helping the industry build smarter, safer vehicles. We are also closely working with startups like Udelv, who are paving the path for autonomous driving to meet the growing demands of the retail delivery space. This week at IAA, Applied Intuition announced the release of their Applied Development Platform optimized on Microsoft Azure. 

The MfS-AD program is another example of our continuing commitment to the AD startup community. We want to empower pioneering startups who are defining what is next in autonomous driving by helping them scale up and scale out through business and technical enablement. As part of the program, all selected startups will receive the premium offer from our Microsoft for Startups program including access to up to $120,000 USD of free Azure cloud.

For technical enablement, startups will receive benefits like:

  • Access to our top engineers and program managers working on autonomous driving infrastructure technology and solutions.
  • 1:1 architectural sessions with Microsoft Cloud Engineers.
  • Early access to autonomous driving capabilities on Azure.
  • Potential co-development opportunities.

For business enablement, startups will receive benefits like:

  • Opportunities to expand your network by becoming a part of Microsoft’s autonomous driving ecosystem. Many of our partners have found their next big customer or partner at one of our automotive networking receptions and other events.
  • Joint customer opportunities.
  • Marketing and amplification support.
  • Preferred showcase opportunities at industry events and conferences.
  • Visibility to M12 (formerly Microsoft Ventures) for potential investment opportunities.

For details on how to apply, nomination requirements, selection criteria and more, visit https://aka.ms/ADstartup

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Empowering Diverse Startups: Microsoft joins forces with Backstage Capital and Black & Brown Founders | Blog

I wanted to share our excitement that Microsoft for Startups will be joining forces with Backstage Capital and Black & Brown Founders to help accelerate opportunities for diverse startups. Over the next 18 months, we will be committing over $6M in sponsorship dollars, cloud technology, and support to empower underrepresented founders identified by these two organizations.

Today, less than 10% of all venture capital deals go to women, people of color, and LGBT founders. As Arlan Hamilton, Founder & Managing Partner of Backstage Capital, said to me when we first met, “Many VCs see this as a pipeline problem. We see it as the biggest opportunity in investment.”

At Microsoft we’re also focused on creating much greater diversity within our startup ecosystem. We fundamentally believe great ideas come from anywhere and have repeatedly found that diversity fuels innovation. We share Arlan’s view of the opportunity in front of us, which is also backed by research showing how diverse founding teams outperform the market average.

I was equally inspired after meeting Aniyia Williams, the originator of Black & Brown Founders. When she described their philosophy in supporting Black and Latinx founders, I knew we wanted to get involved and support their efforts. Their approach is to enable entrepreneurs through workshops, community, and regional conferences focused on the foundations of entrepreneurship, which is profitability, people development, and both business and technical innovation. I also really appreciated the distinction between how they approached the various communities and designed their program to adapt as their members’ needs evolved.

When we launched Microsoft for Startups in February, we shifted our program to an incessant focus on how we can best be of service to the startup community and assist them on their terms and timelines. We paired Microsoft cloud technology access with the technical and business support our startups were requesting (e.g. go-to-market partnership with access to our enterprise customer base through Microsoft’s worldwide channel and salesforce).

As part of these new partnerships with Backstage Capital and Black & Brown Founders, we’ll be offering the following:

  • Premier technology and business partner of Backstage Capital’s new accelerator program. 
  • Sponsoring Black & Brown Founders’ Project NorthStar, a 3-day tech conference in Philadelphia that provides connections, education, and opportunities for current or aspiring entrepreneurs and professionals from the Black and Latinx community.
  • Deliver the benefits of the Microsoft for Startups offer to eligible startup members of these organizations. The program provides startups with up to $120,000 in free Azure credits, enterprise grade technical support and development tools as well as dedicated resources to prepare startup marketing and sales teams to effectively sell their cloud solutions to enterprise organizations in partnership with Microsoft’s global sales organization and partner ecosystem.
  • Provide continuous training and mentorship to help underestimated entrepreneurs tackle issues such as selling to large enterprises, building a learning organization, designing your partner channel, and architecting durable technical solutions.
  • Provide 1:1 office hours for entrepreneurs to meet with Microsoft experts and tailor discussion to their needs across strategy, technology and business topics.

These new partnerships are core to our company’s mission to empower every person and organization on the planet to achieve more and build on several recent investments we’ve made to promote the success of diversity in startups, including our recently announced partnership with The Riveter and the M12 Female Founders Competition.

There is so much potential in these communities and we are honored to work with Backstage Capital and Black & Brown Founders. Together, we will work to change the makeup of startup communities around the world that will fuel the growth of new and diverse innovation.

New Elastifile CEO intensifies startup’s cloud focus

New Elastifile CEO Erwan Menard said he plans to intensify the startup’s focus on scale-out, enterprise-grade file storage for the public cloud, as he tries to fuel the company’s growth phase.

The stronger public cloud emphasis will mean changes to the product strategy that Elastifile initially laid out when emerging from stealth in April 2017. For instance, Elastifile designed its distributed file system to run on flash storage. But, Menard said, Elastifile’s software will be available with spinning HDDs and SSDs in public clouds, although on-premises deployments will continue to require flash.

Prior to joining Elastifile, Menard was president and COO at object storage vendor Scality. He previously held the same positions at DataDirect Networks, a storage vendor that caters to high-performance computing. Menard also served as vice president and general manager of Hewlett-Packard’s communications and media solutions business unit and in various leadership roles at Alcatel-Lucent.

The newly appointed Elastifile CEO recently replaced founder Amir Aharoni, who remains with the startup as chairman. Aharoni was unable to relocate from Israel to the United States, “where we want the growth to be led from,” Menard said as part of this Q&A. Elastifile’s sales and marketing office is located in Santa Clara, Calif., and its research and development arm is in Herzliya, Israel.

What are your primary areas of focus for the next year and beyond?

Erwan Menard: We were born upon the idea that file storage is here to stay, because a number of workloads in enterprises rely on it, and that file storage should be addressed in a software-defined manner designed for flash. That was the initial DNA of the company, from a product point of view.

Elastifile CEO Erwan MenardErwan Menard

Now, if we look at the market, we’re observing a growing demand for enterprise-class file storage in the cloud. If you look at the data that’s going into public clouds, there’s either very cold data for archival or disaster recovery purposes, or there’s hot data in very small quantities for workloads that are compute-centric. But there is a huge piece missing, which is all the data residing on NAS in the data center. Why aren’t those data and associated workloads in the cloud yet? Because there’s no decent enterprise-grade file storage service in public clouds.

At Elastifile, we spent four years developing a modern-age, software-defined file system for flash. And we’re taking that intellectual property and focusing on adding a strong, enterprise-grade file system to Amazon and Google and Azure. It’s two clicks on Google Launcher, which is their marketplace. We automatically provision a scale-out file system. We definitely aim at doing the same thing on the other clouds if customers choose Azure and Amazon. This is going to happen in the next few months.

Elastifile has a flash requirement with on-premises deployments. Is flash a requirement in the public cloud?

Menard: We designed for flash, because silicon is taking over infrastructure. But you can effectively run it on classic disk. In Google terminology, you can run on so-called PDs, [or] persistent disks, which are groups of SSDs at Google Cloud. Or, you can run it on standard PDs, [or] standard persistent disks, which are effectively classic HDDs. We run on both.

The good thing about designing for flash is that we’re able to provide significantly better performance than other solutions out there in the cloud. For example, we are able to provide much better performance than Amazon Elastic File [System] storage. I want to think that’s because we designed for the flash era.

Does the ability to run on HDDs extend to on-premises Elastifile deployments?

Menard: No. The on-prem deployment option is to run on bare-metal SSDs.

What significant features are in the Elastifile 2.7 release?

Menard: We are updating the [Google] Launcher experience. That experience is going to be significantly simpler in the way you install. The people who are touching our products in the data center are typically storage admins. In the cloud, sometimes it’s an application developer who happens to need storage, or someone who is even less technical. And the first impression people have with the product is extremely important in their decision to adopt it or not.

Also part of the package is what we call CloudConnect. It’s a tool that allows you to migrate your data from any NAS in your data center to any cloud. When people are absolutely convinced about the benefits of running stuff in the cloud, they often struggle with moving the data to the cloud. Most of the tools on the market tend to go from one certain type of NAS to one certain type of cloud destination. We’ve done a tool to go from any to any, and that tool is part of the subscription to our product.

Can users buy CloudConnect as a separate product?

Menard: No. Our goal isn’t to become a data-mover company. Our goal is to facilitate adoption of the cloud. The Elastifile software is available as a subscription. And, as part of that, you get CloudConnect.

Can we expect more partnerships, such as Elastifile’s OEM deal with Dell EMC signed last year? Do customers want to pick their own hardware and take a do-it-yourself approach, or do they prefer to buy your storage software bundled with hardware?

Menard: I think people want to buy software only, because that unlocks the value chain and allows them to commoditize the hardware and separate software and hardware from a procurement point of view. I think there’s a market for software only in the data center — do it yourself — that is for sophisticated organizations who decided to continue developing their data center for whatever strategic or regulatory reasons.

That being said, I think the overall trend is effectively slightly different. At the whole market level, the trend is to go to the cloud. The data center is less and less an area where you want to experiment with complicated things. If anything, you want to consume very simple offerings.

So, I think those two trends coexist — sometimes in the same enterprise account. Frankly, our focus is on the cloud, because this is the next frontier. We’re much more involved in conversations around lifting and shifting stuff to the cloud.

Do people want to move everything to the cloud, or do you think the hybrid model will win out?

Menard: I’m not comfortable with the word ‘hybrid,’ because I’m not sure people are clear on what it means. If hybrid means I have a full stack — application, infrastructure — that’s delivering a certain business outcome in the data center, and I want to replicate that in the cloud, that scenario does exist.

We have a customer in common with Google, called eSilicon. They are doing chipset design. They’ve augmented the capacity of their data center on a per-project basis. They don’t size for the peak. They size for a lower load. And they run the peak activities in the cloud. They did it with us because they didn’t need to modify their application at all when running it in the cloud. That’s a bursting scenario. I run peak activities in the cloud and continue running baseline activities in the data center.

Another scenario we see happening is people who are lifting and shifting an entire workload to the cloud. And that creates a period of time where both workloads are in the data center and in the cloud — the target being to run everything in the cloud. If we want to call that hybrid, then hybrid does exist.

Do you think you may have customers that run your software only in the cloud?

Menard: Absolutely. Four years ago, when we were all focusing on the software-defined data center, we were all undersizing the speed at which workloads could move to the cloud.

Is that why you plan to focus less on OEM partnerships and more on getting your software to work better with more clouds?

Menard: Absolutely.

Are customers moving their applications to the public cloud? Or, are they just moving their data and leaving the applications running on premises?

Menard: I think the only case where it makes sense to move the data without the application is when you’re looking at archiving or disaster recovery. The object stores of public clouds do a great job at that. When you talk about hot data, having an application running in the data center and tapping into a data pool in the cloud may look great on a slide, but I don’t think it makes economic sense.

Which vendors do you go up against in competitive scenarios?

Menard: In the cloud right now, the de facto standard — but it’s a fairly low one — is Amazon EFS [Elastic File System]. Another option is, of course, the status quo: using the same vendor you’ve been using for decades in the data center and trying to make that work in the cloud. We’ve seen announcements by the likes of NetApp in that regard. While it’s probably a good defensive play, it’s very hard with products designed many years ago for the data center to truly take advantage of the cloud. It’s going to come with a level of complexity and cost that’s probably not viable in the long run.

Announcing the public preview of Azure Archive Blob Storage and Blob-Level Tiering

From startups to large organizations, our customers in every industry have experienced exponential growth of their data. A significant amount of this data is rarely accessed but must be stored for a long period of time to meet business continuity and compliance requirements. Examples include employee data, medical records, customer information, financial records, backups, etc. Additionally, recent and coming advances in artificial intelligence and data analytics are unlocking value from data that might have previously been discarded. Customers want to keep more of these data sets for a longer period but need a scalable and cost-effective solution to do so.

Last year, we launched Cool Blob Storage to help customers reduce storage costs by tiering their infrequently accessed data to the Cool tier. Today we’re announcing the public preview of Archive Blob Storage designed to help organizations reduce their storage costs even further by storing rarely accessed data in our lowest-priced tier yet. Furthermore, we’re excited to introduce the public preview of Blob-Level Tiering enabling you to optimize storage costs by easily managing the lifecycle of your data across these tiers at the object level.

The CEO of HubStor, a leading enterprise backup and archiving company, stated: “We are jumping for joy to see the amazing design Microsoft successfully implemented. Azure Archive Blob Storage is indeed an excellent example of Microsoft leapfrogging the competition.”

Azure Archive Blob Storage

Azure Archive Blob storage is designed to provide organizations with a low cost means of delivering durable, highly available, secure cloud storage for rarely accessed data with flexible latency requirements (on the order of hours). See Azure Blob Storage: Hot, cool, and archive tiers to learn more.

The Archive tier, in addition to Hot and Cool access tiers, is now available in Blob Storage accounts. Archive Storage characteristics include:

  • Cost-effectiveness: Archive access tier is our lowest priced storage offering. Customers with long-term storage which is rarely accessed can take advantage of this. For more details on regional preview pricing, see Azure Storage Pricing.
  • Seamless Integration: Customers use the same familiar operations on blobs in the Archive tier as on blobs in the Hot and Cool access tiers. This will enable customers to easily integrate the new access tier into their applications.
  • Availability: The Archive access tier will provide the same 99% availability SLA (at General Availability (GA)) offered by the Cool access tier.
  • Durability: All access tiers including Archive are designed to offer the same high durability that you have come to expect from Azure Storage with the same data replication options available today.
  • Security: All data in the Archive access tier is automatically encrypted at rest.

Blob-Level Tiering:  easily optimize storage costs without moving your data

To simplify data lifecycle management, we now allow customers to tier their data at the blob level.  Customers can easily change the access tier of a blob among the Hot, Cool, or Archive tiers as usage patterns change, without having to move data between accounts. Blobs in all three access tiers can co-exist within the same account.

Flexible management

Archive Storage and Blob-level Tiering will be available on all Blob Storage accounts. For customers with large volumes of data in General Purpose accounts, we will allow upgrading your account to get access to Cool, Archive, and Blob-level Tiering at GA.

A user may access the feature using .NET (see Figure 1), Python (preview), or Node.js client libraries or REST APIs initially. Support for the Java client library and portal (see Figure 2) will roll out over the next week. Other SDKs and tools will be supported in the next few months.

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Figure 1: Set blob access tier using .NET client library

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Figure 2: Set blob access tier in portal

Pricing

Pricing for Azure Archive Blob Storage during preview will be reduced. Please refer to the Azure Blobs Storage Pricing page for more details.

How to get started

To enroll in the public preview, you will need to submit a request to register this feature to your subscription. After your request is approved (within 1-2 days), any new LRS Blob Storage account you create in US East 2 will have the Archive access tier enabled, and all new accounts in all public regions will have blob-level tiering enabled. During preview, only LRS accounts will be supported but we plan to extend support to GRS and RA-GRS accounts (new and existing) as well at GA. Blob-level tiering will not be supported for any blob with snapshots. As with most previews, this should not be used for production workloads until the feature reaches GA.

To submit a request, run the following PowerShell or CLI commands.

PowerShell

Register-AzureRmProviderFeature -FeatureName AllowArchive -ProviderNamespace Microsoft.Storage

This will return the following response:

FeatureName         ProviderName      RegistrationState 
-----------         ------------      ----------------- 
AllowArchive        Microsoft.Storage   Pending 

It may take 1-2 days to receive approval.  To verify successful registration approval, run the following command:

Get-AzureRmProviderFeature -FeatureName AllowArchive -ProviderNamespace  Microsoft.Storage

If the feature was approved and properly registered, you should receive the following output:

FeatureName         ProviderName      RegistrationState 
-----------         ------------      ----------------- 
AllowArchive        Microsoft.Storage   Registered  

CLI 2.0

az feature register –-namespace Microsoft.Storage –-name AllowArchive

This will return the following response:

{
  "id": "/subscriptions/xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx/providers/Microsoft.Features/providers/Microsoft.Storage/features/AllowArchive",
  "name": "Microsoft.Storage/AllowArchive",
  "properties": {
    "state": "Pending"
  },
  "type": "Microsoft.Features/providers/features"
}

It may take 1-2 days to receive approval.  To verify successful registration approval, run the following command:

-az feature show –-namespace Microsoft.Storage –-name AllowArchive

If the feature was approved and properly registered, you should receive the following output:

{
  "id": "/subscriptions/xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx/providers/Microsoft.Features/providers/Microsoft.Storage/features/AllowArchive",
  "name": "Microsoft.Storage/AllowArchive",
  "properties": {
    "state": "Registered"
  },
  "type": "Microsoft.Features/providers/features"
}

Get it, use it, and tell us about it

We’re confident that Azure Archive Blob Storage will provide another critical element for optimizing your organization’s cloud data storage strategy. As this is a preview, we look forward to hearing your feedback on these features, which you can send by email to us at [email protected]