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Tag Archives: startups

Nvidia’s GTC event will shine a spotlight on 200 AI startups

October 4, 2020   Big Data

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Nvidia’s GPU Technology Conference (GTC) kicks off Monday with a keynote speech by CEO Jensen Huang, who has led the company to a market value of $ 322 billion. The now virtual conference will highlight an ecosystem with millions of developers. Coincidentally, it will run alongside the DevSummit hosted by Arm, which Nvidia has agreed to buy for $ 40 billion.

More than 200 new AI startups will appear at GTC in some form, Jeff Herbst, VP of business development and head of the Inception virtual AI program at Nvidia, said in an interview with VentureBeat.

“We love startups,” said Herbst. “We’re like a mouthpiece and a helper for the companies. We help them learn from the collective knowledge of the industry. Our ecosystem is growing like a weed. We have passed 2 million developers on our platform.”

If Nvidia gets approval to buy Arm, that developer count will cross 15 million. Nvidia, which evangelizes developers to use its graphics chip and AI technology, has come a long way.

Nvidia’s GPU Technology Conference (GTC) started in 2009 in San Jose, California. I went to the first event and remember it was nowhere close to filling the sprawling San Jose Convention Center. Over the years, I have attended many GTC events, where Herbst drew attention to startups using Nvidia’s tech.

Herbst’s division invests in startups that use Nvidia’s technology, but Nvidia now tends to give away its technology to companies that are getting started with AI or graphics technology. Over the years, Herbst has formed alliances with venture capitalists to help them narrow their focus on the best startups, with Nvidia often investing alongside the VCs.

For many years, Herbst ran a contest for the best GPU (graphics processing unit) startups, but the field became so crowded it was hard to narrow the pack down to a single winner, Herbst said.

“We have over 6,000 companies in the Inception program, and it’s still growing,” Herbst said. “These developers train on our platform for years. It’s becoming more popular, like a flywheel. We have found other ways to help them than to invest money into them.”

Above: Nvidia’s GTC event in 2019.

Image Credit: Nvidia

GTC has more than 30,000 mostly paid registrants, and it promises to be one of the largest, most complex virtual tech conferences to date, with five days of programming, nearly 24 hours a day, across seven time zones.

More than 1,000 live and prerecorded sessions will be available in 40 topic areas. They will be delivered in one of five languages: English, Mandarin, Japanese, Korean, and Hebrew.

Huang’s keynote will take place from 6 a.m. to 8 a.m. Pacific time on Monday. His talk will cover advances in chips, AI, enterprise and edge computing, robotics, and remote collaboration. He will speak again when he appears with Arm CEO Simon Segars at the Arm DevSummit event Tuesday morning at 8:20 am. Pacific.

Participating organizations include Amazon Web Services, American Express, Audi, BMW, Caltech, Carnegie Mellon University, Facebook AI Research, Google Cloud, IBM, Johns Hopkins University, Lockheed Martin, Microsoft, MIT, Oak Ridge National Labs, OpenAI, Oracle, Sony, VMware, and Volvo.

On Tuesday at 12 p.m. Pacific, Huang will join Herbst at the Inception virtual startup incubator to talk about AI startups. Nvidia uses its Inception program to provide startups with software and hardware without taking an equity stake.

“We’re going to talk about the combination of Nvidia and Mellanox and how we’re approaching things at a system level for compute and storage,” Herbst said. “If AI is about programming using data, the system approach is about facilitating the movement, cleaning, and storage of data. Jensen’s view is that the datacenter is the new compute unit.”

AI startups

Among the companies being highlighted during the AI startup showcase sessions are:

  • United States: BroadBridge Networks, Clarifai, Datalogue, Drishti, and Whiteboard Coordinator. Live Tuesday, October 6 at 10 a.m. Pacific.
  • United States: Algorithmia, Paperspace, Runway, SafelyYou, and Snorkel AI. Live Tuesday, October 6 at 11 a.m. Pacific.
  • Europe and the Middle East: AnyVision, Cybertonica, Exasol AG, Instadeep, and Owkin. Live Tuesday, October 6 at 11 p.m. CEST (2 p.m. Pacific).
  • India: Innoplexus, Netradyne, Qure AI, and SigTuple. Live Wednesday, October 7 at 7:30 a.m. IST (Tuesday, October 6 at 7 p.m. Pacific).
  • South Korea: Lunit, Qraft Technologies, SI Analytics, StradVision, and VUNO. Live Tuesday, October 6 at 12 p.m. KST (Monday, October 5th at 8 p.m. Pacific).
  • Japan: ABEJA, ExaWizards, and Ridge-i. Live Wednesday, October 7 at 2 p.m. JST (Tuesday, October 6 at 10 p.m. Pacific).

Nvidia will post videos on the site of startups it can’t showcase live, Herbst said.

“We want to position ourselves as helpers and educators, taking our collective knowledge of the industry and distributing it as equally to as many companies as possible,” he said.

Public sector talks

More than 40 sessions will be held on the intersection of AI and the public and private sectors, with topics including national and global AI policy and infrastructure, data science, autonomous machines, conversational AI, preventative maintenance, edge computing, and cybersecurity.

Among the highlights, members of Congress will talk about developing legislation and policy frameworks to support the U.S.’ national AI policy. The panel includes U.S. representatives Will Hurd, Robin Kelly, and Jerry McNerney.

On Tuesday, October 6 at 11 a.m. Pacific, Federal Communications Commission (FCC) chair Ajit Pai and Nvidia telecommunications global lead Soma Velayutham will discuss the role of AI in 5G. They will also talk about the FCC’s plans to ensure the country’s 5G infrastructure delivers on its promise to transform the telecom industry.

Diversity

Herbst said thousands of women and underrepresented developers have registered to learn about AI, robotics, and GPU computing. More than 100 female tech leaders are scheduled to give talks, and over 25% of registered attendees are women.

The event includes two all-female panels. “Aligning Around Common Values to Advance AI Policy” will look at what needs to happen to pave the way for responsible AI on a global scale. “Advancing Equitable AI” will explore how to give underrepresented youth more access to AI resources and education.

Nvidia is offering free conference passes to professional organizations that support women, Black, and Latinx developers who are working in AI or interested in getting started. The company is providing training passes for professors at historically Black colleges and universities (HBCU) and the organizations Black in AI and LatinX in AI.

Nvidia has an added responsibility to address diversity and inclusion because it’s the giant of the industry now, with a market capitalization even bigger than that of rival Intel.

“I joined 19 years ago because Jensen said we weren’t going to be just a chip company,” Herbst said. “He said we were going to be a computing platform. That’s true, and we’re always evolving.”

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Intel Capital commits $132 million to 11 AI startups

May 12, 2020   Big Data
 Intel Capital commits $132 million to 11 AI startups

Intel today announced that Intel Capital, its global investment organization, committed a total of $ 132 million to 11 startups focused on AI, automation, and chipset design. It follows a year in which the firm invested $ 466 million in 36 new companies (and 35 follow-on investments) and led 72% of its deals through 22 successful exits. In 2020, Intel Capital says it’s on track to invest around the same amount — between $ 300 million and $ 500 million — in startups specializing in AI, with a particular focus on intelligent edge devices and network transformation.

Intel doubling down on AI and machine learning is business as usual. During an earnings call late last year, CEO Bob Swan said the company generated $ 3.8 billion in AI-based revenue in 2019, and that he anticipates the market opportunity will reach $ 25 billion by 2024. To position itself for growth, Intel recently acquired Habana Labs, an Israel-based developer of programmable AI and machine learning accelerators for cloud datacenters, as well as Moovit, a mobility startup that could be central to Intel subsidiary Mobileye’s plans for a robo-taxi service.

Intel Capital’s expanded investment portfolio includes Redwood City, California-based Anodot, which uses machine learning to perform autonomous business monitoring for clients across telco, finance, and digital sectors. The startup’s platform for real-time, contextual alerts helps to spot incidents — e.g., drops in success rate, customer incidents, app performance, and business metrics — that might impact revenue and costs. In fact, Anodot says it cuts incident management by as much as 80%.

Astera Labs, another new Intel Capital investment, is a fabless semiconductor company headquartered in Santa Clara, California that develops purpose-built connectivity solutions for data-centric systems. It aims to remove performance bottlenecks in compute-intensive workloads like AI and machine learning, with products that span system-aware semiconductor integrated circuits, boards and services, and more.

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Intel Capital’s investment in Hypersonix could bolster the San Jose, California-based company’s autonomous analytics platform, which targets consumer industries like retail, restaurants, hospitality, and ecommerce. Through voice and text search and data visualization, Hypersonix provides real-time actionable insights from disparate data sources like regional business performance and website traffic.

Zhejiang, China-based KFBIO, which also received an Intel Capital investment, builds pathology systems such as a scanner that ostensibly improves on traditional microscopes with digital capabilities and connectivity. Using a combination of big data, cloud computing, and AI, the company’s medical image processing tech scans and digitizes images to make them easier to share for remote consultations with experts.

New Intel Capital portfolio company Lilt provides AI-powered language translation software and services. The San Francisco, California-based firm taps machine learning, a translation management system, and professional translators to enable organizations to scale their localization programs and improve their customers’ experiences.

As for Retrace, which recently received a cash infusion from Intel Capital, it applies machine learning to real-time data to improve dental decision-making. The San Francisco startup’s predictive platform aims to reduce the oral disease burden for health plans, providers, and patients by creating a more cost-effective and evidence-based oral healthcare experience.

Other new Intel Capital investments in 2020 include:

  • Axonne, which is developing next-generation high-speed Ethernet network connectivity solutions for automobiles.
  • MemVerge, which provides petabyte-size pools of shared persistent memory and data services for AI, machine learning, and high-performance computing workloads.
  • ProPlus Electronics, an electronic design automation company specializing in device modeling and fast circuit simulation solutions.
  • Spectrum Materials, a high-purity gas and material supplier for semiconductor fabricators.
  • Xsight Labs, a developer of chipset designs that promise to enhance scalability, performance, and efficiency.

Intel Capital, which launched in 1991, made a total of 1,588 investments prior to today’s announcement, according to Crunchbase data. Its new commitments soberingly come as an estimated 390 startups, including companies like Uber and Airbnb, have laid off over 44,600 employees as a result of pandemic-related economic headwinds. Crunchbase anticipates a “more pronounced” reset in investments as venture firms reassess their existing funding needs.

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Startups: How to Manage your OEM for Exit Planning

March 8, 2020   TIBCO Spotfire
StartupAcquisitionsTIBCOOEM e1583444736359 696x365 Startups: How to Manage your OEM for Exit Planning

Reading Time: 3 minutes

In the modern-day startup business, an exit to public markets through an initial public offering (IPO) of stock has become increasingly challenging due to regulatory pressures and less-than-desirable market valuations. Look no further than what happened to WeWork. Today, founders and institutional investors of startups are more focused on developing an exit strategy that involves selling to a larger player in the market. During the course of developing a robust exit strategy, most startups often overlook key decisions while building their product that might cause problems downstream, when future acquirers start to value the business for acquisition. In this short article, we examine the topic of software OEM as it pertains to future acquisition consideration.

In my prior article, Focus your Energy on your Application, not your Infrastructure we compared building infrastructure capabilities for an application software startup to using OEM software for accelerating time to market and other efficiencies. Similarly, when it comes to exit planning there are trickle-down decisions that have to be made at the product level and should be carefully considered as it might impact exit valuations. 

Let’s explore this further with a startup M&A example

Company A and Company B both compete with each other in a hotly contested startup market for next-generation, artificial intelligence (AI)-driven HR software that employs machine learning and lots of data integration. Both companies, A and B, have raised nearly the same amount of venture capital, enjoy similar market success, and both have very good teams. Company C, a large publicly-traded company is now looking to “fold in” a market-leading AI technology into their existing HR application software and has decided to buy either Company A or Company B. 

While going through initial product exploratory calls with Company A and Company B, the acquirer puts a small table together that might look like this:

Category Company A Company B Risk
Product Completeness 95% 90% N/A
Technology Ruby on Rails Node.JS Minor as both products are mature
Infrastructure Homegrown OEM Company A has an older version and a lack of permissible licenses. Need to drill down.

The CTO of Company A always insisted on using the “best” engineered solution, even if the long-term consequences were not fully vetted. In the case of Company A, the CTO chose to use a myriad of open source tools and homegrown, customized adaptations to address the data integration requirements for their HR solution, which often needed to connect with multiple ‘cloud’ solutions like Salesforce, and ‘on-premises’ solutions like PeopleSoft. In building everything in-house, engineers in the trenches of development made suboptimal choices. When incorporating open-source tools that lacked permissible licenses and also require heavy customization, Company A made it difficult for Company C to merge with their infrastructure. Moving off those investments when an acquisition happened would not be easy for Company C (or any other company for that matter) and would perhaps require a triage-based re-architecture approach at different levels of the infrastructure software stack.

In comparison, Company B has a Founder/CTO who is a pragmatist who continuously optimized for speed to market along with scale and cost of ownership. As such, Company B employed OEM-based tools to address infrastructure needs for connectivity, analysis, and so forth. In addition, the OEM tools have “assignable” contracts, which means they could be easily incorporated into Company C, with little legal risk. They also put in place strict measures behind selecting and using open-source tools without explicit permission from the CTO.  

As evident in the above example, the good intention of Company A’s CTO results in a scenario where, after years of product development, the acquiring Company C has to rip and replace core infrastructure elements of the product to de-risk the acquisition. This will result in a longer path to market after post-merger integration. Given this situation, Company C decides to reduce the valuation for Company A by 30%, which doesn’t sit well with the founders and investors of Company A, and in the end, results in Company B being acquired.

No one approach is the perfect way to grow your software infrastructure investments. There are always pros and cons. That said, it is wise to keep a couple of sacrosanct best practice rules in place as follows:

  1. Insist on using permissive licenses, especially when incorporating open-source software
  2. When incorporating OEM software into your startup software, insist on “assignable” contracts, so that at the time of acquisition the acquirer can take ownership of the contract with the least amount of legal friction

The best way to think through your infrastructure investment is to consider a balanced strategy that considers speed to market, customer needs, and future acquirer objections that might arise.  

Learn how TIBCO’s deeply embedded OEM solutions can help you get your tech start-up’s infrastructure right and allow you to focus your energy on your applications. 

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Startups: Focus your Energy on your Application, not your Infrastructure

February 7, 2020   TIBCO Spotfire
TIBCOStartUpsOEM 696x521 Startups: Focus your Energy on your Application, not your Infrastructure

Reading Time: 2 minutes

While smart infrastructure decisions are vital to application software companies, the most important aspect of intellectual property (IP) sits in the product capabilities expressed at the application feature and function level. The application layer is most likely where your company will realize its greatest IP value. 

Newly formed application software companies typically have one very important job, which is to validate the market with a ‘minimum viable product’(MVP). Behind the scenes, the process to build the MVP is usually driven by a set of market requirements that are almost always closely tied to substantive feedback by different types of potential users. In simpler terms, the product development focus must have a good grasp on what the customer wants and align that to the features within the software solution. As a consequence of the above-stated approach, one can imagine, nearly 90% of important conversations for application product development at an early stage will center around application capability as opposed to application infrastructure. 

An overweight focus on the application functional layer is generally a good thing, as your company’s priority should be to get the application features to align with early customer needs and drive adoption. That said, after going to market and maturing beyond the MVP stage, most software teams will need to start paying attention to the infrastructure capability, which generally sits behind the scenes and will touch the areas of: security, scalability, microservices, and integration, just to name a few.  

Most startups face the difficult decision of how much and where to invest infrastructure capability. They must choose between building it in-house (organic) and using an (OEM) solution as a deeply embedded option. Let’s take a moment to look at the pros/cons and market value impact of the aforementioned options at a high level.

Building your infrastructure in-house vs OEM

Infrastructure Options Pros Cons Market Value Conclusions
Organic
(In-House) 
Very specific to the app use cases
Full IP ownership
Expensive to hire
Evolving requirements will require further investment $ $ $
Longer to go to market
Medium-IP owned by the firm but not viewed as essential by the customer because it’s behind the scenes. So, bang for the buck is moderate at best and execution risk is high given low expertise
OEM (Deeply Embedded) Fastest to market
Provides road-tested capability to reduce risk
Quicker to adapt to customer technology shifts quickly
Less expensive to maintain than hiring, building, and growing in-house infrastructure team
Generally broad capability hammer for a thumbtack
IP is owned by OEM company
Need to invest in learning and embedding OEM through series of POCs
High-market value is driven by much faster time to market and less technology risk and debt that might accrue if product landscape shifts

As you can see from the above chart, embedding your application will give you a much higher market value because you will get your application to market faster. You will also experience less technology risk that might accrue if the product landscape you are working in shifts.

Learn how TIBCO’s deeply embedded OEM solutions can help you get your tech start-up’s infrastructure right and allow you to focus your energy on your applications. 

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AI startups stand out at Comcast Lift Labs Accelerator 2019

October 11, 2019   Big Data

This evening in Philadelphia, Comcast NBCUniversal’s Lift Labs Accelerator showcased the 11 companies in its second-ever class during a demo day in front of investors and the local tech community. The event marked the finale of the program’s 13-week program, during which each startup worked with Techstars’ bench of industry experts and Comcast brands including Xfinity, NBC, Telemundo, NBC Sports, Universal Studios, DreamWorks Animation, Comcast Business, Comcast Ventures, and Sky.

While not every startup completed proof of concept or a pilot project with Comcast, eight of the 11 announced that they did. And one company, NICKL, said it would relocate its headquarters to Philadelphia.

“Today marks the culmination of the 11th program I’ve run at Techstars,” said Lift Labs Accelerator managing director KJ Singh. “Having invested in over 100 companies during my tenure and run more programs than anyone else at Techstars, past or present, this is without a doubt the class I am most excited about.”

One of the spotlight participants in this year’s cohort was Diana AI, which is developing a conversational business intelligence tool designed to help users analyze enterprise data using voice or text. During the accelerator, founders Geeta Banda and Teja Nanduri acquired their first paying customers and signed six new enterprise customers, including Comcast.

 AI startups stand out at Comcast Lift Labs Accelerator 2019

Another standout was Edisn.ai, which provides a platform that generates real-time personalized sports content from live video streams using AI. Ashok Karanth, Akshay Chandrasekhar, and team launched a soon-to-be-expanded pilot with Comcast’s Watchwith Xfinity platform to deliver interactive content for football games. Additionally, they kicked off pilot discussions with NBC10, Universal Pictures, and Telemundo62 Philadelphia for sports, news, and entertainment programming.

David Sturgeon’s and Constantine Tsang’s Pivan Interactive, another cohort graduate, leverages computer vision and AI to provide training and analytics for competitive gaming athletes. They’ve partnered with Comcast Spectacor’s T1 Entertainment & Sports, an esports venture, to develop a suite of data-driven tools. And they’re in discussions with the Philadelphia Fusion (a team competing in Blizzard’s Overwatch) around a future partnership involving the newly announced Fusion Arena.

 AI startups stand out at Comcast Lift Labs Accelerator 2019

Last but not least, there’s Respeecher, whose technology transforms voices with natural language processing such that one person can imitate the voice of another. (It’s a bit like the recently acquired Montreal-based Lyrebird in that way.) Founders Oleksandr Serdiuk, Grant Reaber, and Dmytro Bielievtsov dramatically improved their product’s efficiency during the accelerator program. (It now requires five times less time to convert speech.) Concurrently, they established relationships with partners covering over 75% of the U.S. entertainment box office and over 40% of the audiobooks market.

“It has been such a fantastic experience for all of the Comcast NBCUniversal mentors to work side-by-side with these dynamic companies to help them grow and launch their businesses,” said Comcast Cable chief business development officer Sam Schwartz. “The Founders of these promising startups have an incredible passion and drive, and we are so excited to see what’s next for them.”

The Lift Labs Accelerator will begin accepting applications for its third class in January 2020, Comcast says, which is scheduled to begin in July 2020 in Philadelphia.

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Facebook Accelerator London opens to non-U.K. startups with a focus on transformative tech

September 23, 2019   Big Data
 Facebook Accelerator London opens to non U.K. startups with a focus on transformative tech

Facebook has announced the third edition of its London-based accelerator program, alongside a rebrand and a renewed focus on startups from across Europe and neighboring regions.

Launched initially in the U.K. capital as LDN_LAB nearly two years ago, the 12-week incubator program will now be called Facebook Accelerator London, to make its purpose as a startup accelerator more clear. The actual physical space where the program takes place will still be called LDN_LAB, a spokesperson added.

While Facebook has previously operated a number of startup incubators around the world, for example one for data-driven startups inside Paris’ Station F campus, LDN_LAB is Facebook’s first ever in-house accelerator, located at its main London HQ. As part of the program, which will operate in partnership with digital consultancy Founders Intelligence, participants get access to Facebook employees, workshops, mentorship, and more.

So far, each intake at LDN_LAB has focused on a single key theme, the first one being startups working on technology to build communities, while the second cohort was all about “deep tech for good.” In a similar vain, the third Facebook Accelerator program, which opens for applicants in November, will target “high-growth startups” working in transformative technologies such as artificial intelligence (AI), virtual reality (VR), augmented reality (AR), and blockchain, among “other Facebook products and technologies.”

Going global

While the Facebook Accelerator program has until now only accepted applications from U.K.-based startups, it is looking further afield for its next cohort.

“Innovation is at the heart of Facebook and today we are opening up our London accelerator program to applications from startups across Europe, the Middle East, and Africa,” noted Nicola Mendelsohn, Facebook’s VP of EMEA region. “The selected startups will gain access to experts from across Facebook including those working in augmented reality, blockchain, and AI.”

There are other caveats for acceptance onto the program too. Facebook said that it’s also focusing on technology that has a “positive impact on the world,” including those working toward improving “digital connectivity” globally.

Each of the program’s various areas of focus tie in with technologies that Facebook is actively working on. It recently announced plans for a blockchain-based cryptocurrency called Libra, for example, while it’s also looking to improve internet infrastructure via various conduits, such as satellite-based Wi-Fi hotspots and subsea cabling projects. Elsewhere, the social networking giant is investing heavily in the VR and AR spheres too.

London, too, has emerged as major hub for Facebook’s technology development. The city is now the company’s largest engineering hub outside of the U.S., and a few months back it announced plans to open a third London office to house 500 new technology roles, around 20% of which will be focused on AI.

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Intel Capital invests $117 million in more than a dozen startups

April 1, 2019   Big Data
 Intel Capital invests $117 million in more than a dozen startups

Intel Capital today announced an investment of $ 117 million in 14 startups doing things like making AI inference faster, helping manufacturers deploy AI systems, building semiconductors, and creating disruptive tech beyond AI in health care and communications.

The companies hail from China, Canada, Israel, the United Kingdom, and the United States.

Companies supported as part of the announcement include Landing AI, a company created by former Google Brain cofounder Andrew Ng that helps manufacturers apply AI to their business practices, and Untether AI, which makes chips specifically for neural net inference.

An Intel Capital spokesperson declined to share specific amounts invested in each startup. Intel Capital routinely invests between $ 300 million and $ 500 million annually in startups creating unique, forward-thinking, or disruptive solutions.

Other AI startups that received backing today include:

  • Cloudpick, based in Shanghai, which uses deep learning and computer vision for ecommerce solutions.
  • Medical Informatics, based in Houston, which uses machine learning and data to bring predictive insights to patient care.
  • Zhuhai Eeasy Technology, based in Zhuhai, China, which makes AI systems for media-related use cases for deployment on the edge, such as video encoding and image processing.

While the majority of the 14 companies being supported by Intel Capital are creating products and services related to artificial intelligence, other companies are in different fields, such as Polystream, which delivers 3D applications for video games in the cloud; Pixeom, which helps clients manage large-scale hybrid cloud and edge computing; and Tibit Communications, which makes a device to improve Ethernet internet connections.

The news was shared today at Intel Capital’s Global Summit, a gathering for venture capitalists and entrepreneurs now in its 19th year, which is taking place this week in Phoenix, Arizona.

Intel also announced today at Global Summit an investment in hbcu.vc, a nonprofit organization that helps students from historically black colleges and universities, as well as Hispanic students, learn more about venture capital and entrepreneurship.

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Why B2B Startups Are On The Rise In India

March 19, 2019   SAP
 Why B2B Startups Are On The Rise In India

2018 was a breakthrough year for business-to-business (B2B) startups in India. B2B ventures stepped out of the shadows from the more visible business-to-consumer (B2C) startups. Of all 7,400 startups in India, 43 percent were B2B companies last year, according to the consultancy firm Zinnov. In comparison, just four years earlier in 2014, just 26 percent of all 3,100 startups were B2B enterprises in India. We not only see a shift towards B2B business models, but B2B startups are also growing at a faster rate than B2C businesses, attracting the interest of venture capitalists and global corporations.

What has triggered the growth of B2B startups in India? Here’s why I believe the growth of B2B startups in India will continue to accelerate.

Most B2B startups compete globally from the launch

As the domestic B2B market for startups in India is still small (albeit growing) compared to that of countries like the U.S., most Indian B2B startups target global enterprises as customers, competing with other startups from around the world from day one. This is not an easy playing field for any company. However, B2B startups in India often have at least two aces up their sleeves: As India is a global innovation hub with R&D labs from many of the world’s largest corporations, startup founders or their team members have extensive knowledge of global enterprises. They also have access to one of the world’s largest IT talent pools, with a growing number of IT skillset programs geared towards the development of capabilities in IoT, analytics, cloud, machine learning, and artificial intelligence (AI).

The latest Global Competitiveness Report by the World Economic Forum (WEF) named India as a growing center for innovation and as one of the countries with the potential to catch up with economies that currently top the global competitiveness ranking. Bengaluru, Mumbai, and Pune appeared in the top 100 innovation centers of WEF’s cluster study. Of these three cities, Mumbai was the fastest-growing startup hub in India last year. Of the 50,000 startups founded in 2018, 14 percent registered in the capital of Maharashtra state, according to a KPMG report.

Indian B2B startups focus on fast-growing tech sectors and harness AI

Indian startups are adept at harnessing the potential of emerging technologies as innovation drivers for large enterprises. One of the fastest-growing B2B market segments is artificial intelligence (AI). According to a study by Accenture, AI could add $ 957 billion to the Indian economy, increasing the country’s income by 15 percent by 2035.

While we are still in the early stages of grasping the full potential of AI for the future of business and work, AI has outgrown its experimental stage for enterprise applications. According to a Capgemini study, India has taken the lead for AI implementation at scale globally. The study found that 58 percent of companies are already using AI at scale in India, beyond pilot and test projects, to innovate, and ultimately grow their business operations. The government’s Digital India initiative has created a favorable regulatory environment to foster the increased use of AI, per the report.

B2B startups benefit from new corporate partnership programs

India has about 210 incubators and accelerators, according to the NASSCOM-Zinnov Indian Start-up Ecosystem 2018 report. More than 35 corporate incubators and accelerators were launched in the past three years alone. Corporate R&D centers in India have started to shift their focus on intelligent technologies, including AI, machine learning, and the Internet of Things, and they have revamped their approach to innovation, opening their doors to external partners to develop new products and services.

An increasing number of innovations have come to market through a collaboration with corporations and tech startups. Many of these joint collaborations happen as part of the corporate incubator and accelerator programs or through a long-term technology partnership. Through these new corporate startup partnership models, Indian B2B tech startups have gained access to much-needed infrastructure support, a global network, and financing to achieve business growth.

Datoin is one B2B startup that is part of the new generation of Indian B2B startups. Since its launch in 2015, the Bangalore-based company has developed an enterprise automation platform that helps enterprises automate their processes by leveraging enterprise data, artificial intelligence, and component-based engineering. With Datoin’s platform, enterprises can build solutions that use intelligent automation to harness enterprise data.

Datoin was one of 16 companies selected for the 2017 SAP Startup Studio accelerator program, which prepares startups to develop and sell products for a global enterprise environment and market. The startup has grown leaps and bounds since then and continues to collaborate with SAP on innovation projects as part of the SAP Leonardo Center.

Thanks to new corporate partnership models, a sharp focus on intelligent technologies and growth sectors, and a global mindset, B2B startups are thriving in India. Their rise shows what we can achieve in the future globally when large corporations and startups work together to push the boundaries of innovation.

For more on how tech innovation is driving growth in the Indian economy, see Indian Startups Fuel Global Tech Renaissance.

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Factory reset: Tech startups raise big bucks to help companies cut waste

August 19, 2018   Big Data

Society has become somewhat accustomed to disposable goods, be it cheap garments, budget phones, or plastic packaging.

But with Earth facing untold apocalyptic catastrophes in the decades to come, there has been a growing push to do something — anything — to counter the predicted cataclysmic events that await us.

A few months back, Seattle became the first major U.S. city to ban single-use disposable straws, while England could become the first country to ban them next year. Starbucks, meanwhile, will usher out plastic straws across all its stores globally by 2020.

These are small measures by anyone’s standard, but they feed into a broader trend that’s striving to cut waste and reduce our dependency on disposable goods.

Food, in particular, is one area where we’re seeing this trend amplified, with big-name investors lining up for their piece of the waste-cutting pie.

Food for thought

Earlier this month, Santa Barbara-based Apeel Sciences raised a whopping $ 70 million from U.S. hedge fund Viking Global Investors, Andreessen Horowitz, Upfront Ventures, and others. This took the company’s total funding to $ 110 million.

So what is Apeel doing to reduce food waste, exactly? Well, it essentially applies a second layer of skin to fruit and vegetables to reinforce protection and prolong their shelf life by reducing water loss and oxidation. The company said that produce that has been given the Apeel treatment typically stays fresher for up to three times longer.

Above: Apeel Sciences applies a second layer of skin to fruit and vegetables to prolong their shelf life.

Image Credit: Apeel Sciences

The funding came just a few months after Apeel Sciences commercialized its product via avocados at Costco and Harps Food Stores in the U.S., which it said led to a 65 percentage-point margin increase and a 10 percent sales increase in Hass avocados.

“As Apeel products continue to hit the shelves, the retail world is now beginning to experience what was clear from day one, which is that Apeel is a product with the potential to change the world,” said Yves Sisteron, founder and managing partner at Upfront Ventures, which first invested in Apeel Sciences as part of its $ 5.8 million series A round back in 2014.

Earlier this week Swedish startup Karma raised $ 12 million for a marketplace that helps restaurants and supermarkets cut food waste by selling their surplus goods at a discount. Investors included Swedish investment firm Kinnevik, with participation from Bessemer Venture Partners (one of the oldest venture capital firms in the U.S.), Electrolux, and E.ventures.

The premise behind Karma is simple. The consumer creates an account and can see what’s available in their area — the offerings are whatever food outlets have an excess of, so there won’t necessarily be a consistent choice of goods each day. But if you’re not fussy and all you’re looking for is a good discount, then you may find cakes, bread, sandwiches, freshly squeezed lemonade, and pretty much anything else.

 Factory reset: Tech startups raise big bucks to help companies cut waste

Above: Karma lunch offerings in London.

Image Credit: Karma

The problem that Karma is looking to fix is this: Roughly one third of food produced globally each year never reaches a human mouth, according to the United Nations’ Food and Agriculture Organization. That’s $ 1 trillion worth of edible food ending up in a landfill.

Karma is available across Sweden, while it also recently launched in London, its first international market. But with a fresh $ 12 million in the coffers, it’s planning to launch into more international markets across Europe and the U.S.

Both these startups show that while ethical concepts are attractive to investors, you’re not going to get anywhere on altruism alone: Your idea and execution needs to be underpinned by a solid business.

“While the Karma team is really going after a good cause, we share a very fundamental belief with the founders: to have a lasting and meaningful impact, companies around sustainability need to be for-profit and have an attractive business model,” said E.ventures partner Jonathan Becker.

Elsewhere in the culinary realm, Full Harvest this week raised $ 8.5 million in a series A round of funding led by Spark Capital. The San Francisco-based startup offers a B2B marketplace that helps farmers sell surplus and imperfect goods to food and beverage companies.

 Factory reset: Tech startups raise big bucks to help companies cut waste

Above: A… deformed apple?

Image Credit: Shutterstock

Up to 40 percent of food in the U.S. goes uneaten each year, according to the Natural Resources Defense Council, and a big part of this problem is that grocery stores and supermarkets don’t want to buy ugly fruit and vegetables because, well, consumers don’t want to buy them either. But a wonky apple is every bit as nutritious as an aesthetically pleasing apple, which is how Full Harvest manages to find a market that connects farms with food buyers. The company already works with a number of U.S. food and drink companies, and it has claimed that it helped one U.S. farm grow its profits by 12 percent per acre.

“A ReFed report has stated that $ 10 billion invested into solving food waste will bring $ 100 billion of value to society due to true cost accounting across the entire supply chain, economy and environment,” the company said in a statement. “We also have sold close to 7 million pounds of produce that would otherwise have gone to waste, which is equivalent of preventing 430 million gallons of water from going to waste  — enough to provide drinking water for 8 million people for a year — and 2.5 million kilograms of CO2e emissions from being produced.”

But it’s not just the food industry that’s seeking traction in the waste-cutting world.

Factory reset

Last week, London-based Unmade raised a modest $ 4 million in a round of funding led by Felix Capital. The Techstars London alumnus develops a software platform for fashion brands to offer customizable clothes directly to consumers.

 Factory reset: Tech startups raise big bucks to help companies cut waste

Above: Unmade: Customizing a sweater on Farfetch’s website.

The on-demand model not only allows fashionistas to fine-tune patterns or mix colors around, but it also promises a more sustainable business. Clothes are not created in bulk before demand is established — each item is effectively made-to-order, thus cutting down on waste. The company said that it now works with three of the top fashion brands in the U.S.

This kind of manufacturing potentially has a big future — last year Amazon was awarded a patent for a similar system that’s capable of producing products, including garments, after an order is placed.

On-demand product manufacturing means that supply meets demand rather than surpasses it, and ensures a bunch of perfectly wearable goods do not end up in the trash.

“By conservative estimates, 10 percent to 25 percent of all clothes made each season are never sold and go to landfill or are burned — after travelling through a network of stores and discount retailers,” added Unmade cofounder and chief product officer Ben Alun-Jones. “When you think the fashion industry today is at least $ 2.4 trillion, this is a huge environmental issue. Our mission is to transform the current business model of the fashion industry, one that frequently leads to significant overproduction and waste, and start to create clothing that is either tailored by or made for the consumer.”

The made-to-order model could also have an impact on return rates, thus reducing waste even further — if a customer has played an active role in designing their garment, they may feel more attached to it when it arrives.

“With our current customers, we have also seen a big reduction in return rates once they start using our platform,” Alun-Jones continued.

Last month, Atomico — the VC firm founded by Skype co-creator Niklas Zennström — led a $ 10 million investment in Oden Technologies. The London-based company serves up the hardware and software for manufacturers to track faults and establish patterns that may affect their factory equipment performance. It’s all about analytics and big data.

While the chief driving force behind Oden Technologies centers on improving efficiency and cutting costs, firmly embedded in this business model is the need to reduce waste. Manufacturing facilities can waste millions of dollars worth of materials each year due to factors such as “variation and imprecise specifications,” something that Oden says it solves.

By improving operational processes on the factory floor, Oden claims it can detect inefficiencies and issues “up to 95 percent faster” and cut waste by “hundreds of thousands of dollars” each year.

And this is what major VC firms like Atomico are investing in: “Industry 4.0,” which includes big data, artificial intelligence, and robotics. It’s about digitizing the $ 12 trillion manufacturing industry to make it more efficient — which means less waste.

“We believe that the global manufacturing industry is on the brink of a new machine age; one in which the industrial Internet of Things and cloud analytics, coupled with machine learning and artificial intelligence, are set to transform existing production processes, slash waste, drive incredible efficiencies and increase output,” Atomico said at the time of its investment.

We’re seeing shifts in this direction across the industrial spectrum. While the world prepares for self-driving cars to infiltrate its highways, some industries are already embracing autonomous driving technology.

Sugarcane is among the largest crop globally in terms of quantity produced. During collection, large trucks normally drive beside the harvester at low speed to take the sugarcane off-site. However, up to four percent can be lost as the truck tramples fledgling crops, which is due to driver error. As such, Volvo revealed last year that it was trialing self-steering trucks to help sugarcane farmers improve crop yield — drivers don’t have to worry about keeping the truck in a straight line as the steering is all automated.

Above: Volvo self-steering truck.

Image Credit: Volvo

Whether it’s moving away from disposable straws, ensuring food doesn’t end up in a landfill, confirming every piece of clothing has a buyer before it’s made, or minimizing factories’ excess material burn rate, the goal is the same: Cutting waste will play a major part in the future of our planet. Crucially, this also means improving a company’s bottom line, which will be pivotal in garnering buy-in from more companies.

“Waste inherently means something of no value or of no use,” Unmade’s Alun-Jones added. “Removing that from manufacturing makes good business sense and is clearly of financial value. Because the scale of waste in some very large industries is so massive, this is clearly a big opportunity for startups.”

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Universities and legacy industries are giving rise to the Midwest’s AI startups

July 9, 2018   Big Data
 Universities and legacy industries are giving rise to the Midwest’s AI startups

Despite the promise artificial intelligence holds to transform many facets of American life, the majority of artificial intelligence companies are still concentrated in traditional tech hubs. According to a Glassdoor analysis from November, 30 percent of open jobs at the time that included the words “artificial intelligence, “AI” or “deep learning” in the job title were located in San Jose, with another 18 percent in San Francisco.

That’s why VentureBeat decided to take a look at what kinds of AI startups are forming in an area that venture capitalists have traditionally overlooked — the Midwest — and what problems they’re trying to tackle. Using data from research firms CB Insights and Crunchbase, VentureBeat looked for Midwestern startups with unique machine learning or artificial intelligence platforms that have raised significant amounts of venture capital. We also spoke with two Midwestern venture capitalists about which startups are worth watching.

Chris Olsen, a partner at Columbus, Ohio venture capital firm Drive Capital is bullish on the Midwest’s ability to produce game-changing AI startups.

“The real benefit of artificial intelligence is the application to traditional problems and products that the world needs, and the really successful companies have that domain knowledge that they can understand how to apply this technology,” Olsen told VentureBeat in a phone interview. “We see more of those domain experts in these industries [with] massive chunks of GDP that exist here in the Midwest.”

One disadvantage that AI startups in the Midwest face is that the area has less talent capable of building AI systems. Gene Munster, the managing partner at Minneapolis‘ Loup Ventures, which invests in AI and VR among other pioneering technologies, estimates that the Midwest has an access to “one tenth” of the AI talent that Silicon Valley does.

“I think the good news is that as AI becomes a more popular field, there’s obviously good schools here and as it becomes a more popular field over the next 10 years, I think that that gap will dramatically close,” Munster told VentureBeat.

In our analysis, VentureBeat found that many of the Midwest’s promising AI startups were born of the city’s universities, or have ties to its historically dominant industries, giving a clue to what other types of startups the Midwest could give rise to.

Chicago

One of the fastest-growing AI startups in the Windy City right now is Uptake, the latest in a string of companies from Groupon cofounders Brad Keywell and Eric Lekofsky. With  $ 264 million in venture capital funding, Uptake’s algorithms help its enterprise customers collect and analyze sensor data on industrial machinery and equipment.

There’s also Narrative Science, which has raised $ 43 million in funding. Born out of a Northwestern University student’s class project, Narrative Science has developed a Natural Language Generation platform to generate written insights, that can be used to assemble material like client reports and marketing copy, in the tone and style of the customer’s business.

Another notable startup is car insurance startup Clearcover, which has raised $ 11.5 million in funding. Clearcover has developed an algorithm that helps the company advertise to potential customers during what it calls,  “moments that matter” — when a consumer is shopping for a car, or trying to save money on their finances. To do so, Clearcover integrates its API with insurance comparison sites, personal finance apps, and other partner websites.

Civis Analytics, a data science startup, has garnered national attention as it’s led by the former chief analytics officer for President Barack Obama’s 2012 reelection campaign, and counts Eric Schmidt as an investor. Civis Analytics, whose clients include Airbnb, Verizon, and Robinhood, has developed a subscription cloud-based data science environment in which data scientists can consolidate data, analyze it, and build predictive models. Civis Analytics closed a $ 22 million round in November 2016.

Lastly, there’s Catalytic, which has raised about $ 16.7 million in funding. Catalytic’s AI powered software advertises the ability to automate over 100 common workplace tasks, such as working with spreadsheets and filling out forms. Catalytic also integrates with software like Salesforce, Dropbox, and Workday.

St. Louis

Two of the St. Louis startups dabbling in machine learning that seemed to have gained the most traction are ones with ties to local research institutions. There’s Cofactor Genomics, founder by three former Human Genome Project scientists who worked out of Washington University in St. Louis. An alumni of YCombinator’s Summer 2015 batch, Cofactor Genomics has built a platform that uses RNA biomarkers to predict drug response and monitor disease — it then uses machine learning to tie cell types, diseases, and treatments, to an encyclopedia of RNA fingerprints. The company has raised about $ 21 million total in venture capital.

Benson Hill Biosystems is based on research that came out of St. Louis’ Donald Danforth Plant Science Center. The company has developed a crop design platform called CropOS that uses machine learning to help agriculture companies identify which seeds will produce the desired traits, such as increase in yield or increase in a certain nutrient, in a crop. Founded in 2012, the company has raised $ 35 million in funding.

Another up-and-comer is Jane.ai, founded by the former CEO of Answers.com, which recently raised an $ 8.4 million round of funding. Jane.ai is another chatbot for businesses that sifts through data from cloud storage providers, emails, and other data files to help employees more easily access company information.

Ann Arbor

Ann Arbor’s University of Michigan has played an instrumental role in the growth of several AI startups in the state of Michigan. Trove, which has developed a platform that scans users’ emails to provide them with insights about their professional network, has worked with a pair of research teams at the University of Michigan, the company previously told VentureBeat.

There’s also Clinc, founded by University of Michigan professors, which specializes in conversational AI. One of the products Clinc has developed is a voice-activated intelligence assistant called Finie, which integrates with certain banks’ mobile applications, allowing customers to ask questions like where the nearest ATM is, and receive a natural language answer.

Finally, May Mobility, which has developed its own fleet of electric self-driving vehicles, was founded by the former head of the APRIl robotics lab at the University of Michigan. A spokesperson for May Mobility also notes that about half of the company’s employees today have some sort of connection to the University of Michigan.

Trove, Clinc, and May Mobility, have raised approximately $ 11 million, $ 7.8 million, and $ 11.6 million in funding, respectively.

Columbus

Like Clearcover, Columbus’ Root Insurance, is using artificial intelligence to try and sell cheaper car insurance. Root, which recently raised a $ 51 million series C, has developed an algorithm that uses sensor data from a person’s phone to determine things like how quickly they drive around a corner, or how much they tailgate, and then uses that to generate a quote for a customer.

Columbus is also home to CrossChx, a healthcare startup armed with about $ 40 million in funding that has developed an AI bot called Olive. Olive helps healthcare companies complete tedious administrative healthcare tasks. Lastly, there’s Nexosis, which has created a machine learning API for developers, and has raised about $ 7 million in venture capital funding.

Minneapolis/St. Paul

Though his firm Loup Ventures is based there, Munster said that he hasn’t invested in any Minneapolis AI startups yet. But he highlighted two promising ones to VentureBeat — Equals 3 and Rambl (formerly known as Aftercode), which have raised about $ 7 million and $ 2 million in venture capital funding respectively, according to Crunchbase.

Equals 3 has developed an AI-powered marketing assistant called Lucy. Lucy scans client and industry reports to make suggestions to marketers on where to spend their money. Rambl’s AI-powered assistant targets sales professionals, promoting the ability to analyze sales calls and suggest follow-up actions — like when to schedule another meeting, or whether professionals should spend more time listening during their next call.

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