Science and Technology
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As artificial intelligence continues to weave its way into more enterprise applications, a startup that has built a platform to help businesses, especially non-tech organizations, build more customized AI decision-making tools for themselves has picked up some significant growth funding. Peak AI, a startup out of Manchester, England, that has built a “decision intelligence” platform, has raised $75 million, money that it will be using to continue building out its platform, expand into new markets and hire some 200 new people in the coming quarters.
The Series C is bringing a very big name investor on board. It is being led by SoftBank Vision Fund 2, with previous backers Oxx, MMC Ventures, Praetura Ventures and Arete also participating. That group participated in Peak’s Series B of $21 million, which only closed in February of this year. The company has now raised $119 million; it is not disclosing its valuation.
(This latest funding round was rumored last week, although it was not confirmed at the time and the total amount was not accurate.)
Richard Potter, Peak’s CEO, said the rapid follow-on in funding was based on inbound interest, in part because of how the company has been doing.
Peak’s so-called Decision Intelligence platform is used by retailers, brands, manufacturers and others to help monitor stock levels and build personalized customer experiences, as well as other processes that can stand to have some degree of automation to work more efficiently, but also require sophistication to be able to measure different factors against each other to provide more intelligent insights. Its current customer list includes the likes of Nike, Pepsico, KFC, Molson Coors, Marshalls, Asos and Speedy, and in the last 12 months revenues have more than doubled.
The opportunity that Peak is addressing goes a little like this: AI has become a cornerstone of many of the most advanced IT applications and business processes of our time, but if you are an organization — and specifically one not built around technology — your access to AI and how you might use it will come by way of applications built by others, not necessarily tailored to you, and the costs of building more tailored solutions can often be prohibitively high. Peak claims that those using its tools have seen revenues on average rise 5%, return on ad spend double, supply chain costs reduce by 5% and inventory holdings (a big cost for companies) reduce by 12%.
Peak’s platform, I should point out, is not exactly a “no-code” approach to solving that problem — not yet at least: It’s aimed at data scientists and engineers at those organizations so that they can easily identify different processes in their operations where they might benefit from AI tools, and to build those out with relatively little heavy lifting.
There have also been different market factors that have played a role. COVID-19, for example, and the boost that we have seen both in increasing “digital transformation” in businesses and making e-commerce processes more efficient to cater to rising consumer demand and more strained supply chains have all led to businesses being more open and keen to invest in more tools to improve their automation intelligently.
This, combined with Peak AI’s growing revenues, is part of what interested SoftBank. The investor has been long on AI for a while; but it also has been building out a section of its investment portfolio to provide strategic services to the kinds of businesses in which it invests.
Those include e-commerce and other consumer-facing businesses, which make up one of the main segments of Peak’s customer base.
Notably, one of its recent investments specifically in that space was made earlier this year, also in Manchester, when it took a $730 million stake (with potentially $1.6 billion more down the line) in The Hut Group, which builds software for and runs D2C businesses.
“In Peak we have a partner with a shared vision that the future enterprise will run on a centralized AI software platform capable of optimizing entire value chains,” Max Ohrstrand, senior investor for SoftBank Investment Advisers, said in a statement. “To realize this a new breed of platform is needed and we’re hugely impressed with what Richard and the excellent team have built at Peak. We’re delighted to be supporting them on their way to becoming the category-defining, global leader in Decision Intelligence.”
It’s not clear that SoftBank’s two Manchester interests will be working together, but it’s an interesting synergy if they do, and most of all highlights one of the firm’s areas of interest.
Longer term, it will be interesting to see how and if Peak evolves to extend its platform to a wider set of users at the organizations that are already its customers.
Potter said he believes that “those with technical predispositions” will be the most likely users of its products in the near and medium term. You might assume that would cut out, for example, marketing managers, although the general trend in a lot of software tools has precisely been to build versions of the same tools used by data scientists for these less technical people to engage in the process of building what it is that they want to use.
“I do think it’s important to democratize the ability to stream data pipelines, and to be able to optimize those to work in applications,” Potter added.
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Today, the release of OpenAI Codex, a new Al system that translates natural language to code, marks the beginning of a shift in how computer software is written.
Over the past few years, there’s been growing talk about “no code” platforms, but this is no new phenomenon. The reality is, ever since the first programmable devices, computer scientists have regularly developed breakthroughs in how we “code” computer software.
The first computers were programmed with switches or punch cards, until the keyboard was invented. Coding became a matter of typing numbers or machine language, until Grace Hopper invented the modern compiler and the COBOL language, ushering in decades of innovation in programming languages and platforms. Languages like Fortran, Pascal, C, Java and Python evolved in a progression, where the newest language (built using an older language) enabled programmers to “code” using increasingly more human language.
Alongside languages, we’ve seen the evolution of “no-code” platforms — including Microsoft Excel, the 1980s granddaddy of no-code — that empower people to program computers in a visual interface, whether in school or in the workplace. Anytime you write a formula in a spreadsheet, or when you drag a block of code on Code.org or Scratch, you’re programming, or “coding,” a computer. “No code” is code. Every decade, a breakthrough innovation makes it easier to write code so that the old way of coding is replaced by the new.
Does this mean coding is dead? No! It doesn’t replace the need for a programmer to understand code. It means coding just got much easier, higher impact and thus more important.
This brings us to today’s announcement. Today, OpenAl announced OpenAI Codex, an entirely new way to “write code” in the natural English language. A computer programmer can now use English to describe what they want their software to do, and OpenAl’s generative Al model will automatically generate the corresponding computer code, in your choice of programming language. This is what we’ve always wanted — for computers to understand what we want them to do, and then do it, without having to go through a complex intermediary like a programming language.
But this is not an end, it is a beginning. With Al-generated code, one can imagine an evolution in every programming tool, in every programming class, and a Cambrian explosion of new software. Does this mean coding is dead? No! It doesn’t replace the need for a programmer to understand code. It means coding just got much easier, higher impact and thus more important, just as when punch cards were replaced by keyboards, or when Grace Hopper invented the compiler.
In fact, the demand for software today is greater than ever and will only continue to grow. As this technology evolves, Al will play a greater role in generating code, which will multiply the productivity and impact of computer scientists, and will make this field accessible to more and more computer programmers.
There are already tools that let you program using only drag-and-drop, or to write code using your voice. Improvements in these technologies and new tools, like OpenAI Codex, will increasingly democratize the ability to create software. As a result, the amount of code — and the number of coders — in the world will increase.
This also means that learning how to program — in a new way — is more important than ever. Learning to code can unlock doors to opportunity and also help solve global problems. As it becomes easier and more accessible to create software, we should give every student in every school the fundamental knowledge to not only be a user of technology but also a creator.
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Thousands of electric vehicle charging stations will be built around the country over the next decade. ChargerHelp!, founded in January 2020 by Kameale C. Terry and Evette Ellis, wants to make sure they stay up and running.
The idea for the on-demand repair app for EV charging stations came to Terry when she was working at EV Connect, where she held a number of roles including director of programs and head of customer experience. She noticed long wait times to fix non-electrical issues at charging stations due to the industry practice to use electrical contractors.
“When the stations went down we really couldn’t get anyone on site because most of the issues were communication issues, vandalism, firmware updates or swapping out a part — all things that were not electrical,” Terry said in an interview with TechCrunch earlier this year.
After Terry quit her job to start ChargerHelp!, she joined the Los Angeles Cleantech Incubator, where she developed a first-of-its-kind EV Network Technician Training Curriculum. Shortly after, Terry and Ellis were accepted into Elemental Excelerator’s startup incubator and have landed contracts with major EV charging network providers like EV Connect and SparkCharge.
The company uses a workforce-development approach to hiring, meaning that they only hire in cohorts. Workers receive full training, earn two safety licenses, are guaranteed a wage of $30 an hour and receive shares in the startup, Terry said.
We’re excited to announce that Kameale Terry will be joining us at TC Sessions: Mobility 2021, a one-day virtual event that is scheduled June 9. We’ll be covering a lot of ground with Terry, from how she developed her EV repair curriculum to what she sees in the company’s future.
Each year TechCrunch brings together founders, investors, CEOs and engineers who are working on all things transportation and mobility. If it moves people and packages from Point A to Point B, we cover it. This year’s agenda is filled with leaders in the mobility space who are shaping the future of transportation, from EV charging to autonomous vehicles to urban air taxis.
Among the growing list of speakers are Rimac Automobili founder Mate Rimac, Revel Transit CEO Frank Reig, community organizer, transportation consultant and lawyer Tamika L. Butler and Remix/Via co-founder and CEO Tiffany Chu, who will come together to discuss how (and if) urban mobility can increase equity while still remaining a viable business.
Other guests include Motional’s President and CEO Karl Iagnemma, Aurora co-founder and CEO Chris Urmson, GM‘s VP of Global Innovation Pam Fletcher, Scale AI CEO Alexandr Wang, Joby Aviation founder and CEO JoeBen Bevirt, investor and LinkedIn founder Reid Hoffman (whose special purpose acquisition company just merged with Joby), investors Clara Brenner of Urban Innovation Fund, Quin Garcia of Autotech Ventures and Rachel Holt of Construct Capital, Zoox co-founder and CTO Jesse Levinson.
We also recently announced a panel dedicated to China’s robotaxi industry, featuring three female leaders from Chinese AV startups: AutoX’s COO Jewel Li, Huan Sun, general manager of Momenta Europe with Momenta, and WeRide’s VP of Finance Jennifer Li.
Don’t wait to book your tickets to TC Sessions: Mobility as prices go up at the door. Grab your passes right now and hear from today’s biggest mobility leaders.
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In recent years, the publicly traded observability service New Relic started adding more machine learning-based tools to its platform for AI-assisted incident response when things don’t quite go as planned. Today, it is expanding this feature set with the launch of a number of new capabilities for what it calls its “New Relic Applied Intelligence Service.”
This expansion includes an anomaly detection service that is even available for free users, the ability to group alerts from multiple tools when the models think it’s a single issue that is triggering all of these alerts and new ML-based root cause analysis to help eliminate some of the guesswork when problems occur. Also new (and in public beta) is New Relic’s ability to detect patterns and outliers in log data that is stored in the company’s data platform.
The main idea here, New Relic’s director of product marketing Michael Olson told me, is to make it easier for companies of all sizes to reap the benefits of AI-enhanced ops.
“It’s been about a year since we introduced our first set of AIops capabilities with New Relic Applied Intelligence to the market,” he said. “During that time, we’ve seen significant growth in adoption of AIops capabilities through New Relic. But one of the things that we’ve heard from organizations that have yet to foray into adopting AIops capabilities as part of their incident response practice is that they often find that things like steep learning curves and long implementation and training times — and sometimes lack of confidence, or knowledge of AI and machine learning — often stand in the way.”
The new platform should be able to detect emerging problems in real time — without the team having to pre-configure alerts. And when it does so, it’ll smartly group all of the alerts from New Relic and other tools together to cut down on the alert noise and let engineers focus on the incident.
“Instead of an alert storm when a problem occurs across multiple tools, engineers get one actionable issue with alerts automatically grouped based on things like time and frequency, based on the context that they can read in the alert messages. And then now with this launch, we’re also able to look at relationship data across your systems to intelligently group and correlate alerts,” Olson explained.
Maybe the highlight for the ops teams that will use these new features, though, is New Relic’s ability to pinpoint the probable root cause of a problem. As Guy Fighel, the general manager of applied intelligence and vice president of product engineering at New Relic, told me, the idea here is not to replace humans but to augment teams.
“We provide a non-black-box experience for teams to craft the decisions and correlation and logic based on their own knowledge and infuse the system with their own knowledge,” Fighel noted. “So you can get very specific based on your environment and needs. And so because of that and because we see a lot of data coming from different tools — all going into New Relic One as the data platform — our probable root cause is very accurate. Having said that, it is still a probable root cause. So although we are opinionated about it, we will never tell you, ‘hey, go fix that, because we’re 100% sure that’s the case.’ You’re the human, you’re in control.”
The AI system also asks users for feedback, so that the model gets refined with every new incident, too.
Fighel tells me that New Relic’s tools rely on a variety of statistical analysis methods and machine learning models. Some of those are unique to individual users while others are used across the company’s user base. He also stressed that all of the engineers who worked on this project have a background in site reliability engineering — so they are intimately familiar with the problems in this space.
With today’s launch, New Relic is also adding a new integration with PagerDuty and other incident management tools so that the state of a given issue can be synchronized bi-directionally between them.
“We want to meet our customers where they are and really be data source agnostic and enable customers to pull in data from any source, where we can then enrich that data, reduce noise and ultimately help our customers solve problems faster,” said Olson.
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Skydio has raised $170 million in a Series D funding round led by Andreessen Horowitz’s Growth Fund. That pushes it into unicorn territory, with $340 million in total funding and a post-money valuation north of $1 billion. Skydio’s fresh capital comes on the heels of its expansion last year into the enterprise market, and it intends to use the considerable pile of cash to help it expand globally and accelerate product development.
In July of last year, Skydio announced its $100 million Series C financing, and also debuted the X2, its first dedicated enterprise drone. The company also launched a suite of software for commercial and enterprise customers, its first departure from the consumer drone market where it had been focused prior to that raise since its founding in 2014.
Skydio’s debut drone, the R1, received a lot of accolades and praise for its autonomous capabilities. Unlike other consumer drones at the time, including from recreational drone maker DJI, the R1 could track a target and film them while avoiding obstacles without any human intervention required. Skydio then released the Skydio 2 in 2019, its second drone, cutting off more than half the price while improving on it its autonomous tracking and video capabilities.
Late last year, Skydio brought on additional senior talent to help it address enterprise and government customers, including a software development lead who had experience at Tesla and 3D printing company Carbon. Skydio also hired two Samsara executives at the same time to work on product and engineering. Samsara provides a platform for managing cloud-based fleet operations for large enterprises.
The applications of Skydio’s technology for commercial, public sector and enterprise organizations are many and varied. Already, the company works with public utilities, fire departments, construction firms and more to do work including remote inspection, emergency response, urban planning and more. Skydio’s U.S. pedigree also puts it in prime position to capitalize on the growing interest in applications from the defense sector.
a16z previously led Skydio’s Series A round. Other investors who participated in this Series D include Lines Capital, Next47, IVP and UP.Partners.
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The Atlanta area is getting a new incubator for startups working with 5G technology courtesy of T-Mobile and Georgia Tech’s Advanced Technology Development Center (ATDC), the companies announced today.
It’s an expansion of the T-Mobile Accelerator program and part of the big carrier’s efforts to boost 5G innovation.
Located in the Atlanta-adjacent exurb of Peachtree Corners’ technology development park, which is already equipped with T-Mobile’s 5G services, the incubator will help developers build and test 5G use cases including autonomous vehicles, robotics, industrial drone applications, mixed reality training and entertainment, remote medical care and personal health, the company said.
Startups working with the 5G Connected Future program will work directly with folks at T-Mobile’s accelerator, Georgia Tech and Curiosity Lab, an initiative in the Peachtree Corners campus.
“In addition to the normal startup concerns, entrepreneurs in the 5G space face a unique set of challenges such as regulatory issues at the state and local levels, network security, and integration testing,” said ATDC Director John Avery.
Peachtree Corners’ setup may help folks navigate that rollout. As part of its involvement, ATDC will offer programing, recruit and evaluate startups, and hire staff to manage the vertical in Peachtree Corners, the organization said.
“This collaboration is a great opportunity for ATDC and Georgia Tech, the city of Peachtree Corners and Curiosity Lab, and T-Mobile, a Fortune 50 company, to create a unique collection to work with these companies, refine their ideas into scalable companies, and bring these solutions to market more quickly,” Avery said.
Such a partnership underscores “Georgia Tech’s commitment to enabling tomorrow’s technology leaders, which remains as strong as when ATDC was founded 41 years ago,” said Chaouki T. Abdallah, Georgia Tech’s executive vice president for research. “Innovation cannot take place in a vacuum, which is why entrepreneurs and startups require the knowledge and resources provided through partnerships such as ours.”
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New space startup bluShift wants to bring a new kind of propellant to the small satellite launching market, with rockets powered by bio-derived rocket fuels. These differ from traditional fuels in that they offer safety advantages during handling, and ecological advantages during production and use. The startup has been working on its solid rocket biofuel since its founding in 2014, and has received grants from the Maine Technology Institute and NASA’s Small Business Innovation Research (SBIR) program to refine its fuel formula and rocket engine design to help it get to this point.
The company achieved a milestone on Sunday with its first rocket launch — a low-altitude flight of a small sounding rocket, called Stardust 1.0. It’s a single-stage prototype, which can only carry 18 lbs of payload and is designed to achieve suborbital space. That may not seem like much, but it is enough to put small research equipment up into suborbital space, at costs that put launches within range for small companies and academic institutions.
Image Credits: Knack Factory/Courtesy Aerospace
Stardust 1.0 is designed to be reusable, though it’s still a prototype, and the company is also working on Stardust 2.0, which is a second prototype that’s expected to increase the payload capacity and act as the primary building block for its subsequent production commercial rockets, including Starless Rogue, a two-stage launcher for suborbital missions, and Red Dwarf, a three-stage, 66-lb capacity launch vehicle that can reach low Earth orbit.
Sunday’s launch looked like it might not have been on track to go well at first, with an initial attempt seeing the rocket’s ignition light — but without a takeoff. After resetting for a second try, there wasn’t any ignition. Finally the rocket did take off late in the day, with a flight that the company said “went perfectly” on a follow-up call with media.
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German drone technology startup Wingcopter has raised a $22 million Series A – its first significant venture capital raise after mostly bootstrapping. The company, which focuses on drone delivery, has come a long way since its founding in 2017, having developed, built and flown its Wingcopter 178 heavy-lift cargo delivery drone using its proprietary and patented tilt-rotor propellant mechanism, which combines all the benefits of vertical take-off and landing with the advantages of fixed-wing aircraft for longer distance horizontal flight.
This new Series A round was led by Silicon Valley VC Xplorer Capital, as well as German growth fund Futury Regio Growth. Wingcopter CEO and founder Tom Plümmer explained to the in an interview that the addition of an SV-based investor is particularly important to the startup, since it’s in the process of preparing its entry into the U.S., with plans for an American facility, both for flight testing to satisfy FAA requirements for operational certification, as well as eventually for U.S.-based drone production.
Wingcopter has already been operating commercially in a few different markets globally, including in Vanuatu in partnership with Unicef for vaccine delivery to remote areas, in Tanzania for two-way medical supply delivery working with Tanzania, and in Ireland where it completed the world’s first delivery of insulin by drone beyond visual line of sight (BVLOS, the industry’s technical term for when a drone flies beyond the visual range of a human operator who has the ability to take control in case of emergencies).
Wingcopter CEO and co-founder Tom Plümmer. Credit: Jonas Wresch
While Wingcopter has so far pursued a business as an OEM manufacturer of drones, and has had paying customers eager to purchase its hardware effectively since day one (Plümmer told me that they had at least one customer wiring them money before they even had a bank account set up for the business), but it’s also now getting into the business of offering drone delivery-as-a-service. After doing the hard work of building its technology from the ground up, and seeking out the necessary regulatory approvals to operate in multiple markets around the world, Plümmer says that he and his co-founders realized that operating a service business not only meant a new source of revenue, but also better-served the needs of many of its potential customers.
“We learned during this process, through applying for permission, receiving these permissions and working now in five continents in multiple countries, flying BVLOS, that actually operating drones is something we are now very good at,” he said. This was actually becoming a really good source of income, and ended up actually making up more than half of our revenue at some point. Also looking at scalability of the business model of being an OEM, it’s kind of […] linear.”
Linear growth with solid revenue and steady demand was fine for Wingcopter as a bootstrapped startup founded by university students supported by a small initial investment from family and friends. But Plümmer says the company say so much potential in the technology it had developed, and the emerging drone delivery market, that the exponential growth curve of its drone delivery-as-a-service model helped make traditional VC backing make sense. In the early days, Plümmer says Wingcopter had been approached by VCs, but at the time it didn’t make sense for what they were trying to do; that’s changed.
“We were really lucky to bootstrap over the last four years,” Plümmer said. “Basically, just by selling drones and creating revenue, we could employ our first 30 employees. But at some point, you realize you want to really plan with that revenue, so you want to have monthly revenues, which generally repeat like a software business – like software as a service.”
Wingcopter 178 cargo drone performing a delivery for Merck.
Wingcopter has also established a useful hedge regarding its service business, not only by being its own hardware supplier, but also by having worked closely with many global flight regulators on their regulatory process through the early days of commercial drone flights. They’re working with the FAA on its certification process now, for instance, with Plümmer saying that they participate in weekly calls with the regulator on its upcoming certification process for BVLOS drone operators. Understanding the regulatory environment, and even helping architect it, is a major selling point for partners who don’t want to have to build out that kind of expertise and regulatory team in-house.
Meanwhile, the company will continue to act as an OEM as well, selling not only its Wingcopter 178 heavy-lift model, which can fly up to 75 miles, at speeds of up to 100 mph, and that can carry payloads up to around 13 lbs. Because of its unique tilt-rotor mechanism, it’s not only more efficient in flight, but it can also fly in much windier conditions – and take-off and land in harsher conditions than most drones, too.
Plümmer tells me that Wingcopter doesn’t intend to rest on its laurels in the hardware department, either; it’s going to be introducing a new model of drone soon, with different capabilities that expand the company’s addressable market, both as an OEM and in its drones-as-a-service business.
With its U.S. expansion, Wingcopter will still look to focus specifically on the delivery market, but Plümmer points out that there’s no reason its unique technology couldn’t also work well to serve markets including observation and inspection, or to address needs in the communication space as well. The one market that Wingcopter doesn’t intend to pursue, however, is military and defense. While these are popular customers in the aerospace and drone industries, Plümmer says that Wingcopter has a mission “to create sustainable and efficient drone solutions for improving and saving lives,” and says the startup looks at every potential customer and ensures that it aligns with its vision – which defense customers do not.
While the company has just announced the close of its Series A round, Plümmer says they’re already in talks with some potential investors to join a Series B. It’s also going to be looking for U.S. based talent in embedded systems software and flight operations testing, to help with the testing process required its certification by the FAA.
Plümmer sees a long tail of value to be built from Wingcopter’s patented tilt-rotor design, with potential applications in a range of industries, and he says that Wingcopter won’t be looking around for any potential via M&A until it has fully realized that value. Meanwhile, the company is also starting to sow the seeds of its own potential future customers, with training programs in drone flights and operations it’s putting on in partnership with UNICEF’s African Drone and Data Academy. Wingcopter clearly envisions a bright future for drone delivery, and its work in focusing its efforts on building differentiating hardware, plus the role it’s playing in setting the regulatory agenda globally, could help position it at the center of that future.
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Bay Area-based construction startup TraceAir today announced a $3.5 million Series A. Led by London-based XTX Ventures, this round brings the company’s total funding up to $7 million. The raise includes existing investor Metropolis VC, along with new additions Liquid 2 Ventures, GEM Capital, GPS Ventures and Andrew Filev.
We first noted the company back in 2016, when it pitched a method for using drones to spot construction errors before they become too expense. It’s a pretty massive field that various technology companies are attempting to solve through a variety of different means, ranging from quadrupedal robots to site-scanning hard hats.
Last February, TraceAir announced a new drone management tool. “Haul Router provides the best mathematically objective hauls for each given drone scan,” the company noted at the time. “Any employee can use the tool to design a haul road and export the results to feed into grading equipment.”
The pandemic has thrown the construction industry for a loop (along with countless others). But unlike other sectors, demand still remains high in many places. TraceAir is hoping its solution will prove beneficial as many outfits seek a way to continue the process in spite of uncertainty.
“The Covid-19 pandemic created new challenges for the U.S. and worldwide construction industries, resulting in delayed projects and growing unemployment rates,” CEO Dmitry Korolev said in a release tied to the news. “Our platform allows industry leaders to manage projects more efficiently and collaborate with their teams remotely, minimizing the need for a physical presence on-site.”
TraceAir says the additional funding will go toward its sales and marketing, along with future product developments, including an unnamed product set for release this quarter.
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TMYTEK recently raised a Series A+ round of about $10 million for products that make it easier to test 5G millimeter wave equipment. So far, the company’s clients include KDDI, NTT DoCoMo and research institutions. But the Taiwanese startup has aspirations to sell its own base stations, too, competing with well-established players like Nokia, Ericsson, Samsung and Huawei. TMYTEK plans to use its expertise, gleaned from helping other researchers develop 5G infrastructure, to create what its chief executive officer describes as a “complete 5G industrial chain.”
Its latest funding round was led by TMYTEK’s manufacturing partner Inventec, one of the largest OEMs in Taiwan, and brings the startup’s total funding so far to $13.3 million. Other investors included Taisic Materials, ITEQ, Tamagawa Electronics and Taiwan’s National Development Fund. TMYTEK also recently took part in SparkLabs Taipei’s accelerator program.
Co-founder and chief executive officer Su-Wei Chang told TechCrunch that it plans to raise a Series B next to develop and commercialize its base stations. To get ready for its base station business, TMYTEK recently joined the O-RAN Alliance, founded by some of the world’s biggest telecoms to create more interoperable mobile networks, in a bid to encourage the development of new technology and faster deployment.
Chang said TMYTEK’s base in Taiwan gives it a strategic advantage. 5G manufacturing is an important part of Taiwan’s economy, with exports reaching record highs during the second half of 2020, thanks in part to demand for 5G-related equipment and technology for smartphones, autonomous vehicles and smart devices.
Chang studied at University of Massachusetts Amherst and when TMYTEK was founded six years ago, he was often asked why he didn’t stay in the United States, where it would have been easier to secure startup funding. But being in Taiwan puts the company closer to many important markets, including Japan, where 30% of its current business comes from, and gives TMYTEK a good foundation to expand into the U.S. and European market, he said.
It has also given the company a supply chain advantage. TMYTEK has manufacturing partners across Asia, including Inventec in Taiwan, and factories in Vietnam and Thailand, in addition to China. Chang said this means TMYTEK was not limited by the COVID-19 pandemic or the U.S.-China trade war.
Before launching TMYTEK in 2014, Chang and co-founder Ethan Lin both worked at Academia Sinica, one of the top research institutions in Taiwan, where they focused on millimeter waves even though at the time most researchers were more interested in the mid-band spectrum.
But as more devices and applications began to crowd the 4G spectrum, mmWave became less niche. With Qualcomm’s launch of next-generation 5G mmWave hardware and chips, and more carriers launching mmWave coverage, mmWave is poised to become mainstream.
Millimeter waves offer powerful signals with wide bandwidth and low latency, but drawbacks include difficulty traveling through obstacles like buildings. It also has a limited range, which is why millimeter waves need more base stations. Beamforming, which directs signals toward a specific device, and antenna array, or multiple antennas that work like a single antenna, are used to extend its coverage.
One of the main challenges for the millimeter wave market, however, is the lack of R&D tools to speed up their development and time to market, resulting in higher costs and slower deployment.
To keep up with market opportunities, TMYTEK transitioned from design and manufacturing projects for clients to offering 5G-focused solutions like the BBox, which stands for “beamforming box.” The BBox was created after a professor at National Taiwan University told Chang that his team was working on antenna design, but didn’t have the resources to work on beamforming technology, too. It lets researchers create 16 beams and control the signal’s amplitude and phase with software, so they can test how it works with antennas and other hardware more quickly. TMYTEK claims the BBox can save researchers and engineers up to 80% in time and cost.
Chang said TMYTEK realized that if researchers at NTU, one of Taiwan’s largest research universities, needed a solution, then other labs did, too. So far, it has delivered 30 sets to companies including KDDI, NTT DoCoMo, Fujitsu, several Fortune 500 companies and research institutions.
While the BBox was created for antenna designers, the company also began exploring solutions to help other designers, including algorithm developers who want to test beam tracking, communicate with base stations and collect data.
TMYTEK vice president Ethan Lin holds the antenna-in-package for its XBeam millimeter wave testing solution (Image Credits: TMYTEK)
For that scenario, TMYTEK created the XBeam, which it describes as a “total solution,” and is meant for the mass production phase, testing modules, smartphones and base stations before they are shipped. Traditional solutions to test modules rely on mechanical rotators, but Chang said this is more suited to the research and development process. The XBeam, which is based on the BBox, electronically scans beams instead. The company claims the XBeam is up to 20 times faster than other testing solutions.
TMYTEK created the XBeam’s prototype in 2019 and launched the commercialized version in November 2020.
The BBox and XBeam will help TMYTEK build its own base station business in two ways, Chang said. First, having its own solutions will allow TMYTEK to test base stations and bring them to market faster. Second, the startup hopes building a reputation on effective research and development tools will help it market its base stations to private and public networks. This is especially important to TMYTEK’s ambitions since their base stations will be up against products from major players like Nokia, Ericsson, Samsung and Huawei.
“Our advantage at TMYTEK is that we’re doing the design and we have good partners for manufacturing. Inventec, our investor, is a top five manufacturer in Taiwan,” he said. “And TMYTEK also builds our own testing solution, so our value is that we can provide a total solution to our customers.”
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