Why Global Brain Formed a Team of Deep Tech Experts

Written by the Universe editorial team.

Global Brain (GB) invests in deep tech, technologies that have not yet been put into use nor have existing markets. We sat down with Keiji Niizu, the leader of the Strategic Technology Investment (STI) team undertaking deep tech investment, to talk about why the team was formed, how it operates, and what are its achievements.

Can you tell us about how the STI team was built?

Niizu: GB is unique in how venture capitalists who are subject matter experts invest in the various areas of deep tech. Deep tech refers to a wide range of fields that can be roughly categorized into two groups: the vertical technologies that are industry-specific and the horizontal technologies that are fundamental and fit all industries.

At GB, we have over 20 venture capitalists who are engineers by background, with experience in these deep tech areas at their previous companies.

However, these venture capitalists who are subject matter experts are assigned to deep tech markets that have already been formed and have high growth potential. Since research and development of new technologies is progressing even as we speak, we will see changes in the areas of deep tech waiting to be invested. Given our funds’ lifetime is ten years, it is highly likely that totally new deep tech markets will be formed during this lifecycle.

To continue achieving high investment performance as a top tier venture capital firm, we acknowledged the need to act quickly and invest in these new deep tech areas. This is why we built a dedicated team of experts, and we call our activities Strategic Technology Investment (STI).

Through our STI initiatives, we currently invest in areas including quantum technology, silicon photonics, next-gen solar/storage batteries, and metamaterials.

It sounds like tough work to keep an eye on the ever-changing technological development. How do you choose new investment areas?

Niizu: We basically follow the five steps below to decide whether we want to invest in a specific technology.

1.Understand the characteristics and the usage of a technology 2.Analyze the market 3.Examine the requirements for the technology to spread 4.Identify promising R&D approaches 5.Source startups

I will explain our investment decision-making process by introducing an actual sourcing we did in the field of next-gen LiDAR (Light Detection and Ranging) using silicon photonics technology.

1.Understand the characteristics and the usage of a technology

LiDAR is a device which measures the relative distance to a target, and I think some people may have come across it in articles on autonomous driving.

While the typical LiDAR is based on a Time of Flight (ToF) architecture, a new type of device based on Frequency Modulated Continuous Wave (FMCW) is attracting attention as the next -gen LiDAR.

Skipping detailed technological talks, the key is that FMCW-based LiDAR can be used for wider purposes including autonomous automobiles and advanced driver-assistance systems (ADAS) that use high-level machine vision (a technology that identifies objects by analyzing images and other data acquired from cameras and LiDAR.)

2.Analyze the market

Next is market potential. The image below shows LiDAR market data per application.

AV/ADAS* (autonomous vehicles / advanced driver-assistance systems) is the strongest market growth driver and this market is projected to grow at a CAGR of 37%, from USD 38 million (2021 actual results) to USD 2 billion (2027 forecast). We can say that the market has enough potential to expand.

*AV/ADAS stands for autonomous vehicles and advanced driver-assistance systems. They refer to systems that improve the safety and comfortability of drivers with autonomous driving or by informing drivers of the vehicle’s surroundings.

3.Examine the requirements for the technology to spread

After understanding the technology and its market potential, we have to examine whether the technology has the potential to spread among the general public.

For example, mutual interference should never happen as it would be useless if the device falsely detects waves emitted from LiDAR sensors mounted on other vehicles.

Cost is another key factor which determines the spread of a product.

By looking at these aspects, we concluded that the requirements below need to be met for LiDAR to spread for use in AV/ADAS.

No mutual interference between LiDAR devices (no false detection of waves emitted from other devices) Low power consumption Low manufacturing cost

4.Identify promising R&D approaches

As I explained in the first section, LiDAR can take on different modalities, roughly categorized into two: ToF and FMCW.

ToF is subject to false detections when used for multiple vehicles and consumes a large amount of electric energy to measure distances up to several hundred meters, required for AV/ADAS. Based on requirement 1 (mutual interference) and requirement 2 (power consumption), ToF is not fit to spread as LiDAR for AV/ADAS.

On the other hand, we found out that FMCW could satisfy these two requirements.

The last item to tick off on the list is requirement 3, manufacturing cost.

The structure of a FMCW-based LiDAR system can be classified into two types: a box-type and a chip-type. Comparing the two, we figured the latter was more suited for mass production and therefore has more potential. An on-chip FMCW LiDAR can be mass-produced from wafers (round thin slices of semiconductor crystal used for the fabrication of IC chips) by leveraging silicon photonics technology which is based on mass manufacturing of semiconductors.

Also, the compact size of IC chip-based LiDAR enables its use for mobile devices in the future.

5.Source startups

The final step was to look into all the startups with high-level silicon photonics technology that were developing IC chip-based LiDAR. After talking with each startup, we compared and considered who we wanted to invest in.

We chose a U.S. startup called SiLC Technologies, outstanding in terms of IC chip-based LiDAR development progress, integration into a single IC chip, fabrication processes, and the executive management’s experience.

I guess it is natural that you examine potential portfolios very carefully. What other companies have you invested in as STI?

Niizu: In addition to SiLC Technologies (U.S.) in the silicon photonics area, we have also invested in QunaSys, a Japanese quantum computing company, and Metalenz, a U.S. meta materials company. We are recently moving forward with investing in a company named Caelux, which is a U.S. next-gen solar battery startup.

Incidentally, we found out that some of the other top tier venture capital firms like Temasek that we have worked with also have dedicated teams doing research and investment in deep tech. Together we had fruitful discussions about startups’ technological challenges and future prospects, and agreed to exchange updates on deep tech and look for co-investment opportunities.

Can you briefly tell me about your three team members?

Niizu: Other than me, we have Brian (in the U.S. office) and Sho Ohtani.

Brian has a long experience as an engineer and as a venture capitalist, and he has connections with deep tech venture capitalists at top tier venture capital firms in the U.S. He leverages his network to source many highly potential deep tech startups.

Ohtani studied electrical, electronic, and control engineering at a college of technology, and took up aeronautics and astronautics at university. As a new-grad, he was a researcher for a major manufacturing company where he wrote research papers and patents. With his interest in a wide range of areas, he is conducting deep analysis of various areas for STI activities.

Lastly, what would you like to try as STI?

Niizu: I have two things. One is to keep up with the rapidly advancing deep tech R&D trends.

For us, staying up to date with the latest science and technology news is a must. In addition, we need to have deep insights in the backgrounds of what is happening and in upcoming developments. This is something that we gain not only by honing our capabilities but also by having discussions with deep tech startups and limited partners (investors in venture capital funds) and supporting collaborations between them.

Moreover, GB has advisory agreements with leading Japanese experts in quantum computing, carbon neutrality, and other areas. The fact that we are able to leverage their knowledge is a big strength for us.

Second is to achieve good performance in investments.

The STI team has only been launched recently, and we are yet to achieve an exit. We think that to achieve a big exit, post-investment hands-on support is crucial in addition to sourcing high-potential startups.

For example, we have supported portfolios with patent strategies and applications, communications with LPs for collaborations, or finding country managers for entering the Japanese market.

Going forward, GB’s STI team will continue to take the lead in identifying new investment areas of deep tech and reaching out to highly potential startups for investment. We will use the knowledge we gain in the process to contribute to improving the performance of our funds and driving open innovation of our LPs. We look forward to your continued support.