The document analyzes GSIT, a technology company focused on memory products and artificial intelligence. It notes that GSIT has a profitable core business, no debt, and is developing two new products - radiation-hardened chips for aerospace/defense expected to launch in 2019, and an AI chip called APU which could provide a significant upside if successful. The analysis sees GSIT as an asymmetric investment opportunity given its undervaluation relative to peers and potential catalysts from new products. However, risks include failure of new products to launch and customer concentration.

1. GSIT Writeup (Done by Dennis)
Market cap: 199M
EV/Revenue: 2.66
Insider ownership: 36%
Gross profit margin: 61%
Quick ratio: 8.2
Current Ratio 8.9
Thesis:
GSIT is a technology company based in Silicon Valley that has a core business selling high
performance memory products such as SRAM (static random access memory) and is currently
self funding their own Artificial Intelligence (AI) roadmap, which if successful, would lead to
tremendous upside. They have also been Included in the Russell 3000 index recently, which
explains the recent uptick in stock prices recently. The key thing to understand about this
company is that there are currently 3 key catalysts set in place that would propel the company
to higher valuation in the near future (nearest by summer of 2019).
1. Introducing Rad-hard chip and Rad-Tolerant chip for aerospace and defense in 2019
(Critical testing successfully completed & management stated that they are
anticipating shipping the RadHard Chip later in 2019)
2. Development of their APU which is an in-place associative computing technology for
artificial intelligence and machine learning applications. These is also where they
spend 100% of their R&D budget on. (Management said that Calendar year 2020 is
when they anticipate the APU1 launch during the Roth conference in 2019 March )
3. Likely beneficiary from trade war as Nokia continues to be a top customer and there
may be higher demand from them in the next few quarters as a result of Huawei
sanctions.
The company has a clean balance sheet with no debt, no cash burn and a profitable core
business which provides ample downside protection. It is trading at EV/Revenue of 2.66x,
with 2 near term catalysts on the horizon. Thus making this an extremely asymmetric bet.
What did the market missed:
I believe that the reason that the market is neglecting this stock is probably because this is a
microcap with nothing much to show for in its income statement (at least currently), and the
technology that the company is developing is pretty hard to understand for investors who are
not experts in the industry. Also, it has only 1 analyst covering it (according to yahoo finance).
Business:
GSIT a fabless semiconductor company that designs, develops and markets static random
access memories, or SRAMs, that operate at speeds of less than 10 nanoseconds (aka Very
Fast SRAMs), and low latency dynamic random access memories (or LLDRAMs), primarily for
the networking and telecommunications markets.
Date of publish: 24 May 2019

2. Their core business involves achieving design wins with leading OEMs in the networking and
telecommunications markets. Their customers are big names such as BAE Systems, Ciena,
Cisco Systems, General Dynamics, Honeywell, Lockheed, Nokia, Raytheon, Rockwell. The
gross margin for current product line is around 61%. The only reason why this company has
negative net income is due to its cost related to the R&D of the development of APU. The
company is also in the process of expanding their product line and will they will be ready for
commercialization very soon.
Current product line: IP ports, low latency DRAMS, QUAD SRAMS, DDR SRAMS, SYNCBURST
SRAMS, NBT SRAMS, specialty SRAMS, asynchronous SRAMS.
Expected product line: In-place associative computing (APU), Rad Hard SRAMS (Rad Hard)
Main business:
The company had relatively stronger results for their core business when issues arose with
ZTE last year. It appears a similar setup is occurring with Huawei, whereby their customers
will now need to shift purchases to Nokia and subsequently that will impact GSI positively.
Nokia is by far their largest customer.
Expected product line expansion:
1. Rad Hard SRAMs (radiation hardening)
Radiation hardening is the act of making electronic components and systems resistant
to damage or malfunctions caused by ionizing radiation. These are normally used in
outer space and high-altitude flight, around nuclear reactors and particle accelerators,
or during nuclear accidents or nuclear warfare. The reason why they are used is that
most semiconductor electronic components are susceptible to radiation damage.
Management has stated that critical testing successfully completed & management
stated that they are anticipating shipping the RadHard Chip later in 2019. In effect, the
product will have a gross margin of 85% with average selling price of $30k. They will
be used for satellites, missiles and high altitude flights.
According to Verified Market Research, the Radiation-Hardened Electronics Market
was valued at $1007 Million in 2018 and is projected to reach USD 1,405.43 Million by
2026 over the forecast period at a CAGR of 4.23%. However, that is for the electronics
segment as a whole and include a lot of other products, the addressable market for
radhard chips is likely to be around $50 million.
According to a representative of GSIT that I talked to, competition is unlikely to be a
big issue as eventhough competitors are currently offering radiation hardened chips,
they are not at the speed and capacity of GSI’s. GSI’s will be the fastest, least power
hungry and most capable chip, and is compatible with the chip slots that competitors
chips plug into, so no customer hardware reconfiguration is needed.
2. APU (in-place associative computing)
GSI is also entering another market with a new model for AI Chip design. Now this is
the real elephant in the room that management is betting their chips on. They are now
spending 100% of their R&D budget on the APU and R&D budget is not expecting to

3. increase. The TLDR is that currently the traditional computing system is based on the
Von Neumann architecture is too inefficient in today’s data driven world. This hinders
technology from progressing. For example, under the Van Neumann architecture,
computation is too slow and requires too much power for big data, self-driving cars
require too much power to run and accuracy is too low, cheminformatic &
bioinformatics for drug discovery is too slow, and visual search is too slow and
accuracy is limited. With the APU, the input/output bottleneck between traditional
GPU and memory can be greatly reduced.

4. Potential customer demographics for APU
According to the management team, these are the demographics of potential customers
1. cheminformatics à smaller customers, but a larger amount of customers. The
company has already collaborated with the Weizmann institute (public research
university in Israel) in order to significantly reduce the time and costs of drug discovery.
Simulation with the GSI's APU for this application have shown to improve search speed
by orders of magnitude with the reductions in clearing time from as much as 10
minutes to as little as 300 milliseconds.
2. ecommerce à some large and some small players.
3. facial recognition à small players and also government entities
GSI currently holds 20 patents and 23 pending patents for the APU.

5. Competition
According to Allied market research, the Artificial Intelligence Chip Market is expected to
reach $91.19 Bn, Globally, by 2025 at 45.4% CAGR. This is what the CEO Lee-Lean Shu has to
say about competition “We, okay, so APU is a very, very good in the similarity search. Okay,
so at this moment in the market, competing solution, we don't see anything close to our
solution.” Thus, if what the CEO said is true, it is likely that GSIT will be a strategic acquisition
target by one of the big boys in the tech industry since none of the big boys are able to achieve
results as good as APU1 in terms of similarity search.
While there may be the possibility of other companies looking to compete in AI similarity
search (because it’s impossible to know for sure). What’s important to understand is that the
performance gains demonstrated by GSI’s APU are due to GSI’s architecture, which is unique
and patented.
To read more about similarity search:
https://medium.com/gsi-technology/the-apu-novel-hardware-for-accelerated-similarity-
search-beaef9b19b97
Timeline for commercialization of APU:
• Current – ongoing sample evaluation
• Summer 2019 – demo boards to alpha and limited beta customers. Alpha customers
plays a key role in connecting with the concept behind a product, adopting &
validating that product. Beta customers is like an early customer, but not a tester.
• 2020 – anticipate launch of APU1

6. An investor friend of mine managed to speak to the management team several days ago and
he gave me an update on the commercialization of APU. “First spin had two major bugs.
Second spin is finished. One major bug was fixed, the second was mostly. They'll begin testing
it this summer and open that up to anyone that wants to. A third spin is likely later this year.
By 2020, they'll be ready to commercialize but they do not know what that will look like and
do not want to guess just yet. (Takeaway: Everything where it should be here with APU).”
According to a representative of the company that I spoke to, “GSI plans on having demo
boards available this summer. GSI’s AI team has been in dialog with visual and similarity
search teams at Google, eBay, Walmart Labs, Wayfair and the AI visual search platform
developer Clarifi. They have also be in dialog about these applications in space with NASA and
the companies that would develop space-based AI. In Cheminformatics/drug discovery they
have been involved with the Israeli-based Weissman institute, who is the research arm for
many U.S. and European big pharma companies.”
A short write up won’t be able to cover everything about this technology, so to learn more you
can read the white papers below:
For a short summary: https://www.gsitechnology.com/APU
For more detailed explanations:
https://drive.google.com/drive/folders/1lttOoZA6Qfu_cuaMcFOlfD5rRslrn5Wu?usp=sharing
Risks:
1. Products fail to launch or someone else beat them to launching the product.
2. Their core business has significant customer concentration risk as they derive most of
our revenues from their sale to Nokia. Purchases by Nokia represented approximately
36%, 41% and 32% of their net revenues in fiscal 2018, 2017 and 2016, respectively.
(but this is also a potential upside due to the Huawei ban)
3. Cyclical nature of networking and communications market.
Upsides and downside:
Upside
Looking at the valuation of past deals in the AI chip industry. The closest comparison to GSIT
is graphcore and it is valued at $1.7 billion. They managed to raise 200 mil from the latest
round of funding from BMW, Microsoft, Atomico, Merian Chrysalis, Investment Company
Limited, Sofina, and Sequoia. Similar interests could be generated if the commercialization of
APU by GSIT is successful. The exact valuation could be anyone’s guess and the use of financial
metrics is pretty much meaningless for a company like GSIT. However, if GSIT is to trade at
these levels, it would be likely to at least double in price in the near term and potentially be
a multi bagger in the long term, and that is without taking into account the current core
business.

7. Downside
The downside is that both products fail to launch, in which case it should trade back down to
the valuation of a normal SRAM company. However, even if you were to add back their R&D
expenses, it will be trading at PE of 7.7x which is also relatively cheap for a memory chip
company. The mean EV/Rev of a memory chip company is 3.75x while GSIT is trading at 2.66x.
Thus, it seems to me that the main business itself is also undervalued. I am unable to
quantitatively determine a potential downside to this investment, though it is likely that the
confidence of investors would fall in the short term if their expansion plans falls through
Conclusion
Going forward, I would like the management team to take part in more stock promotion
activities so that investors know about the story that is transparent in the company over the
next few quarters. To end it all off, I will quote what the representative answered me when I
said that the company seemed too good to be true, “Anything is possible, but remember
Nvidia was a gaming chip company before some university students wrote a white paper in
the early 2000’s on how the GPU could be used for processing deep learning neural networks.
At that time nobody thought Nvidia would become the company that is has today (a decade
later).” Only time will tell whether this works out well, but I am currently very bullish on this
stock.
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only subjective views. This information should not be relied on for investment decisions
and is subject to change due many factors, including fluctuating market conditions and
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could differ materially from those set forth in, contemplated by, or underlying these
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