innovation

Unleash the Full Potential of Scientists and Their Innovations

In the past few years, I have been spending much of my time with researchers, professors, and deep tech founders sitting on remarkable breakthroughs and asking a difficult question:

What does it take to turn this innovation into a world-class company?

That question has become central to how I think about this chapter of my life.

This month marks the fifth anniversary of the Wattpad acquisition in 2021. That milestone naturally invites reflection. I am deeply grateful for that chapter and everything I learned from it, but I have 100% moved on.

Why?

Because I have even more fire in the belly for what comes next.

People sometimes ask me: Do I miss operating? Why am I doing this now? Why not just start another company and do it all over again?

Those questions all lead to a deeper one:

What does winning look like for me now?

For me, winning has always been about impact. Of course, many other things matter too. But without impact, I am not interested.

That has not changed.

What has changed is where I believe my experience is most useful, where I can have the highest-leverage impact, and what kind of challenge I feel most drawn to now.

I have no interest in simply repeating the last chapter. I have already co-founded and led one iconic company that reached 100 million users globally and became a cultural phenomenon. Fewer than two hundred companies in the world have achieved that 100-million-user milestone. Even fewer founders have stayed for the full marathon, from the first user all the way to a home run.

Rather than taking it easy, I want a new and even more ambitious challenge.

I have come to believe that one of the most important challenges in deep tech today is helping scientists and deep tech founders cross the very difficult bridge from scientific and engineering breakthrough to building a world-class company.

That is the work I feel most drawn to now. It is also work I feel unusually prepared for.

I started three companies. Between them, I have seen almost every major founder outcome: one VC-backed failure as CTO with tons of very stupid mistakes, one bootstrapped company as CEO with a small exit, and one VC-backed home run in Wattpad as CEO.

From the outside, Wattpad looked deceptively simple. In reality, it became an incredibly complex global business spanning consumer, enterprise, subscriptions, virtual goods, social media, frontier technology, traditional publishing, entertainment, and even geopolitics.

We were one of the pioneers in UGC and mobile, before the iPhone even existed. Over time, Wattpad also became a deep tech company. We started building our first of many proprietary machine learning models around 2013, long before most people had even heard of AI. That shaped how I think about technology disruption and how real technical innovation becomes an enduring advantage.

I also lived through strategic investors, IPO preparation, multi-bidder acquisition processes, the constant need to disrupt and reinvent ourselves, moments when tech giants were clearly trying to kill us, and a few phoenix-from-the-ashes moments.

I do not say any of this to dwell on the past. I say it because seeing that many startup permutations from the inside gives you a massive toolbox of practical judgment and wisdom.

Those tools were built and tested through real-world operating experience from day one, scaling a business into a world-class company while enduring the full roller-coaster ride.

You learn them by starting a company when the market is not ready. You learn them by doing things no one has done before. You learn them by making painful mistakes. You learn them by carrying a company through long periods when it is working, but not yet obvious. You learn them by navigating the transition from prototype to product, from product to business, from business to company, and from startup to an enduring world-class venture.

That sequence matters deeply in what I do now, because very few people have lived it end to end: a breakthrough is not yet a product. A product is not yet a business. And a business is not yet an enduring, world-class company.

The bridge between those stages is turning innovation into product and then commercializing it. That is where many promising breakthroughs fail. Not because the innovation is weak, but because turning groundbreaking innovation into a world-class company requires a different set of skills and judgments: timing, technical moat, customer need, business model, smart capital, team building, endurance, and grit.

You need to understand how all of the pieces connect and work together to build a world-class company.

I now know what I did not know.

That belief sits at the center of how I now spend my time. My mission is to unleash the full potential of scientists and their innovations by helping them become entrepreneurs and build world-class companies.

That, more than anything else, is what this chapter is about for me.

That is also part of what makes TSF distinctly TSF.

We are not trying to be a generic early-stage fund. Across our whole investment team, without exception, we bring together a combination that is very rare in venture globally: deep technical chops, real-world operating experience, scar tissue from world-class company building, and a mission-driven commitment to helping scientists and technical founders build enduring, world-class companies. We are also proven full-cycle investors with the experience of backing multiple companies of exceptional scale.

To me, TSF is not simply an investment platform. It is one of the highest-leverage ways I can apply what I have learned to make the greatest impact.

Building one iconic world-class company is hard. Leveraging that experience to help build multiple world-class companies may be even harder.

That is the challenge I want.

The next chapter started four years ago when I stepped down as Wattpad CEO, and I have been building into it ever since.

I am entering this next stretch with a lot of fire in the belly and 100% commitment. For me, that is what winning looks like.

P.S. Don’t forget, I am moving from Allen’s Thoughts to my new Substack: recoveringceo.substack.com.

While I will continue to post here for the time being, please take 30 seconds to subscribe to my new Substack, A Recovering CEO’s Thoughts by Allen Lau.

Announcing Our Investment in Tiptree Systems: Extending the AI Research Commons

We are super excited to share our investment in Tiptree Systems!

Founded in Montreal by two Mila AI researchers, Dr. Martin Weiss and Nasim Rahaman, Tiptree is building an AI-native researcher and knowledge network: infrastructure for how AI researchers share, exchange, and advance knowledge.

There is an irony here. AI has advanced remarkably quickly, yet until now, there has not really been an AI-native way for AI researchers themselves to share knowledge and build on one another’s work. Tiptree is solving that problem.

This is exactly the kind of company that fits our thesis at Two Small Fish. We invest in technologies that can reshape large-scale behaviour, enabled by foundational shifts in computing. The collapsing cost of intelligence is changing not only how software is built but also how work gets done. It is also changing how knowledge can be organized, explored, and shared.

That is what makes Tiptree so interesting to us.

My partner, Brandon, himself an AI scientist, and I wrote more about why we invested. Here is our blog post on Two Small Fish’s website.

Uniquely World Class

Every VC says they back high-quality companies.

That is like saying humans need to sleep, eat, and drink. True, yes. Useful, no.

The more important question is: what does “high quality” actually mean in venture?

For us, it means the potential to become uniquely world class.

A company that can become the clear winner in an important category. A company with real moats. A company that can build something enormous.

This is why we spend so much time trying to understand what is truly unique about a company. Not what is interesting. Not what demos well. Not what sounds differentiated in a pitch deck. Not what the ARR is today. What is actually hard to replicate? What gets stronger over time? What creates a widening gap versus everyone else? And the only way to know is to spend time with these deep tech founders and really understand how the technology, the product, and the company work.

I have written a long blog post on this topic on Two Small Fish’s website. Here is the link.

100 Years of the Canadian Iron Ring and a Uniquely World Class Vow of Trust

I spent Saturday morning in Hong Kong as a speaker at the Canadian Engineering Asia Pacific Conference, a gathering that felt historic.

Not one, not two, but eight deans of Canadian engineering. In the same room, on the same program, in Asia. The conference materials called it a “historic gathering,” and that’s not an exaggeration.

Hong Kong is the perfect place for this to happen. It has a very large base of Canadian engineering alumni. You could feel it immediately. The electromagnetic pull of hundreds of iron rings in the room. A community that’s stayed connected not just to each other, but to an idea.

And despite the diversity of schools, disciplines, and career paths represented, the conference kept circling back to a single word.

Trust.

Yes, one panel was explicitly about modern engineering ethics and building trust. It was moderated by Dean Kevin Deluzio (Queen’s University) and featured Dean Heather Sheardown (McMaster University), Dean Mary Wells (University of Waterloo), and Dean Caroline Cao (University of Ottawa). What struck me was how the theme showed up everywhere else too. Education, innovation, even the informal hallway conversations. Trust wasn’t a topic. It was the subtext.

This is where Canadian engineering has something uniquely world class to contribute. Why? Because we have a cultural and professional tradition that keeps pulling us back to first principles. What we build touches people. And we take an oath to uphold high ethical standards, safety, and integrity in our professional work. That oath is not performative. It is a commitment the public can hold us to. That is trust.

This conference also marked 100 years since the Calling of an Engineer tradition began in 1925, a uniquely Canadian ritual built around that vow, to uphold high ethical standards, safety, and integrity in our professional work.

That vow is trust.

My panel focused on the future of engineering education, and it was moderated by Dean Chris Yip (University of Toronto). I had the privilege of sharing the stage with Dean Phillip Choi (University of Regina), Dean James Olsen (University of British Columbia), and Dean Viviane Yargeau (McGill University). I shared a view that we are going through a platform shift driven by AI disruption. It is a foundational change that will reshape every sector and touch every aspect of our lives, including university education, where AI can reshape how university students learn and how courses are designed.

That is why I also believe this may be the best time to become an engineer. As an early stage investor in the next frontier of computing and its applications, I get to see this shift firsthand every day. The collapsing cost of intelligence, and hence abundance, is changing what is possible, and it is creating the conditions for entirely new category defining companies.

The most moving part of the day was the re obligation ceremony, hundreds of Canadian engineers forming a human chain to renew our vows.

Standing there, I was reminded of something simple. Canada’s brand, when we earn it, is built on trustworthiness.

Trust becomes a competitive advantage for Canada. But it’s not something you declare. It’s something you practice day in and day out.

That’s what the iron ring symbolizes at its best, not nostalgia, not ceremony, but a commitment to be worthy of trust through ethics, safety, and integrity, in the work we do and the systems we leave behind.

A century in, the ring still does what it was meant to do. And right now, that feels more important than ever.

And on that note, I trust we do not have to wait another 100 years for the next one. Let’s do an Iron Ring 101 next year!

P.S. The group picture is only University of Toronto, so you can tell how big the crowd was. We have eight universities represented!

Portfolio Highlight: ABR’s Funding Round

Edge AI has been a key pillar of our Advanced Computing Hardware investments and a core part of our thesis for a long time. It is the same arc I wrote about in The Next Data Centre: Your Phone a while ago.

We need new architectures to meet the speed, security, and energy demands of the next frontier of computing and its applications, which is the lens I used in The Factory Analogy.

Our portfolio company Applied Brain Research (ABR) just achieved a new milestone: ABR announced the successful closure of its oversubscribed seed funding round, including investment from TSF as a lead investor, with Eva Lau joining the board.

ABR created and patented a new type of AI model, called state space models, to make AI smaller, faster, and more energy efficient than transformer models. State space models deliver real-time voice and time series intelligence without the cloud, built for privacy and efficiency. ABR’s first chip, TSP1, delivers real-time, fully on-device voice AI without the cloud. Full vocabulary speech-to-text and text-to-speech are now possible at under 30mW.

At the edge, every millisecond and every milliwatt count.

For context:

30mW is 100× less than a 3W LED lightbulb.
A data-center GPU lives in a different universe: an NVIDIA H200 NVL is up to 600W.

Now connect that to the three constraints that define the edge:

Speed: for voice and interaction, half a second is half a second too late. Cloud voice is “a terrible experience,” plagued by delays.
Security: shipping voice data to the cloud bakes in privacy risk by default — which is why we keep coming back to intelligence that stays close to the user, as Brandon argued in his post In Favour of Intelligence That Stays Put. ABR calls out “privacy concerns” as a core issue with cloud voice.
Energy: edge devices are constrained by battery life and on-device resources. ABR’s on-device voice numbers move this from “interesting” to “deployable.”

This is why ABR enables numerous new use cases that weren’t viable before in categories like AR, robotics, wearables, medical devices, and automotive.

Imagine AR glasses (or other wearables) that respond to your command in real time without draining the battery. Imagine a robot that reacts with no hesitation. Imagine a medical device that can provide insight securely, without exporting sensitive data. Imagine a car that can respond to voice commands even when the network is unreliable. These are just a few examples. The list can go on and on.

Or as Eva put it in ABR’s announcement: sophisticated voice AI doesn’t require the cloud.

Reflections from the Impact 2025 Summit

I had the opportunity to join a panel at the Impact 2025 Summit in Calgary, moderated by Raissa Espiritu, with Janet Bannister and Paul Godman. Ironically, none of us are labelled as impact investors, and I explained on stage why Two Small Fish Ventures does what we do.

At Two Small Fish Ventures, we’ve never called ourselves an impact fund. That’s not because we’re indifferent to impact; in fact, it’s core to what we do. Our focus is on deep tech, the next frontier of computing, where innovation can create meaningful, long-term change. Specifically, we invest in five key areas: Vertical AI Platforms, Physical AI, AI Infrastructure, Advanced Computing Hardware, and Smart Energy.

We care deeply about scientific advancement, and more importantly, about turning those breakthroughs into real-world impact. That’s how meaningful progress happens.

Eva is our General Partner, and both of us are immigrants. Diversity isn’t a marketing point for us; it’s part of who we are. It naturally shows up in our portfolio: about half of our companies have at least one female founder, and many come from underrepresented backgrounds. That said, uncompromisingly, we back amazing deep tech founders who are turning their creations into world-class companies.

It’s actually rare that we talk about topics like women investing or investing in underrepresented groups in isolation. Not because we don’t care, quite the opposite. The fact that Eva is one of the few female GPs leading a venture fund, and that we’re both immigrants, already says a lot. Our actions speak volumes. We walk the walk and talk the talk.

We need to deliver results. Period. Our competition isn’t other venture funds; it’s every other investment opportunity available in the market. If we can’t perform at the highest level — top decile in everything we do — we can’t sustain our mission. Delivering some of the best results in the industry enables us to do what we love and make an impact.

That’s why I believe impact and performance are not opposites. The most powerful kind of impact happens when companies succeed, when they become world-class companies. Strong returns and meaningful impact can, and should, reinforce each other.

I also talked about the importance of choosing the right vehicle for the right purpose. When we made a 2 million dollar donation to the University of Toronto to establish the Commercialization Catalyst Prize, it wasn’t about investing. It was about supporting a different kind of impact — helping scientists and engineers turn their research into innovations that can reach the world. Not every kind of impact should come from the same tool.

At the end of the day, labels matter less than intent and execution. We don’t need to call ourselves an impact fund to make a difference. Our goal is simple: to back bold deep tech founders using science and technology to build a better future and to do it with excellence.

A big thank you to Raissa, George Damian, Sylvia Wang, and the entire Platform Calgary team for putting together such a thoughtful and well-run event.

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This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.

Quantum: From Sci-Fi to Investable Frontier

When I was studying electrical engineering, out of my curiosity, I chose to take an elective course on quantum physics as part of advanced optics. It sparked my curiosity in quantum. The strange, abstract, counterintuitive rules, for example particles existing in multiple states or being entangled across distance, captivated me.

Error correction, closely related to fault tolerance in quantum systems today, is the backbone of telecommunications, one of the areas I majored in.

Little did I know these domains would converge in such a way that my earlier academic training would become relevant again years later.

For me, computing is not just my profession, it is also my hobby. As a science nerd, I actively enjoy following advances, and I keep going deeper down the rabbit hole of the next frontier of computing. That mix of personal curiosity and professional focus shapes how I approach both the opportunities and risks in the space. Over the past few years, I have gone deeper into the world of quantum. My academic and professional background gave me the footing to evaluate both what is technically possible and what is commercially viable.

From If to How and When

In June, I wrote Quantum Isn’t Next. It’s Now. We have passed the tipping point where the question is no longer if quantum technology will work, it is how and when it will scale.

This momentum is not just visible to those of us deep in the field. As the Globe and Mail recently reported, we at Two Small Fish have been following quantum for years, but did not think it was mature enough for an early-stage fund with a 10-year lifespan to back. This year, we changed our minds. As I shared in that article: “It’s much more investible now.”

The distinction is clear: when quantum was still a science problem, the central question was whether it could work at all. Now that it has become an engineering problem, the questions are how it will work at scale and when it will be ready for commercialization.

This shift matters for investors. Venture capital focuses on engineering breakthroughs, hard, uncertain, but achievable on a commercialization timeline. Fundamental science, which can take many more years to mature, is better supported by governments, universities, and non-dilutive funding sources. I will leave that discussion for another post.

One of Five Frontiers

At Two Small Fish Ventures, we have identified five areas shaping the next frontier of computing. Quantum falls under the area of advanced computing hardware, where the convergence of different areas of science, engineering, and commercialization is accelerating.

Each of these areas is no longer a speculative science experiment but a rapidly advancing field where engineering and commercialization are converging. Within the next ten years, the winners will emerge from lab prototypes and become scaled companies. Quantum is firmly on that trajectory.

How We Invest in Quantum

Our first principle at Two Small Fish is straightforward: we only invest in things we truly understand, from all three technology, product, and commercialization lenses. That discipline forces us to dig deep before committing capital. And after years of study, it is clear to us that quantum has moved into investable territory, but only selectively.

Not every quantum startup fits a venture time horizon. Some promising projects will take too many years to scale. But we are now seeing opportunities that, within a 10-year window, can realistically grow from an early-stage idea to a successful scale-up. That is the standard we apply to every investment, and quantum finally has companies that meet it.

From Sci-Fi to Reality

Canada has played an outsized role in building the foundation of quantum science. Now, it has the chance to lead in quantum commercialization. The next few years will determine which teams turn breakthrough science into enduring companies.

For investors, this is both an opportunity and a responsibility. The quantum era is not a distant possibility, it is here now. What once sounded like science fiction is now an investable reality. And for those willing to put in the work to understand it, the frontier is already here.

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Jevons Paradox: Why Efficiency Fuels Transformation

In 1865, William Stanley Jevons, an English economist, observed a curious phenomenon: as steam engines in Britain became more efficient, coal use didn’t fall — it rose. Efficiency lowered the cost of using coal, which made it more attractive, and demand surged.

That insight became known as Jevons Paradox. To put it simply:

Technological change increases efficiency or productivity.
Efficiency gains lead to lower consumer prices for goods or services.
The reduced price creates a substantial increase in quantity demanded (because demand is highly elastic).

Instead of shrinking resource use, efficiency often accelerates it — and with it, broader societal change.

Coal, Then Light

The paradox first appeared in coal: better engines, more coal consumed. Electricity followed a similar path. Consider lighting in Britain:

Period	True price of lighting (per million lumen-hours, £2000)	Change vs. start	Per-capita consumption (thousand lumen-hours)	Change vs. start	Total consumption (billion lumen-hours)	Change vs. start
1800	£8,000	—	1.1	—	18	—
1900	£250	↓ ~30×	255	↑ ~230×	10,500	↑ ~500×
2000	£2.5	↓ ~3,000× (vs. 1800) / ↓ ~100× (vs. 1900)	13,000	↑ ~13,000× (vs. 1800) / ↑ ~50× (vs. 1900)	775,000	↑ ~40,000× (vs. 1800) / ↑ ~74× (vs. 1900)

Over two centuries, the price of light fell 3,000×, while per-capita use rose 13,000× and total consumption rose 40,000×. A textbook case of Jevons Paradox — efficiency driving demand to entirely new levels.

Computing: From Millions to Pennies

This pattern carried into computing:

Year	Cost per Gigaflop	Notes
1984	$18.7 million (~$46M today)	Early supercomputing era
2000	$640 (~$956 today)	Mainstream affordability
2017	$0.03	Virtually free compute

That’s a 99.99%+ decline. What once required national budgets is now in your pocket.

Storage mirrored the same story: by 2018, 8 TB of hard drive storage cost under $200 — about $0.019 per GB, compared to thousands per GB in the mid-20th century.

Connectivity: Falling Costs, Rising Traffic

Connectivity followed suit:

Year	Typical Speed & Cost per Mbps (U.S.)	Global Internet Traffic
2000	Dial-up / early DSL (<1 Mbps); ~$1,200	~84 PB/month
2010	~5 Mbps broadband; ~$25	~20,000 PB/month
2023	100–940 Mbps common; ↓ ~60% since 2015 (real terms)	>150,000 PB/month

(PB = petabytes)

As costs collapsed, demand exploded. Streaming, cloud services, social apps, mobile collaboration, IoT — all became possible because bandwidth was no longer scarce.

Intelligence: The New Frontier

Now the same dynamic is unfolding with intelligence:

Year	Cost per Million Tokens	Notes
2021	~$60	Early GPT-3 / GPT-4 era
2023	~$0.40–$0.60	GPT-3.5 scale models
2024	< $0.10	GPT-4o and peers

That’s a two-order-of-magnitude drop in just a few years. Unsurprisingly, demand is surging — AI copilots in workflows, large-scale analytics in enterprises, and everyday generative tools for individuals.

As we highlighted in our TSF Thesis 3.0, cheap intelligence doesn’t just optimize existing tasks. It reshapes behaviour at scale.

Why It Matters

The recurring pattern is clear:

Coal efficiency fueled the Industrial Revolution.
Affordable lighting built electrified cities.
Cheap compute and storage enabled the digital economy.
Low-cost bandwidth drove streaming and cloud collaboration.
Now cheap intelligence is reshaping how we live, work, and innovate.

As we highlighted in Thesis 3.0:

“Reflecting on the internet era… as ‘the cost of connectivity’ steadily declined, productivity and demand surged—creating a virtuous cycle of opportunities. The AI era shows remarkable parallels. AI is the first technology capable of learning, reasoning, creativity… Like connectivity in the internet era, ‘the cost of intelligence’ is now rapidly declining, while the value derived continues to surge, driving even greater demand.”

The lesson is simple: efficiency doesn’t just save costs — it reorders economies and societies. And that’s exactly what is happening now.

If you are building a deep tech early-stage startup in the next frontier of computing, we would like to hear from you. This is a generational opportunity as both traditional businesses and entirely new sectors are being reshaped. White-collar jobs and businesses, in particular, will not be the same. We would love to hear from you.

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Five Areas Shaping the Next Frontier

The cost of intelligence is dropping at an unprecedented rate. Just as the drop in the cost of computing unlocked the PC era and the drop in the cost of connectivity enabled the internet era, falling costs today are driving explosive demand for AI adoption. That demand creates opportunity on the supply side too, in the infrastructure, energy, and technologies needed to support and scale this shift.

In our Thesis 3.0, we highlighted how this AI-driven platform shift will reshape behaviour at massive scale. But identifying the how also means knowing where to look.

Every era of technology has a set of areas where breakthroughs cluster, where infrastructure, capital, and talent converge to create the conditions for outsized returns. For the age of intelligent systems, we see five such areas, each distinct but deeply interconnected.

1. Vertical AI Platforms

After large language models, the next wave of value creation will come from Vertical AI Platforms that combine proprietary data, hard-to-replicate models, and orchestration layers designed for complex and large-scale needs.

Built on unique datasets, workflows, and algorithms that are difficult to imitate, these platforms create proprietary intelligence layers that are increasingly agentic. They can actively make decisions, initiate actions, and shape workflows. This makes them both defensible and transformative, even when part of the foundation rests on commodity models.

This shift from passive tools to active participants marks a profound change in how entire sectors operate.

2. Physical AI

The past two decades of digital transformation mostly played out behind screens. The next era brings AI into the physical world.

Physical AI spans autonomous devices, robotics, and AI-powered equipment that can perceive, act, and adapt in real environments. From warehouse automation to industrial robotics to autonomous mobility, this is where algorithms leave the lab and step into society.

We are still early in this curve. Just as industrial machinery transformed factories in the nineteenth century, Physical AI will reshape industries that rely on labour-intensive, precision-demanding, or hazardous work.

The companies that succeed will combine world-class AI models with robust hardware integration and build the trust that humans place in systems operating alongside them every day.

3. AI Infrastructure

Every transformative technology wave has required new infrastructure that is robust, reliable, and efficient. For AI, this means going beyond raw compute to ensure systems that are secure, safe, and trustworthy at scale.

We need security, safety, efficiency, and trustworthiness as first-class priorities. That means building the tools, frameworks, and protocols that make AI more energy efficient, explainable, and interoperable.

The infrastructure layer determines not only who can build AI, but who can trust it. And trust is ultimately what drives adoption.

4. Advanced Computing Hardware

Every computing revolution has been powered by a revolution in hardware. Just as the transistor enabled mainframes and the microprocessor ushered in personal computing, the next era will be defined by breakthroughs in semiconductors and specialized architectures.

From custom chips to new communication fabrics, hardware is what makes new classes of AI and computation possible, both in the cloud and on the edge. But it is not only about raw compute power. The winners will also tackle energy efficiency, latency, and connectivity, areas that become bottlenecks as models scale.

As Moore’s Law hits its limit, we are entering an age of architectural innovation with neuromorphic computing, photonics, quantum computing, and other advances. Much like the steam engine once unlocked new industries, these architectures will redefine what is computationally possible. This is deep tech meeting industrial adoption, and those who can scale it will capture immense value.

5. Smart Energy

Every technological leap has demanded a new energy paradigm. The electrification era was powered by the grid. Today, AI and computing are demanding unprecedented amounts of energy, and the grid as it exists cannot sustain this future.

This is why smart energy is not peripheral, but central. From new energy sources to intelligent distribution networks, the way we generate, store, and allocate energy is being reimagined. The idea of programmable energy, where supply and demand adapt dynamically using AI, will become as fundamental to the AI era as packet switching was to the internet.

Here, deep engineering meets societal need. Without resilient and efficient energy, AI progress stalls. With it, the future scales.

Shaping What Comes Next

The drop in the cost of intelligence is driving demand at a scale we have never seen before. That demand creates opportunity on the supply side too, in the platforms, hardware, energy, physical systems, and infrastructure that make this future possible.

The five areas — Vertical AI Platforms, Physical AI, AI Infrastructure, Advanced Computing Hardware, and Smart Energy — represent the biggest opportunities of this era. They are not isolated. They form an interconnected landscape where advances in one accelerate breakthroughs in the others.

We are domain experts in these five areas. The TSF team brings technical, product and commercialization expertise that helps founders build and scale in precisely these spaces. We are uniquely qualified to do so.

At Two Small Fish, this is the canvas for the next generation of 100x companies. We are excited to partner with the founders building in these areas globally, those who not only see the future, but are already shaping it.

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Legends of Semiconductors: The Only Dinner Where the Edition Number Matters

At most dinners, introductions start with your name and maybe what you do.

At this one, we began with:
“Second edition.”
“Fourth edition.”

Why? Because this was our “School of Fish – Legends of Semiconductors” dinner, hosted at our home, where your relationship with the Sedra & Smith textbook was the common thread.
(I’m second edition, if you’re wondering.)

We were incredibly honoured to have Dr. Adel Sedra, former Dean of Engineering at the University of Waterloo, join us. Recently appointed to the Order of Canada, Dr. Sedra is a towering figure in the world of electrical engineering. Since 1982, his textbook has taught more than three-quarters of the world’s electrical engineers. It is hard to find someone in the field who has not studied from it. I consider myself extraordinarily fortunate, not just to have learned from his book, but to have been his student more than 30 years ago at the University of Toronto. Few have had the privilege of learning directly from a legend.

We were equally honoured to host Benny Lau, co-founder of ATI Technologies, whose legacy lives on in AMD’s GPUs to this day. AMD acquired ATI for $5.4 billion nearly 20 years ago, still one of the largest tech acquisitions in Canadian history. When Eva worked at ATI, she had the chance to work closely with Benny. His presence brought our conversation full circle, from classroom to commercialization. Adding even more depth to the evening, Benny was also once a student of Dr. Sedra. Two generations of engineers at the same table, both shaped by the same teacher.

From left to right: Benny Lau, Eva Lau, Ljubisa Bajic

This evening was also a chance to reconnect with those who shaped my own journey. Martin Snelgrove and Raymond Chik, my professor and TA respectively, were both there and are now serial entrepreneurs. They are also co-founders of Hepzibah, a Two Small Fish portfolio company. (I still can’t help but sometimes call him Professor Snelgrove.) Xerxes Wania, another one of my TAs from back in the day, went on to build and exit two semiconductor companies and added his voice to the conversation.

From left to right: Xerxes Wania, Dr. Adel Sedra, Allen Lau, Martin Snelgrove, Raymond Chik

We were also joined by Ljubisa Bajic, former CEO of TensTorrent and now CEO of Taalas, who also spent part of his career at ATI, further adding to the thread that connected many of us. Chris Yip, Dean of Engineering at the University of Toronto, and Deepa Kundur, current Chair of U of T’s Department of Electrical & Computer Engineering—continuing the legacy of leadership that Dr. Sedra once held in that position—also attended. Professor Tony Chan Carusone, now also CTO of Alphawave Semi and coauthor of the Sedra & Smith textbook starting with the 8th edition, brought both academic and commercial perspectives to the table.

From the TSF portfolio side, we were thrilled to have Professor Doug Barlage of the University of Alberta and Professor Chris Eliasmith of the University of Waterloo, co-founders of Zinite and ABR, respectively.

And of course, our partner Dr. Albert Chen joined us. He is a graduate of Waterloo Engineering and knows a thing or two about semiconductors himself.

Semiconductors brought us together that night.
Textbook and tapeout were what we talked about, and we all loved them.

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Computing. Then Connectivity. Then Intelligence. For Half a Century, Cost Collapses Drove Massive Adoption.

In the history of human civilization, there have been several distinct ages: the Agricultural Age, the Industrial Age, and the Information Age, which we are living in now.

Within each age, there are different eras, each marked by a drastic drop in the cost of a fundamental “atomic unit.” These cost collapses triggered enormous increases in demand and reshaped society by changing human behaviour at scale.

From the late 1970s to the 1990s, the invention of the personal computer drastically reduced the cost of computing [1]. A typical CPU in the early 1980s cost hundreds of dollars and ran at just a few MHz. By the 1990s, processors were orders of magnitude faster for roughly the same price, unlocking entirely new possibilities like spreadsheets and graphical user interfaces (GUIs).

Then, from the mid-1990s to the 2010s, came the next wave: the Internet. It brought a dramatic drop in the cost of connectivity [2]. Bandwidth, once prohibitively expensive, fell by several orders of magnitude — from over $1,200 per Mbps per month in the ’90s to less than a penny today. This enabled browsers, smartphones, social networks, e-commerce, and much of the modern digital economy.

From the mid-2010s to today, we’ve entered the era of AI. This wave has rapidly reduced the cost of intelligence [3]. Just two years ago, generating a million tokens using large language models cost over $100. Today, it’s under $1. This massive drop has enabled applications like facial recognition in photo apps, (mostly) self-driving cars, and — most notably — ChatGPT.

These three eras share more than just timing. They follow a strikingly similar pattern:

First, each era is defined by a core capability, i.e. computing, connectivity, and intelligence respectively.

Second, each unfolds in two waves:

The initial wave brings a seemingly obvious application (though often only apparent in hindsight), such as spreadsheets, browsers, or facial recognition.
Then, typically a decade or so later, a magical invention emerges — one that radically expands access and shifts behaviour at scale. Think GUI (so we no longer needed to use a command line), the iPhone (leapfrogging flip phones), and now, ChatGPT.

Why does this pattern matter?

Because the second-wave inventions are the ones that lower the barrier to entry, democratize access, and reshape large-scale behaviour. The first wave opens the door; the second wave throws it wide open. It’s the amplifier that delivers exponential adoption.

We’ve seen this movie before. Twice already, over the past 50 years.

The cost of computing dropped, and it transformed business, productivity, and software.

Then the cost of connectivity dropped, and it revolutionized how people communicate, consume, and buy.

Now the cost of intelligence is collapsing, and the effects are unfolding even faster.

Each wave builds on the last. The Internet era was evolving faster than the PC era because the former leveraged the latter’s computing infrastructure. AI is moving even faster because it sits atop both computing and the Internet. Acceleration is not happening in isolation. It’s compounding.

If it feels like the pace of change is increasing, it’s because it is.

Just look at the numbers:

Windows took over 2 years to reach 1 million users.
Facebook got there in 10 months.
ChatGPT did it in 5 days.

These aren’t just vanity metrics — they reflect the power of each era’s cost collapse to accelerate mainstream adoption.

That’s why it’s no surprise — in fact, it’s crystal clear — that the current AI platform shift is more massive than any previous technological shift. It will create massive new economic value, shift wealth away from many incumbents, and open up extraordinary investment opportunities.

That’s why the succinct version of our thesis is:

We invest in the next frontier of computing and its applications, reshaping large-scale behaviour, driven by the collapsing cost of intelligence and defensible through tech and data moats.

(Full version here).

The race is already on. We can’t wait to invest in the next great thing in this new era of intelligence.

Super exciting times ahead indeed.

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Footnotes

[1] Cost of Computing

In 1981, the Intel 8088 CPU (used in the first IBM PC) had a clock speed of 4.77 MHz and cost ~$125. By 1995, the Intel Pentium processor ran at 100+ MHz and cost around $250 — a ~20x speed gain at similar cost. Today’s chips are thousands of times faster, and on a per-operation basis, exponentially cheaper.

[2] Cost of Connectivity

In 1998, bandwidth cost over $1,200 per Mbps/month. By 2015, that figure dropped below $1. As of 2024, cloud bandwidth pricing can be less than $0.01 per GB — a near 100,000x drop over 25 years.

[3] Cost of Intelligence

In 2022, generating 1 million tokens via OpenAI’s GPT-3.5 could cost $100+. In 2024, it costs under $1 using GPT-4o or Claude 3.5, with faster performance and higher accuracy — a 100x+ reduction in under two years.

Quantum Isn’t Next. It’s Now.

In the early 2000s, it was a common joke in the tech world that “next year is the year of the smartphones.” People kept saying it over and over for almost a decade. It became a punchline. The industry nearly lost its credibility.

Until the iPhone launched. “Next year is the year of the smartphones” finally became true.

The same joke has followed quantum for the past ten years: next year is the year of quantum.

Except it hasn’t been. Not yet.

And yet, quietly, the foundations have been built. We’re not there, but we’re far from where we started.

We’re getting closer. Much closer. I can smell it. I can hear it. I can sense it.

Right now, without getting into too much technical detail, we’re still at a small scale: fewer than 100 usable qubits. Commercial viability likely requires thousands, if not millions. The systems are still too error-prone, and hosting your own quantum machine is wildly impractical. They’re expensive, fragile, and noisy.

At this stage, quantum is mostly limited to niche or small-scale applications. But step by step, quantum is inching closer to broader utility.

And while these things don’t progress in straight lines, the momentum is real and accelerating.

Large-scale, commercially deployable, fault-tolerant quantum computers accessed through the cloud are no longer science fiction. They’re within reach.

I spent a few of my academic years in signal processing and error correction. I’ve also spent a bit of time studying quantum mechanics. I understand the challenges of cloud-based access to quantum systems, and I’ve been following the field for quite a while, mostly as a curious science nerd.

All of that gives me reason to trust my sixth sense. Quantum is increasingly becoming a reality.

Nobody knows exactly when the iPhone moment or the ChatGPT moment of quantum will happen.
But I’m absolutely sure we won’t still be saying “next year is the year of quantum” a decade from now.

It will happen, and it will happen much sooner than you might think.

At Two Small Fish, our thesis is centred around the next frontier of computing and its applications.

This is an exciting time and the ideal time to take a closer look at quantum, because the best opportunities tend to emerge right before the technology takes off.

How can we not get excited about new quantum investment opportunities?

P.S. I’m excited to attend the QUANTUM NOW conference this week in Montreal. Also thrilled to see Mark Carney name quantum as one of Canada’s official G7 priorities. That short statement may end up being a big milestone.

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A Decade of Fish – Celebrating 10 Years of Two Small Fish Ventures

This year marks a big milestone: Two Small Fish Ventures turns ten!

That’s 10 years, 120 months, and 3,653 days (yes, we counted the leap years). What started as a bold experiment in early-stage investing has become a decade-long journey of backing audacious founders building at the edge of what’s possible.

Over the weekend, we wired funds for our 60th first investment. That’s not including the many follow-on cheques we’ve written along the way—if we counted those, the number would be much higher. We’re not naming the company just yet, but like the 59 before it, this one reflects deep conviction. We think it’ll make a splash!

For years, we’ve said we write 5 to 7 new cheques per year. Not because we aim for a quota, but because this is what a power-law portfolio construction strategy naturally produces. In venture, just a few outlier companies drive the vast majority of returns. The trick is to consistently back companies with 100x potential. That’s the focus—not pacing. And yet, the numbers tell their own story: we’ve averaged exactly six new investments a year. Apparently, clarity of focus brings consistency as a byproduct.

We’re now six months into our tenth year, and we’re right on pace.

To the founders we’ve backed: thank you for trusting us at the earliest, riskiest stage.

To those we haven’t met yet: if you’re building deep tech in the next frontier of computing, we’d love to hear from you. We invest globally. If you’ve got a breakthrough, we can help turn it into a product. If you’ve got a product, we can help turn it into a company.

Sound like you? Reach out.

Here’s to the next 10!

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Contrarian Series: Your TAM is Zero? We love it!

Note: One of the most common pieces of feedback we receive from entrepreneurs is that TSF partners don’t think, act, or speak like typical VCs. The Contrarian Series is meant to demystify this, so founders know more about us before pitching.

Just before New Year, I was speaking at the TBDC Venture Day Conference together with BetaKit CEO Siri Agrell and Serial Entrepreneur and former MP Frank Baylis.

When I said “Two Small Fish love Zero TAM businesses,” I said it so matter-of-factly that the crowd was taken aback. I even saw quite a few posts on social media that said, “I can’t believe Allen Lau said it!”

Of course, any business will need to go after a non-zero TAM eventually. But hear me out.

Here’s what I did at Wattpad: I never had a “total addressable market” slide in the early days. I just said, “There are five billion people who can read and write, and I want to capture them all!”

Even when we became a scaleup, I kept the same line. I just said, “There are billions of people who can read, write, or watch our movies, and I want to capture them all!”

Naturally, some VCs tried to box me into the “publishing tool” category or other buckets they deemed appropriate. But Wattpad didn’t really fit into anything that existed at the time. Trust me, I tried to find a box I would fit in too, but none felt natural.

Why? That’s because Wattpad was a category creator. And, of course, that meant our TAM was effectively zero.

In other words, we made our own TAM.

Many of our portfolio companies are also category creators, so their decks often don’t have a TAM slide either.

Yes, any venture-backed company eventually needs a large TAM. And, of course, I don’t mean to suggest that every startup needs to be a category creator.

That said, we’re perfectly fine—in fact, sometimes we even prefer—seeing a pitch deck without a TAM slide. By definition, category creators have first-mover advantages. More importantly, category creators in a large, winner-take-all market—especially those with strong moats—tend to be extremely valuable at scale and, hence, highly investable.

So, founders, if your company is poised to create a large category, skip the TAM slide when pitching to Two Small Fish. We love it!

P.S. Don’t forget, if you have an “exit strategy” slide in your pitch deck, please remove it before pitching to us. TYSM!

It’s The Final Curtain Call. A New Story Begins.

After spending 15 years at the helm of Wattpad, today I am starting a new role as Executive Advisor to the WEBTOON family of brands. That’s right, I’m stepping aside as CEO of Wattpad to apply my experience and skills to this new role alongside my other activities as an investor and board member.

As I reflect on the journey of building Wattpad over the years I am amazed at what I’ve accomplished together with my co-founder Ivan Yuen and the entire Wattpad team.

What started as a place to read and write stories on your mobile device, has grown into a product and community loved by close to 100 million people.

We pioneered storytelling technology, changed how people read, write and engage with fictional stories, and transformed the entertainment and publishing industries. Leveraging our massive built-in fandoms and data, we turned numerous top Wattpad stories into hit movies, TV shows, and bestselling books. These movies and shows have topped the box office and ‘most watched’ charts on streaming services, gone on to win Teen Choice Awards, a People’s Choice Award, and even received Emmy nominations, and all have changed the lives of a new generation of creators. It’s been an honour and privilege to democratize who gets to tell their story and redefine how the world reads and shares fiction.

We raised record amounts of capital at the time from top-tier investors in Canada, US, and Asia. We were one of the first to commit to scaling our company in Toronto and then successfully proved you could build a world-class tech company here. We played a part in re-shaping the overall narrative of the innovation ecosystem in Canada.

These are the things you simply don’t think about when you’re starting out, writing code, and bringing an idea to life. To say I am incredibly proud is an understatement.

The past year was record-breaking for Wattpad. Since the acquisition – one of the largest for a Canadian technology company – we have never grown faster. With the Grand Plan in place, it’s the perfect time to pass the baton to Wattpad President Jeanne Lam and Wattpad WEBTOON Studios’ President Aron Levitz in leading the team to achieve the vision. With such strong leaders, Wattpad is in great hands.

I’ve always been a natural builder and I will continue to help build the “next big thing” as Executive Advisor to WEBTOON, as a venture partner of Two Small Fish Ventures, and board member of two of Canada’s most important cultural and innovation organizations, the Toronto International Film Festival and MaRS.

It has been a life-changing 15-year journey for me, my family, the Wattpad team, and millions of Wattpadders around the world. Thanks for all your support. Thanks for sharing all the emotions. Thanks for all the wonderful times and good memories. Thanks for being here with me. I can’t say thank you enough.

Calling this a new chapter or the next season would be a misnomer – it’s the final curtain call of my career as a CEO. But I’m not done yet! I’m still at the top of my game. I’m still hungry for more wins. I still want to make an even bigger impact. My new story begins today.

C100 Dinner

Last evening the Laus hosted an intimate dinner with a dozen of fellow C100 members in our backyard. After locking down for 18 months, we all appreciate what in-person gatherings can bring while pixels cannot. We had meaningful conversations about how the fantastic Canadian tech ecosystem can win in style on the global stage even more and many other topics. Thanks C100’s Lauren Howe for organizing and Andre Perey from Osler for co-hosting.

Look forward to more in-person gatherings as we are slowly but surely winning over the virus!

Strategic Partners Turn Your Vision Into Reality Faster Than You Can

A few months ago, Wattpad announced a partnership with Anvil Publishing in the Philippines. Together, we’re launching Bliss Books, a new Young Adult imprint that’ll bring some of the biggest Wattpad stories and authors to bookshelves across the country.

The news means Wattpad can realize the vision I laid out in the Master Plan much, much faster. But really, speed is just one of the values a strategic partner brings to the table.

Anvil also has deeper insights into local purchasing habits and consumer behaviour than we do. The first part of the Master Plan is to “Discover more great stories,” and we do this by leveraging our Story DNA machine learning technology and a passionate community to find unique voices and amazing stories that are validated in Tagalog. With their local insights, Anvil can corroborate our insights using their local knowledge to guarantee a successful adaptation.

The best strategic partners also have a reputation you can piggy-back off of. Another element of the Master Plan is ‘Turn these stories into great movies, TV shows, print books, etc.,” Anvil has a reputation for publishing high-quality books, and that’s exactly what we want to do.

Anvil is the publishing arm of the National Book Store with hundreds of bookstores. It’s established presence means we – through NBS – have the ability to distribute Wattpad books to every practically every part of the country tying into another key part of the Master Plan to “Distribute and monetize content on and off Wattpad and earn money for storytellers.”

The Philippines is one of Wattpad’s largest markets and a very important one since its home to some of our most passionate users. Plus, when you factor in the expertise and reach of Anvil, it was an easy decision to partner with this local company who can help us continue to celebrate and reward Filipino authors and their fans.

Entrepreneurs: if you have the ability to form a partnership with another complementary company, seize it. The strategic upside is great and may help you realize your vision faster than you ever could alone.

Your iteration rate is the key to finding product-market fit for your app

For any entrepreneur launching an app finding product-market fit is a lot like finding the Golden Ticket; it’s rare, but when it happens it’s life-changing.

Unlike an enterprise business, when you build a consumer app your end-user can’t easily tell you what they want (vs. enterprise apps that are focused on solving a known problem or a pain point for clients). Think about it this way: Before the iPhone launched, no consumer research would point out the need for a touchscreen, keyboardless device. Before Snapchat, no consumer would say they wanted the ability to send ephemeral messages.

Consumers aren’t able to tell you what they want; this makes consumer products a shot in the dark. There is no guarantee if or when product-market fit can be found. It’s usually a long journey of continuous iteration.

And ongoing iteration is what gets you to product-market fit. Each iteration gives you one extra at-bat. Hitting a home run is easy if you can strike out 10o times instead of 3. Y Combinator’s Sam Altman said it best in this tweet:

Finding product-market fit is hard. Look at how many consumer products Facebook and Google shut down even with their massive resources (remember FB Paper, FB Groups app, Google+ app?) Massive resources can help, but it’s not the most critical.

In the early days of Wattpad, despite only having a handful of employees, every day the product looked a bit different. We implemented new concepts in the morning, checked in the afternoon, measured overnight and killed it the next morning if it didn’t work out. That’s how we found product-market fit in many things. And that’s how we left our competitors in the dust.

Although finding product-market fit is freaking hard, it is also very fun and rewarding once you have figured it out.

Keep on iterating!

Don’t Be a Parasite If You Want To Be A Disruptor

I spoke with an entrepreneur whose company is building a new, disruptive product for the education sector. One of the challenges he’s facing is that none of the company’s co-founders have worked in the education sector before. He wondered if he should hire someone with some relevant experience.

Another entrepreneur friend of mine is building a tool that is catered to the public sector. The company is struggling to scale as a business. The sales process is too slow. The product is becoming too specific for one sector.

In both cases when these entrepreneurs asked for my advice, I told them: Don’t be a parasite if you want to be a disruptor.

There are so many verticals out there that still have not been fully transformed by the Internet — education, public sector, book publishing, the list goes one. But it’s extremely hard to transform any industry if you have a lot of dependencies with the old systems. You can’t think out of the box. Your sales cycle is too long. And often you end up with a product or a service that is incremental at best rather than revolutionary.

Now, there’s nothing wrong with that. In fact, a lot of people have built great businesses by providing incremental solutions like consulting services to the government. But, if you want to build something truly transformative and net-native, then you have to stay as far away from the traditional systems as possible and draw closer to your end users or customers.

If you want to create something truly game-changing and be a disruptor, you can’t begin the journey as a parasite.

When tech giants move next door

A slew of international tech companies – Google, Uber, Samsung, Microsoft, Amazon – have committed to or expressed interest in setting up shop in Toronto. If you’re a homegrown startup or scaleup you can’t help but think about the implications of having these giants in your backyard.

Companies often expand their footprint to lower costs, access specialized talent or for a host of other reasons. It’s not new. They aren’t the first international companies who want to set up shop in Toronto, and won’t be the last.

And why not? Toronto is a world-class city with some of the best universities in the world producing some of the finest technical and business talents. We’re home to an incredibly diverse community who have the perspective and understanding to solve global issues and build products and services that work for the world.

Colleagues and friends have recently been asking me for my take on these moves. Are they helpful or harmful to the city and the local tech ecosystem?

In my opinion, we should welcome these moves – but be wary of them.

When a few foreign companies decide to move to a burgeoning city, they can help build a critical mass that directly supports homegrown companies by spurring interest in the region. They attract high caliber talent and then provide opportunities for these employees to hone their skills and learn new ones so they can further develop into well-rounded and in-demand workers.

But too many foreign companies in a single locale can make it seem like they’ve colonized the area, leaving little room for local businesses. It gets too difficult to compete, too expensive to stay in your backyard. Think about this: If data is the new oil, do you really want all the ‘oil companies’ to be foreign-owned?

So it’s not a choice of either-or. Having zero international companies who operate locally won’t stimulate the ecosystem. With too many foreign companies, locals lose the ability to control their our own destiny, and eventually, ideas and innovation become stifled.

For now, I welcome these new companies into our backyard but make no mistake, it can never replace building our own homegrown giants. I’m certain that the incredible Toronto tech ecosystem will continue to make waves regardless of who moves next door.

Welcome to Allen’s Thoughts

I’m Allen and I’m a serial entrepreneur, angel investor and a champion of the Canadian startup ecosystem. Welcome to my new blog where I plan to share my ideas, insights and inspirations.

I like to write. Over the years I’ve probably shared in excess of 300,000 words. I’ve contributed to media outlets like Inc. and Entrepreneur. My previous blog, Making Things Out of Nothing, covered technology trends, my latest investments and company milestones. For several years, I’ve also maintained an internal blog to communicate with 100+ employees around the world. This private blog encompasses everything from company strategy to technology shifts to management advice. Through my internal blog, I created a lot of content that’s applicable to many people, but discoverable by few.

My hope is that this new blog changes that and becomes a central place for me to share the things I’m passionate about more broadly. And yes, of course, there will be a ton of new content as well. I know there is no shortage of business and tech insights available on the internet, but I believe I can offer a different perspective – from a scale-up or Canadian lens, for example – that sometimes can be difficult to find.

So what am I passionate about?

I’m passionate about entrepreneurship. I’ve launched three companies; the first one failed, I sold the second one, and the third, Wattpad, has grown from a reading and writing app, to a global entertainment powerhouse with a vision to entertain and connect the world through stories (and is well on its way). Both failures and successes have taught me valuable lessons and I’m excited to share these lessons with others – it’s my way to pay it forward so others can avoid (and learn from) the mistakes I’ve made.

I’m a believer in the power of the innovation economy to transform the world by creating a virtuous cycle of disruption and innovation. As both an entrepreneur and investor, I’ve seen some incredible ideas that will dramatically change the way we work, live and play.

As a proud Canadian and as an immigrant myself, I am certain that diversity is a strength, especially in the workplace. It’s no vanity metric either, I can cite numerous examples where diversity powered progress and drove real business results.

So what can you expect from this new blog? In a nutshell, I’ll share my experiences, ideas and even advice about the things that matter to me – entrepreneurship, startups, tech and innovation, leadership, diversity and a whole lot more.

Welcome to Allen’s Thoughts. I’m excited to have you here!

Canada’s Economy Needs a Second Act

Note: This blog post was originally shared on BetaKit, Canada’s startup and tech innovation publication of record.

This weekend, while celebrating Canada Day with family and friends, and in the midst of a constant stream of news about a growing trade war with the US, I had a chance to reflect on the future of this country and our economy.

Canada’s economy is the 10th largest in the world, of which a massive 70.7 percent comes from services. We are unusual among developed countries in that some of our largest industries are oil and forestry, natural—and finite—resources that contribute huge amounts to Canada’s economy. Canada has the world’s third-largest proven petroleum reserves and is the fourth largest exporter of petroleum. We are also the fourth largest exporter of natural gas.

While the oil industry helped propel Canada to the top 10 in the world, the good times won’t last forever. Why? This price history of solar cells says it all: since the 1970s the per-watt cost of solar energy has fallen from more than $76 to less than 74 cents.

The genie is already out of the bottle. Renewable energy will create a dramatic shift in demand for oil and gas. In the next decade, the energy sector will see more change than it has in the past century.

Canada also has a sizable manufacturing sector, particularly in the automobile industry. However, more often than not, Canadian plants are merely branches to foreign companies. Unfortunately, Canada has no ownership in the brands and the intellectual properties that are very valuable and have lasting value.

Entertainment is another major sector for Canada, employing hundreds of thousands of people and representing close to 2.8 percent of our GDP. While many Hollywood TV and movies projects are produced in Canada, we capture few of the upsides; even if a locally-produced project is a mega-hit, we’re still providing a service to the Hollywood studios. Studios based in Los Angeles can easily choose to make their next movie somewhere else if Canadian locations aren’t price-competitive. Unlike Hollywood, Canada’s rich and creative entertainment industry heavily relies on government subsidies and remains transactional.

Energy and entertainment create many jobs in Canada, but we all know that industries can turn on a dime. Case in point: the ongoing trade war with the US. Canada can’t solely rely on oil and providing services to foreign companies to sustain our growth in the future.

Canada’s economy needs a second act. Fast.

The good news is that we have all the raw material to pull it off. How? Canada has already emerged as one of the world’s leaders in artificial intelligence and blockchain. Ethereum-one of the most important blockchain-based technologies-was born in Toronto. As such, the city has a disproportionate number of blockchain experts. AI and blockchain are two great examples of why Canada is leading the pack in the new data-driven economies. At the moment, the top 10 most valuable companies in the world are data-driven tech companies. This includes the likes of Amazon, Apple, Microsoft, Tencent, Alibaba, Alphabet and Facebook. Data is clearly the new oil.

With a thriving tech ecosystem and abundance of experts in leading fields like AI and blockchain, Canada has the potential to create the next generation of tech giants.

Canada’s leadership has led to many foreign companies to set up their AI research labs here. But you’d be right to point out that this just recycles a problematic model, in which foreign companies control these important jobs and retain intellectual properties generated by publicly funded research.

These are valid concerns. At the same time, we see a virtuous cycle emerge from this situation, in which (often) foreign companies help attract and retaining talent in Canada, benefiting the country in the long term. That said, if all of the new jobs created by these data-driven companies are all foreign-owned, it will be a missed opportunity for Canada. We’ll be reproducing what we now see in the auto and the entertainment industries. Canada could have created a Ford or a Warner Brothers decades ago.

The solution is not to prevent foreign companies from setting up shops here. Tariffs and walls are not the solutions. Just look at the Valley. Many foreign companies open up branch offices there, but the domestic firms are all thriving at the same time. If Canada produces many billion dollar companies, who cares if Amazon opens up an office here or not?

What Canada really needs is an environment where many—not just one or two—domestic world-class tech giants can emerge. The kind of companies that make a lasting impact on the Canadian economy. Fortunately, the seed has been sowed. For the first time, the environment has been created for domestic data-driven tech firms to thrive and succeed. I know because I’m the CEO & co-founder of Wattpad, one such company. In Canada’s technology sector, the wind is at our back. It is up to us to pull this off.

I am absolutely grateful for the opportunity to lead one of the rocket ships that is helping Canada pull off its second act.

#HappyCanadaDay.