#15 Pere Mayol
Co-CEO & COO at AvatarCognition, an AI lab startup solving General Intelligence. Angel investor at companies like Wuaki.tv (acq by Rakuten), Glovo ($1.2B+ funding) & Wallapop ($840M+ valuation)
Pere Mayol is co-founder, co-CEO and COO of AvatarCognition, a Barcelona-based AI lab solving General Intelligence. The company has a novel patent-pending computational model of biological cognition and has implemented a new game-changing algorithm to solve General Intelligence, upscaling from motor perception towards figurative processing.
Before being a founder, was a really successful business angel focused on spotting very innovative pre-seed stage projects. He is a super early investor in companies like Wuaki.tv (media, acquired by Rakuten in 2012), Wallapop (e-commerce, 15M users, $190M+ funding, $840M valuation) and Glovo (delivery, 10M users, $1.2B+ funding, $1.7B+ valuation).
Previously, he spent 12+ years as board member in representation of multiple LPs (Limited Partners) at Nauta Capital, a Pan-European venture capital firm based in London, Barcelona and Munich, investing in early-stage software companies with $500M AUM and investments like Privalia (e-commerce, $500M+ acquisition by Vente-Privee) and Socialpoint (gaming, $250M acquisition by Take-Two).
He started his career as an engineer and spent some years in consulting at firms like DiamondCluster International or DCI (later acquired by Oliver Wyman), other smaller tech consulting firms, and software vendors. Pere studied Telecommunications Engineering at Universitat Politècnica de Catalunya · BarcelonaTech (UPC) and did an MBA at ESADE Business School.
👤 Brief intro: engineer, tech consulting, business angel, founder
🥇 Win: do what you love, value freedom
🚫 Fail and lesson: over believing in a project, balance out vision and facts
🚀 Ideal founder: storytelling, dual teams, exp (B2B), freshness (B2C)
💸 Ideal investor: strong thesis, solid knowledge, intangibles’ domination
📈 Markets: deep tech, AI, private AI labs, General Intelligence
Could you give us a brief intro about you and your origins?
I am a telecommunications engineer and with 40 years old I did an MBA. I’ve worked in different technological and strategic consulting houses, and I am a proud DiamondCluster alumni, where I learned the most. What passionates me is innovation and the implications it has.
I eventually left but was lucky enough to be there and live close to a lot of innovation. Then I became the CEO of a startup while I was studying for my MBA, and at that moment was when I cemented the decision of always be looking for innovation and only learn in a holistic and heuristic manner.
At Nauta Capital I touched base again with some DCI partners, and I ended up playing an LP role without putting money on the table. For 12 years I was an LP (Limited Partner, the people that put money into the VC itself) at Nauta’s second fund representing more than 10 investors, without any experience in the role. I didn’t earn anything but I learned so much from the successes and mistakes I’d do it again 12 more years. Incredible opportunity, forever thankful to Nauta.
Whilst doing what I have mentioned, I also started advising investors as a freelance, and in time that led me to invest in Wuaki.tv thanks to having met Jacinto Roca and Josep Mitjà (Wuaki founders and ex DiamondCluster).
At the end, a career of ups and downs around innovation and investment. I’ve been a business angel for while and it is a world of intangibles, it is about building relationships and storytelling. Founders have stories to tell, are really smart and live their story with passion. They want to be heard, they want others to sit down with them and truly listen. Human connection and mutual trust are a must, once you understand it, you realize these are the important things. You have to go everywhere, to all the events, to all places where founders explain their beautiful stories. The core of the angel business is to listen and also to build your own story so it explains why you are a worthy investor, and remember, learn to differentiate what part from a story has value and what part can end up being self-deception, in yourself and in others.
Another important rule that is part of who I am is to never become an employee or founder of a startup if you are an investor. A lot of investors say they want to invest but they truly want to be founders. And yes, I broke that rule. And still, I believe is important to mention because with so many intangibles you need rules (having financial vision, your own thesis, managing your portfolio) but you also need to be able to break them and have a little craziness in you to succeed in such a dynamic world we live in.
In terms of AvatarCognition, I met Enric Guinovart at DimondCluster and some years after we connected again as I was deeply interested both in analyzing and understanding the disruption crypto technologies, quantum computing, and AI. It was at that moment that he showed me his AI invention. Thanks to my previous analysis, I was able to understand his approach as well as the incredible and disruptive value it could generate. That’s when we founded Avatar Cognition, I ended up jumping off of the cliff with all that it implied, leaving everything else behind and devoting 100% to it.
Randomness played a role and I made some “home runs”, my hits have been driven by thesis thesis thesis and I learned this is a “home run” business, fact. 80-90% of the companies are walking death or plain death companies and 10-20% generate a profit, the impact comes when out of this 10-20%, you have a high percentage of “home runs”.
What would you say has been the biggest win in your life?
Doing what I love, which in my case is being close to innovation.
You don’t have to be a multimillionaire to do what you want to do, but sometimes it can be hard, specially if it implies not working for anyone else but you, because you will experience significant peaks and valleys.
Understanding the value of freedom is also part of this win. Learning about your minimum requirements to have a decent life and then jumping into what you really want to do. I took that risk, I did not have any relevant personal wealth when I started and I still don’t have it now, but I have earned a decent live doing what I love and with freedom.
Many people would prefer to work for others, get a salary and remain frozen in a dream ad eternum that never actually happens. It is good to pay bills but we should look forward to freedom.
And being more specific, I’d say to be able to build up a successful investment thesis as a BA (Business Angel) which resulted in a few home runs.
Related to the above, and your biggest failure?
From an investor point of view, it is really hard to share as it is very cruel. All teams are good and smart, have high potential thesis, execution capacity, and interesting market opportunities. Yet, they can fail anyway.
My biggest lesson is to learn from the biggest failure, to identify why you were wrong with your bet, absorbing the lesson and not repeat it again.
Some examples are believing more in the project than in the person and thinking you could change the founders’ behavior to execute the project following your vision. Sometimes you analyzed so much, believed so hard, and are so invested, that you go blind, lose touch with reality and you open the door for people to lie to you, so founders execute their vision but make you think they are doing what you would rather see.
One of my biggest failures is to let myself be blinded by my own vision. Being too close to a project can be risky as you have to keep your feet on the ground.
With time, as an investor I have learned that you don’t have to always help your founders. You only have to be there for urgent stuff, that’s it. If you have to be always helping the founders, you have an issue. Being too hands on can be as dangerous for a project as it can be to have investors on board with few investments, no portfolio, and no investment thesis.
As a contradictory example, 21buttons. I failed with my bet but I’d do it again. If Marc and Jaime came to me again I would give them money one more time. Brutal founders, smart, good traction … Now they are pivoting to different things, not sure whether if it is a failure but I still don’t understand it. This is also part of the game, failing and not always understanding everything.
What is your ideal founder profile?
I could say the typical things everyone share on this question: resilience, storytelling skills, a founder that knows the ins and outs …
But I’d like to highlight a founder who is able to create expectations without being eaten by their own storytelling. It is a dangerous game though, as you are always walking on the edge. Do not lie.
I like dual teams, they work incredibly well - commercial profile devoted to expansion + operational profile who is more introspective.
Founder teams that bring together dual experience work incredibly well: commercial profile devoted to expansion + operating profile. Wuaki was like that and Glovo is too, with the special dynamic of Sasha and Oscar.
And if talking about different business models …
In B2C, it’s important to have a team of dreamers with few experience on the area to be disrupted. A B2C profile with a lot of experience in the specific market, tends to have too much of a legacy and that has a negative effect in innovation. So juniors without experience can do interesting things.
In B2B is good to have a profile who is less dreamer and more senior. The more experience close to the business itself and knowledge of the ins and outs, the better.
What is your ideal investor profile?
Someone that knows how to play this schizophrenic game and who has a strong thesis, a consistent portfolio, solid equity knowledge and that values and nurtures the intangible vision that helps spot great humans and incredible stories, while being able to extract what they need to know from those variables.
Neither very financial nor very naive.
Nauta Capital is an example from who I learned the most about this.
What present and future markets are you most interested in?
Obviously AI, what should I say? Haha
Deep tech in general, we have to understand that standardization has reduced drastically the industry’s cycle. People hear deep tech and think in a lab and super long time frames, but the game is changing and standardization is a major driver. For instance, it is hard not to believe that in 20 years we will have access to genetic engineering because of it, impact will be incredible.
Specifically, private AI labs are pretty interesting, having superior success to competition because their startup-like vision versus main alternatives such as academia labs that follow super slow legacy standards.
However, I believe AI brutal hype is bad for the industry, because it tells people that it is more than it really is. Some think we are going to be controlled by Skynet tomorrow or get pissed off when Alexa is not super smart. So too much hype can bring deception.
The truth is, AI is not properly intelligent right now, we still have a significant way to walk. We can see how the industry is simulating a mechanism that achieves certain factors somewhat close to intelligence, but on a basic level and with a huge need for big amounts of data. GPT-3 is brutal but people that know about it will tell you that the system does not understand as much as some want to sell, but rather it is based on brutal amounts of data to give that answers. Imagine asking someone:
You: “Hey, you know how to write really well but do you know how to get back home?”
Someone: “No, I don’t”
You: “Damn, then how do you know to write so much?”
Someone: “Just digested 3 million data
That Someone is GPT-3 and a lot of current AI models, memory but not intelligence.
I am conscious of the oversimplification but I do not think we have intelligence, we have correlation machines, stochastic super parrots. Current AI is addicted to data and that is not only a limitation by itself but has a significant margin of error such as bias and extra algorithmic complexity. Everything is so scrappy and complex that we have an industry of big companies creating closed black boxes of AI knowledge.
So within deep tech, I like AI, and within AI, I like a new type of artificial intelligence based on biological cognition, a paradigm change. Not thousands of technicians creating algorithms or coders working, but neither skynet nor human replicas. An intelligence able to share knowledge and digitalize, that can think like us and be educated by us, but it is synthetic, not superhuman.
Imagine a gardener that can write in excel his knowledge, and then a machine does the job and takes decisions, when to water plants or not, or how to put insecticide or not.
Some labs are working on it such as Open AI or DeepMind, but the problem of general intelligence is still pending. They have made a bunch of spectacular solutions but really narrow and not actually intelligent.
There is room for this market to grow.
Could you share with us 3 startups you like and why?
Ourselves at AvatarCognition, for sure. We are a Barcelona AI LAB solving General Intelligence, focusing on a new computational model of biological cognition.
Additionally, private labs that are working on AI and trying to solve it are:
Numenta. Advocate of neurosimulation and neural networks).
Vicarious, backed by over $200M from investors like Jeff Bezos, Elon Musk, Mark Zuckerberg and Samsung they are developing intelligent robots.
OpenAI, an AI research and deployment company with the mission to ensure that artificial general intelligence benefits all of humanity founded by Elon Musk and Sam Altman, that recently received $1B investment commitment by Microsoft.
RobustAI, who are reinventing the way robot software is written and reducing the time to get robots up and running.
DeepMind, which is the AI subsidiary of Alphabet Inc. after it was acquired by Google in 2014. Their long-term vision is to solve intelligence, developing more general and capable problem-solving systems, known as artificial general intelligence (AGI).
But none of them has a public roadmap where they show how to solve general intelligence. As they haven’t solved the General Intelligence aspect they have been excluding it from their front row (i.e. web pages) and have focused on developing spectacular solutions but very narrow still. If you have to give the systems millions and millions of data to learn something, you are doing something wrong.
I would like to include other companies as well:
Wikiloc, which is the largest GPS routes network in the world led by Jordi Ramot. He has a strong startup spirit. For instance, he could have sold but he’d rather stay and provide a high-quality service to people whilst growing and having lots of users. Everything via bootstrapping. Very interesting case.
Glovo, I just love it. Not only because I am an early investor but because I’ve seen the project from inception. Oscar is spectacular, Sasha is spectacular. Some people haven’t understood Glovo and use it as a weapon against the startup ecosystem, but it is a spectacular team and project. Value for users is super high, brings opportunities for everyone to have a job, and has made strong efforts to ensure Glovers (their employees) are okay.
Minoryx Therapeutics, within the biotech space. A project with a different soul. Very hard business and very high need of money. They tackle a specific case of minority diseases, and it can be tough to justify the money when the target is so narrow. I love health investors because they seriously put up a fight to help solve big problems that improve people's health and lives.
Could you share with us 3 investors you like and why?
Nauta Capital. Clearly. I was an LP for a long time and I had a lot of visibility, lots of human interactions with people that learn from their mistakes, are consistent, and have a clear thesis. A phenomenally talented team.
Galdana Ventures. A very successful fund of funds born in Barcelona. What Didac Lee and Marcel Rafart have achieved is incredible, building a Fund of Funds from Barcelona that eventually becomes an LP in global investment firms providing successful returns is unique.
Carles Florensa. He is a super business angel in Barcelona and also teaches at ESADE.
Additionally, I like the way Lánzame approaches startups, they have my attention. Very smart people doing great work. Also Javier Cebrian from Bonsai Partners, his VC approach is interesting, similiar to a business angel, a curious guy, super low profile. Then you have the great names of Kibo Ventures, JME Ventures or K Fund also doing great stuff for the ecosystem.
What are the 3 books you feel everyone should read and why?
I don’t like management books, I think you have to create something heuristically and be super flexible, specially in a world of innovation and intangibles. I am not aligned with books that try to impose rules and normalize, you can’t fix time and location. I just don’t believe it, it is all bullshit and ends up repeating the same thing in only 5 pages.
I like to directly read storytelling, and the best ones are in novels. I love good novels. That’s the value, the cornerstone of business angels and pre-seed/seed stages.
“One Hundred Years of Solitude” by Gabriel Garcia Marquez. Fantasy, innovation, risk, value, great storytelling.
“The Hobbit” by JRR Tolkien. I’ve read it in Spanish, Catalan and English. I don’t like to repeat books but this is incredibly good. Innovation, exploration, being pushed to the adventure of entrepreneurship.
“Moon Palace” by Paul Auster. It tortures characters, makes them suffer and pushes them to the limit. Dark side of storytelling, shows the resilience you need to have in a world where there are a lot of positive and negative things. Great storytelling, it takes you to the edge but it ends up well.
What lessons from being a successful business angel investing super early in companies like Wuaki.tv (media, acquired by Rakuten), Wallapop (e-commerce, €840M valuation) and Glovo (delivery, $1.2B+ funding) do you think have had a significant positive impact for your current founder role?
Could you share with us what is the improved unique angle to AI that you could bring to the game through Avatar Cognition innovative proposal, how does it compare to current state of the art and what could be some of the future implications?
About lessons from being a business angel, being expansive and loyal.
Expansive in the sense of having a sensitivity for grand storytelling that navigates complexity to communicate clear values, whilst careful of not being eaten by the story. Having an ambitious vision but being aware of the challenges and understanding that you have to execute and have your feet on the ground. Also, be good. Lots of times I have heard entrepreneurs with failed fundings talking negatively from investors and vice versa. Don’t do that. The investor is not the enemy, the founder is not the enemy. Be good and don’t be negative.
About Avatar, we are developing a new way to do AI. For us, the solution is general intelligence, not artificial general intelligence. Bear in mind that functional intelligence is that from living creatures, not exclusively humans. We look through human lenses and we believe we are the best, but animals have pretty interesting intelligence too.
Some algorithms have tried to tackle general intelligence but in a more narrowed way. We want our solution to think like a dog, monkey, or human. Our systems implement computational mechanisms of extraction, we have a product roadmap to prove that our technology can support the creation of these machines, machines that absorb knowledge and express and mimic biological cognition. I don’t relate to traditional intelligence work as it hasn’t a clear description, it’s subjective, purely external qualification to a specific fact over a concrete behaviour. It doesn’t describe the mechanism.
The biggest mistake is trying to emulate intelligence as it was a mechanism and this is not the problem, the problem is cognition. If we are able to build these machines we believe we will have the first one working like low cognition reptiles and afterwards as high cognition mammals. The biological differences of the brain between us and rats is not as much as we think, the only difference is the jump from low cognition to high cognition - we do have imagination, creativity, and consciousness but not as much magic sauce as those who don’t understand mechanism say.
Thanks to our bigger brain, a better sensorial aspect and the ability to articulate language we are able to do structural knowledge. We should work on that, stop programming and start educating. And we can also educate systems based on different language from humans, for instance, like a lizard. It is time to do something different than the black boxes addicted to data with a lot of random knowledge which we have now, we have to be careful as we can create monsters unintentionally.
Big thanks Pere for sharing your views with us !
Big thanks to you, reader, for your time and interest !
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