Waverly Monthly Update — July 2022

Lots of exciting things to share in the last month…

First, we officially graduated from the Creative Destruction Lab (CDL)! There were 20 startups like ours at the starting line*, 8 months ago, and only 4 of us made it all the way to the end. What a journey! We have the whole CDL team and our mentors to thank for some of the big leaps we’ve made recently, including our new go-to-market strategy.

Our new direction is rooted in the feedback we got from our raving users — those who open Waverly multiple times a week and browse more than 500 articles a month. These users all come from the business world. They are consultants, analysts, or content creators who use Waverly to track trends, perform desk research and find inspiration on things that matter to them and their customers.

You’ll therefore see us doubling down on these use cases. We want Waverly to be the best modern platform for professionals who need to track information — about a specific topic, a domain, competitors… As long as you can express what you need to know in plain English, Waverly will be able to help you.

Typical market intelligence tools are complex and require extensive training. Not Waverly. Thanks to our reliance on natural language, Waverly will remain both powerful and easy to use. We’ve designed it from the ground up to be a modern platform that can be used by anyone. It is therefore ideal for spreading important knowledge throughout an organization and for gathering the feedback of your insightful employees.

Stay tuned, and thanks  for being a part of the Waverly journey.



The Sentience Question: Opening the AI Black Box

Opening the AI black box is not a hard as you might think.

At least not to get the basic knowledge you need to understand the difference between an AI language generator and a speaking human.

An AI generator looks at the words forming the beginning of a sentence and rolls a dice to select the next word. To do this, they use a table associating a different word to any dice roll.

Yes, AI generators need an unimaginably large number of tables to perform this feat — one for the beginning of any possible sentence. Fortunately, they have clever tricks to compress these tables and store them in memory.

At their heart, however, that’s how they operate:

  • Step 1. Fetch the table that corresponds to the beginning of the sentence.
  • Step 2. Roll a dice to look-up a word from that table, append that word to the sentence.
  • Step 3. Go back to step 1.
  • Step 4. Use the generated sentence to convince humans you’re sentient. 😉

Yes, it’s simplified. For example, modern AI language generators produce sentences letter-by-letter. You get the gist of it though, and it’s enough to understand just how different these systems are from your fellow humans.

We get fooled because AI is the very first non-human thing that can generate fluent language. Unconsciously we imagine their black box work the same way as our black box. We imagine that if an AI writes “I’m afraid of dying” it reflected on its existence and experienced a feeling of fear. After all, if a fellow human wrote that sentence, it would very likely be the expression of such an internal experience.

Same goes for a simpler sentence. If a human writes “peanut butter and jelly are delicious together” it’s likely because they tried that famous dish and experienced joy as the tastes mixed on their tongue. We know our computers dont have a tongue, so if an AI generator wrote that we wouldn’t assume it really experienced the joy of biting into a peanut butter and jelly sandwich.

For humans, language is most often the tip of a complex iceberg that finds its roots in our conscious experiences. For an AI, it’s the result of a series of dice rolls.

This article, written by experts in the field, goes deeper into that “cognitive illusion” of believing that fluent language means conscious experience.

In particular, it shows how this illusion often operates in reverse — in a way that can be much more damageable. Indeed, we often imagine that a human who doesn’t express themselves fluently is having a lesser conscious experience. That is, we imagine they’re less intelligent.

Now that’s a cognitive illusion worth fighting.


Waverly monthly update — June 2022

Where do insights come from? I care about this question more and more everyday. I care because that’s what Waverly has grown into: a machine for finding and refining the best insights.

Our most active users rely on Waverly to help them step outside of the beaten track. To seek content that will stimulate their imagination in a way that matters to them, to their work, to their customers.

So, where do insights come from? The seed of insights can come from anywhere. A Slack conversation, a video you stumbled upon, an old browser tab you randomly clicked on. Anything could trigger that little light bulb in your head.

But that’s only the seed, what about the insight itself? It comes from nurturing that seed. Finding that passage from an article that’s particularly relevant to you. Discussing it with your colleagues. Finding other related ideas and connecting them together.

You can now share anything to Waverly!

With Waverly, we want to embrace the fact that the seed of insights can come from anywhere. Our pioneers will soon discover, in the upcoming release, our Share to Waverly feature. A way to send whatever you find — an article, a podcast, a video — into Waverly so that you can nurture it and turn it into a valuable insight.

It’s not like any bookmarking feature: our goal is to give you the full power of Waverly’s recommender system. As a first step, our AI will automatically suggest a Wave to attach the link to. As we develop Waverly, though, we’ll add more and more ways for Waverly to help you and your community nurture these little seeds into insights that matter to you.

Stay tuned, and thanks  for being a part of the Waverly journey.



Waverly Monthly Update — May 2022

The thrill of the search. Building something you believe in, working towards a vision — an ideology recently said one of our mentors — is at once exciting and anxiety-inducing. You’ll hear most startup founders say as much.

Personally, I wouldn’t trade this for anything.

Navigating the choppy waters of the early startup ocean has recently led us to a promising new opportunity. Not a pivot per se, but a way to use our platform and technology to help enterprises solve a problem they all face in a way that builds on their greatest asset: their people.

We’re not quite ready to lift the veil on this. However, if your team shares links on slack, or if you’re in a leadership position and feel your employees are experts at sensing what’s out there, please reach out to me. I’d love to hear from bold organizations who are eager to embrace new approaches for understanding the world that matters to them.

What a Waverly Quote Deck looks like when you share it.
You can to browse through the selected quotes.

In the meantime, the platform keeps on moving forward by leaps and bounds. We recently released Quote Decks: a way for you to share a beautiful mobile-friendly deck that captures why you found an article interesting. Here’s one I created in a few taps from my iPhone. You can browse it from any device, just click on the image.

Again, let me personally thank you for being a part of the Waverly journey.



Recreational Bug Seeding as a Complement to Code Coverage

Many metrics have been proposed to evaluate the quality of a piece of code: nesting depth, cyclomatic complexity, relational cohesion… although my favorite remains WTFs per Minute.

Testing also plays a big role in software quality and is therefore also being measured. One of the most popular unit testing metrics is code coverage, which evaluates the fraction of lines of code that have been executed at least once during testing.

Code coverage is not a bad metric per se, but reaching 100% is not a guarantee that your code is bug-free. Far from it. So, how could we do better?

I’m sure countless Ph.D. theses have been written on this question, but I’d like to propose another idea in the vein of WTFs per Minute. Something not totally serious but not totally ridiculous either.

I call this approach Recreational Bug Seeding and it goes as such…

On a regular basis, you invite your software engineers to do a bug seeding session. Something like a hackathon, but where the goal is to introduce bugs.

During a session, software engineers are encouraged to go through the code — not the tests! — and to modify it in any way they want. Anything goes. They can add a character to a regular expression, change the start index of a loop, return early from a function, invert the clauses in an if-else. As long as the change should break things, it’s valid.

Once a change has been made, the bug seeder runs the suite of unit tests. If they all pass then the dev scores a point and brags about it on slack.

The total number of seeded bugs gives you an interesting indication of the ingenuity of your software engineers, but — assuming this ingenuity is constant over time — it also gives you a pretty good indication of how thorough your tests are.

If devs don’t put too much effort into thinking of weird things that could go wrong, then it’s going to be fairly easy for bug seeders to score points.

One obvious drawback of that method is that it costs engineering time. However, if done well, it might be fun engineering time — with cakes and all — which could have a positive impact on your company culture. As an engineer, I know I would have liked a bug seeding session every now and then. 😀

Waverly is still too small to do this, but I’d be really curious to know if anyone has tried something similar in a larger company. Please reach out if you have!

Update: Many of you pointed me to an automated version of this idea, mutation testing. Thanks!


User-Centered Design is Killing Innovation

If I had asked people what they wanted, they would have said faster horses.”

That Henry Ford quote is equally loved and despised by my friends in the startup community. Some see it as a celebration of the mythical designer genius. The next Steve Jobs who’s going to kick the world out of its passéist ways. Others see it as a celebration of authoritarian design in which egotistic designers ignore the people they pretend to help.

In that evergreen debate, user-centered design seems to be the flavor of the month. That approach to design proposes to start with a study of user characteristics, their environment, the tasks they do, and the workflow they adopt. Only once we’ve learned about our users and their need should we take our pen and start designing the product.

User-centered design sounds like a wise approach. Petulant kids invent spaceships that no one will use while us, serious designers, we take things slowly. We talk to people. We show humility. We are wise and mature.

And we suck the whole fun out of the party.

I was recently reading an article touting the merits of user-centered thinking and how it should be adopted by everyone in the software industry — not just designers. They gave the example of a dev who implemented the export feature users had asked for. Our petulant coder dives into the task, wraps it up and ships it… What a mistake. If only they had talked to users, they would have discovered that they wanted to export their work because the software crashed too frequently! Clearly, our petulant coder did not have a user-centric mindset. Clearly, they started with how instead of why.

Breaking news: people hate crashes. They also hate slow apps. They hate unresponsive UIs. You don’t need user-centricity to solve these problems, you need good monitoring and devs who know their stuff.

User-centric design encourages us to ask why, but in doing so it evades the most important question: how many times should you ask it.

Let’s imagine Henry Ford surveying his users with a user-centric mindset:

So, Mr. Cooper, why do you want new horseshoes?

Because my horse’s feet are hurting, Mr. Ford.

Welcome to an alternate reality where the Ford Corporation is the maker of the great Model T Horseshoe, trusted by farriers all over the world. You’ll object that Mr. Ford is not that stupid…

Why do you want to relieve your horse from its pain, Mr. Cooper?

Because my horse is too slow when its hooves hurt.

Now you’re in the dystopian future where everyone has a genetically engineered super-fast Ford thoroughbred. You can even have it in any color, as long as it’s black. But Henry Ford is not quite done yet:

And Mr. Cooper, why do you want your horse to run faster?

Because I need to be at my brother’s place for the Superbowl!

Armed with that knowledge, will Mr. Ford invent the car, will he invent the Netflix viewing party, or will he skip a full century and give us the Metaverse?

The more you ask why, the more you end up with big and generic problems. Big problems have a multitude of potential solutions. These solutions are novel and alien to people. Therefore, users cannot help you figure out which one is the best. You have to build it, place it in their hands, see if they like it or not, and, above all, you have to iterate.

Humility is critical for designers. You need it to kill the countless darlings you will have to kill in order to build a product people want. But dressing up this humility in the fancy clothes of user-centered design is too often used to mute creativity, to artificially slow down energetic exploration, and to turn design into a bureaucratic process that may feel comfortable but is definitely not going to solve humanity’s biggest problems.

So, here’s to the petulant kids. Build that thing.


Celebrating the Role of Academics in a Startup Ecosystem

Oh, how I miss Korea!

Yesterday I had the opportunity to present the Montreal AI Ecosystem and its research culture in a conference organized by the Korea Development Institute.

Here’s what I said, in a nutshell: I feel we’ve been doing a pretty good job of nurturing human-to-human relationships across the industrial / startup / academic boundary.

Personally, I’m grateful for our special vibe. I feel I regularly get the opportunity to have fruitful exchanges with academic researchers and graduate students even though I’m not a part of their world. These discussions typically flow in both directions: I’m equally excited to learn about their research than they are to listen to me and my startup struggles. Their insights and creativity give me a regular boost.

Historically, we’ve seen the role of academics in a startup ecosystem as purveyors of the initial idea. We need them to invent our deep tech, but then they can take a back seat while entrepreneurs convert their idea into a commercial product.

I don’t like this. I think it’s a reductive view. For me, the real value academics can bring to a startup ecosystem is through their unique blend of creativity and broad expertise. They have the rare ability to approach problems with wild ideas that are nonetheless technologically feasible. This is a skill you need again, and again, and again as you build a startup. You need this ten times more than you need a brilliant initial idea. Pivot is the name of the game, so creative resilience is the key. Academics have plenty of that.

To all of you researchers who help keep that special vibe alive: thank you!

More specifically, thanks to all of you who gave me a personal boost since I started Waverly: Yoshua Bengio, Blake Richards, Marc G. Bellemare, Graham Taylor, Anirudh Goyal, Dr. Sasha Luccioni, Dzmitry Bahdanau, Nicolas Chapados, Nicolas Le Roux, Joelle Pineau, Craig Reynolds, Vicky Kaspi, Kory W. Mathewson, Irina Rish, Eilif Benjamin Muller, Pedro O. Pinheiro, Anqi Xu, Xiang Zhang, Glen Berseth, Michiel van de Panne, Charles Onu, Edith Law, Max Welling, Michael McCool, James O’Brien, Eugene Fiume, Pierre Poulin, Hugo Larochelle.

BTW, I’m not saying it’s unique to Montreal — some of the researchers named above are from across the world — but I feel that spirit is alive and well here.


To the Founders Who Show Up

One of the thing you have to do again and again, as a startup founder, is to lay your dream raw, on the table, in front of a group of strong-willed people who will critique it. They may be advisors, investors, potential customers… But you will have to do this constantly.

You’ll have to do this no matter which state the company is in — fresh from a new release that is picking up steam, in a lull as you struggle to bring users back, as you’re undergoing a pivot and are still struggling to find the right words to talk about what you want to do…

You’ll have to do this no matter which emotional state you’re in.

These meetings are often scheduled weeks in advance and each of them could be the opportunity that unlocks the next stage for you.

You have to show up no matter what.

It’s hard. You can do it by building an armor that lets you hold strong when someone decides to take a stab at your dream. Or you can show up as your authentic, vulnerable self. Accepting that pain will be a part of the journey.

As a founder — as a human — I’ve learned that I can only be successful if I show up without artifice. I therefore lay my dream raw, for you to examine and critique. I’m there to listen and learn… and if your advice hurts I will accept the pain and leverage my support network to get back up.

If you sit across from a founder and are called to critique what they present, please be fully honest. Please tell it like you see it. That’s why we seek your advice. But please, also, bring in that human touch and recognize the challenge the person across the table might have to face.

And to the founders out there, kudos for showing up.


A New Type of Sudoku

On Waverly, one of my most idiosyncratic wave is Puzzles by Humans. It allowed me to discover a hidden world of creative puzzlers. Amongst them, I found a growing group fueling what is now being known as the golden age of sudoku. These so-called setters are inventing countless sudoku variants that can be mixed and matched to create puzzles which force solvers to come up with original deductions.

Leading the popularization of that new puzzling form is the excellent YouTube channel Cracking the Cryptic. It led me onto the (very difficult to navigate) German puzzle portal Logic Masters, which seems to be the birthplace of every new sudoku variant.

Some of these new types of puzzle rely on arithmetics, which I’m not a fan of because it requires solvers to memorize frequent sums. This feels like memorizing frequent definitions in crossword puzzles, which is not what I enjoy in problem solving.

However, there are some new clever variants that dont require you to memorize anything, just to put on your logician hat and prove some theorems. I couldn’t sit idly by the sidelines so… I invented one new such variant! Behold the…

Ant Sudoku

  • Standard sudoku rules apply.
    Digits can’t repeat on lines, columns or 3×3 regions.
  • An ant starts on each of the shaded cells.
  • Each ant must be able to reach at least one of the circled cells with the same letter.
  • Ants must not be able to reach any other circled cell.
  • An ant can move from a cell to an orthogonally adjacent cell if its digit is less or equal to the current digit plus 1.
    Ex: An ant on 4 can move to an orthogonally adjacent 5, 3, 2, or 1 but not to a 6, 7, 8 or 9.

You can play this puzzle online either on F-Puzzles or Penpa+. If you want you can also download a PDF version and print it.


If you get stuck here are some hints, just rot13 decode them:

  • Svaq pryyf fbzr bs gur nagf zhfg nofbyhgryl tb guebhtu.
  • Pna gjb cnguf rire gbhpu gurzfryirf?
  • Znxr fher lbh qba’g fgrc ba gur gbc sbhe.


Here’s the solution, don’t hesitate to give me feedback on Facebook or Twitter.


AI and Consciousness

NeurIPS, the most famous conference in AI these days, was born of the intentional collision of neuroscience and AI — a handful of researchers in both fields seeing value in getting inspired by one another.

My recent conversations with AI researchers, most notably with Yoshua Bengio, have thrown me on a collision course with another group of researchers, one often vilified by us, explorers of “hard” science: philosophers.

Indeed, one of Yoshua’s belief is that to increase the generality of AI we need to uncover more generic priors: general guidelines we could bake into our untrained models so that, as they start to observe data, they learn a more effective hierarchy of structures. Structures that allow them to apply their knowledge in more situations, or to adjust their model faster when new data is observed, or to be more robust when faced with contradictory data… In short, Yoshua (and many other researchers, myself included) believe that better and more generic priors could help tackle the challenges AI is facing these days.

In an infamous paper, Yoshua called one of these very generic (and elusive) priors The Consciousness Prior. Some researchers went up in arms at the use of such a loaded term, accusing him of the academic equivalent of clickbait.

In my case, however, it just made me aware that I had no clue what consciousness was.

In the last few months, through a random encounter with an excellent popularizer of analytical philosophy, I dove deep into the topic. I gained a better understanding of terms like qualia, consciousness, dualism, illusionism, etc. Words that philosophers use to approach questions that us, hard scientists, don’t even dare to ask.

Beyond my own improved understanding of some non-scientific (yet very important) questions, I discovered a community of thoughtful thinkers that are not as enamoured as I imagined with useless rhetorical debates.

I discovered, against my own biases, that philosophy offered a very valid approach to improving our understanding of the world.

The following article, that I discovered via Waverly, explores the difficult topic of emotions from a psychological and philosophical angle. Since we often talk about emotions when discussing Artificial General Intelligence, I felt the article might be interesting both to my AI friends and to my (soon to grow?) group of philosopher friends. Maybe we need a PhilIPS conference, creating an intentional collision between these two worlds? (I kinda like that name 😉)