Diederik van Liere

ARE WE IN A RECESSION? As mentioned in our prevision post, the NBER's Business Cycle Dating Committee took 4 to 21 months to declare past recessions. Sometimes, they even do so AFTER the recession ended. Therefore, how do we know whether we are in a recession today? And are we in one? We know by looking at a handful of indicators. One is the Smoothed U.S. Recession Probability (at the top on the image below), the other is the Real-time Sahm Rule Recession Indicator (at the bottom). Both datasets are updated monthly. The former tells us that we are not in a recession, but the latter suggests that we might be. Because of this uncomfortable ambiguity, the STOIC Recession Index will include a real-time horizon, which will provide the probability that we are in a recession. It will be updated on a monthly basis as well. Right now, it would probably stand between 25% to 50%, meaning that we are not in a recession, but that we might get very close to one.

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My 7-year journey via Maple VC with Clay. Thanks Josh Scott at BetaKit for covering the story. I was first introduced to Kareem Amin through a fellow Canadian expat and now Maple founder, Michael Hershfield of Accrue Savings. They first met working at Sailthru in NYC where Kareem sold his first company. In 2016, Kareem started to tinker on new ideas with his cofounder Nicolae Rusan and I was fortunate to meet them at this time. This happened to align with me establishing Maple 1 in November 2016 on the simple thesis of backing Canadians building in America. We noticed that Canadian expats, who graduate from Canadian universities, go on to build some of the biggest companies in tech – Uber, Slack, Instacart, Notion, Faire, Databricks, Cloudflare, Roblox and most recently, OpenAI. Kareem and Nicolae seemed to match this pattern as two graduates from McGill University building in the US. In 2017, they landed on a very clear mission to make programming accessible to all. They painted a picture of replacing the black terminal that developers use, with a spreadsheet that is connected to the internet which could allow non-developers to automate work. What we saw immediately that gave us conviction was a very big ambition (making programming accessible to all) with a unique insight (using a spreadsheet) via a new method of no-code tooling. This reminded us of the early days at Uber: The promise to deliver you anything (big ambition) by starting with a black car that takes you from point A to point B (unique insight) via your phone (new method). We first committed to investing in Clay in Jan 2017 before the company had a lead. In June 2017, we were thrilled to learn that First Round Capital was going to lead their Seed. Sequoia Capital led the Series A in June 2019, which was surprising, since we had no revenue and were still figuring things out. However, the low-code no-code category was starting to take off. Then, they spent the next 3 years figuring out where to focus. During this phase it was fascinating to witness the many disbelievers. We had folks tell us that we should mark this investment to $0. In late 2021, they decided to narrowly focus on automating sales and this turned out to be the big unlock. Varun Anand joined as a cofounder leading their GTM efforts. The timing played out beautifully with new LLMs that we could use to automate growth in a way that hadn’t been done before. Clay relaunched in Feb 2022 with $0 in revenue and has not looked back since. We 10x’d two years in a row, all organically, achieving 100k users, 2500+ customers, and 11k people exchanging ideas in our Slack community. Maple has tripled down since the Seed through the Series B which was just led by Meritech Capital. We have a strong feeling that Clay has a real shot at realizing that vision they first shared with us 7 years ago.

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Cohere CEO Aidan Gomez says that #1 blocker for Enterprise GenAI use cases is data privacy and #2 blocker is the cost (implies ROI). He also explained what Canadian AI startup, Cohere does and how they make money. A must watch for anyone who is interested in Enterprise GenAI use cases. He also said that GenAI fear mongering is cheap ways to get attention (I am paraphrasing, he didn’t use the word cheap). Quite a bit commentary on Google Cloud AI developments as well. Other mentions Oracle and Massachusetts Institute of Technology. Aidan comes across as a mature tech leader for his young age. He sounds more realistic and less me too, in GenAI hyped era. Aidan was talking to CNBC’s Steve Kovach. https://lnkd.in/g36SFYfn ____________________ Last month, Cohere has raised $450 million in funding from returning investors such as Nvidia and Salesforce Ventures, as well as new investors including Cisco and Canadian pension fund PSP Investments cc David Vellante David Linthicum John Furrier Ron Miller Shelly DeMotte Kramer Robert Hof

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Just a few days out from my talk at Toronto Machine Learning Society (TMLS)‘ Summit. I will be speaking next Monday July 15 at 11:30 in Room 1. My talk, “GenAI: A New Renaissance in Product Development” is about actionable tips for how to incorporate GenAI in your day to day workflows. I cover three major topics on how to: 1. Get the most from work with global teams 2. Expedite user research (while still talking to real humans!) 3. Find the best tools to leverage during the product development process Along the way I’ll be sharing caveats and pitfalls to be on the lookout for. I’ve got some fun visuals to backdrop the talk. Plus, I will be launching my playbook for how to use GenAI in the product development process. It covers a whole lot more and the audience will have first access! So come on out from 11:30 - 12 in Room 1! And it’s my first trip to Toronto so please send tips!

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In Montreal, a taxi has a base rate of $4.10, then $2.05/km and $0.77 per minute waiting. I hate to break it to the CBC but that's also an algorithm. Any pricing scheme is going to be better for some and worse for others. And like with almost all AI, transparency or explainability is an illusion. Is it better to know how your taxi fare is calculated, as above, but have no idea how much the trip will cost, or to know how much the trip will cost but have no idea how it's calculated? It's not about the underlying technology, or what constitutes an algorithm, it's the impact that matters. It would be a very cool study to look at who benefits from one-size-fits-all time and distance pricing, vs. who benefits from customized pricing. It's not a slam dunk that the latter is worse. https://lnkd.in/gvjiPKnZ

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#Collision2024 Takeaways, in between mingling galore around Toronto: - VC panel: AI is a means to an end, like Email, with AI “startups” are largely a feature, not a business, that companies can easily replicate/improve for their own specific use cases. Advances in AI have led to quantifiable benefits to convey as KPIs (value to customers) vs. subjective “improvements” previously not easily measured at scale. - AWS gen AI VP Product: Evolution of an innovation starts as a single use case, gradually increasing in specificity (specialization) & eventually, an entire ecosystem - An ML Model = a cake you find… do you eat it? Latent, malicious issues & secret management might be in a hidden spoonful! Parallels to when orgs hesitated to move data into cloud infras - Move faster, but at what risk — security, privacy, bias. - Large enterprises’ silos might mean models are in production having circumvented processes & protocols’ rigors (understand/audit/monitor for vulnerabilities) - Willing to let AI operate autonomously & understand its decision-making, or can you intervene/course-correct? - Goal is to delegate increasingly complex tasks, so need to ensure it’s right for important/sensitive use cases Regulation & Insurance as guardrails (forcing functions) for trust, security & peace of mind Leadership applicable to all, via Latinas in Tech - Canada DEI workshop by Verônica Heringer & Stephanie Gomez: - Add your grain of salt: be a sponsor/mentor/panelist because representation matters. - Who's your “go to” mentor/support system at work? What did they do for you to think of them right away? - People we trust = people like us… formerly a survival strategy. - [Thinking Fast = biases, reflexes, “known” instead of Thinking Slow = Aware & conscious, analytical] --> employ that with your relationships! - Invisible common ground is so vital to forge ties, try to find it beyond the visible demographics & overt tendencies. - As a leader, you have power… & it is your job to have empathy & support others upwards - Create psychologically safe spaces, be cognizant, curious, commit, collaborate & embody courage emotional/cultural intelligence. & as for the future of comms, a Snapchat dev founded a video AI generator for translation/localization/full-on “avatarization” for those uncomfortable on-camera… will this replace charismatic communicators? My generational bias disagrees, especially after meeting incredible entrepreneurs with palpable passion beyond salesmanship. …but my number 1 tip to get the party going at your next tech event: make “Inflection Point” a drinking game. CHEERS!

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Canadian Founders Shouldn’t need to leave Canada. We need to fix our system. 🍁 Last week I was catching up with a founder from Canada. She had just returned from spending 3 months in SF. She said it was insane how the entire ecosystem there is built to incubate and launch startups but then also support them for the entire lifecycle through Series A and beyond.  In Canada we’re ok at getting companies started but then we have little support beyond that and we ultimately lose them to the valley. Her suggestion was to take all the money the Canadian government is throwing at our tech sector, and instead use it to send our Founders to SF for 3 months for a Founder crash course. As a Canadian, hearing that is super depressing but also accurate. My roadmap at Developer Capital is to find and fund great Canadian companies in the pre-seed and seed round, but then get them into the US for their Series A. Why? Valuations are better, risk appetites are sharper and it will help your sales when breaking into the US market. How can we as a country support them and encourage them to stay in Canada? The Challenge: Canada’s Startup Ecosystem is Broken 💔 If we don’t want to lose our brightest founders to the US, we need to re-evaluate our approach. We need to provide the SF experience right here at home. Here’s what we can do: ⚫ Access to capital. Yeah, im sure you’ve heard this before. Pre-seed doesn’t exist in Canada. Developer Capital is trying to change that but we’re only one firm. There needs to be more deal flow sharing amongst the pre-seed and seed stage funds. This one’s on us in the VC community. We can do better. We can share our deals. We can get out in the world more and meet Founders. Rather than waiting for others to validate our own opinions we can lead rounds and be first money in. ⚫ Ecosystem support. It’s pretty nuts the difference this one makes. When a company comes out of SF they instantly have access to a network of 1000’s of early adopter companies to go out and buy their product. And the VCs who invest ask all their Portcos to take a deep look at buying these great new products. Incestuous? Yes but it works, and gets these start ups to millions in ARR fairly quickly. ⚫ The right infrastructure: Accelerators and incubators sometimes get a bad rap, but the good ones do the job of acting like a bootcamp to get your company launched, understand how to get financed, and then how to iterate until you find product market fit. Canada needs to up its game and come out with a couple of AAA accelerators. If McGill is the “Harvard of the North” why can’t Canada have a “YC of the North”? I’m not pretending to have all the solutions. This is clearly a “hard problem to solve”. But as a proud Canadian I know we can do better and I want to be able for our best companies to stay here forever (whatup Shopify). We have the talent and the ideas; now we need the infrastructure and the networks to match. Let's make Canada a powerhouse! 🍁 🚀

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Collision Conf is one of the biggest tech+AI events in North America and I am looking forward to learning more in this exploding space. If anyone is heading that way, feel free to ping and we can connect! #AI #generativeAI #digitaltransformation

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Good Canadian Kid Does and Sings AI Nick Frosst, co-founder of AI company Cohere, simultaneously leads a successful indie band called Good Kid. An unexpected blend of technology and music! Song recommendation: Listen to "Nomu" by Good Kid. The song includes interesting references to technological topics such as syntax, semantics, and lost language - concepts related to the world of AI. https://lnkd.in/dKBpKx5F This shows how the band members' technological background influences their musical creation. "The syntax skips, semantics slip And what was left a growing cleft of language lost, tokens unknown" To view the full lyrics: https://lnkd.in/d-78VdXr A moment of nostalgia: "How do you convert PDF to JPG?" by the (Israeli) band Umlala? What a classic! Today, we'd ask an LLM how to do that ;-) https://lnkd.in/dyMiq9cv What musical association comes to your mind?

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Recently I interviewed Nathaniel Simard, founder & CEO of Tracel Technologies and inventor of the burn ML framework: Jan: Nathaniel, we're excited to have you as our guest today! To kick off our conversation, could you please introduce yourself and share a bit about your background and what got you into ML? Nathaniel: Sure, I'm the creator of Burn, a deep learning framework written in Rust, and the founder of Tracel AI. I started coding in the first year of university, where I was studying mechanical engineering, but I quickly switched to software engineering after, since I instantly fell in love with programming. Then I explored different facets of the field from backend to frontend development, and I decided to start my career as a consultant focused on software quality. After some time, I wanted to go deeper into AI, since I was always interested in the process of learning, so I enrolled for a master's degree at MILA. J: According to Github you started to work on burn in summer 2022. Since then has already earned over 7000 stars on GH. What was your initial motivation to develop a new ML framework? N: I always had a side project going on, for fun mostly and to learn new things. I wanted to explore asynchronous and sparse neural network architectures, where each sub-network can learn and interact with other sub-networks asynchronously and independently. I wasn't able to actually create something useful because I needed fine control over the gradients and the concurrency primitives, which is not easily done with Python and PyTorch. At the same time, I was working on machine translation models at my current job, and it was quite painful to put models into production. I decided to switch my side project to a new deep learning framework, with more flexibility regarding gradients and concurrency primitives as well as being more reliable and easier to deploy on any system. J: Amazing to see that this was born out of a side project! I feel the struggle with concurrency in Python and this is something where Rust really shines. What are some of the other key features that makes burn special? N: I think there are two things that really set Burn apart. First, almost all neural network structures are generic over the backend. The goal is that you can ship your model with almost no dependency, and anybody can run it on their hardware with the most appropriate backend, even embedded devices without an operating system. Second, Burn really tries to push the boundaries of what is possible in terms of performance and flexibility. It offers a fully eager API, but also operation fusion and other optimizations that are normally only found in static graph frameworks. The objective is that you don't have to choose between portability, flexibility, and performance; you can have it all! To read the rest of the interview with Nathaniel's plans for burn & trends in AI here: https://lnkd.in/dKv9ztMm #ml #ai

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Unapologetically Technical's newest episode is now live! In this episode of Unapologetically Technical, I interview Hubert Dulay the author of Streaming Data Mesh and Developer Advocate at StarTree. We talked about his early experience with web backends like CORBA and SOAP and how those prepared him for data work. He shares his advice for those with web development skills to transition into data and what it's like for a person leaving a company after a long tenure there. We discuss his time at Cloudera and Confluent and how the data industry has changed over time. We talk about his recent experience with Flink and StarTree. We go in-depth into streaming data mesh, covering what it is and how to create real-time data products. We discuss the ways teams can create joined or enriched data products across domains. We round out the discussion with some tips on how to get data mesh adoption. Watch the full episode here:

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I'm at #Collision Conf here in Toronto, and I'm seeing a ton of AI startups. Many of them are asking me how to scale and where to find the right people. It's interesting because the vast majority of these “Ai companies” have never even heard of agentic engineering approaches. The ability to use agents in place of traditional people-based processes is the next step for startups. The next major trend will be billion-dollar startups with just a handful of people. Most of the startups here don't need to worry about hiring a big team. What they need is a core group who understand the basics of agentic engineering. They need the ability to deploy agents within their startup structure, building a company around these autonomous systems that can scale operations, manage finances, drive sales, and handle internet / data infrastructure and cloud computing deployments. With a small, knowledgeable team, you can create and manage these systems, scaling your startup to thousands of agents at a fraction of the cost of hiring a large staff. Sometimes at cost reduction of 1000 to 1. The real question is, where do you find the people who can help you do this? Define their roles and responsibilities clearly. If you can do that, you can build any company. Honestly, half the companies here at the Collision Conference could massively benefit from this approach.

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We've been hard at work over the past year at Immitracker, adding new program trackers and analytical reports! We're excited to announce that we now support analytics for four new Canadian visa and immigration program trackers 🇨🇦 Starting this August, analytical reports became available for the following program trackers: 1. Ukrainian Family Sponsorship 2. Study Permits  3. Work Permits 4. Startup Visas These analytical reports can help applicants gain unique insights into the processing timelines and current trends for their programs as well as estimate when they can expect to receive their approvals! For example, by reviewing the analytics for the Startup Visa program, we can notice just how long on average it takes applicants to even receive their AOR after application submission. Another example, for the Ukrainian Family Sponsorship program, we can notice that very few applications submitted in 2024 have even moved past the submission stage - most of them are still awaiting to begin processing. Looking for program trackers or analytical reports we don't currently have available? 🤔 Please let us know your thoughts and feedback in the comments! #immigration #canada #australia #canadaimmigration #data #analytics

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AI makes labour and capital fungible - they become interchangeable factors of production. This is why it's so revolutionary. That insight - framed by Zachary Wojtowicz of Harvard with a clarity I haven't heard before - was a key takeaway for me from two days of great discussions at the Association for the Advancement of Artificial Intelligence (AAAI)'s AI in Ethics and Society conference in San Jose, CA. Since Adam Smith, economists have recognised three factors of production: land, labour and capital. The industrial revolution reassigned work from labour to machines (capital) for the first time at massive scale. But intellectual work remained the domain of humans, albeit assisted by technology. AI transforms that, representing not a true second industrial revolution but the logical conclusion of the first - it means that we can switch human labour with the capital of AI interchangeably as we need, whether for efficiency, productivity, safety or to overcome scarcity. I won't get into human-in-the-loop, human-machine teaming or questions of job security here, as that's a separate and important conversation, but these questions all derive from this simple fact of fungibility. This is the clearest articulation I've heard of why AI is so revolutionary. It is not, as Accenture said in 2017, an entirely new factor of production. Rather, it facilitates trades between two existing such factors. How those trades are made and their impact? Well, that's another conversation. #ai #airevolution

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Why Palantir Technologies alumni are great at founding impactful companies: • They've solved hard problems at scale. • They know how to build products enterprises & governments actually use. • They've seen firsthand how data can transform industries. We’ve posted about ex-Palantir founders before, but here are even more that can call themselves part of the ‘Palantir Mafia’: Alex Arjun Dhillon is building the future of content intelligence at Outtake. Outtake is automating cybersecurity & legal workflows for some of the world's most recognizable organizations by tackling gritty problems in identity, authenticity, and multi-modal AI. Anneli Scopazzi founded Boulevard Recruiting. After scaling teams at Palantir and Figma, she's partnering with both startups and VCs to build out early teams. John Doyle founded Cape, a privacy-first mobile network with secure 5G/4G coverage nationwide. The mobile carrier also blocks hackers and spam. Youssef Rizk and Dimitris Nikolaou were colleagues at Palantir. They went on to found Wondercraft (YC22), an AI-powered audio creation studio for brands and creative teams. Mihir P.  founded Overstand Labs (YC24), a cross-selling platform for enterprise companies. Their AI product has perfect awareness of all your product features and customers, to ensure no revenue is left on the table. Steve Heitkam co-founded Hence Technologies to help companies manage legal risks from geopolitics. Hence helps firms establish efficient legal processes that support smarter decision-making over time. Nick Noone co-founded Peregrine, a platform providing real-time data integration and visualization to help public safety agencies make better decisions. Shaun Springer co-founded Archetype Labs to transform how businesses build custom software. They help companies create tailored software with their AI-driven, no-code tool without the steep cost of custom solutions.

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💡 Why Every New Founder Needs to Hear This: Real Talk About the Highs and Lows of Entrepreneurship I had an amazing time on the latest episode of Collisions YYC with Jade Alberts and Tyler Chisholm! There’s something truly special about having real conversations with these two—discussing both the highs and the lows of being an entrepreneur. 🎢 In this episode, we dive deep into what it really takes to navigate the rollercoaster of startup life—how to manage those big wins, like landing a new client, and how to push through the tough moments, like missing payroll. We shared some hard-earned lessons on avoiding the common mistakes founders make, staying grounded through the chaos, and most importantly, knowing when to keep going and when it’s time to pivot. 🌱 For all the new founders out there: This journey isn’t easy, but it’s totally worth it. Prepare yourself for the challenges, and keep in mind that the highs and lows are all part of the adventure. 🚀 🎧 Tune in to hear these raw, real, and invaluable insights from Team Awesome: https://lnkd.in/e6CKrASG 💬 I’d love to hear your thoughts—what challenges have you faced as a founder? And how did you know when it was time to pivot or keep pushing through? #TeamAwesome #KeepBeingAwesome #Koridor #Entrepreneurship #FoundersJourney #CollisionsYYC #StartupLife #YYCFounders

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The Scientific Research and Experimental Development (SR&ED) tax incentive is one of Canada's most powerful tools for fostering tech innovation - enabling businesses to recoup up to 65% of their R&D salary costs. Here's the troubling reality though: While this program distributes ~$4B annually to 20,000 businesses, an unnecessary "SR&ED consulting industry" has emerged that extracts $400M-800M from these funds. Why? These consultants capitalize on companies' fears about complex paperwork, despite the fact that 94% of SR&ED applications are approved. They charge 10-20% of the tax credit simply to complete forms. Let that sink in: Nearly a billion dollars meant for Canadian innovation is instead diverted to middlemen who add minimal value. At Publicus, we're passionate about streamlining government processes through automation. While SR&ED reform isn't our current focus, we believe in raising awareness about the systemic, government-related inefficiencies that hold back Canadian tech companies. #CanadaTech #GovTech #Grants #Innovation

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Reflecting on the recent CEO Summit in Montreal, I found myself both inspired and anxious. Bringing together top leaders to discuss Canadian innovation in the context of post-COVID recovery and current macroeconomic challenges is invaluable. Networking, exchanging ideas, and sharing experiences are crucial in these uncertain times. However, I wonder about the tangible outcomes. Such gatherings should lead to actionable results, like a roadmap or clear recommendations. Hosting an online session or providing a detailed publication summarizing key conclusions could significantly enhance the event's impact. There's also a need for direct communication between these discussions and policymakers. Canada boasts ambitious entrepreneurs, but without supportive policies, their potential is limited. The government must listen, understand, and act to empower our innovation ecosystem. It's time to focus on outcomes that genuinely support Canadian innovation beyond the publicity. #CanadianInnovation #CEOsummitoutcomes #Policymakers #InnovationEcosystem Council of Canadian Innovators | Conseil canadien des innovateurs

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Today's experiment: I tried creating an AI Avatar from Vidyard (I stumbled upon their integration when I went to make a different video). Soon AI will be a natural part of every workflow. And tools that don't incorporate genAI capabilities will feel like they are missing something. In this experiment, I created a script in ChatGPT with the prompt, "Create a script that can be read that discusses the best things about visiting Whistler, keep it casual and upbeat. Mention that it is an all season resort. Maximum 1000 characters." I ran a second prompt asking to refine the script for a global audience and set context about where Whistler is located. Vidyard does have a script tool built in FWIW. I think this could be a process that is easily scaled to either add videos to existing websites or social feeds. And yes, the video itself is kind of boring, I just had a static page behind, but I think it could have easily been a demonstration. 🤖

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