Phil Rivard

Facts about BDC and why you should avoid them as a Black led startup. According to Crunchbase:  Total investments: 697 Total white investment: 695 Total black/women investment: 2  My experience with BDC: I have no problem paying for the application. But when financial institutions decide to invest in a startup and have a risk department review - that is a red flag. Every damn startup is risky - so what exactly are you looking for and taking the application fee upfront?  They pull you in with a term sheet and take a 1% application fee of the money upfront before determining your risk factor.  You have a sales pitch from their analyst who poured their heart into building their case for your business. My problem is when they demand confidential documents, some information has nothing to do with their decision. They have no clear guidelines on what you should provide, and the decision is based on a handful of people in the "risk department." There is no proper representation of people of colour. Everyone knows BDC is run by top management -aka "risk department". Why steal innocent startup money through application fees, and collect a lot of data and share it with government agencies without prior written consent? That is an abuse of startup data; they have no NDA and do not disclose who they share the company data with. That is privileged information, and there should be a class-action lawsuit.  Instead of advising the startup of the risk of losing the application fee and who they share their information with, they expect you to give privileged information without equal rights.  Think of BDC as a money-making data farm. The question still remains: who else has my company information, and for how long? I don't need your money - I just hate thieves.

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Last month, I talked to +35 B2B founders doing north of $3M. Turns out, most of the time, building a founder brand goes through these 5 phases: (check out the timestamps) 0:01 - founder tries do-it-yourself way We start seeing more of 'thrilled to announce...' & 'we just launched...' posts with brick-sized blocks of text. Corporate-speak is the official language. They don't put much effort in and admit defeat, and we don't get to consume all the subject matter expertize they could've shared. 0:22 - founder hires a ghostwriter Turns into a disappointed very quickly. They have to spend a similar amount of time but the outcome is even worse. Probably because the young ghostwriter learned his trade from a Linkedin guru's course and has ZERO understanding of the subject matter.... They only know how to write motivational 'being a dad taught me these 5 lessons about startups' posts, strictly following what guru prescribed. 0:53 - founder hires a ghostwriting agency The agency is founded by 2 guys that grew their following by posting memes and Twitter screenshots of truisms ('marketing is about empathy', 'talk to customers'...), and now they outsource all the work to cheap ghostwriters, so eventually, the same happens. 1:29 - founder buys a $997 course from a LinkedIn guru It may not be the same course that the young ghostwriter bought, but it's basically the same. All of them are. The course creator grew their following by talking about growing on LinkedIn and joining engagement pods and now shares advice that only works if you want to... sell a LinkedIn course. 1:53 - Raven comes and saves the day Founder realizes they have to do this themselves because this new age calls for a distribution-first founder and they make marketing their top priority. They find that they need to find message-founder fit (overlap of their lived experiences + customer jobs to be done + product offering). They improve their tactical mastery (writing hooks, structuring, better writing). They now have a peer support group and direct access to an expert. They're held accountable because all progress is tracked in a collective dashboard. Their founder brand finally starts growing. PSS. You can sign up for my founder brand community waitlist here and get 30% off when we 'go public': https://lnkd.in/d59AzBG2

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Some VCs call it "diversification" when it is really just a lack of conviction.  They spread their investments in as many companies as possible and hope one succeeds—” spray and pray,” as it's called. At Bonfire Ventures 🔥, we do the opposite: Instead of chasing every shiny opportunity, we invest in fewer companies and go all in. We are a low-volume, high-conviction, high-support investor, and as Fred Wilson says, "That is who you want on your side." We invest in 8-10 deals per year, with a first check of $2-4 million each, and reserve plenty of follow-on capital. Why? Anyone can write a check. The real challenge—and the actual value—is in the subsequent and ongoing partnership. You can’t build meaningful relationships with founders, provide hands-on support, and be there for the good days and the bad if you're juggling a hundred projects. You need to know the founders, the market, and the business inside and out. That's what we do. During my investment banking days, I learned that you can’t work with every company that knocks on your door. You pick the ones you truly believe in, where you can see the potential in both the people and the product. Scopely is a prime example. We didn’t just invest in 2012. We worked closely with them and rolled up our sleeves. That partnership turned into a $5 billion cash exit in 2023. That’s what happens when you focus on quality over quantity. At Bonfire, our founders aren’t just another check in a portfolio. We’re not in the game of betting on every horse - we’re here to invest in the right ones - and then we go to work. How do you decide where to focus your energy? What drives your decisions, whether you're building a business, launching a project, or choosing investments?

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I just released the April edition of my AI & the Web newsletter. Nathaniel Simard, founder & CEO of Tracel Technologies and inventor of the burn ML framework, spoke with me about how he got into ML, burn, Tracel and the future of AI. WebGPU, the successor of WebGL, will soon also be supported in Firefox and Safari. Small, powerful LLMs running right in the browser is not a distant future, but are the next big thing in cost-effective and privacy-friendly AI. Google is working hard on better WASM support in the browser that makes ML models running fast even on low-end devices without GPU. With Llama 3 by AI at Meta and Phi 3 by Microsoft AI we got some exciting new, small modells. Llama 3 was already ported to run in the browser and we'll see Phi 3 soon as well. MusicGen has been ported to the browser in transformers.js by Hugging Face engineers and developed an online Jukebox running right in the browser. #webgpu #webml #ai #ml #llama3 #wasm https://lnkd.in/drJCY7Ew

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Generative AI is not just a Silicon Valley game. The core computer science was developed at the University of Toronto (Geoffrey Hinton), University of Montreal (Yoshua Benigo) and Yann LeCun (Bell Labs and NYU). DeepMind was based in London. And Chinese companies have been hyperactive in the space. It is important to keep an open mind on where the innovations will come from. https://lnkd.in/gCTVNFJ3 #AI #generativeAI #innovation

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𝗚𝗿𝗲𝗮𝘁 𝘁𝗲𝗮𝗺𝘀 𝗮𝗿𝗲𝗻’𝘁 𝗷𝘂𝘀𝘁 𝗳𝗼𝘂𝗻𝗱—𝘁𝗵𝗲𝘆’𝗿𝗲 𝗯𝘂𝗶𝗹𝘁 𝘄𝗶𝘁𝗵 𝗶𝗻𝘁𝗲𝗻𝘁𝗶𝗼𝗻𝗅 (here is how 👇) More than half of startups fail due to co-founder conflict. Unspoken expectations, unclear roles, and misaligned goals can derail even the best ideas. The solution? Build your co-founding team with intention. Before you dive into your business, align on the critical aspects of your venture and working relationship. A founder agreement is a great tool to guide these essential conversations. Here is a framework to get started: 1️⃣ Personal Goals & Vision What motivates us to start this company? What does success look like, and are we aligned on timelines and growth aspirations (e.g., Unicorn vs. sustainable business)? 2️⃣ Roles & Responsibilities Are roles clearly defined, or do we have skill gaps? How will decisions be made, and how will conflicts be resolved? 3️⃣ Personal Situations Are we financially ready for this journey? How will we manage other commitments and distractions? 4️⃣ Trust & Relationships Have we worked together enough to understand our dynamics? Can we communicate openly, honestly, and constructively? 5️⃣ Equity, Vesting & Investment How will we handle equity, funding, or co-founder changes in the future? 6️⃣ Commitment Are we all ready to go all-in, and what are our timelines? Building the right team and aligning on these areas can make all the difference. 💡 Full Founders Agreement framework available in the comments! (credit to @Talentkick)👇

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There is a new #searchengine in town going after #Google and #Perplexity out of Canada A new AI-first search engine, Upend, has emerged from stealth, aiming to democratize access to advanced generative AI models. Upend is a Canadian startup that has just launched its AI-powered search platform, offering users a unique and powerful search experience. Access to 100+ Large Language Models (LLMs): Upend provides users with a wide selection of LLMs, including models from #OpenAI , #Claude , #Mistral , and more, allowing for diverse and specialized search capabilities. Upend offers the option to base search results on Wikipedia, providing users with grounded and cited information. Affordable Pricing: Upend aims to democratize access to advanced AI search by offering team plans starting at $20/month, significantly lower than competitors. Upend's mission to make AI search more accessible and affordable is a significant step towards empowering students, professionals, and businesses to harness the power of generative AI. _______ 🤩 Enjoy being the first to get news like this? ♻️ Repost it to your network and follow Ben Silverman for more! Want to stay up to date on all of the latest news and tools and get them directly to your inbox every week? ⛏️ Join our community of 2,000 + subscribers today https://lnkd.in/gMDQ6CDd https://lnkd.in/dneXZDbK https://lnkd.in/gfMvRbyq

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I’ve noticed many founders don’t realize how much non-dilutive capital is flying under the radar in Canada. So I’ve shared a list of alternatives you should know about before choosing to raise capital: 1. Business Scale-up and Productivity (BSP): BSP provides funding to help you scale your operations and increase your market reach. It’s a great way to drive growth without sacrificing equity. 2. Industrial Research Assistance Program (IRAP): IRAP offers financial support for research and development. It’s perfect for taking your technical ideas to the next level. 3. Scientific Research and Experimental Development (SR&ED): SR&ED provides tax incentives for technical development. It’s one of the most generous programs in Canada, helping you reclaim a portion of your R&D costs. 4. FedDev Ontario: If you’re based in Southern Ontario, FedDev offers funding to help businesses scale, innovate, and compete globally. It’s a solid option for companies looking to make a big impact. 5. Canada Small Business Financing Program (CSBFP): This program helps small businesses access loans for purchasing or improving assets like equipment or property. It’s designed to help companies grow and invest in their infrastructure. 6. CanExport SMEs Program: If you’re looking to expand into international markets, CanExport provides funding to cover costs related to market research, business travel, and participation in international trade events. 7. Canada Media Fund (CMF): For those in the digital media industry, CMF offers funding for the development, production, and marketing of innovative media projects. 8. Ontario Centres of Excellence (OCE) Programs: OCE offers various funding programs aimed at driving innovation and commercialization in Ontario. Their programs often focus on collaboration between businesses and academic institutions. 9. Mitacs Accelerate: This program provides funding to support research internships, allowing companies to collaborate with universities to solve specific challenges while benefiting from academic expertise. 10. Strategic Innovation Fund (SIF): Targeted at larger-scale projects, SIF offers funding to support R&D, commercialization, and the growth of innovative businesses in Canada. 11. Women Entrepreneurship Strategy (WES) Ecosystem Fund: This fund supports organizations that help women entrepreneurs grow their businesses. It’s part of a broader effort to increase women’s participation in the economy. 12. Innovative Solutions Canada (ISC): This program helps Canadian startups by funding R&D projects that address government challenges. It’s a great way to secure funding while working on real-world problems. 13. Alberta Innovates: For businesses in Alberta, Alberta Innovates offers several funding programs to support R&D, commercialization, and business growth. They focus on fostering innovation in sectors like energy, health, and technology. Have I missed any?

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Exciting news in the #AI world! 🚀 Cohere, the Toronto-based generative AI startup, just secured a massive $500M funding round, skyrocketing its valuation to $5.5B. Three key takeaways from this TechCrunch article: - Cohere's enterprise-focused approach is paying off. By customizing AI models for companies like Oracle and Notion, they've grown from $13M to $35M in annualized revenue in just three months. - Major tech players are taking notice. Investors in this round include Cisco, AMD, Fujitsu, and even AI chip giant NVIDIA. - They're doubling down on growth. With plans to expand their 250-person team by 100% this year, Cohere is gearing up for something big. As someone watching the AI space closely, I'm intrigued by Cohere's strategy of tailoring models to specific business needs. It is setting them apart in a crowded field. What do you think about Cohere's approach? Do you see enterprise-focused AI as the next big wave in tech? Let's discuss it! #AI #TechInvestment #FutureOfBusiness

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🚨 One-third of AI projects just for show #Relief! And Kudos! Calgary Public Library 📈 How To Make Decisions Like A Billionaire My weekly Tech news round-up of news you can use: 🚨 One-third of AI projects just for show 💡 The main purpose of AI initiatives is to show investors and stakeholders their organization is doing something with AI. However, “You can’t put the toothpaste back in the tube.” AI is happening, and businesses need to embrace it. Here’s how: 👇 https://lnkd.in/ghrkEUz9 #Relief! And Kudos! No personal data leaked in Calgary Public Library cybersecurity attack 🎉 👏 Kudos to Calgary Public Library's cybersecurity team and incident response protocols that blocked a recent cyber attack. Ransomware attacks are on the rise—stay vigilant, folks! 🔐 https://lnkd.in/gpHGap8C 📈 How To Make Decisions Like A Billionaire These well-known billionaires prove that a boring, principle-driven approach can lead to massive success. 💼 Ray Dalio has detailed playbooks guiding every decision, from investing to hiring. 📊 Bill Gates says measure everything: "If you can’t measure it, you can’t improve it.” ⏰ Warren Buffett lives by a strict routine. Choose method over madness. https://lnkd.in/gczGwq_s

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According to Harvard Business School, around 65% of promising startups fail due to co-founder disagreements. And yet the general thinking - according to YC - is that it’s still more advisable to look for a co-founder than to go solo. So if the pressure of finding your ideal co-founding team wasn’t enough, it becomes even more daunting when you’re aware of the risks. And yet, I find it interesting that some of the most successful partnerships arise more or less serendipitously. Take Dropbox as an example: initially a solo venture, Drew Houston was advised by Paul Graham to find a co-founder if he was serious about YC. Through friends of friends, he met his co-founder, Arash Ferdowsi, spent a grand total of 2 hours talking in a coffee house, and in his words, “got married on the first date”. Against all odds, the two had an incredibly successful collaboration that lasted 13 years. Embracing serendipity whilst actively seeking out compatible partners seems like a contradiction - but it’s often the case that when it does work, it’s really something to see. 🍀 Check out Drew's story below! #cofounders #founderstories #ycombinator #startups #founders

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🚀🔍 A great analysis by Index Ventures on Vertical AI companies as part of the Application Layer of the AI stack. "With the AI Platform Shift upon us, we believe that the next logical iteration of vertical SaaS will be Vertical AI – vertically-focused AI platforms, bundled alongside workflow SaaS, built on top of models which have been uniquely trained on industry-specific datasets." The few things that will differentiate the winners in the race, as mentioned in the article:  - access to proprietary industry data,  - effectively train large language models against those datasets,  - package those models via applications,  - deliver tremendous utility with fast time-to-value for customers, At Neurolabs, we care a lot about the time-to-value, which is why we’ve built these exact steps for our Image recognition solution.✅ With speed of execution & user experience at core, we go a step further and train our large vision models with synthetic data, delivering an even faster onboarding experience for our CPG customers & partners. 🤝 If you're facing challenges with your IR projects, let’s talk. There's no need to rely on outdated methods. Synthetic IR is here to propel us into the future! 🚀 #syntheticimagerecognition #syntheticdata #computervision #imagerecognition #cpg #retailexecution  

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In 1903 - five weeks before the first flight - the NYT was adamant: there won't be airplanes for a million years. Yesterday, a developper told me “AI wouldn’t code as well as he does before at least 2050”.  Both claims are equally delusional. So why do people get so wrong on predictions - and especially experts? 2 years ago, chatGPT came out ; the model was, for today’s standards, very stupid. Midjourney could barely generate a coherent image. Video was completely out of the picture.   Today, random people that have never written a line of code spit out functional applications with Cursor in a few hours ; I have our “AI developper agent” fix stuff on our platform every day. Nobody can make the difference between a Midjourney image and a real one ; VEO2 outputs video with an incredible understanding of physics. Yet, had I made these predictions in 2023, I would’ve been called all sorts of names by experts in each of these fields.  It turns out there are 2 very counter intuitive facts about predictions: • Generalists outperform specialists • Specialists aren’t better at making predictions in their own fields than “monkeys throwing darts” (quoting Philip Tetlock here).  In his book Range, David Epstein’s shows that the “jack-of-all-trades” approach often leads to better foresight. When you see problems from multiple angles, you can spot patterns that specialists—often stuck in the details—completely overlook. In fact, Philip Tetlock's 40 years of research on forecasting shows that deep domain expertise can lead to overconfidence by ignoring signals outside of your field. When you’re only working on one part of the puzzle, you may not see that there are other parts around that could click well with yours. You also tend to be defensive about your expertise.  This is why recently, an ex Google AI researcher told me that most of his colleagues thought that the OpenAI team was a bunch of lunatics until chatGPT came out, which was an absolute shock for them, both in terms of capabilities and adoption. Had he had to guess in 2016, he would’ve been decades off, he told me.  This is also why investing on the opposite predictions of expert Jim Cramer was one of the best investment you could make in 2024.  Many entrepreneurs innovated precisely because they weren’t specialists: Invisalign was founded by someone who hadn’t studied teeth ; James Dyson went to art school.  Yes, the progress of AI raises more questions than it answers ; making predictions is not about giving solutions but simply raising flags and bringing awareness - starting vital conversations. It has to come with caution, and it’s easy to extrapolate from trends that may very well plateau soon. But one thing is pretty clear: AI won’t take 30 more years to have an impact on the world. Get ready.

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Launch Like a Pro: 10 Easy Steps to Get Your Startup Rolling So you've built this amazing product, but how do you get it out there? No worries, we've got you covered! Here are 10 simple steps to launch like a pro: 📌 Really Know Your Customers: Talk to real people who might use your product. Find out what problems they have and how yours can help. 📌 Get People Excited Before Launch: Build some buzz! Create a website with a signup for early birds. Tease your product on social media or partner with influencers. 📌 Become the Expert: Share your knowledge! Write blog posts, make videos, or create anything that shows your product's awesomeness. 📌 Let People Try Before They Buy: Offer a free trial or a free version of your product so people can see what they're missing! 📌 Team Up with Others: Partner with businesses that sell similar things to reach new people. Maybe you can offer something together? 📌 Get in the News! Tell the world how amazing your product is! Write a press release and send it to websites, magazines, or podcasts. 📌 Build a Community: Create a space online where people who love your product can chat and learn from each other. 📌 Track What's Working: Keep an eye on how your launch is going. Is it working? Change things up if it's not! 📌 Help People Use Your Product: Make it easy for new customers to get started. Offer guides, videos, or even a support team! 📌 Turn Happy Customers into Fans: Reward people who love your product for telling others. Referral programs can be super helpful! Remember, launching a startup is all about learning and adjusting. These are just a few ideas to get you started! What other tips do YOU have for a killer launch? #startups #tips #canada #business

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Tinkerer founders are better than researcher founders. Don't get overwhelmed if you don't know about transformers or self-attention when building an AI startup. Researcher founders would give a very technical Gen AI definition; it's the successor to Generative Adversarial Networks (GAN), or an AI that has a chat interface. In my view, technically it's using any AI architecture that is state-of-the-art beyond the 'transformer.' More broadly, Gen AI has moved 'AI below the API', where traditional AI companies had to build that intelligence from the ground up. Also in GenAI, the companies that are winning are the ones able to design magical user experiences (UX) that this AI enables. It is not about the research behind it. A favorite consumer example is Suno.AI, where what would have taken weeks now happens in 2 minutes - an entire song is generated that quickly. It's true that investors in the Valley were funding only if you were ex-Google Brain, Stanford, or from any AI research lab. They wanted to back founders with prior experience in pre-training, using GPU clusters, etc., because they thought that was scarce and therefore a source of differentiation and defense. They have learned their lesson after Inflection.AI (acqui-hired by Microsoft), Adept.AI (acqui-hired by AWS), and Character.AI (acqui-hired by Google). Founders of Adept and Character.AI were among the authors of the groundbreaking paper "Attention is All You Need," considered groundbreaking AI research of the last 60 years. When I built my computer vision startup 15 years ago, this is one of the first things I realized: a research background can be a source of insight, but that's never enough. Since then, with every company I've worked with or invested in, I get concerned if there are research-only experienced founders without broader founder skills. Founders succeed because of their emotional resilience. Among functional skills, they need a mix of product chops, customer empathy, and the ability to inspire a team to work on a mission and a few more. You would say Character.AI had most of it; yes, it had the best promise, they had the best retention in the history of AI products. Reddit was filled with teenagers reporting addiction to Character.AI, spending 8 hours or more daily. But they likely faltered in capitalizing the business, the ran out of funding before sustainable revenue in sight. Tinkerer founders never make this mistake. If you tinker fast, pivot to the direction where growth takes off, get early and sufficient revenue to keep control of your startup's fate, and keep customers and employees happy, you don't need to know which of 'tanh', 'relu', or 'sigmoid' are better activation function for your GenAI model.

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