Vojta Rocek

What would be the future of documents in the new AI world? I think we will see significant changes outside the contracts and legally binding documents. The most important change will be that content is more generated v/s written. 1. Creation and Writing ⏩ Generation and Editing. 2. Static documents ⏩ Live/Fluidic/Assembly of content. 3. Searching of docs ⏩ Querying for info. 4. Same doc for all ⏩ Personalized info for each. 5. Text-heavy docs ⏩ Multi-modal and info-rich. 6. Coarse Access control ⏩ Fine-grained node level access control. 7. Version control of doc ⏩ Version control of node. 8. Remembering docs ⏩ Remembering prompts/queries. This transition will take time, but I am seeing the beginning. What else one should expect to see?

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In the most recent episode of the Mobile Dev Memo podcast, I speak with Mikołaj Barczentewicz about the EDPB's recent opinion on the Pay or Okay model. We discuss the implications of the EDBP's opinion and the future of the Pay or Okay model for "large online platforms" in the EU. Find this episode wherever you consume podcast content by searching for Mobile Dev Memo.

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Good news about European venture performance is always welcome! 🇪🇺 🥳 But...and actually there are many "buts" on this one...these numbers are pretty meaningless. Where to start? - Apparently the European data is based on just 223 European VC funds spanning vintages from 1986 to 2023*. That's a low single digit percentage of the total number of European VC funds raised over that time. That's incredibly statistically insignificant. - It's IRR and not DPI. IRR can be more easily manipulated. It's done a lot. DPI matters way, waaay more than IRR. - The numbers are of unrealized performance. 😳 Which we all know you can't eat, and can also be rigged. Seriously, who gives a shit about unrealized gains? - Despite all that the numbers end up so close anyways that they're within any reasonable margin of error. So pretty neck and neck in an illiquid asset class. 🤷🏼‍♂️ - Also, let's be honest, averages don't matter in venture. It's a top decile driven asset class. It's all about outliers. That's way more important than geography. European VC is notoriously opaque. Academics often avoid including it in research on VC because of this. Much of European government LP data isn’t public, and government LPs make up a large chunk of LP commitments in Europe. Also, there have been examples of European government LPs selling underperforming fund stakes to other government buyers to prop up their numbers. Any report should be taken with a grain of salt. It’s adorable though that some quickly point to it having to be accurate simply because CA is involved, as if CA is infallible. CA has an agenda in doing this for a client (Invest Europe) which itself has an agenda to push. European venture has made great progress. It's a strong asset class that deserves more LP attention (much of the upside in European tech goes to North American LPs). Let the real numbers speak for themselves though. This ain't that. TLDR: These numbers are unrealized IRR based on a statistically insignificant dataset of funds. It's a nothingburger. https://lnkd.in/eytxpqpk * https://lnkd.in/eE3HTV5W

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Back then one of the main problems I had in fundraising for my startup was not knowing valuation benchmarks. That's why ~year ago we prepared key data for every founder in Central Eastern Europe. We're preparing the 2024 edition right now, so if you see any trends in the market, we're happy to include them! :) 👉 What size of the round can you expect? At what valuation? 👉 What do you have to deliver for every round? 👉 What is the expected capable structure? And many many others. Link to the 2023 benchmarks: https://lnkd.in/de3qvJBT #benchmarks #startups #fundraising

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Beyond The Hype: Should You Invest In Deeptech Today? 2024 is overflowing with talk about AI, quantum computing, and fusion breakthroughs. But is it just another tech bubble? And where is Europe on the global map? I decided to write an article about it for investors looking at the asst class and European founders building within it. The key points: - Grounded in Reality: Unlike the dot-com and crypto frenzies, deeptech is rooted in foundational innovations—think semiconductors in the 60s. We'll look into some data and examples. - Investment Stats: Nearly $15 billion has poured into European deeptech this year, despite a 70% funding dip in sectors like fintech. 📊 I also uncovered some interesting data on exit timing, value, and return for investors specialising in deeptech. - True Deeptech: Not all .ai companies are deeptech. Quite the contrary. The real deeptech players are solving core problems, not just riding the AI wave. In fact, the challenges they take on almost force deeptech solutions to emerge from these companies. And more! I'm adding the link to the article below, in the comments, and a major thanks to Yash Gaikwad for gathering most of the data and helping with the structuring. 👇 _______________________________________________________ #deeptech #familyoffices #limitedpartners #venturecapital #angelinvesting I'm a soloVC building my firm & community in public. 📢 On a mission to build a new kind of tech-driven VC firm at the intersection of Venture, Science and Community 👩‍🔬 👨‍💻 👫 💹 ❤️ & Follow+ to keep up with the journey 🛣️

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🚀 Investment Criteria and Fundraising Success 🚀 🔍 Techstar’s Marting Schilling delved into the success of 58 companies in the Tech Start DeepTech Berlin portfolio (2022-2024), analyzing 17 investment criteria to identify the strongest signals for early-stage fundraising success. 💡 💰 Top Indicators of Success: Monetisation Potential (0.61) Domain Expertise (0.59) Speed of Execution (0.57) Market & Timing (0.55) ❌ Least Correlated with Success: Role Clarity (0.12) Team Co-Location (0.08) Number of Cofounders (0.02) 🌟 To attract investors, founders should emphasize the top 4 categories and spend less time optimizing for less impactful factors like role clarity or co-location. While these might have other benefits, they don’t significantly boost fundraising success. 📈 #Investment #Fundraising #Techstars #DeepTech #StartupSuccess #VC #EarlyStage #Monetisation #DomainExpertise #MarketTiming #ExecutionSpeed

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🇪🇺 European companies in Y Combinator’s S24 batch [Part 1] (#goEurope) 👇 autarc (YC S24) (Berlin, Germany) 🇩🇪 founded by Etienne-Noel Krause, Thies Hansen and Marius Seufzer autarc is building the OS for Europe’s One-Stop Energy Installers, integrating CRM, planning, and design tools into a unified platform. Their solution helps SMB energy installers reduce pre-installation phases drastically, enabling efficient scaling of heat pump and photovoltaic systems. omnidock (YC S24) (Berlin, Germany) 🇩🇪 founded by Shayan Zakerzadeh, Christian Kohrs and Sebastian Rödling Omnidock provides an OS for global e-commerce expansion, allowing brands to plug in and expand across multiple marketplaces effortlessly. Acting as the merchant of record, Omnidock handles transactions, optimizes logistics, and simplifies multi-marketplace selling, increasing merchant revenue by at least 20%. Argil (YC S24) (Paris, France) 🇫🇷 founded by Laodis Menard and Brivael Le Pogam Argil is the video generation engine for the creator economy. Leveraging state-of-the-art deepfake models, their platform enables content creators to clone themselves, input a script, and generate engaging videos in minutes. It makes video production accessible for branding, education, and social media growth. The Forecasting Company (Paris, France) 🇫🇷 founded by Geoffrey Négiar and Joachim Fainberg The Forecasting Company is building foundation models for time series, providing enterprise-grade forecasting systems. Their plug-and-play solutions help enterprises improve operational decision-making, using a massive dataset of time-stamped information to create accurate and flexible predictions. Saturn AI (London, UK) 🇬🇧 founded by Amal Jolly, Michael Ettlinger, and Rohit Vaish, CFA Saturn is an AI-powered operating system for wealth management, automating compliance and back-office workflows. By streamlining processes and personalizing investment research, Saturn empowers wealth managers to focus on client engagement while reducing operational costs and inefficiencies. Patchwork Technologies (YC S24) (London, UK) 🇬🇧 founded by Benjamin H., Samuel Kramer, and Alex Maass Patchwork Technologies is developing the next-generation logging and observability platform. Automating logging from code to storage, Patchwork creates context-rich, actionable logs across entire codebases without manual intervention, simplifying the lives of developers and improving reliability in production environments. Tabular (Berlin, Germany) 🇩🇪 founded by Tim Hermes, Markus Jungnickel, Kilian Justus, and Leonard von Kleist Tabular is an AI copilot for accounting firms, automating core workflows such as booking expense accounts and VAT filings. Their solution enables accounting firms to generate finished ledger entries with a single click, addressing labor shortages in SMB accounting by transforming time-intensive tasks into streamlined processes. #euvc #venturecapital #vc

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Can the HOUSING PROBLEM really be solved with TOKENIZATION? Today, according to the 2025 building construction costs in Istanbul, a 100m2 house costs approximately 30-35.000USD. Sales prices for houses of the same size, for example in Kayabasi-Istanbul (Image below), start at around 125,000USD. Land shares are worth around 90.000USD, especially in publicly owned areas. In Türkiye, where the minimum wage is around 700USD, someone who saves all the money they earn for a 'house' can only pay for it in 14-15 years. So, where will people be housed? As tenants forever? SOLUTION: PUBLIC LAND can be TOKENIZED and collected in installments from property owners who will buy their 'first house' after the buildings are built (For example after 3 years).  In the meantime, for the first 3 years, all homebuyers can focus on paying for the building costs (around 1000USD per month). Central governments can also earn value from these LAND TOKENS by putting them on the market with bonds.  It is good for governments to make a profit, but not from low-income people trying to buy their first home! #tokenization #token #blockchain #web3 #housing

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🎉 Congratulations the Team! 🎉 Our product, YouKnowMeBest Social, has been recognized in a cutting-edge study from TU Vienna on Social-Aware Fashion Recommendation Systems (SAFRS) lead by Julia Neidhardt’s team, Head of the CD Lab for Recommender Systems. This research highlights the power of #usercentric and #socialaware recommendations, and I couldn’t be prouder of our team for leading the way in innovation. 💪 Here’s to more groundbreaking achievements ahead! 🚀 YouKnowMeBest. Real-life shopping experience online!  youknowme.best #ecommerce #onlineshopping #aiforgood #digitalhumanism #recommendersystems #innovation #digitaltransformation #InnovaticGroup #YouKnowMeBest #SocialShopping #chatgpt #gpt4

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VC in Europe: State of European Tech 24 by Atomico report is out. For sure an interesting read. The ecosystem is still growing quick. In an era where DPI is the new IRR, all eyes are on exits. Report is here: https://lnkd.in/eGdU4Thm #venturecapital #VC #Atomico #privatemarkets

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#dealtime! Just in time for our (overbooked) VII. PT1 Family Day (https://lnkd.in/dMzngJGk) Sifted (Financial Times) broke the news this morning that we led an excellent consortium of investors including Commerzbank Group's Neosfer, 468 Capital, Maximilian Tayenthal and the scout founds from Hedosophia & Andreessen Horowitz in the seed-round of Berlin-based Terra One - a special warm welcome to Tony Schumacher & Thomas Antonioli! This is not only portfolio company #23 for the PT1 funds but also our second bet on battery storage technology. Why are we so bullish on this sector and Terra One specifically? Decentralized storage enables the green energy transition by offloading stressed grids and also already today can earn decent $$/€€ if the operations & energy trading is done in a clever way, what is exactly Terra One's AI-enabled secret sauce. These IRRs are highly attractive for deep-pocket infra/renewable-investors that need to look beyond traditional solar, wind and RE-assets as the ROIs there are melting off.

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European VC Fundraising Uptick Germany's KfW Capital, has reported a significant uptick in VC fundraising, indicating a positive trend for startup investments. Jörg Goschin, managing director at KfW Capital, noted that fundraising was sluggish in 2022 and 2023, but things are "steadily improving." He highlighted that KfW Capital examined around 220 funds last year, expecting an even higher number this year. Goschin stated, “I think we can say that the light at the end of the tunnel which we saw last year is getting brighter.” KfW Capital is a prominent limited partner (LP) in various European VC funds, including Germany’s Project A, Earlybird Venture Capital, and France’s Partech. Since its establishment in 2018, KfW Capital has invested in 120 VC funds, with nine funded this year. Goschin also mentioned an increase in capital calls from VCs, which he described as a “reassuring” sign that investments in startups are also on the up. In analyzing the types of funds being considered, KfW Capital found that 50% of the 220 funds were from the ICT sector (SaaS startups, AI, marketplaces, and e-commerce). About a quarter of the funds focused on life sciences, while the remainder were generalist funds without a specific sector focus. Notably, KfW Capital is also witnessing an increase in deeptech funds seeking investment, which Goschin identified as necessary, given the longer development times associated with these types of investments. Gender diversity is a key focus for KfW Capital in its due diligence process, with 46.3% of the funds having at least one female GP in 2023. The firm’s €200 million emerging manager facility, aims to invest in funds with €50 million in AUM that prioritize representation of women and non-binary individuals in leadership roles. Its first investment through this facility was in Nucleus Capital, a deeptech and climate tech VC fund led by GPs Dr. Isabella Fandrych and Maximilian A. Schwarz. In terms of increasing private capital in VC, Goschin highlighted the launch of Germany's €1B Fund of funds last year, which aims to boost investments in German and European VC funds. He noted the importance of mobilizing private capital, especially as state budgets become tighter. “The mobilization of capital from private investors is very important, especially from a point of view as a sovereign investor,” he remarked. ✅ Looking to raise capital for your #VCfund and increase the international pool of your LPs?   🤝 Need warm #LP introductions?   📝 Selling #secondaries to increase liquidity?   🧐 Looking for co-investments (Series A/Series B)?   ▶ Please use G+QUANT's link for inquiries and fund decks, or send an inquiry to [email protected] #VentureCapital #VentureFunding #VentureDebt #Fundraising #Innovation #Technology #Entrepreneurship #Investing #Network #Investors #LPs #GPs #EmergingManagers #Economy #Business #Founders #Startups #StartupFunding #ai #artificialintelligence #unicorn #secondaries #secondarydeals

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Let’s assume that LLM GPT (n+1) variants do materially increase in reasoning and language skills which enable them to take on tasks with increasing complexity. Will the COGS of servicing those "more complicated" tasks create a market dynamic where older and less performant LLMs are good enough, especially if they are radically cheaper to operate? Maybe that implies some sort of distribution (bell curve?) where most tasks don't need state of the art LLMs, shifting usage and therefore dollars away from the highest performant LLMs. We might even get to a stage where open source models with near zero marginal cost to operate perform the vast majority of future task work. If that future comes to pass, maybe the business models of LLMs will reflect the very nature of current human labor. i.e. We pay interns a lot less than a PhD. Maybe an LLM that can solve a sophisticated analytical problem will need to have a very different pricing / compensation model than one that can only perform more rudimentary and repeatable work.

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https://lnkd.in/dmsFBj_T "My old boss Marc Andreessen liked to say that every failed idea from the Dotcom bubble would work now. It just took time - it took years to build out broadband, consumers had to buy PCs, retailers and big companies needed to build e-commerce infrastructure, a whole online ad business had to evolve and grow, and more fundamentally, consumers and businesses had to change their behaviour. The future can take a while - it took more than 20 years for 20% of US retail to move online." "A lot of these charts are really about what happens when the utopian dreams of AI maximalism meet the messy reality of consumer behaviour and enterprise IT budgets - it takes longer than you think, and it’s complicated (this is also one reason why I think ‘doomers’ are naive). The typical enterprise IT sales cycle is longer than the time since Chat GPT3.5 was launched, and Morgan Stanley’s latest CIO survey says that 30% of big company CIOs don’t expect to deploy anything before 2026." "In other words - “These things are the future and will change everything, right now, and they need all this money, and we have all this money.” As a lot of people have now pointed out, all of that adds up to a stupefyingly large amount of capex (and a lot of other investment too) being pulled forward for a technology that’s mostly still only in the experimental budgets." "Of course, the crazy dreams of the Dotcom bubble really did happen, and the AI maximalists might be right - it may be that LLMs can do the whole thing. LLMs may be able to swallow most or all of existing software, and they may be able to automate vast new classes of task that were never in software before, just by themselves and with whole new layers of product, company and enterprise sales built around them. This might be the first S-Curve in tech history that turns out to be a J-Curve. But not this year."

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#interestingdata 🤔 GenAI is now the largest category in cloud/SaaS venture capital investing in Europe + Israel according to Accel‘s Euroscape. 😮 TBH it is surprising that it is not more dominant. See source in comments. #AI #saas #cloud #venturecapital #europe

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The average number of planned market entries seems to drop after a certain amount raised (European tech companies). I'd welcome suggestions as to why that might be the case! Two hypotheses: - Founders that have raised more know how difficult it can be - Prior investment was used to expand already to a target market (not mutually exclusive) #internationalexpansion #fdi #capitalraising #startups #fundraising #founders #venturecapital #investors #vc #vcfunding #technology

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𝗕𝗲𝘆𝗼𝗻𝗱 𝘁𝗵𝗲 𝗢𝗯𝘃𝗶𝗼𝘂𝘀: 𝗛𝗼𝘄 𝗗𝗮𝘁𝗮 𝗖𝗮𝗻 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗲 𝗣𝗿𝗲-𝗦𝗲𝗲𝗱 𝗗𝗲𝗮𝗹 𝗙𝗹𝗼𝘄 𝗪𝗶𝘁𝗵𝗼𝘂𝘁 𝗩𝗲𝗻𝘁𝘂𝗿𝗲 𝗦𝘁𝘂𝗱𝗶𝗼𝘀 𝗼𝗿 𝗔𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗼𝗿𝘀 As a data-driven VC, I always believe that data can tell a story, and within that story lies the answer to seemingly impossible questions. One such question I’ve been thinking about is: how can pre-seed VC firms create new deal flow without being a venture builder, having a venture studio, running an accelerator, or having an entrepreneur in residence program? To think outside the box, I decided to let the data speak to me. The journey started with a search on LinkedIn for people who have the word founder or co-founder in their current titles, and Careem as a past company. Essentially, I wanted to see how many founders came out of Careem, one of the most successful startups to emerge from the MENA region. My search led me to 362 results! I did the same search with Talabat: 128 results, Foodics: 38 results, Anghami: 24 results, and even Tamara: 11 results. If you search for more, and dig deeper into the journeys of those individuals, you start to notice fascinating patterns. Some trends stand out: what roles they held, how long they worked there, and what they did before joining. Did they come from a corporate background or a consulting firm? Had they started or worked at venture-backed startups previously? What about their education — where did they study, and which cities did they live in? If you collect the data from LinkedIn alone, you can mine it and find even more trends. Ask a data scientist to help in this, and I’m sure he or she will be able to summarize surprising insights and stories from the data. Data science can reveal complex relationships and patterns that may not be immediately obvious. Machine learning techniques, for example, can cluster individuals with similar career paths or identify key predictors of future founders. By mapping the career trajectories of individuals coming out of unicorns or companies that experienced successful exits, we can begin to recognize potential founders who may already be working on promising ideas but haven’t reached out to angels or pre-seed VCs yet. As a pre-seed VC firm or an active angel investor, if you conduct this analysis, you can then identify dozens of potential founders, reach out to them, invite them for coffee or lunch, to either seed their companies if they have something already, or seed the relationship for future ideas. 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗲 𝗿𝗲𝗮𝗱𝗶𝗻𝗴 the full article here:

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