Daniel (Dano) Jejcic

Interesting look at timing for funding companies from start up to series D thanks to data from Carta. The trend of going longer between rounds is certainly in play as companies struggle to meet the evolving proof points that each stage requires. Key takeaway - it always takes longer than you anticipate.

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Fundraising is a tough sport. In today's Startup Riders newsletter, insights on: - 3 hacks to improve your pitch deck in today's newsletter. - Netscape CEO’s guide to world-class communication. - 18 startup deals in Spain (>€150M). - I launched a YouTube channel. - Meme of the month Read it via link in bio Ivan Landabaso and in the comments below 👇 #founders #startups #entrepreneur #venturecapital #vc #tech #technology #B2BSales #ai #llm #artificialintelligence #saas #fundraising #business #entrepreneurship

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Congratulations to the 2024 YC Top Companies! Since 2005, YC has funded over 4,500 startups, including many that have become household names. The companies on this year's list are collectively valued at $458B, with a combined $57.2B in total revenue generated in 2023. Here are some more facts about the YC Top Companies this year: 🔸 13 companies (27%) on the list have had an exit, 11 are publicly traded. 🔸 Together, these companies employ over 80k people. 🔸 Over 50% are headquartered in the Bay Area. 🔸 Over 90% were founded by 2 or more co-founders. Congrats to the founders who are making something people want!

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🌟 What are the advantages & challenges of leveraging LLMs in startups? Last week we had a panel discussion on this topic featuring Bo Tranberg, CTO & Co-founder at Libra, Gabriela Hernández Larios, Machine Learning Specialist at Google, Lennard Schmidt, CEO & Co-founder at Langdock (YC S23). The discussion centered around various aspects of AI entrepreneurship, covering topics such as data access, compliance, model evaluation, and scalability. Here are some of our key takeaways: 1. Data's Crucial Role in AI Startups: High-quality data generation is vital for AI startups, offering monetization opportunities and aiding in training large language models. Successful startups often excel in data production and management. 2. Overcoming GPU Access Challenges: Access to GPUs in Europe can be tough. Solutions like Germany's open Telecom Cloud and partnerships with academic institutions provide valuable resources for AI development. 3. Importance of Compliance and Certification: Compliance with standards such as ISO 27001 and SOC 2 Type 2 is crucial for handling proprietary data securely. With the upcoming EU AI Act, staying informed and prepared for new compliance requirements is essential. 4. Efficient Model Management: Managing multiple AI models poses scalability challenges. Techniques like LoRA fine-tuning can optimize performance, enabling the efficient hosting of multiple models with minimal latency. 5. Preparing for the EU AI Act: The EU AI Act will introduce new compliance requirements based on risk categories. Startups should focus on documenting decision-making processes and maintaining transparency to prevent future issues. 🎥 Would you like to watch the full discussion? You can check it here: https://lnkd.in/dJAVtzaW 🤔 Want to check the latest insights on AI? https://lnkd.in/ebF8hpGi #AI #TechStartups #FoundationModels #MachineLearning #DataScience #TechFounders #ArtificialIntelligence #AIRegulation #DataManagement #AIResearch #CloudComputing #LLMs

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