All-in-AI (as Pankaj.ai 🚀🚀🚀): AI Portfolio Career || AI Investor, Founder, Advisor, Speaker, Educator, Board Member @ 2468Ventures.vc | Former Internet, Mobile, Cloud Intrapreneur @ QCOM/INTC | Global AI150 Honoree |
Another masterpiece by Sequoia Capital !!! “Apps: The most interesting layer for venture capital. ~20 application layer companies with $1Bn+ in revenue were created during the cloud transition, another ~20 were created during the mobile transition, and we suspect the same will be true here.” I agree with the thesis AND actually think we will have 100+ application layer companies in the AI era with gargantuan outcomes because AI is impacting and disrupting EVERY industry sector in ways never seen before. Imagine a few *unicorns*, *decacorns*, *hectocorns*, *kilocorns* in healthcare and education and industrial and consumer and retail and … and … and…. Perhaps a couple of *megacorns*? Oh, what exciting times and investor’s dream 🚀🚀🚀. Aileen Lee, would love to hear your perspectives. Full report here: https://lnkd.in/g44cBgGS #AIDecade #InvestorDecade
Sebastian S.
2mo
I am hesitant to jump on this analogy. AI apps are either highly vertical or easy to be replaced by the infra layer (think: GPT wrappers). Unlike cloud or mobile, the infra layer for AI already has their own app layer build out and infra providers are used as apps by end users (chatgpt, claude, gemini, metaai, ...). The design of that app layer is very expandable too. What that means: 1) highly specific vertical solutions are prone to early acquisition (usually way before unicorn status) and might be capped in growth over time 2) horizontal solutions are quickly absorbed by infra layer or established SaaS players with existing distribution looking to diversify their AI app layer 3) most AI apps will be hard pressed to develop scale and longevity to grow beyond unicorn and sustain their moat over 10+ years (speed of technology change, opex, etc.)
Samir Kumar
2mo
What's missing from this stack is the investments Sequoia already made in the developer, data, security and infra layer for AI prior to this post ;)
Ram Patrachari
2mo
Excited about the potential to enhance the casino/hospitality industry that i am part of... Real-Time Player Interaction: Personalized experiences through virtual AI hosts, enhancing guest engagement. Operational Automation: Streamlining processes like staff scheduling and game floor optimization for maximum efficiency. Enhanced Security: Real-time monitoring and advanced fraud detection to safeguard operations. Targeted Marketing: AI-driven campaigns tailored to improve player retention and boost revenue. Predictive Maintenance: Ensuring smooth operations with AI-powered equipment monitoring and reduced downtime.
Anton L.
2mo
Pankaj Kedia Fascinating insight from Sequoia Capital! While their prediction of ~20 billion-dollar companies emerging in the AI era aligns with historical patterns, I believe we're underestimating AI's transformative power. The pervasiveness of AI across all sectors could indeed lead to an unprecedented boom, potentially yielding 100+ unicorns and beyond. The prospect of AI-driven megacorns in healthcare, education, and other critical industries is truly exciting. However, we should also consider the challenges: Market saturation: With so many AI startups, differentiation will be key. Ethical considerations: AI's rapid growth raises important questions about data privacy and algorithmic bias. Regulatory landscape: As AI becomes more prevalent, navigating evolving regulations will be crucial. While the potential for astronomical valuations is enticing, we must also focus on creating sustainable, responsible AI companies that deliver real value. The true measure of success in this AI revolution will be how these technologies improve lives and solve global challenges. What are your thoughts on balancing the excitement of this AI boom with responsible development and implementation?
Frederik Sally
2mo
Definitely excited about the potential, but as someone working in this space, i think scaling AI apps comes with unique challenges. Most apps today rely on infrastructure controlled by a few major players, which limits how much you can truly differentiate. but that’s also where the opportunity lies - finding creative ways to integrate and add value beyond just being a simple wrapper. Replicability is a real issue too, but the ones that break through will be the ones offering something unique, whether that’s in the user experience or in how they solve specific problems. so yeah, while we might not see hundreds of unicorns, there’s still huge potential for those who can carve out a space with real staying power. exciting times for sure!
Mahesh Ram
2mo
Pankaj I thought Aileen Lee ‘s perspective that she wrote about in late September was spot on and offers a different frame: https://www.cowboy.vc/news/do-startups-have-a-chance-vs-big-tech-in-the-age-of-ai-history-says-yes-in-due-time
Jason Bell
2mo
Now imagine that the three companies on the right acquire the tooling, data and security companies on the left. A scary prospect in reality. All control in a handful of companies.
Loved the flip concept of 'Services-as-a-software' that expands the market size of AI application companies from ~$300B to trillions. 🚀
You can add Xpdeep in the developer section. It's the first and only self-explainable deep learning framework. A game changer for understanding, optimizing and explaining deep models, and often for unlocking competitive advantage for products, services, and operations.
All-in-AI (as Pankaj.ai 🚀🚀🚀): AI Portfolio Career || AI Investor, Founder, Advisor, Speaker, Educator, Board Member @ 2468Ventures.vc | Former Internet, Mobile, Cloud Intrapreneur @ QCOM/INTC | Global AI150 Honoree |
2moPlus Angela Hoover