THEO Growth’s Post

🚀 The Generative AI Revolution is Here! AI is no longer just a tool—it’s reshaping industries by automating creativity, sparking new business models, and driving unprecedented productivity. Companies adopting generative AI are seeing massive potential, but success depends on strategic implementation. This isn’t just about tech—it’s about innovation 5 Key Takeaways on Generative AI and Where to Play in AI Next: 1. Creativity on Autopilot: AI is transforming creative processes and accelerating innovation. 2. Industry Disruption: Generative AI is redefining entire industries with game-changing capabilities. 3. Strategic Integration: Companies need thoughtful AI integration to unlock its full value. 4. Service-as-a-Software: AI is expanding beyond software to transform entire service industries—a trillion-dollar opportunity. 5. Apps Layer is Booming: The most attractive space for innovation, with fewer competitors from the tech giants. For more insights, check out Sequoia’s take on this exciting shift: Read more. https://lnkd.in/gAq8ih_a

From Fast Thinking to Slow Thinking: The AI Leap You Need to Know About We know how most AI gives instant answers, like a reflex? Well, we’re entering a whole new phase. Now, it’s learning to stop and think. AI is getting smarter—not just faster. Daniel Kahneman’s “Thinking, Fast and Slow” talks about two ways humans make decisions. There’s System 1, which is fast and intuitive, and System 2, which is slower, more thoughtful. Until now, AI has been like System 1—great at rapid responses, but not so good at complex reasoning. That’s changing. OpenAI’s new “Strawberry o1” model doesn’t just predict—it pauses, considers options, and reasons. Just like a person stepping back to solve a tricky problem. This is huge. Imagine AI solving math problems, writing code, or making strategic decisions—not by guessing, but by thinking through the problem. Remember when AlphaGo surprised the world by strategizing instead of just playing by the book? We’re at that same moment with AI now. We’re not just seeing speed; we’re seeing real intelligence. Kahneman would say fast thinking is great for simple stuff, but the real breakthroughs happen when you slow down and think. That’s where AI is headed. And honestly, it’s about to outthink us all in some ways. The real question is, how far can we take this? are we ready for AI that truly thinks? #GenerativeAI #ThinkingFastAndSlow #AIThinking #System2 #AIRevolution

AI is moving quickly and the sooner organizations learn how best to adapt it's uses to their operations, the bigger jump they will have on the competition!

Generative AI has undergone a remarkable transformation, moving beyond pattern matching ("System 1") to developing reasoning capabilities ("System 2"), marking a pivotal shift in its evolution. As Sequoia Capital's latest insights suggest, OpenAI's model update "o1" exemplifies this change with "inference-time compute," enabling models to "stop and think" before responding. For businesses, this presents both challenges and opportunities. Founders may no longer compete in foundational models, as tech giants dominate this space. Instead, value creation now resides in agentic applications—domain-specific AI that combines reasoning with real-world utility. Startups that understand the nuances of cognitive architectures can disrupt vast service industries as AI becomes increasingly capable of handling complex workflows autonomously. In short, the race is no longer just about who has the best models, but who can turn reasoning into scalable, valuable AI-driven services—making this an exciting time for innovation. Read Sonya Huang and Pat Grady's full essay here: https://lnkd.in/eQY5tWiY

The shift from "thinking fast" (rapid responses) to "thinking slow" (deliberate reasoning) is turning out to be crucial for the next generation of AI applications. This transition enables AI systems to engage in more complex problem-solving and cognitive operations during inference, rather than just relying on pre-trained data. Thinking ahead, multi-agent systems, like Factory’s droids, may begin to proliferate as ways of modeling reasoning and social learning processes. Once we can do work, we can have teams of workers accomplishing so much more. Quite an insightful article from Sequoia capital. Read on!! #AI #LLM #AIagents

Sequoia's analysis of generative AI's evolution towards more sophisticated reasoning aligns with the growing needs of enterprises for advanced AI-powered tools. Enter Glean. Enterprises today face challenges in managing vast amounts of information and optimizing knowledge worker productivity. They require solutions that go beyond simple information retrieval to provide context-aware assistance and facilitate complex decision-making processes. With Glean's knowledge graph and ability to allow models to understand your Enterprise (docs in comments), it understands enterprise-specific contexts and workflows. Glean offers a more nuanced and valuable solution than traditional enterprise search tools. This aligns with the "thinking slow" concept (RIP Daniel Kleinman) Sequoia mentions, where AI systems engage in more deliberate reasoning to tackle complex tasks. An AI assistant that can not only find relevant information but also help analyze it and suggest actions based on company-specific processes could substantially enhance productivity is a game changer. https://lnkd.in/gU7rAXhm #glean #knowledgegraph #RAG #AI

Could AI's dependence on AI-generated data lead to a "model collapse"? Are we truly doomed? Let's discuss! 💥➡ Experts are raising red flags about the potential for "model collapse" within the world of generative artificial intelligence. As our reliance on this innovative technology deepens, so too does the amount of data generated by these AI systems themselves. But could this cycle ultimately result in diminishing quality and functionality? This calamity, referred to as "model collapse", is worrying tech pundits. The term arises from the scenario where evolving algorithms start producing repetitive, irrelevant or even nonsensical outputs due to a lack of fresh, organic input data. All of which poses an important question: Is there a looming pitfall that could unravel years of progress in generative artificial intelligence? Or can we steer clear from this technological doom through guided strategies and preemptive measures? For more insights read here: https://lnkd.in/d6DCnB_T These experts' warnings highlight why innovation is crucial for progress. Ignite your corporate innovation with us! 🚀 We offer specialized AI solutions and automation tools tailored to drive growth and elevate corporate success stories. Join over 160K+ decision-makers, investors, innovators leading companies across industries transforming their operations & creating new revenue streams through strategic collaborations & startup investments driven by our advanced technology solutions. Book your meeting today ➡ \[https://lnkd.in/d4tYzr3j) Stay ahead with us! #AI #ArtificialIntelligence #ModelCollapse #AIinnovation #AIGrowth #AiGeneratedData #TechnologyTrends #AutomationTools #CorporateInnovation ##CrisisManagement

New Blog Alert! We're excited to share Aman Tailor's latest blog on InsideTechie: "The Power of AI and ML: Innovations Building the Future Technologies." In this insightful post, Aman delves into how artificial intelligence and machine learning are transforming various industries and what the future holds. Whether you're a tech enthusiast or a professional in the field, this article offers valuable insights. Read more: https://lnkd.in/dUCkqADJ Stay ahead with our latest insights and blogs: https://insidetechie.blog/ #InsideTechie #AI #machinelearning #techinnovation #technology #developers #techTrends #futuretrends #techtrends #techblog #appdevelopment Vishal Shah Rahul Pixel Pratik Trivedi Rupali Soni

Sequoia’s recent article, “Generative AI’s ‘Act 0.1’”, explores how generative AI is entering a new phase—moving beyond content creation to enabling intelligent agents that can autonomously perform tasks and interact more naturally with humans. This got me thinking about how this evolution might reshape our perspective on SaaS and our interaction with the internet. Are we reaching a threshold where the internet transforms from a tool or point of consumption into a relationship? Imagine setting requirements and providing direction to intelligent agents, then letting them work autonomously—checking in as we would with team members to monitor progress and offer feedback. This shift could move us away from prioritizing websites that are just ‘fast’ and attention-grabbing, towards platforms that are accurate and reliable within our specified parameters. Consider the role of an analyst. Instead of manually crunching numbers and compiling reports, we could point an intelligent agent at our datasets and ask for a comprehensive analysis with actionable insights and next steps. These agents could even incorporate external data sources we don’t own, enriching the insights with market trends or competitive intelligence. We’d interact with them by reviewing their findings, providing feedback, and refining their algorithms—much like collaborating with a human analyst. This paradigm shift could fundamentally change how we design and engage with digital products. It’s an exciting prospect that invites us to rethink productivity, user experience, and our relationship with technology. How do you see this transformation impacting the way we build and use technology? #AI #GenAI #product https://lnkd.in/gxJ6KeWy

Could AI's dependence on AI-generated data lead to a "model collapse"? Are we truly doomed? Let's discuss! 💥➡ Experts are raising red flags about the potential for "model collapse" within the world of generative artificial intelligence. As our reliance on this innovative technology deepens, so too does the amount of data generated by these AI systems themselves. But could this cycle ultimately result in diminishing quality and functionality? This calamity, referred to as "model collapse", is worrying tech pundits. The term arises from the scenario where evolving algorithms start producing repetitive, irrelevant or even nonsensical outputs due to a lack of fresh, organic input data. All of which poses an important question: Is there a looming pitfall that could unravel years of progress in generative artificial intelligence? Or can we steer clear from this technological doom through guided strategies and preemptive measures? For more insights read here: https://lnkd.in/d6DCnB_T These experts' warnings highlight why innovation is crucial for progress. Ignite your corporate innovation with us! 🚀 We offer specialized AI solutions and automation tools tailored to drive growth and elevate corporate success stories. Join over 160K+ decision-makers, investors, innovators leading companies across industries transforming their operations & creating new revenue streams through strategic collaborations & startup investments driven by our advanced technology solutions. Book your meeting today ➡ \[https://lnkd.in/d4tYzr3j) Stay ahead with us! #AI #ArtificialIntelligence #ModelCollapse #AIinnovation #AIGrowth #AiGeneratedData #TechnologyTrends #AutomationTools #CorporateInnovation ##CrisisManagement