Navdeep Manaktala’s Post

Pondering whether integration or modularization is the better approach is a favourite pastime of techies that's akin to contemplating the popular chicken and egg dilemma. Being a Christensen follower, I believe that both have their places (the tech approaches not the poultry): 👉 If the technology is new - integrate 👉 If the technology is sufficiently advance - modularize However, if things were that simple Apple's integration approach in a very mature space should have failed several times over by now. What's better for AI - integration or modularisation? Big tech players like Apple, Google, and Microsoft are divided on the best approach. Ben Thompson dives deep into this topic in today's article.

This is a great post outlining the developing AI stacks being developed by the biggest players in the market. There will be different approaches for different reasons. | AI Integration and Modularization – Stratechery by Ben Thompson https://ow.ly/usKU50S4Gj0

AI Integration and Modularization Breaking down the Big Tech AI landscape through the lens of integration and modularization https://lnkd.in/gDYJDmBv

A very good read on AI and more in depth on Google..

Interesting article exploring the balance between integrated and modular AI models, highlighting how each approach drives innovation and efficiency in different ways. Insights: • Flexibility vs. Cohesion: Modular models offer flexibility and easy integration into existing systems, while integrated models provide cohesive, end-to-end solutions. • Innovation Pace: Modular AI enables faster innovation by combining specialized components, whereas integrated AI focuses on comprehensive, streamlined solutions. • Strategic Use Cases: Understanding when to use modular versus integrated AI can provide a competitive edge, optimizing technology deployment and scalability.

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AI conundrum - go modular or integrated? The debate between vertically integrated and modular components has been a long-standing one in tech. Now, as AI becomes increasingly central, healthcare product and marketing executives must consider how this dynamic will play out in their industry, and its strategic implications. Ben Thompson provides a great analysis into this topic in this Stratechery blog. Traditionally the business world has viewed this debate as one of agility (modular) versus reliability (integrated)- we've seen this dynamic play out with Microsoft PCs versus Macs and Androids versus iPhones. (Note that for consumers, a seamlessly integrated user experience is the preferred choice) . In the AI realm, however, NVIDIA's chip is used by most big tech players except Google. The AI/AGI platform strategies range from modular (i.e., AWS, Apple, Microsoft) through to fully integrated (i.e., Google). Their ultimate success will largely hinge on how disruptive large language models (LLMs) will be on computing (beyond search) and who is the best at optimizing their AI performance for that new paradigm. The worse the disruption, the bigger the advantage for integrated systems (easier to optimize performance). From his analysis, Thompson believes that while LLMs will vary, the real value will come in building platforms that treat them more like processors-fostering broader horizontal reach rather than vertical integration. What do you think? Here are some key take aways to consider for product and marketing: 1.   Understand the Landscape and Audience: Recognize the different approaches to AI integration. Modular systems offer flexibility, while integrated systems provide reliability and a seamless experience. 2.   Identify the Right Partners: Look for partners who align with your AI strategy, whether it’s modular or integrated. Consider how these partners can help optimize performance around LLMs and other AI technologies. 3.   Focus on Platform Building: Invest in platforms that maximize the horizontal reach of AI technologies. This approach can enhance scalability and adaptability in a rapidly evolving landscape. 4.   Prepare for Disruption: Stay agile and be ready to adapt as LLMs and other AI advancements disrupt the industry. The ability to pivot quickly can be a significant competitive advantage.

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Your AI toolkit just got a powerful upgrade. In our latest Technically Speaking, discover how AI-powered composability and AsyncAPI are transforming integration.

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