Are AI Models Getting Commoditised?

AI commoditisation is something I’ve seen many people in the industry talking about lately, and it really reflects where things are headed. For AI companies, this calls for a strategic shift in how they approach AI.

Hi folks! 😀 It’s been a busy few weeks, but now that I’ve got some time, let’s dive into today’s topic!

Satya Nadella recently pointed out that AI is becoming more of a commodity. The value in AI is shifting from the models themselves to how they are used. With AI models becoming more accessible and similar in performance, the real impact now lies in creating customized solutions that bring tangible benefits. 

Nandan Nilekani shares a similar view- 

“Ultimately, the models will become more commoditized, and the value will switch to the application layer and the whole stack.”

So, the question isn't about "Who has the best model?" but "How to use these models effectively to create real value?"

All the big names in AI are pushing this movement forward, and the real value now lies in how businesses apply AI to achieve results. Let’s explore what that means in today’s edition!

First, What’s Driving AI Commoditization?

I think there are several key factors at play:

• Increased Accessibility: Open-source AI models and platforms are making advanced AI tools available to a wider audience, reducing the exclusivity of advanced AI.
• Standardization: As AI models become more similar in performance, differentiating between them becomes harder.
• Cost Reductions: Lower costs for computing power and data storage are making it easier for companies to build and deploy AI solutions.
• Widespread Adoption: AI is being integrated into everyday workflows, making it less of a novelty and more of a standard tool.

How Are Big Players Responding?

Here’s how some of the major players are reacting to this shift:

• Microsoft: The latest wave of Microsoft 365 Copilot is a perfect example of how AI is being integrated into everyday workflows to enhance productivity.
• OpenAI: By reducing the costs of using GPT-4 and its latest model, GPT-4o, OpenAI has made AI tools more affordable and accessible for businesses.
• Google: The Gemini models offer powerful AI with custom features at competitive prices, enabling companies to integrate AI efficiently across industries.
• Meta: By embracing open-source AI, Meta has positioned itself as a leader in collaboration and innovation. This contributes to the growing trend of AI becoming more widely available. Embracing open-source AI allows for more community-driven development and ensures that AI advancements can progress quickly and be accessible to many.

What Does This Mean for Companies Building AI Solutions?

This trend calls for a strategic shift in how companies approach AI models for two key reasons:

1. AI models will keep evolving, but there may come a point where further improvements are minimal.
2. AI is transitioning from being a capital-intensive investment to more of an operational focus, pushing investors to become more strategic about where they place their money in AI.

So, for companies, it’s crucial to recognize these trends and focus on smart application and integration rather than just having the latest model. 

What's your take on this shift in AI? Share your thoughts in the comments below.

Until then, stay excited and stay curious! 

Signing Off, Raghav. 

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