Beauty meets brains 💅 🧠

L'Oréal and IBM: AI-Powered Beauty

Earlier this year, IBM and L'Oréal, the world’s largest cosmetics company, joined forces to use IBM's generative AI technology to transform cosmetic development. The collaboration aims to uncover new insights in product formulation, helping L'Oréal adopt more sustainable raw materials and reduce energy and material waste.

Together, they are creating a custom AI foundation model designed to empower L'Oréal's Research & Innovation team to drive higher performance and customer satisfaction across all cosmetic categories and regions worldwide.

👉 Read more about the first-of-its-kind formulation foundation model

👉 In this episode of Smart Talks with IBM, Malcolm Gladwell dives into the exciting collaboration between L'Oréal and IBM. He explores how a custom AI model could help L'Oréal’s researchers shape the future of what we put on our faces every morning.

Gen AI: One Size Doesn't Fit All

Gen AI models come in many flavors. What they can do, how well they work—and how much they cost—varies widely. 

With the massive amount of data and resources it takes to train a single large language model (LLM), the question of size is monopolizing many conversations about gen AI. As a result, many CEOs wonder whether they should scale large gen AI models for their business. Or if they should develop smaller, niche models for specific purposes. The answer is, they need to do both.

IBM Institute for Business Value research has identified three things every leader needs to know:

1. There’s no such thing as an all-purpose gen AI model 

2. Gen AI costs are completely in your control 

3. Gen AI advantage is fleeting 

👉 Download the CEO’s guide to learn 3 things every leader needs to do right now 

Curious about AI models? Discover size vs. use case pros & cons ⤵

👉 Explore IBM Granite models