🚨❓What happens if LLMs cook our meals and the kitchen has a missing ingredient?

Jun 16

LLMs can cook our meals, but the kitchen has a missing ingredient.

The level of sophistication and integration with your kitchen environment would determine how proactive and helpful the LLM can be in dealing with missing ingredients.

A basic LLM might offer suggestions, while an advanced LLM could potentially handle the entire process, from identifying the issue to finding a solution.

Basic LLM (limited integration):

Information source: The LLM would primarily act as a digital recipe book and substitution suggestion engine.
Functionality: Imagine a recipe app that allows you to input missing ingredients. The LLM would search its database and provide basic substitute suggestions based on taste or function.
Limitations: This LLM wouldn't have real-time access to your kitchen inventory or the ability to interact with appliances directly.

Advanced LLM (an “integrated kitchen environment”):

Smart Kitchen Integration: This LLM connects seamlessly to your smart appliances and kitchen systems.
Functionality: Imagine a voice-activated AI assistant in your kitchen. You tell it the recipe you want to cook, and the LLM checks your smart fridge and pantry to see if you have everything. If something's missing, it can:
- Suggest substitutes based on real-time inventory.
- Access online grocery stores and order the missing ingredients for quick delivery.
- Search for entirely new recipes that work with the ingredients you have on hand.
Advanced Features: The LLM could potentially analyze the recipe, understand the role of the missing ingredient, and suggest replacements that maintain the original dish's integrity (acidity, sweetness, texture).

Level of sophistication:

Basic LLM: Relies on pre-programmed data and may be unable to adapt to unexpected situations or complex recipe modifications.
Advanced LLM: Could continuously learn and improve its ability to handle missing ingredients. It might consider your preferences, past experiences with substitutions, and even dietary needs to suggest the best course of action.

In other words, “How do we build mass-market solutions that change the world for good around a technology that can get things ‘wrong’?

AI and its extended possibilities are exciting, but they are still new. LLMs will make mistakes. Even though they’re improving daily, LLMs can provide inaccurate information or make offensive statements.