Lessons Learned - Viral Marketing & Aligning Language Models to Follow Instructions

Lessons Learned - Viral Marketing & Aligning Language Models to Follow Instructions

Introduction:

Viral marketing and aligning language models to follow instructions may seem like unrelated topics at first glance. However, upon closer examination, we can find common points and insights that can help us understand how to create effective marketing campaigns and develop safer and more helpful language models. In this article, we will explore the key lessons learned from both these areas and provide actionable advice for marketers and developers.

Lesson 1: The Power of Viral Growth

In viral marketing, two key parameters drive viral growth: the Viral Coefficient and the Viral Cycle Time. The Viral Coefficient is the number of new customers that each existing customer successfully converts. To achieve viral growth, the Viral Coefficient must be greater than 1. This means that each customer should be able to bring in more than one new customer.

However, while the Viral Coefficient is important, the Viral Cycle Time plays an even more significant role in increasing growth. The Viral Cycle Time is the time it takes for the viral cycle to complete. By reducing the cycle time, companies can experience a dramatic effect on growth. Shorter cycle times lead to faster customer acquisition and increased reach.

Lesson 2: The Importance of Sharing and Incentives

For a product or service to become truly viral, it needs to be shareable. The most viral products are those that only work if they are shared. This means that the value proposition of the product should be compelling enough for customers to want to share it with others.

To encourage sharing, companies should also provide incentives to both the existing customer and the friend receiving the invitation. By offering equal incentives, companies can motivate customers to spread the word about their product or service.

Lesson 3: Safety and Alignment in Language Models

Language models, such as GPT-3, are trained on large datasets of internet text. While they can generate impressive outputs, they often lack alignment with users' intentions and safety measures. InstructGPT models, on the other hand, are designed to follow instructions more effectively and generate safer outputs.

By using reinforcement learning from human feedback (RLHF), developers can align language models with users' needs. Fine-tuning on curated datasets of human demonstrations helps reduce harmful outputs and increase the appropriateness of generated content.

However, it is crucial to note that even with these advancements, language models are still far from fully aligned or safe. They may generate biased, toxic, or inappropriate content without explicit prompting. Refusing certain instructions reliably remains an open research problem that needs to be addressed.

Conclusion:

In conclusion, viral marketing and aligning language models to follow instructions share common principles that can guide marketers and developers. By understanding the importance of viral growth, sharing, incentives, alignment, and safety, companies can create effective marketing campaigns and develop language models that are more helpful and safer for users.

Actionable Advice:

1. Focus on reducing the Viral Cycle Time to accelerate growth. Shorter cycle times lead to faster customer acquisition and increased reach.

2. Make your product or service shareable and compelling. The value proposition should be strong enough to encourage customers to share it with others.

3. When developing language models, prioritize alignment and safety. Use reinforcement learning from human feedback to reduce harmful outputs and increase appropriateness, but remember that further research is needed to address alignment challenges.

By implementing these actionable advice, marketers can create viral campaigns, and developers can create language models that are more aligned, helpful, and safe for users.