The Dawn of a New Era: Exploring the Early Days of AI and Pragmatic Thinking for Success

The Dawn of a New Era: Exploring the Early Days of AI and Pragmatic Thinking for Success

Introduction:

Artificial Intelligence (AI) has evolved significantly over the years, reaching a point where it is considered a new era and a discontinuity from past technologies. This article delves into the early days of AI, highlighting the transformative capabilities of LLMs, Transformers, and diffusion models. Additionally, we explore the importance of pragmatic thinking and learning in navigating the AI landscape successfully.

The New Era of AI:

Contrary to popular belief, AI should not be viewed as a continuum with previous technologies. Instead, it represents a step function in terms of capabilities and products enabled. With the launch of ChatGPT, mainstream recognition of AI's potential skyrocketed. However, we are still far from reaching peak AI usage or peak AI hype. We can identify at least four distinct waves of AI development during these early days.

Wave 1: GenAI Native Companies:

The first wave consists of companies like ChatGPT, Midjourney, Character.AI, Stable Diffusion, Github Copilot, and others. These pioneers have gained significant revenue and user traction, paving the way for future advancements.

Wave 2: Early Startup Adopters and Fast Mid-Market Incumbents:

The current wave involves startups leveraging GPT-3.5/4 technology, such as Perplexity, Langchain, and Harvey. Simultaneously, a small number of founder-led multi-billion companies like Navan, Notion, Quora, Replit, and Zapier have swiftly embraced AI-powered products.

Wave 3: Next Wave of Startups:

The upcoming wave will witness the founding of new startups exploring novel applications of AI. This phase may introduce voice and video formats, utilize natural language in diverse verticals, and introduce new types of infrastructure. Companies like Eleven Labs/LMNT/LFG Labs, Braintrust, and many more are poised to provide incremental experiences.

Wave 4: First Big Enterprise Adopters:

Anticipated to arrive around 2024/2025, this wave will witness larger companies beyond the likes of Microsoft, Adobe, Google, and Meta adopting AI in their products. Due to the long planning and build cycles in enterprise settings, these companies will offer mature AI-powered products, showcasing the true potential of AI in various industries.

Pragmatic Thinking and Learning:

In the quest for success in the AI landscape, pragmatic thinking and learning play a crucial role. The following actionable advice based on Andy Hunt's book, "Pragmatic Thinking and Learning," can guide individuals and organizations in their AI endeavors:

1. Consider the Context:

Understanding the context is vital as everything is interconnected within a system. By avoiding isolated thinking and considering the broader picture, one can make better-informed decisions and avoid potential pitfalls.

2. Use Rules and Intuition:

In the Dreyfus skill model, rules are essential for novices, while intuition guides experts. Recognize when to rely on established rules and when to trust your intuition, allowing for a balanced approach in problem-solving.

3. Step Away and Change Perspectives:

Taking breaks and allowing your mind to wander can be immensely beneficial when facing complex challenges. Engaging in activities like walking, taking a shower, or simply having a break provides the necessary space for your subconscious mind to process and solve problems. Additionally, changing your viewpoint, reversing the problem, or exaggerating it can unlock new insights and innovative solutions.

Conclusion:

As we navigate the early days of AI, it is crucial to acknowledge the transformative capabilities of advanced models and the distinct waves of AI development. By embracing pragmatic thinking and learning principles, individuals and organizations can make informed decisions, adapt to evolving landscapes, and unlock the full potential of AI. Remember to consider the context, trust your intuition, and step away from the keyboard when needed. With these strategies in place, the future of AI holds immense possibilities for innovation and growth.