The Evolution of AI in 3 Waves

Summary & Additional Insights

Jun 30, 2023

Source: For B2B Generative AI Apps, Is Less More? | Andreessen Horowitz (a16z.com)

Key Points

Wave 1: AI supports humans in valuable and creative work, but human refinement is still crucial for tasks requiring creativity and expertise.
Wave 2: involves AI synthesizing important information from large datasets to condense and present key ideas efficiently.
Wave 3: enables AI to perform actions with minimal human interaction, leveraging insights to prompt decisions and actions.

Introduction

This piece from a16z presents their perspective on the unfolding of the first two waves of AI. Building upon their insights, I will summarize their thoughts and add my own perspective on the three distinct waves in AI that contribute to its transformative nature. In the first wave, the primary emphasis was on enhancing human capabilities and utilizing AI in valuable and creative endeavors. The second wave centers around the synthesis of information using AI as a powerful tool. In my view, the third wave represents a shift towards AI actively taking action based on the insights derived from the advancements of the previous two waves. This progression in AI technology holds great potential for reshaping industries and driving significant advancements.

Wave 1

According to Barry McCardel, “AI is here to augment and improve humans, not replace them.” This wave focuses on infrastructure building and aims to help humans apply their brainpower to valuable and creative work. While AI has been successful in the brainstorming and drafting stages, human refinement is still crucial, particularly for tasks that require creativity and domain expertise. This phase emphasized the importance of AI supporting humans rather than replacing them. Prominent examples include Chat-GPT, GPT-4, and Bard, which have already proven successful in these brainstorming and drafting stages.

Wave 2 (Synthesis AI)

Synthesis AI involves applications that synthesize information from large datasets into more efficient and presentable ideas. Instead of overwhelming users with excessive content, AI will condense and present the most important information. For example, AI can synthesize key ideas from missed calls or meetings, allowing users to review essential details efficiently.

*Short 1 minute video as an example: ZoomInfo To Integrate GPT Into Its Go-to-Market Platform*

Wave 3 (My insights)

In the third wave, AI performs actions with minimal human interaction, although human oversight is still necessary to monitor the work. This phase involves taking insights derived from AI and translating them into action. For instance, AI can prompt actions based on business goals, such as ordering less of failing products, optimizing lead time, or providing real-time balance sheets and income statements. While human oversight is necessary to monitor the work, this wave enables better decision-making by leveraging AI insights and reducing emotional bias.

Example: Accountant using AI to aid spreadsheet creation

Wave 1: Soon, AI will be able to reformat uploaded Excel files, generate graphs, and identify potential errors within balance sheets or income statements. It will also provide autofill recommendations based on prior entries, saving time and enhancing productivity.
Wave 2: In addition to the capabilities of Wave 1, AI will identify weak points in the business and suggest actions for efficiency, growth, or profitability. This generates ideas for decision-making and improves the overall quality of decisions.
Wave 3: Prompting AI with the desired business goals (e.g., profitability, growth, efficiency) enables it to act based on provided insights. This includes ordering appropriate quantities of products, streamlining lead time, and providing real-time financial updates based on current sales. The biggest advantage of this wave is the ability to make better decisions with less emotional bias that is catered towards the need of each specific business.

Overall Thesis

The widespread adoption of AI will revolutionize business operations, making them more efficient and effective while reducing the need for a large workforce. Embracing AI technology is crucial for businesses and employees to thrive and stay relevant in an ever-changing landscape. However, it’s important to acknowledge that resistance to change can present challenges along the way. One significant advantage of AI is its ability to bridge the gap in specialized skills. Even individuals with minimal coding or design capabilities can interact with AI systems using plain English commands. This shift empowers teams to become leaner, requiring smaller initial investments, and paving the way for scalable and impactful businesses.

Furthermore, the value of unique datasets and the ability to derive insights from them will become paramount, especially for established companies. They will prioritize harnessing the potential of AI to unlock hidden value within their data, gaining a competitive edge in the market. As AI investments continue to grow, we can expect larger companies to build physical data centers to handle their data infrastructure needs. On the other hand, mid-sized to large companies are likely to rely more on cloud data retention services provided by industry giants such as AWS, Azure, Oracle, and Google. This enables them to leverage the scalability and flexibility of cloud computing while benefiting from the expertise and infrastructure of these established providers. Meanwhile, small companies and startups will leverage smaller data companies that offer competitive prices and tailored services. Companies like Lambda Labs, Coreweave, and Fluidstack will play a crucial role in providing affordable and accessible data solutions for these emerging businesses.

Embracing AI will drive efficiency and productivity in business operations. The ability to adapt to this transformative technology will be vital for success, and those who resist change may struggle to stay competitive. By leveraging AI, businesses can streamline processes, reduce costs, and make data-driven decisions. The future lies in embracing the potential of AI and harnessing its power to drive innovation and growth.

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