[Part 2 of a Three-Part Series respectively on the Past, Present, and Future of AI: A Non-Technical Exploration!]
The launch of ChatGPT by Sam Altman in November 2022 was a significant milestone in the journey toward Artificial General Intelligence (AGI). ChatGPT proved that machines can be trained in natural language to understand and engage with the target domain, making it the first step in the progression towards AGI. Sam Altman outlined five steps of AGI, with the ultimate goal of achieving Artificial Superintelligence (ASI) by 2029. These steps are:
- Step-1: Language Models (LLMs)
- Step-2: Reasoners (Next phase, AI with the ability to reason)
- Step-3: Agents (AI systems capable of autonomous action)
- Step-4: Innovators (AI systems that can innovate and generate new ideas independently)
- Step-5: Fully Autonomous (ASI)
ChatGPT, with its remarkable progress, has already reached Step-2: Reasoners in its initial release -ChatGPT o1. It’s expected to evolve rapidly towards the next stages.
The Battle Between Tech Giants
Meanwhile, Facebook AI Research, led by Yann LeCun, was also developing its own LLM, LLaMA. In October 2022, LeCun’s team demonstrated him capabilities of LLaMA, LeCun had doubts about its immediate practical utility due to the model’s tendency to hallucinate or produce incorrect information. Despite his concerns, Sam Altman’s launch of ChatGPT took him by surprise. In just five days, ChatGPT onboarded over one million users, and within three months, the user base grew to a staggering 100 million active users. This success left LeCun and Meta scrambling, as they had missed the consumer-driven market rush.
ChatGPT now has 250 million users out of which it has 12.5M premium users paying $20 per month making staggering $2.5B revenue only from consumer business.
The next major frontier is the AI agents market, expected to reach $32 billion by 2029. To regain its position, Meta is focusing on developing AI agents for businesses. Their strategy includes open-sourcing the LLaMA models, enabling developers to build agents. Meta plans to dominate this market as LLaMA models gain reasoning capabilities in the upcoming LLaMA 4.0 release, making them powerful tools for autonomous AI agents.
The Growing AI Agents Market
The competition for AI Agents is heating up. Both ChatGPT o1 and LLaMA 4.0 will be central to this battle. These foundation models, trained on vast amounts of human knowledge, are extremely expensive to develop, costing billions of dollars. However, Meta’s decision to open-source LLaMA allows developers worldwide to access and build on it for free, potentially accelerating the development of AI agents for business applications.
In contrast, Sam Altman’s OpenAI will likely push developers to use ChatGPT o1 to build AI agents. ChatGPT’s advanced capabilities have already made it a go-to tool for a variety of applications, and Altman’s vision for AGI will likely spur even more development in the agent market.
Emerging Players: World Labs and Other Startups
On a different front, Fei-Fei Li has launched World Labs, a platform designed to build Phenomenal World Models to help developers create more effective AI agents. These world models are designed to enable AI to understand and interact with the world more deeply, supporting more complex and nuanced AI agents. In addition to World Labs, numerous startups are emerging with tools and platforms aimed at helping developers create, refine, and deploy AI agents.
The Future of AI Agents
The market for low-level AI agents is expected to flourish rapidly with tools like ChatGPT o1 and LLaMA 4.0. Developers will be able to build basic AI agents relatively quickly. However, crafting more complex AI specialists—agents with deep expertise in specific domains—will require expert craftsmanship and considerable development time, typically around 6 to 8 months for proficient AI developers.
Foundation Models and the Global Landscape
Training foundation models remains an expensive and complex endeavor. Think of it like trying to teach gravity—no matter the language, the fundamental concept remains the same. The language used to teach it is just the medium. This is why, despite the global reach of human knowledge, most foundational models have been trained primarily in English. However, with advancements in real-time translation technologies, users in non-English speaking regions can benefit from these models without having to “re-teach” them in their own language.
In conclusion, as both Meta and OpenAI advance their respective AI strategies, the race to develop AI agents is on. ChatGPT and LLaMA are poised to reshape the landscape of AI-driven business applications, but the path to AGI is still long and complex, with much more to unfold in the coming years.
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