Mustafa Suleyman Introduces a New ACI Framework to Link Weak AI and AGI
In Brief
Suleyman presents the concept of Artificial Capable Intelligence (ACI), aimed at closing the divide between basic AI and Artificial General Intelligence.
At the heart of ACI is the assessment of how well a model interacts with its environment and achieves concrete objectives, such as generating a million dollars from an online sales platform.
Suleyman predicts that ACI could usher in significant changes in the global market, yet there are unresolved issues regarding how to fairly compare different models based on their performance and real-world interactions.
Mustafa Suleyman As co-founder and CEO of Inflection AI and a prior co-founder of DeepMind, Suleyman offers a new perspective on evaluating AI’s potential. He advocates for shifting our focus from just measuring overall intelligence to examining the tangible actions that AI systems can execute.

The concept known as ACI (Artificial Capable Intelligence) seeks to unify weak AI with AGI (Artificial General Intelligence). Instead of focusing only on a model’s communication abilities, ACI emphasizes its capacity to engage with the environment and achieve designated goals.
Suleyman uses an intriguing illustration: assigning an AI model the task of turning an investment of $100,000 into a million dollars through online sales. To meet this challenge, the AI must construct a robust strategy and engage in numerous related tasks—ranging from product concept development to negotiating contracts and strategizing marketing efforts. retail platform Suleyman envisions that reaching ACI could be achievable within a few years. He asserts that this breakthrough could dramatically transform the global economy, moving us towards a future where AI is not merely a tool for specific challenges, but an integral part of the economic infrastructure.
However, the viability of comparing different AI models in this context remains ambiguous. Additionally, the challenge of evaluating these models intensifies when their performance requires genuine interactions with people. For example, the AI would need to generate real revenue by handling actual dollar amounts, selling physical goods to real customers, and navigating various human exchanges. This testing could be resource-intensive both financially and in terms of human involvement.
In his upcoming book, titled 'The Coming Wave: Technology, Power, and the Greatest Dilemmas of the 21st Century,' Mustafa Suleyman is expected to expand on these concepts, offering depth into the changing dynamics of AI. Slated for release on September 5, the book is anticipated to provide deep insights into the implications of ACI.
To dive deeper into this innovative idea, check out the article showcased in Back in 1950, Alan Turing introduced the Turing test as a means to evaluate a machine's cognitive abilities. Fast forward to December 2022, and ChatGPT, an advanced AI chatbot, has emerged. Notably, ChatGPT's performance in the Turing test was commendable, as it successfully replicated human-like dialogue in front of a panel. Next, ChatGPT is aiming to broaden its horizons by integrating with platforms like Facebook Messenger and Slack, enhancing its functionalities and expanding its database.
The Turing test has come under scrutiny as technologies like ChatGPT and GPT-4 are woven into the fabric of online interactions. A gamified experiment called 'Human or Not?' challenged users to differentiate between human and AI dialogues. With over 1.5 million participants, the web game revealed that only 68% accurately identified their conversation partners, dropping to 60% for interactions with the AI. This outcome underscores the creativity and versatility of individuals trying to intertwine human and machine conversations. Nonetheless, doubts linger regarding the Turing test's effectiveness in truly assessing AI's potential. The 'Human or Not?' experiment marks the beginning of deeper inquiries and investigations. MIT Technology Review .
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