AI Paper Reveals New Tong Test Benchmark for AI General Intelligence Progress


Are you fascinated by the capabilities of AI? Have you ever wondered how close we are to achieving Artificial General Intelligence (AGI), which can replicate human intelligence? Well, get ready to dive into the world of AGI evaluation with the Tong test! In this blog post, we will explore the groundbreaking research conducted by the National Key Laboratory of General Artificial Intelligence, which proposes a new way of evaluating AGI. But wait, there’s more! This research introduces the concept of DEPSI, a complex environment that allows us to assess AGI’s human-like abilities. Trust me, you don’t want to miss this intriguing journey into the realm of AGI evaluation.

Let’s start by understanding what sets AGI apart from specialized AI systems. Unlike narrow AI, AGI possesses a wide range of functions that aim to replicate human intelligence. It can make autonomous decisions, adapt to various situations, and comprehend ambiguous or incomplete information. Achieving AGI is no easy feat, as it requires solving numerous challenges in machine learning, natural language processing, robotics, and other AI-related fields.

Now, here comes the exciting part – the Tong test. Taking its name from the Chinese character for ‘general’ in AGI, the Tong test provides a unique perspective on AGI evaluation. The researchers emphasize the importance of DEPSI, a complex environment, in assessing AGI’s human-like abilities. DEPSI allows us to evaluate AGI’s commonsense reasoning, intention inference of social interactions, trust, and self-awareness. It’s a game-changer in the field of AGI evaluation, shifting the focus from task-oriented assessments to value-oriented evaluations.

So, what exactly is the Tong test? It’s a benchmark and evaluation system that focuses on essential features such as infinite tasks, self-driven task generation, value alignment, and causal understanding. The proposed virtual platform supporting the Tong test also facilitates embodied AI training and testing. Agents within this platform acquire information, learn, and fine-tune their values and abilities interactively. It’s like stepping into a world where AI agents continuously evolve and adapt.

To support the infinite tasks that AGI can perform, the researchers utilize a compositional graphical model. This model serves as a knowledge representation framework, parsing spatial, temporal, and causal relations within a given scene. They also define a fluent space for time-varying variables, representing all possible configurations in a continuous DEPSI environment. It’s like building the foundation for AGI’s understanding and decision-making abilities.

Now, let’s dive deeper into the Tong test itself. This evaluation platform spans two domains – the U-system and the V-system. The U-system focuses on the agent’s understanding of extrinsic physical or social rules, while the V-system comprises the agent’s intrinsic values. These values shape the agent’s self-driven behaviors. The Tong test platform includes modules for intermediate data visualization and a performance panel, providing insights into how the tested model performs.

In summary, the Tong test based on DEPSI presents a novel and practical approach to evaluate AGI. By defining five multidimensional levels of values and abilities, this research provides theoretical guidance for developing AI algorithms. It’s a significant step forward in our journey towards achieving AGI and understanding its capabilities.

If you’re curious to dig deeper into this research, make sure to check out the paper for all the technical details. And don’t forget to join our vibrant community, where we share the latest AI research news, cool projects, and more. Whether you’re an AI enthusiast or a curious mind, our newsletter will keep you up to date with the exciting world of AI.

Remember, the future of AI is unfolding, and the Tong test is just one stepping stone in this incredible journey. So, join us, and let’s embark on this thrilling adventure together!

[Click here to read the full research paper.](https://www.sciencedirect.com/science/article/pii/S209580992300293X?via%3Dihub)

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