智力的进化
The Evolution Of Intelligence

原始链接: https://www.zerohedge.com/technology/evolution-intelligence

专家团队估计,实现类人机器智能最多可能需要到 2059 年。 然而,Visual Capitalist 和 VERSES 提出的一种可能方法建议在短短 16 年内实现这一目标。 这种创新方法依赖于“主动推理”,这是一种先进的认知模型。 该模型不是被动的,而是允许人工智能系统不断更新其信念,以最大限度地减少不确定性并提高预测准确性。 主动推理的好处包括好奇心——人工智能会主动寻找有关世界的新信息。 与当今的人工智能(例如 ChatGPT 或 Gemini)不同,这些系统在训练后保持静态,没有进一步的学习能力。 通过结合主动推理,人工智能不仅会表现出智能行为,而且人类也可以观察和理解其推理过程,从而培养责任感和信任。 这一进步遵循人工智能发展的四个阶段:系统人工智能对输入做出响应,有感知力的人工智能收集信息,复杂的人工智能制定计划,以及有同情心的人工智能识别情绪。 最终,一种共享智能或超级智能出现,其进化可能超出人类的理解范围。 VERSES 旨在创建一种基于主动推理的可解释人工智能,该人工智能能够思考并阐明其潜在的思维模式。

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原文

The expert consensus is that human-like machine intelligence is still a distant prospect, with only a 50-50 chance that it could emerge by 2059.

But what if there was a way to do it in less than half the time?

Visual Capitalist partnered with VERSES for the final entry in our AI Revolution Series to explore a potential roadmap to a shared or super intelligence that reduces the time required to as little as 16 years.

Active Inference and the Future of AI

The secret sauce behind this acceleration is something called active inference, a highly efficient model for cognition where beliefs are continuously updated to reduce uncertainty and increase the accuracy of predictions about how the world works.

 An AI built with this as its foundation would have beliefs about the world and would want to learn more about it; in other words, it would be curious. This is a quantum leap ahead of current state-of-the-art AI, like OpenAI’s ChatGPT or Google’s Gemini, which once they’ve completed their training, are in essence frozen in time; they cannot learn. 

At the same time, because active inference models cognitive processes, we would be able to “see” the thought processes and rationale for any given AI decision or belief. This is in stark contrast to existing AI, where the journey from prompt to response is a black box, with all the ethical and legal ramifications that that entails. As a result, an AI built on active inference would engender accountability and trust.

The 4 Stages of Artificial Intelligence

Here are the steps through which an active-inference-based intelligence could develop:

  1. Systemic AI responds to prompts based on probabilities established during training: i.e. current state-of-the-art AI.

  2. Sentient AI is quintessentially curious and uses experience to refine beliefs about the world. 

  3. Sophisticated AI makes plans and experiments to increase its knowledge of the world. 

  4. Sympathetic AI recognizes states of mind in others and ultimately itself. It is self-aware.  

  5. Shared or Super AI is a collective intelligence emerging from the interactions of AI and their human partners.

Stage four represents a hypothetical planetary super-intelligence that could emerge from the Spatial Web, the next evolution of the internet that unites people, places, and things. 

A Thoughtful AI for the Future?

With AI already upending the way we live and work, and former tech evangelists raising red flags, it may be worth asking what kind of AI future we want? One where AI decisions are a black box, or one where AI is accountable and transparent, by design.

VERSES is developing an explainable AI based on active inference that can not only think, but also introspect and explain its “thought processes.”

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