cover of episode EP 393: When will we achieve AGI? And one secret aspect holding us back

EP 393: When will we achieve AGI? And one secret aspect holding us back

2024/11/1
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Everyday AI Podcast – An AI and ChatGPT Podcast

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J
Jordan Wilson
一位经验丰富的数字策略专家和《Everyday AI》播客的主持人,专注于帮助普通人通过 AI 提升职业生涯。
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我们比大多数人认为的更接近人工智能通用 (AGI) 的实现。AGI 的定义一直在变化,这可能是我们尚未"正式"实现 AGI 的原因之一。OpenAI 与微软之间的合作关系的细节可能是阻碍 AGI 发展的因素。传统的 AI 基于一组规则和算法,而生成式 AI 则不同。生成式 AI 标志着人工智能的新时代,它降低了使用人工智能的门槛。生成式 AI 使任何人都可以通过简单的语音或文字与 AI 系统交互并获得令人印象深刻的输出。人工智能通用 (AGI) 能够理解、学习和应用知识,完成各种任务,类似于人类。AGI 与生成式 AI 的区别在于,AGI 可以执行广泛的任务,其能力与人类相同或更高。大型科技公司现在公开致力于 AGI 的研发,这与十年前的情况大相径庭。许多大型科技公司现在公开追求或合作研发 AGI。对 AGI 到来的时间预测一直在变化,部分原因是专家对生成式 AI 的理解不足。在 GPT-3 出现之前,专家们预测 AGI 还要 80 年才能实现;而现在,这个预测已经缩短到了 8 年以内。对 AGI 的定义随着时间的推移而演变。OpenAI 与微软之间的合作关系及其未来可能的变化,可能是 AGI 发展中一个鲜为人知的因素。OpenAI 可能有意推迟宣布实现 AGI,以维护与微软的有利合作关系,并促进未来的融资。大型科技公司公开致力于 AGI,以及 AGI 技术的成本降低,是 AGI 发展加速的原因。我们很快就会实现 AGI,根据旧的定义,我们可能已经实现了。AGI 的实现比我们想象的要快。

Deep Dive

Key Insights

Why are the predictions for achieving AGI changing so rapidly?

The predictions are changing because advancements in AI, particularly generative AI and large language models, have significantly accelerated the timeline. Experts initially estimated AGI to be 80 years away, but now, post-ChatGPT and GPT-4, the forecast is less than eight years. This rapid shift reflects the exponential pace of AI development.

What is the role of big tech companies in the development of AGI?

Big tech companies like Microsoft, OpenAI, Meta, and NVIDIA are openly working toward AGI. Microsoft collaborates with OpenAI, Meta is developing an open-source AGI, and NVIDIA provides the hardware and software for AI development. These companies see AGI as the next step in AI evolution and are actively researching and investing in AGI technologies.

How has the definition of AGI evolved over time?

The definition of AGI has evolved as AI technology has advanced. Early definitions from 10-20 years ago focused on a system's ability to learn and solve problems across different areas, similar to a human. However, as large language models and generative AI have become more sophisticated, the goalposts for what constitutes AGI have shifted, making it harder to officially declare AGI has been achieved.

What impact does the OpenAI-Microsoft partnership have on AGI development?

The partnership between OpenAI and Microsoft is pivotal for AGI development. Microsoft has invested $13 billion and holds a 49% stake in OpenAI. However, once OpenAI declares it has achieved AGI, the partnership terms change, potentially altering the dynamics of their collaboration. This relationship is crucial as it provides OpenAI with significant resources and insights, but also complicates the declaration of AGI achievement.

Why might OpenAI delay declaring AGI achievement?

OpenAI might delay declaring AGI achievement because doing so could alter their partnership with Microsoft, which provides significant funding and resources. Additionally, declaring AGI could complicate future fundraising efforts, as investors might see less potential in a company that has already achieved its primary mission. Therefore, OpenAI might continue to move the goalposts to maintain its current advantageous position.

How has the cost of AI development changed, and what does this mean for AGI?

The cost of AI development, particularly compute power, has decreased exponentially in recent years. This has made it feasible for more companies to pursue AGI. Additionally, companies like OpenAI and Google are offering AI capabilities for free, further reducing barriers to entry. This democratization of AI resources is accelerating the development and potential achievement of AGI.

Chapters
This chapter defines artificial intelligence (AI), artificial general intelligence (AGI), and artificial superintelligence (ASI). It highlights the differences between traditional AI and generative AI, emphasizing the democratizing effect of the latter. The chapter concludes by defining AGI's benchmark as the ability to perform any task at a human or higher level.
  • AI performs tasks requiring human intelligence.
  • Generative AI democratizes AI capabilities.
  • AGI performs a broad range of tasks at a human or higher level.
  • ASI surpasses human intelligence in all aspects.

Shownotes Transcript

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It's the trillion dollar AI question. When will we achieve Artificial General Intelligence? (And what the heck is it, anyway?) We'll give you the 101 on what you need to know, and one secret that could be holding the official discovery back.Newsletter: Sign up for our free daily newsletter)**More on this Episode: **Episode Page)**Join the discussion: **Ask Jordan questions on AGI)Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup)Website: YourEverydayAI.com)Email The Show: [email protected])**Connect with Jordan on **LinkedIn)**Topics Covered in This Episode:1. Definition of AI, AGI and ASI2. Evolution of AGI3. Impacts of Advancements in AGI4. Future of AGITimestamps:**02:00 When is AGI coming?09:54 Machines performing tasks requiring human intelligence.13:10 Generative AI brings impressive outputs through language.14:04 Generative AI democratizes US AI capabilities; narrow compared.19:00 Correct prompting with PPP course at podpp.com.20:52 Big tech companies openly working toward AGI now.25:37 AGI development inevitable, desirable, surpassing human capabilities.28:16 Pre-2020, experts said AGI was 80 years away.31:25 Criticism of experts in generative AI misunderstandings.33:49 Has AI's definition of AGI changed?37:21 Definition of AGI has evolved over time.40:45 Partnership between Microsoft and OpenAI pivotal.45:21 OpenAI benefits from important Microsoft partnership changes.47:08 Tech companies must focus on AGI development.**Keywords:**AGI, Artificial General Intelligence, OpenAI, Microsoft, partnership, AI development, AI startup, Anthropic, copyright infringement, Google's Gemini team, Token offering, AI models, USAID, ChatGPT Enterprise, AI pace estimation, AI evolution, Artificial Superintelligence, AI prediction chart, ARK Invest, GPT 3 technology, Traditional AI, Generative AI, AI democratization, AGI benchmark, ChatGPT course, AI startups, Big tech companies, AGI cost reduction, Future of work, Everyday AI podcast.

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