The latest advances in AI (GPT, LLM, transformers, etc.) are like a Nokia phone in the 90''s – everyone could see the appeal, but no one could predict all that it would lead to. The tech world has a new obsession with Large Language Models (LLMs), GPTs, and AI in general.

人工智能的最新进展（GPT、LLM[大规模语言模型--译注]、transformers[一种神经网络--译注]等）就像90年代的诺基亚手机——每个人都能看到它的吸引力，但没有人能预测它会带来什么。科技界对大型语言模型（LLMs）、GPT和人工智能有了新的痴迷。

There is no question that LLMs and transformers are important technically, The latest developments mark a major breakthrough in software capabilities. That being said, we are not sure anyone really knows what to do with those capabilities.

毫无疑问，LLM和transformers在技术上是重要的，最新的发展标志着软件能力的重大突破。话虽如此，我们不确定是否有人真的知道如何使用这些能力。

A few weeks ago, we spoke at the AI Edge Summit, where the organization's Chairman, Jeff Bier, said something that catalyzed our view of AI and GPT. To paraphrase, he said ChatGPT is like seeing the first Nokia phone in the 1990's. We had all heard about mobile phones before that, and these Nokia devices were for many the first phone that looked like something we would actually want to buy. But at the same time, no one looking at the device then would be able to predict all the things that would eventually stem from it – 3G, mobile data, smartphones, the iPhone, apps, and a complete reorganization of how we structure our time and daily activities.

几周前，我们在人工智能边缘峰会上发言，该组织的主席Jeff Bier说了一些话，催化了我们对人工智能和GPT的看法。换句话说，ChatGPT就像是看到了上世纪90年代的第一部诺基亚手机。在此之前，我们都听说过手机，这些诺基亚设备对许多人来说是第一部看起来像我们会真正想买的手机。但与此同时，当时看到这款设备的任何人都无法预测它最终会带来的所有东西——3G、移动数据、智能手机、iPhone、应用程序，以及我们如何安排时间和日常活动的完全重组。

That seems like a good analogy for ChatGPT. It is useful. The first "AI" application that is useful to ordinary people, but not something that is going to change their lives too meaningfully. For those who have been watching technology for a long time, it is clear that LLMs and transformers have immense potential, we may very well just be scratching the surface of what they can provide.

这似乎是ChatGPT的一个很好的类比。它是有用的。第一个对普通人有用的“人工智能”应用，但不会对他们的生活产生太有意义的改变。对于那些长期关注技术的人来说，很明显LLM和transformers有着巨大的潜力，我们很可能只是触及了它们所能提供的东西的表面。

This has a few implications for what happens next:

这对接下来发生的事情有几点启示：

1. We are very much in the middle of a massive hype cycle. Absent some incredible product surprise, this cycle will eventually fade away and turn to a trough of doubt and despair. It is no coincidence that the media's eye of Sauron has turned so intently on AI just as the rest of the Bubble is deflating.

1. 我们正处于一个大规模炒作周期的中间。如果没有一些令人难以置信的产品惊喜，这个周期将最终消失，并转向怀疑和绝望的低谷。就在泡沫的其他部分正在缩小的时候，媒体对索伦的关注转向了人工智能，这并不是巧合。

2. No one really knows what all of this means. Maybe somewhere there is a rogue genius sitting in her cubicle or his mother's basement with a vision of 1,000 suns pointing the way forward. For everyone else, the future is much less certain. There are plenty of people who argue (very quietly right now) that AI is a dead end, with ChatGPT as just the latest version of chat bots (remember when those were the hot thing? It was only a few years ago.) There are also AI maximalists currently building their Skynet-proof bunkers in preparation for the imminent AI apocalypse because LLMs are just that awesome. Of course, the reality is somewhere in between.

2. 没有人真正知道这一切意味着什么。也许在某个地方有一个流氓天才坐在她的小隔间里或他母亲的地下室里，幻想着有1000个太阳在指引着前进的方向。对其他人来说，未来的确定性要小得多。有很多人认为人工智能是一条死胡同，ChatGPT仅仅是聊天机器人的最新版本（还记得那些热门的东西吗？）这只是几年前的事。）目前也有一些人工智能极端主义者正在建造他们的天网防御掩体，为即将到来的人工智能末日做准备，因为LLM就是这么棒。当然，现实是介于两者之间。

3. We need to remember that AI is just software. These latest new tools are very powerful, but for the foreseeable future we should mostly just expect some aspects of our interaction with software to improve. Developers definitely seem to be enjoying huge benefits from tools like Microsoft's Copilot. Everyone else can probably just expect better written spam e-mail content for the time being.

我们需要记住，人工智能只是软件。这些最新的新工具非常强大，但在可预见的未来，我们应该主要期待我们与软件交互的某些方面得到改善。开发人员似乎确实从微软的Copilot(应该指的是github的copilot--译注)等工具中享受到了巨大的好处。其他人暂时只能期待一些有内容变得更好的垃圾邮件。
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We do not mean to be pessimistic, we are shooting for realistic. From what we can tell, LLMs and GPT offer huge potential to tackle really large data sets. Critically, transformers are probably going to allow us to interrogate problems that previously were too big to approach, or even data problems we had not even realized existed before. Moreover, there is the tantalizing possibility that these gains will be self-reinforcing, a Moore's Law for data analysis. This is important, albeit unexplored.

我们并不是要悲观，我们正在追求现实。据我们所知，LLM和GPT提供了处理真正大型数据集的巨大潜力。至关重要的是，Transformer可能会让我们审视以前太大而无法解决的问题，甚至是我们以前甚至没有意识到存在的数据问题。此外，这些收益很可能会自我强化，这是数据分析的摩尔定律。这很重要，尽管尚未探索。

Finally, we think everyone needs to take a more sober approach to the ethics and societal implications of these tools. We do not usually cover this subject, and would skip over it here except for the fact that almost everyone engaged in these advances seems to be blithely (maybe deliberately) avoiding the subject.

最后，我们认为每个人都需要对这些工具的伦理和社会影响采取更清醒的态度。我们通常不涉及这个主题，并且会在这里跳过它，几乎每个参与这些发展的人似乎都在愉快地（也许是故意的）回避这个主题。

We are likely months away from the ability to create highly realistic videos of anything. Anything. That is going to mess with a lot of people's heads and maybe we should take a more constructive approach to preparing the world at large for what that means. At the same time, the alarmists calling for a complete end to AI need to face the reality that the ship has sailed.

我们可能还需要几个月的时间才能制作出高度逼真的任何视频。任何事物。这会扰乱很多人的头脑，也许我们应该采取更具建设性的方法让整个世界为这意味着什么做好准备。与此同时，呼吁彻底终结人工智能的危言耸听者需要面对船已起航的现实。

All in all, we are deeply excited by these latest developments. After years of incremental SaaS improvements being hailed as "technology advances," it is exciting to have a genuinely compelling new capability before us. We just wish everyone would take a breath.

总而言之，我们对这些最新进展深感兴奋。经过多年被誉为“技术进步”的SaaS(软件即服务--译注)的不断改进之后，在我们面前真正拥有引人注目的新功能是令人兴奋的。我们希望每个人都能喘口气。