The 10 Biggest AI Stories of 2025

**Nathaniel Whittemore** (0:00)
Today on the AI Daily Brief, the 10 biggest AI stories of 2025 The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
Now, we are in the early stages of our end-of-year coverage. From here on out, most of our episodes will be either looking back or looking forward. And today, we're starting with the 10 biggest AI stories of 2025 Now, these are not in ranked order. Instead, I put them in a combination of a linear and narrative sequence, but I will call out when I hit my vote for the biggest story of the year. And we're going to kick off with the very first big story of the year, which was the absolute hullabaloo around the release of DeepSeek R1. Now, DeepSeek started to have models that people were paying attention to at the end of 2024 But in January, when they released their first reasoning model, R1, everyone stood up and took notice. There were a couple of reasons for that. First of all, while all the American labs were spending hundreds of millions if not billions of dollars to train their models, DeepSeek was saying that R1 was trained for just a few million dollars.
On top of that, however, alongside the model, DeepSeek also released their very own Chatbot app, and it rocketed to the top of the App Store charts, even displacing ChatGPT for a while. As markets tried to digest the news, there was a deep sell-off of AI stocks. NVIDIA lost $593 billion in market cap in a single day, the single biggest one-day loss in stock history. Now, of course, markets were covered. But this DeepSeek story set up so many of the themes that would shape the rest of the year. One that we'll discuss in a few minutes is the rise of reasoning. Part of what made the DeepSeek application so popular was that while OpenAI had released their O1 reasoning model at that point, and while O1 remained ahead of what you could get with DeepSeek R1, O1 was at the time entirely behind a paywall, so the vast majority of people had never seen a reasoning model. They were delighted both with the reasoning traces that DeepSeek exposed in their app, as well as just the differentiated quality of the results. Of course, that market squirm would portend everything that we've been dealing with for the past five months around the AI bubble debate, and from a lasting legacy perspective, one thing that was absolutely true about DeepSeek was that Chinese models were much closer in nipping on the heels of Western closed-source models than the vast majority of people had thought coming into the year. That has played out throughout the year with models like Ken and Quimmy as well as later DeepSeek models being right up in the thick of things as some of the best models available. You can see Kimi K2 and DeepSeek 3.2 behind Gemini 3, GPT 5.2 and Opus 4.5, but ahead of pretty much everything else. It would also kick off a back and forth debate around the appropriate US policy vis-a-vis China that has continued to be dynamic throughout the year. With the latest big change, of course, being the Trump White House deciding to allow Nvidia to sell H200 chips into China, the most advanced chip we've allowed to be sold to China in a number of years. All in all, the DeepSeek story started 2025 off with a bang, and it has not let down ever since. Our second big AI story for the year also kicked off in January, which was the massive AI infrastructure buildout. It started oh-so-innocently, just OpenAI and a couple of friends like SoftBank, MGX, and Oracle, announcing their intention to invest a half trillion over the next four years to build AI infrastructure in the United States. The initiative was called Project Stargate, and it was announced at the White House on Tuesday, January 21st, with President Trump in attendance, with Oracle founder Larry Ellison, OpenAI CEO Sam Altman, and SoftBank CEO Masayoshi Sun. Of course, since then, the AI infrastructure deals have done nothing but increase throughout the year. We have seen a massive amount of hyperscaler capex and expansion, with basically every major company, Microsoft, Google, Amazon, Meta, all increasing their guidance around their capex for 25 and 26 We saw initiatives like the Global AI Infrastructure Investment Partnership between BlackRock, Microsoft, MGX and others, which was a $100 billion investment vehicle focused on data centers and the electricity to power them. We had Elon Musk's XAI Colossus expansion, which sees that company attempting to scale from their current 100,000 GPUs to a million GPUs or more. And of course, with all this data center build out, there is also going to be energy requirements leading to announcements like the Google and NextEra Energy Partnership, which is an agreement to develop gigawatt scale data center campuses that have power generation on site thanks to an investment in nuclear. Now, as we discussed, this was a theme throughout the year. And right up until the end of the summer, it was a major theme driving up stock prices. But then came the Oracle and OpenAI deal. At the end of August, Oracle revealed that it had added $317 billion in future contract revenue during its quarter that ended August 31st. That led the company's stock price to surge by as much as 43%, temporarily pushing his net worth up over even Elon Musk. When a couple of days later, it was revealed that OpenAI was the customer driving about $300 billion of that, markets started to get a little bit more nervous. And this of course brings us to our next big story of the year, which is the AI Bubble Debate. Now, if we were just looking for what theme or topic was most discussed, particularly in mainstream media, for sure this is the biggest AI story of the year. Like I said, at least in terms of the amount of sheer ink spilt on it. Every week even to now sees an endless stream. Of AI Bubble Debate related articles. And interestingly, a lot of the focus is on Oracle, that big deal with OpenAI, and the debt that they're taking on to finance the build out. One of the key themes of the Bubble Conversation is the circularity of revenue. I'm sure you've seen some version of this chart, which shows the dense web of investment and customer relationships between major companies including Microsoft, OpenAI, Intel, Oracle, NVIDIA, XAI and AMD. Now to some this screams house of cards. To others, it shows the dense web of relationships that is driving the mass AIification of the economy writ large. AI Bubble Talk is so ubiquitous that it now has its very own Wikipedia entry, complete with a section on that circular financing. Now part of what makes this such a juicy and resonant theme is that it's one that's impossible to prove or disprove in the short term. In other words, even if we are in the midst of an AI bubble, the way that that would be manifest and problematic in terms of, for example, open AI missing financial obligations with these big deals, is not coming to bear in the short term. That means that it's ripe territory for narrative debates as market actors try to drag participants to their view of the world. Now one good resource that I pointed to before, if you are interested in this story, comes from Exponential View, who put together a boom and bubble monitor. This came out of a blog post where they looked at five historic indicators for financial bubbles, economic strain, industry strain, revenue momentum, valuation heat, and funding quality and now turn them into a live tracker. Now at this stage, they argue we are still firmly in boom territory with only one in the five gauges in the red, which is the industry strain. That said, there is a lot to watch here and it's a great resource. You can find it at boomerbubble.ai.