What the Freakiness of 2025 in AI Tells Us About 2026

The truth is, it's probably not possible to satisfactorily condense 12 months worth of weird progress in AI, as well as predictions for the year to come into just one video. To be honest, I'm going to try anyway because it has been a very strange time. We are mid singularity for some people and pre-bubble burst for others. But wherever you are on that spectrum, here's my 10 takeaways from 2025 as someone who does little other than follow AI, plus five things we can confidently anticipate in 2026.

2025 was always going to be the year of reasoning models, models that take longer to think and spend more tokens doing so. That led, of course, most famously with Gemini 3 Pro, to benchmark after benchmark being beaten, but inevitably also skepticism about the inherent value of benchmarks being beaten. But frankly, just the fact that whatever test you or I or the industry can create, AI models can soon surpass is itself a fascinating phenomena. Yes, model aptitude is jagged or spiky, but man, those spikes are getting pretty impressive.

whether it comes to video understanding, chart table analysis, coding or general knowledge and reasoning. This is the same year though that we caught glimpses of a flaw in that paradigm that thinking longer may boost accuracy but reduce diversity of outputs. By browbeating base models until they can beat benchmarks, we are ensuring that the first answer a model gives as shown in yellow here is much more likely to be smart. But this 2025 paradigm does not seem to be producing reasoning paths that weren't already present in that base model and couldn't have been found if you sample that base model enough times.

But the thinking longer approach isn't everything. There's also scaling up the parameters and data that go into that base model and we have seen rich rewards from that approach. Here's Deis Arus speaking just the other week. >> We're recording now.

Gemini 3 has just been released and it's leading on this whole range of different benchmarks. Um, [clears throat] how how has that been possible? Like wasn't there supposed to be a problem with scaling hitting a wall? >> I think a lot of people thought that, especially as other companies are sort of had slower progress, should we say?

But I think we've never really seen any wall as ...