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The AI Daily Brief: Artificial Intelligence News and Analysis
The 5 Biggest AI Stories to Watch in November
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Today we are talking about the most important stories in AI from October and the five stories that I'm most closely paying attention to for AI in November. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. Welcome back to the AI Daily Brief. Today we are doing something that is going to become, I think, more of a feature on the show going forward, which is early at some point in each month, trying to recap everything that happened the previous month as well as give you a preview of what I think is coming next with the specific intention of helping people who aren't able to follow along every single day, check back in much less frequently and get a sense of what's happening. October was an absolutely monster month, so this is a pretty good one to start with. And to kick us off, we get right at the theme which is going to show up throughout this episode, which is OpenAI just relentlessly pushing out new products and features. I'm actually cheating a little bit going back to September 30th for the launch of Sora 2 as our first event. Now, Sora 2 was significant not only because OpenAI finally had a model that was commensurate with the state of the art from Google and Chinese companies, but also because they decided to launch it with a companion social app. Now this was a highly controversial move. While for OpenAI they said it was about giving people an environment in which to share and explore their video generations, some thought that it represented OpenAI just heading straight in the direction of every other ad supported tech company. Sam Altman continues to insist that the company has not made decisions about ad based revenue, but one thing that is notable in that the interest in the Sora app has extended longer than I think a lot of people thought it would. For a time it had made it all the way to number one on the app charts, and even now, a month on from launch, it's still at number two in the free app charts, just behind ChatGPT. A couple weeks after Sora was released, Google joined the party with VO 3.1, an incremental upgrade to the model that they had released earlier in the year, which set the new template for AI generated video by incorporating sound into the generation. Now, in addition to the model release, Google also made some updates to the Flow app, which is the AI powered editing suite. This I think gets it a theme that we're going to be talking a lot more about in the months to come, which is something I'm loosely referring to as the product era of AI Increasingly we are seeing not just model releases get top billing, but also new product releases that put models in some useful context. In that way, both VO 3.1 with Flow and Sora 2, certainly with the Sora app, are demonstrative of that trend now. One more note on Google While a lot of this month's story is about new OpenAI releases, Google has been having just a massive run of it recently. As part of their Q3 earnings call, they revealed that the rate of growth in the Gemini app had taken a serious leg up over the last quarter. Gemini grew from 350 million to 450 million monthly active users between March and July and then made a massive jump from 450 to 650 million between July and October. Meanwhile, Google delivered its first ever $100 billion quarter, beating all estimates of growth both top line and in their cloud division, further cementing them at the very front of the hyperscaler pack now moving on sort of linearly through the month, October also saw OpenAI's latest Dev Day. The two big announcements were first the Apps SDK, which is basically a way to build applications directly into ChatGPT, making it so that you can do more without having to leave that interface. The other big announcement was Agent Kit, which was a set of new tools for building agents. While the first 24 hours was full of people asking if this had killed companies like Eniden and Lindy forever, the response in practice has been a little bit more subdued. And yet I don't think anyone is taking for granted the significance of OpenAI being more intentional about creating tools to help people build a broader array of agents. Now one interesting thing that happened during Dev Day was that the public companies that got mentioned by Altman and others on that stage, these were partner companies that had, for example, built apps on the Apps SDK, saw a big burst to their stock price. So let's talk for a minute about what this month was like in the broader macro and market conversation around AI. While we didn't see the same sheer volume of big crazy infrastructure deals that we did in September. Remember, September saw Both the Nvidia $100 billion OpenAI deal as well as Oracle booking $300 billion of OpenAI future business, we did get an announcement of a strategic partnership between AMD and OpenAI to deploy a not so slight 6 GW of AMD GPUs in the years to come. That was also not the only big infrastructure deal. Anthropic and Google announced a deal by which Anthropic will expand their use of Google Tensor processing units, or TPUs, in a deal that could be worth more than 10 billion now. As you might imagine with all of this, the AI bubble conversation has been constant background noise throughout the month. What really picked up, though, was the connection between AI and increasing tech layoffs. Amazon laid off 14,000 people, intel had a big announcement, and they were just the tip of the iceberg. And what we saw is those companies heavily implying that this had to do with AI. Even if it wasn't the direct result of AI, you're starting to see a lot more chatter like this tweet from Sergio who writes, these layoffs should concern everyone. These shifts are happening at a rapid pace and the average person is not prepared. In my opinion, we're entering the most unpredictable period in human history. Others tried to bring some rationale to the conversation, sharing a Wall Street Journal piece called Tens of Thousands of White Collar Jobs Are Vanishing as AI Starts to Bite, investor Chamath Palihapitiya wrote It's convenient to blame AI, and this diagnosis may eventually turn out to be right. But the current wave of job losses are not because of AI. It is companies unwinding ZIRP and DEI hiring excesses that left them bloated and inefficient. Yet still, nuance is the enemy of narrative and the narrative of AI as the layoff scapegoat is taking hold. If those were some of the big outside looking in conversations, there was a lot of insider to insider chatter this month as well. And nothing got the folks squawking as much as the interview with OpenAI co founder Andrej Karpathy on the Dwarkesh podcast. Andrej, freed from the restriction of working for one of the big labs, dropped some serious bombs. The most quotable part of it was the idea that current agents are, in his word, slop and that AGI is still a decade away. The response was so big that he actually had to go back and clarify that in his estimation, he's pretty bullish on these timelines. It's just not as crazy bullish as the folks who are out here saying that we're going to get AGI tomorrow. Still, this has provoked an entire internal conversation around the nature of where we are in the hype cycle, whether we're promising too much, and what the potential implications of that could be. And you better believe that Andre's comments found their way back into the AI bubble debate as well. Now, if Andre is pushing AGI timelines out, one area that might have seen some People accelerate their timelines. This month was robotics. There were two big announcements. The first was the figure 03, which had a range of significantly increased functionality and capabilities that makes it more prepared for both industrial and home use. But honestly, the thing that really captured people's attention was the One X Neo. Not nearly as slick as the Figaro 3, it's specifically designed to feel more warm and fuzzy. This one is not meant to do double duty in industrial environments. This is strictly for the home. Still, what made people sit up and take notice was that the company was promising that this thing would start shipping next year, in 2026, and you could buy it for just $20,000 or for a 500amonth subscription. Now, when people dug into the details, it was a little less exciting. They basically said that for a lot of tasks and functionality, the robot is not going to be there from an autonomy perspective. And so you're going to have to schedule time with a remote operator, which of course brings up all sorts of weird questions around privacy given someone vring into your house to fold your laundry. But still, you can definitely feel the awareness of the robotics moment starting to accelerate all around us. Coming back to OpenAI because we could not escape product announcements from that company for very long. This month, as we moved from the middle, towards the end of the month, they introduced ChatGPT Atlas, their entrance into the new AI browser wars. Like Perplexity, Comet and some of the other AI browsers that we've seen, the browser features an embedded instance of ChatGPT and also promises to have more agentic capability to take actions on your behalf. Now, in my estimation, we're still mostly in the period where the value proposition of an AI browser is not about agents doing things for you, but is about not having to transport the context of whatever you're doing on the browser over into your LLM assistant. And there are many use cases that make it worth considering. If not using an AI browser like Atlas all the time, at least having it in your repertoire. Still, obviously the big long term bet is on that more agentic set of capabilities. I just don't think we're there yet. And if one of the watchwords for the ChatGPT browser story was context, that was also at the core of what could end up being the most significant feature introduced by any AI company this month, which is Claude's skills. Skills are effectively little folders full of context that Claude can tap into as needed when they're relevant to the task at hand. So skills can have things like instructions, scripts and other resources. When Claude is starting to figure out how to execute a task, it can use a smaller number of tokens with a simpler, cheaper model to determine which skills might be relevant, and then only upgrade its model use and token consumption with the context of skills when it can actually draw upon them to get the prompt done. Skills are also composable, portable, transportable across all of Claude's apps, and are at the moment growing even faster in terms of GitHub stars than MCP did when it was introduced. Couple more to round us out One makes my cut because of how surprising it was to folks, we got news this month that Suno had quadrupled its annual recurring revenue to 150 million and was also in the process of a potentially monster raise. Now, as I explored in the show all about that, what makes that interesting is that the use case for Suno for a big chunk of that 150 million is perhaps not the social media content and advertising type of business use that you might imagine, but just people who love to create music with Suno. As we look for new social network primitives, it feels possible to me that Suno lowers the bar sufficiently to music generation that that could actually be the core of a new type of social experience. That is, of course, unless it gets sued off of the planet. We also did get wind that Suno competitor Yu Dio had settled its lawsuit with one of the big record labels, but as part of the consequence it was turning into something very different, effectively a remix platform for your favorite Taylor Swift singles. Whether that's what people actually want out of AI music remains to be seen. Last story from Our biggest news from October has to be OpenAI completing its for profit business conversion. Now I say complete in big air quotes as there are inevitably going to be continued legal challenges, not least of which from Elon Musk around this, but at least when it comes to the California and Delaware Attorneys General, OpenAI has officially shifted its structures and can operate as such. It took about five minutes after that conversion for us to hear that OpenAI was planning to go public, probably in 2027, but potentially as soon as the second half of next year. And in my estimation, it can't come soon enough. Okay, so those are the big stories from October, but what are the five AI stories that I'm watching most closely in November? This episode is brought to you by Blitzy, the enterprise autonomous software development platform with infinite code context. Blitzy uses thousands of specialized AI agents that think for hours to understand enterprise scale code bases with millions of lines of code. 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From aligning culture and leadership to building trust, data readiness and deploying AI agents. Whether you're a C suite, executive strategist or innovator, this podcast is your front row seat to the Future of Enterprise AI. So go check it out at www.kpmg.us aipodcasts or search you can with AI on Spotify, Apple Podcast or wherever you get your podcasts. Meet Rovo, your AI powered teammate. Rovo unleashes the potential of your team with AI powered search, chat and agents or build your own agent with Studio. Rovo is powered by your organization's knowledge and lives on Atlassian's trusted and secure platform so it's always working in the context of your work. Connect Rovo to your favorite SaaS app so no knowledge gets left behind. Rovo runs on the Teamwork graph, Atlassian's intelligence layer that unifies data across all of your apps and delivers personalized AI insights from day one. Rovo is already built into Jira Confluence and Jira Service Management Standard, premium and enterprise subscriptions. Know the feeling when AI turns from tool to teammate? If you Rovo, you know Discover Rovo, your new AI teammate powered by Atlassian get started at ROV as in victory o.com let's start with the big obvious thing that everyone really wants, which is for Google to release Gemini 3. Man, there have been rumors about Gemini 3 coming for months at this point. You hang around on AI Twitter long enough and you're going to see someone sharing some video screen capture claiming that something is Gemini 3. We've even got to the point where we're now hearing rumors of Google nerfing Gemini 3 in advance of release. You've got people speculating that Google knows that Gemini 3 is such a big improvement that they're intentionally delaying it, draining money from other war chests. To be perfectly honest, and a bit of a wet blanket, I've seen nothing to indicate that Gemini 3 is coming other than that we want it. And I think people are radically underestimating the stakes of this release for Google. It's actually a sign of how much Google's narrative has improved that people are now assuming that Gemini 3 is just going to totally blow everything else out of the water, as opposed to assuming that it's going to have similar dynamics to GPT5, where people are actually disappointed in the incremental improvements. Point being, just because Gemini 3 is the next release, just because 2.5 has been out for a while, and just because we really want it does not mean it's necessarily coming soon. That said, I appear to be in the minority in this over on Polymarket, there's almost $5 million in volume on the Gemini 3.0 released by question, with 25% betting that it would happen by November 15th and 66% betting that it would happen by Nov 30th. Certainly there is no bigger potential release for really the rest of the year at all than a potential Gemini 3.0. So that is, with a bullet, the first big AI story that I'm watching. The next thing that I'm watching is to see how the AI bubble narrative evolves. For the last month and a half, we have been inundated with some version of this chart showing the circularity of deals between these companies. And yet, one of the things that strikes me is that the AI bubble thesis is basically completely unprovable right now. In other words, even if you think that this is a bubble, it's going to take a meaningful amount of time for it to reveal itself as such. These deals are laid out over a period of a half decade, and does anyone really think we're going to see such a dramatic downturn in the demand profile for AI in the next six months that all of a sudden they're going to come crumbling? Plus, as we've talked about on this show, companies aren't yet super overleveraged when it comes to this stuff, and I would anticipate that we're going to finally start to get a little bit bored, at least with this iteration of the conversation. The flip side is that I think that the political dimension of the conversation is going to increase dramatically heading into next year's midterm elections. As the bellwether of that, just keep your eye on Bernie Sanders, who is now tweeting about this just about every day. Take one of him posting this highly controversial ad from about a year ago. Sanders writes, billboards across the country are promoting the replacement of millions of jobs with AI and robotics. Great idea. One simple question. How will those displaced workers survive when there are no jobs or income for them? Once again, at the risk of getting political, it would be bad if the entire Democratic Party decided that they should be contra AI and blame it for the economic malaise that is engulfing big parts of the country. It would be even worse. And it seems to me that this is an increasingly likely outcome. That populist sentiment on both sides of the aisle decides to go after AI. It could get more hairy before it gets better. So, especially as we head into a heightened election period, I am absolutely keeping my eye on this piece now, flipping all the way to the other end of the spectrum and getting into the super technical and inside baseball type of story. Vibe coding as a concept remains less than a year old. This time last year, the reasoning models were only just starting online Lovable was like a month old or less. Maybe it even launched this month. And vibe coding as a term wouldn't be coined for another few months. Over the last year, however, this has become undisputedly the big theme and breakout use case of AI. This entire year as that has happened, a complete, robust, rich and diversified market of providers have flooded into every potential crack and use case for AI coding from mobile based vibe coding to asynchronous background agents to synchronous companion assistants and everything in between. Interestingly though, recently we have an intra software engineering conversation around what the optimal configuration of AI assisted coding actually is. One of the reasons that I'm watching this, even though it's specifically about this one admittedly important use case for AI is that I think that this conversation around the trade offs of autonomy versus speed as an assistant are going to model conversations that we're going to be having about basically every use case in the months to come. As always, your best follow on this one is Swyx Wyx on Twitter. As I mentioned before, he'll also be on the show later this week. By the way, I am traveling this week so I have a couple of preloaded shows. I will have my equipment with me so I'll be popping in and out especially if there is really important news. But you're going to get a few different types of shows this week as well. Fourth AI story I'm watching for in November is what I would call Emergent 2026 discourse. There are three big themes that I'm watching, especially when it comes to AI at work business AI heading into 2026 and those are the idea of the product era of AI or an emphasis on the productization and applications rather than just models, context engineering and orchestration. And the big focus that companies are going to have on data and a real focus on roi. We are starting to see some really interesting glimpses of where companies are seeing roi and frankly it's more bullish than I think people would have even anticipated. Now of course we have roisurvey AI live right now. It's a big end of year benchmarking study on exactly this. We have hundreds and hundreds of use cases that have been shared with information about the ROI that they have driven. I would love to be able to share the complete results of that with you, which you will get by just contributing a few of your use cases at roisurvey AI. In any case, I think that all three of these ROI context products are going to be a major part of the conversation coming into the end of the year and so I'm keeping an extra close eye on that. Finally, outside of a potential Google Gemini 3, the one other big event from the big tech companies that is on the books for 2025 is AWS's Reinvent which will take place at the very beginning of December. Amazon, among the big tech companies, has struggled the most relative to its peers and I am super interested to see how they position themselves heading into 2026 if they make any big, unexpected announcements. So while this is cheating a little bit as it gets into December, it is certainly something that I'm going to be watching for to see if we get any hints heading into the event. So that's that. Those are the big stories from October and the stories that I'm watching most in November. Let me know what you think and what you're interested in in the comments. But for now, that's going to do it for today's AI Daily Brief. Appreciate you listening or watching as always. And until next time, peace.