GenAI is Being Adopted Faster than PCs or the Internet

Today on the AI Daily Brief, generative AI adoption is going faster than the PC or the Internet. Before that in the headlines, OpenAI releases a new interface and it's good the AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. To join the conversation, follow the Discord link in our show. Notes. Welcome Back to the AI Daily Brief Headlines Edition. All the daily AI news you need in around five minutes. We kick off today with yet another OpenAI update, but one that is sort of expected but still really cool. Basically, for a little while now, it's been clear that part of the battle when it comes to the state of the art in AI is not just about models themselves, or even this new sort of agentic break that we're seeing with O1, but also just about simple user interface and user experience. Anthropic really jumped out ahead of OpenAI on this front when they announced their Artifacts feature. Basically, Artifacts was a second window that came up alongside the Prompt window that allowed you to better see the document that was being built by Claude as it was happening. And while it seems like a small UI upgrade, it was a significant one, one that was meaningful enough that many people, myself included, were often finding themselves going to Claude even more often just to get access to that interface. Well, now OpenAI has announced their own version and they're calling it Canvas. It does something very similar to Claude's Artifacts, where it opens a second window to view and edit AI projects. Daniel Levine, a product lead at OpenAI, said, The core thing we're trying to solve is a better way to collaborate with ChatGPT on writing and coding. Still, there are some things that are a little bit different about Canvas that are really cool as well. In an announcement post they Write with Canvas, ChatGPT can better understand the context of what you're trying to accomplish. You can highlight specific sections to indicate exactly what you want ChatGPT to focus on. Like a copy editor or a code reviewer, it can give inline feedback and suggestions with the entire project in mind. So this feature then allows ChatGPT to suggest inline edits automatically, adjust the document length to be shorter or longer, adjust the reading level anywhere from kindergarten to grad school, check for grammar, clarity and consistency, or even add emojis, which Sam Altman would go on to suggest is the best feature that they've ever pushed. One of the big game changers in image generation AI was when tools like midjourney allowed you to start modifying very specific sections of the image, rather than just having to re prompt the whole thing and this is sort of the equivalent for writing both words and for code. This is one of those things that now that it exists, it's basically impossible to believe that it didn't exist up till now. It's just such a much more intuitive way to interact. But it is such a huge improvement and one that I think really will benefit basically every ChatGPT user. Now, while that was the main focus with OpenAI yesterday, there was yet another notable departure from the company as well. One of the leads on Sora, OpenAI's video generator left to join Google Tim Brooks announced on Twitter X I will be joining Google DeepMind to work on video generation and world simulators. Can't wait to collaborate with such a talented team. I had an amazing two years at OpenAI making Sora. Thank you to all the passionate and kind people I worked with. Excited for the next chapter. Now this whole idea of a world simulator seems to be really the focus, DeepMind CEO Demis Hassabis said. So excited to be working together to make the long standing dream of a world simulator a reality in terms of what a world simulator is. DeepMind researchers explained it in a 2023 paper by saying as applications of a real world simulator range from controllable content generation in games to movies, to training embodied agents purely in simulation that can be directly deployed in the real world. As always, there could be some very simple personal reason for Tim Brooks leaving, but it does bring up further questions around Sora, which, while blowing people's socks off with its previews back in February when it was announced, seems to have lost a lot of ground from rivals like Luma Runway and others. Just as I began to record this, I also saw that Meta had released some new video generation models, which I'm sure we'll be talking about next week. There's also the competitive dimension where, as TechCrunch puts it, OpenAI has appeared to seed valuable partnership ground video generation challengers in recent months. They point to stability, recruiting James Cameron to be on its board, and a deal between Runway and Lionsgate to train a custom video model on Lionsgate's movie catalog. Now again, this doesn't mean that we're not going to see something amazing from Sora that redefines our expectations of what can be. And it also doesn't mean that we're not about to see it announce some big partnership with a studio that's just happening behind the scenes. Still, any sort of departure like this is going to bring up questions for which of course right now we don't have answers. One thing we do have answers for is what the demand looks like for Nvidia's newest Blackwell AI chips. According to CEO Jensen Huang, the demand is insane. During an interview on cnbc, Jensen said Blackwell is in full production, Blackwell is as planned, and the demand for Blackwell is insane. Everybody wants to have the most and everybody wants to be fast first, he continued. When you look at the performance boost that you're going to get on Blackwell vs Hopper, every hyperscaler is going to aggressively buy this stuff up, not to mention enterprise customers and tier 2 cloud players. Nvidia's stock loved the news, gaining 4% in an otherwise flat market. Basically, every time you want to think that we're past any sort of hype cycle, the Nvidia train just keeps on rolling. For now, though, that is going to do it for today's AI Daily Brief Headlines edition. Next up, the main episode. Today's episode is brought to you by Fractional when we wanted to build an AI powered feature of Superintelligent, our AI tool finder, I went straight to Fractional. The Fractional team is a group of senior engineers in San Francisco working on some of the most exciting projects in applied AI. Working with them is basically like hiring an absolute top flight AI engineering team, but in a way that you can customize exactly for your particular needs. 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The platform features over 600 fun, highly practical AI tutorials that get you using AI fast and with an eye to actually transforming how you get things done. We've just launched super for Teams. So if you have a group of people at your company that want to figure out how to use AI together, I highly suggest you check it out. But for those of you who are using superintelligent as an individual, once again, if you sign up for Super Intelligent between now and the end of the month using Code Soback, you will get your first month 100% free. Go to be super AI and check it out today. Welcome back to the AI Daily Brief. Today we are talking about how generative AI adoption is moving faster than both PC and Internet adoption. And moreover, this is a study from an extremely reputable source. You guys might have seen this study floating around. It came out on September 20th. It was called the Rapid Adoption of Generative AI and it was written by someone from the Harvard Kennedy School, someone from Vanderbilt and someone from from the Federal reserve Bank of St. Louis. In other words, this isn't a Microsoft supported study or something like that saying AI is growing fast. It's from a group that doesn't have any stake in the results of what they found. Now, one apology in advance for those of you who are watching this. This is going to be a much less visually interesting piece as it's really just me summarizing a study. But we're going to do what we can and maybe I'll ask the editors to throw in some B roll here and there. So this study is interested in the economic impact of AI and the way that they're coming at that was the question how quickly and intensively AI is being adopted. Importantly, the data from this survey was really recent. It was just captured in August of this year, and some of the headline statistics are really profound. 39.4% of the working age population has used AI and 32% overall said they were now using it at least once a week. Keep in mind, this is a technology that is less than 2 years old and a third of adult Americans are using this thing at least once a week. Now, digging into workplace numbers, they were even more revealing. 28% of employed respondents said they had used AI at work, and 24% said they were using it at least weekly. 10% reported daily use. A couple of other things that I thought were really interesting about this study. First of all, we definitely have a tissue kleenex situation where ChatGPT is by far and away the most used service. In fact, it is enough associated with Genai that the paper took the release of ChatGPT as Day Zero. This is where the comparison to the Internet and PC came from. With the Internet seeing 20% adoption in its first two years, whereas PCs took three years to get to 20%. So given that AI is seeing 39.4% adoption after two years, basically AI is outpacing the Internet by a factor of two. Now, one of the interesting things in the study is that part of the reason that AI is being adopted faster is that while rates of adoption at work are Fairly similar to PCs and the Internet, AI is being adopted outside of work much more quickly than previous technology. This sort of makes sense, right? In 1984, for example, PCs were extremely expensive, but worth it for workplaces due to massive cost savings in document processing and file storage. But in the case of AI, it's obviously very cheap outside of work. People have access to tons and tons of free tools that are really interesting, fun and useful right now, basically, whereas PCs were an unaffordable luxury at home well into the early 90s. People can get their feet wet with AI right away when it comes to AI usage at work. On the one hand, there are some things that are not surprising. Programming and management work leads the way with nearly 50% adoption. But at the same time, 22% of blue collar workers said they've used AI in their profession, and 16% said they were using it on a weekly basis. In fact, aside from personal services, every single job category had at least 20% adoption, which was classified as having used AI at least once in the past. One concern that the report flagged was workplace inequality based on AI usage. Workers, for example, without a bachelor's degree are half as likely to have used AI at work as their college educated counterparts. And just broadly, AI usage is more common among younger, more educated and higher income workers. Then again, part of what makes the inequality question even more complicated in this circumstance is that it's a lot of these jobs that are most on the chopping block from AI as well. The fact that it is white collar jobs like programming that seem most in the eye of the hurricane is a fundamentally different phenomenon to past technology waves that we've seen now. When it comes to what people are using AI for, writing by far leads the way, probably reflecting ChatGPT's dominance. That's both at work and outside of work. At work, performing administrative tasks is also high on the list, and both inside and outside work interpreting, translating and summarize are fairly high. What's interesting is that outside of work there are a lot of uses which have some meaningful uptake that are different than those happening at work. The number of people using IT for tutoring or education is much higher outside work than inside work. People outside of work are using AI for things like entertainment recommendations, health and wellness recipes and cooking support with friends and family, and even home improvement. Now of course, this coming from the St. Louis Fed. The main focus was to try and understand what growing levels of AI adoption might do to the economy and to the labor force. Specifically, they're interested in time saving and productivity. Researchers showed the data for which tasks were being assisted by AI in the workplace in Raw Firm, and found that for each of the 10 groups of tasks, over a quarter of the people using AI were applying the technology to that task. Writing, summarizing, obtaining instructions, and searching for information were all use cases for over 45% of people who have integrated AI into their workflow. But in general, what this section really shows is that once workers adopt AI, they use it in as many ways as they possibly can. The survey also found that the more frequently people use AI, the longer they use AI. Although only 25% of AI users said they were using it for an hour or more a day at work, 42% of daily users said they were spending more than an hour each day using AI. Applying some extremely back of the napkin math, the report suggests that between 0.5% and 3.5% of all work hours are already AI assisted. What makes this stat interesting is that it's driven almost entirely by the power users, with 76% of workers reporting zero hours a week using AI. The implication is that when use cases are found, AI use jumps up dramatically to become a ubiquitous part of the workday. Overall, there is a ton of interesting stuff in this study. I very much suggest you go check it out. For now though, that is going to do it for today's AI Daily brief. Once again, Gen being adopted faster than the PC or the Internet. And of course, until next time, peace.