xAI Releases AI API

Today on the AI Daily Brief, XAI has launched an API and many more stories. 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. Today, because I am traveling, we are doing an extra extended headlines edition. So basically the entire episode will be headlines. There'll be a little bit more in depth and we'll cover a few more topics, but there won't be a headlines and main episode division. We'll be back to more normal formats later in the week. We kick off with some news out of xai, which has launched their API to allow developers to build on top of the company's Grok models. The APIs can access Grok 2 and Grok 2 Mini, which are the latest multimodal models from XAI. Developers can also generate images using Black Forest Labs Flux 1 diffusion model. Now, some early users were reporting difficulty accessing anything other than a model referred to as GROK Beta, so there could still be some teething issues going on. This launch moves XAI from early beta testing to a point where they are now Openly competing against OpenAI and other foundation models. At the moment, it appears that XAI is priced at almost twice the cost of GPT4O, although it still comes in well below OpenAI's Reasoning Model 01. Grok 2 is documented as feature complete, on par with other models including text and code generation, as well as vision to process image inputs. The LLM also supports function calling. That said, these features aren't fully available yet and have no current timeline for release. This is an important moment in many ways because there are such a small number of companies that actually have the ability to compete when it comes to foundation models, and up until now we really haven't seen what XAI is capable of. Grok and Grok 2 have been live within Twitter X for some time, but mostly get used to provide news summaries or generate images. That said, XAI is moving very quickly. The company raised 6 billion in May at a $24 billion valuation and immediately plowed the money into one of the fastest and largest data center projects in history, building a 150 megawatt training supercluster. The first training run has reportedly begun with XAI training their next model on 100,000 H1 hundreds. The big promise, of course, from this API and XAI in general is the ability to access and train on X data. That means the model has real time access to social media feeds, which presumably you would think developers would find some interesting, unique thing to build using that data. Some of the most interesting details about the effort came from founding XAI employee Toby Pollin, who said that the entire system was written from scratch by six engineers over four months, which is a pretty insane effort. Ultimately, I think developers are excited to have another option and just thrilled for more competition. Next up, we turn to a recent survey from kpmg. The company released its latest digital innovation quarterly Pulse survey and had some interesting insights around Genai adoption in the enterprise. Vice Chair of AI and Digital Innovation Steve Chase summed up the results, saying despite trending skepticism in the media around Gen AI, business leaders overwhelmingly see it as truly transformative. More and more we're seeing levels of investment in tech data and talent to support Gen AI that matches the potential disruption on the horizon. I don't think you guys need me to tell you that I completely agree with that sentiment. I basically spent the entire summer explaining why the skepticism headlines were just that, headlines. But a couple of the interesting things from this survey There's a lot of focus on AI leadership. One of the stats that I thought was most interesting was that 42% of leaders have or are planning to hire new AI leadership, which is up from 27% the previous quarter. What's more, it seems like leaders are leading when it comes to AI training. 70% of leaders have participated in mandatory AI training compared to only 28% of employees. Another interesting note, 52% of executive managers are using Genai versus 20% of entry level employees. In fact, this study shows a reverse distribution where the more senior you are, the more likely to be using Gen you are, which is a statistic that I would love to push more into. On the one hand, I can see this making sense from the standpoint that it is executives that are getting the most pressure to transform and remake their organizations for the AI era. But at the same time, I wouldn't be surprised if some of those reported numbers are soft and reflect the trend that we've seen over and over again of employees not being sure that they're actually willing to talk about their AI usage for a variety of reasons. Anyway, interesting stuff in that survey. Definitely worth checking out. Two things I feel qualified to talk about Organization and productivity apps and AI tools. Which is why I am very happy that today's episode is sponsored by Notion. Notion combines your notes, docs and projects into one space that's simple and beautifully designed and the new Notion AI has the capability of multiple AI tools built in, which means you can search, generate, analyze and chat all inside Notion. The new Notion AI is a single AI tool that does it all. Search across Notion and other apps, generate docs in your own style, analyze PDFs and images, and chat with you about anything. Notion is a perfect place to organize your tasks, track your habits, write beautiful docs, and collaborate with your team. The more content you add to Notion, the more Notion AI can personalize its responses for you. Basically, unlike generic chatbots, Notion AI already has the context of your work. There are also a bunch of great integrations. Notion uses AI knowledge from GPT4 and Claude, and with AI connectors, which is now in beta, Notion AI can also search across Slack discussions, Google Docs, sheets and slides and more. Tools like GitHub and Jira are coming soon. Notion is used by over half of Fortune 500 companies, but more importantly, it's used all day, every day by me. Try Notion for free when you go to notion.com aidaily brief that's all lowercase letters notion.com aidaily brief to try the powerful, easy to use Notion AI today. And when you use that link, you're supporting the show once again. That's notion.com aidaily Brief Today's episode is brought to you by Venice. 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That's a process by which our super intelligent team sits with your organization, figures out the specific use cases that matter most to you, and helps actually ensure support for adoption of those use cases to drive real value. Go to BeSuper AI to learn more about this AI enablement network. And now back to the show. Next up, another big theme in the enterprise is of course agents, and yesterday Microsoft announced what they called new agentic capabilities, including 10 new autonomous agents in Dynamics 365 focused on sales, service and supply chain teams. Now one of the interesting things about this is that some folks have tried to draw a sharp contrast between the assistant era of AI and the agent era of AI. Chief among those is Marc Benioff from Salesforce, whose current press line is basically that Microsoft has sold the world a bill of goods and that assistants aren't really all that valuable. But where we'll really get business value is in the agent experience. And oh by the way, of course check out Salesforce's agents. Unsurprisingly probably. I think that the agent versus Assistant thing is not actually an either or, it's a both and and you're going to see both of these experiences impact the enterprise in different ways. That said, of course agents are a lot earlier in their life cycle, whereas there are some pretty breakout and default and regular use cases of assistance. Agents are really still getting up and running at this point, although certainly in areas like customer service they're starting to become more de rigueur and normal. There will be a lot to watch on the agent experience if you're interested. Something that I'm thinking about for at some point this year is a week long or so deep dive into the agent world, which might be something that we look at doing in December. Next up, we've had a lot of fawning coverage for Perplexity recently as frankly the product kicks butt and the company seems to be doing great as well. But they are not without their struggles as exemplified by yet another lawsuit against the company for copyright infringement. On Monday, News Corp. Sued Perplexity for allegedly, quote, engaging in a massive amount of illegal copying of publishers copyrighted works and diverting customers and critical revenues away from those copyright holders. The plaintiffs include Dow Jones, who published the Wall Street Journal and the New York Post. Perplexity CEO Aravon Shrinivas declined to comment on the lawsuit, however did Tweet Check out WSJ.com today where they had paid for a front page ad about Perplexity's partnership with Uber. One of the things that makes the Perplexity copyright cases different and interesting from, for example, those being levied at OpenAI is that they're more about how the AI summary overviews take away and cause material harm to journalistic production versus those publishers having problems with the way that their material has been used in training. It's a super interesting wrinkle on the copyright question, and one that I think the answer to, which could have a significant impact on how the industry evolves. Austin Schmidt pointed out that while startups may be defiant about these lawsuits, they could have real consequences. He writes, LLM content costs are about to skyrocket. This is an advantage for Google. They have the advertiser base to monetize today. The others do not. Raising capital to fund insane losses is easy today, but let's circle back in a year staying on the copyright and training theme the largest book publisher in the world, Penguin Random House, has changed their copyright page to reject AI training. The standard page in both new and reprinted books will now read. No part of this book may be used or reproduced in any manner for the purpose of training artificial intelligence technologies or systems. The page also states the work is expressly reserved from the Text and data mining exception, a reference to EU data laws. Penguin Random House is the first major publisher to make this change. As the battle around AI copyright heats up, the Verge writes, what gets printed on that page might be a warning shot, but it also has little to do with actual copyright law. The amended page is sort of like Penguin Random House's version of a robots. Txt file, which websites will sometimes use to ask AI companies and others not to scrape their content. But robots. Txt isn't a legal mechanism. It's a voluntarily adopted norm across the web. Copyright protections exist regardless of whether the copyright page is slipped into the front of the book, and fair use and other defenses also exist even if the rights holders say they do not. Basically, nothing about this changes the fact that this is going to have to be settled in court Author Cory Doctorow wrote a long thread on Packing the Takes, commenting these writers are assuming that just because they're on PRH's side, PRH is on their side. They're assuming that if PRH fights against AI companies training bots on their work for free, that this means PRH won't allow bots to be trained on their work at all. This is a pretty naive take. What's far more likely is that PRH will use whatever legal rights it has to insist that AI companies pay for the rights to train chatbots on the books we write. It is vanishingly unlikely that PRH will share license money with the writers whose books are shoveled into the bot's training hopper. It's also extremely likely that PRH will use the chatbots to erode our wages and fire us altogether and replace our work with AI slop I'm always a little bit hesitant to cover these very interstitial battles when it comes to copyright because as I've said a million times and will unfortunately keep saying no amount of chatter on Twitter and no amount of pages on books is going to solve this. These are cases that are going to get litigated in court and frankly not going to be done until they get to the Supreme Court. Over in the world of AI and finance, the securities and Exchange Commission is cracking down on the use of AI in the financial sector. The Division of Examination published their priorities next year with AI integration featuring heavily throughout investment advisors, brokers and clearing agencies can expect the SEC to scrutinize their use of AI to ensure it meets regulatory standards. So far during this phase of adoption, the SEC has largely focused on active misrepresentations and fraud around AI. In March, the regulator sued two asset managers for making allegedly false claims about their AI enhanced training, while just last week the SEC sued a robotics company for making misleading statements about their AI powered robot. This will be the first time that the SEC takes a closer look at the way compliant financial firms are using AI in their business. The agency will focus on things like adequate supervision and risk to customer records and information through the use of third party tools for advisory firms using AI to generate investment strategies. The SEC will be looking at whether these recommendations fit the high standards demanded of registered advisors. Basically, I think that this serves as a warning notice that the chatter is becoming real and that the SEC is going to put a strong emphasis on figuring out the relationship of AI and finance. Lastly, today Uncle Sam wants you to join the AI Reserve Corps. The Defense Department is seeking to bring Silicon Valley's top talent into the military reserves. According to the Wall Street Journal, quote, the department is considering asking chief technology officers and other senior tech professionals to take up high ranking positions in the reserves. The tech reservists would be periodically summoned to help with short term projects in cybersecurity, data analytics and other areas. Brent Paramido, the department's chief talent management officer, said, we're creating this people industrial base that is going to help us solve our national security problems and national security challenges in the decades to come. While the Marines already have a recruiting program for cybersecurity specialists, this would be the first time that tech specialists are brought in as paid reservists. Commitments would be in line with the 700,000 combat reserves who attend training one weekend a month and two weeks a year. They are eligible to be called up for active duty, which wouldn't be a case for the specialized tech reservists, Parameter said. It's not like put down your keyboard and pick up a rifle. Parameter hopes to have the first group of military roles by September. The scope will start extremely small with just a dozen reservists. However, he hopes to expand the program to thousands over the coming years. Some of the trickier issues are figuring out which branch of the military should house this unit and how to appropriately rank senior private sector executives once they join up. This is all part of a broader push to rethink the military's relationship with the tech world and to more effectively compete for top talent with the private sector. What's more, it's certainly in line with the broader shift that's happening right now, where things that were previously anathema, including using tech for defense purposes, have become some of today's hottest projects. That, however, is going to do it for today's AI Daily Brief Appreciate you listening or watching. As always and until next time, peace.