The 5 Most Important Stories in AI This Week

Today on the AI Daily Brief, we are counting down the biggest stories in AI this week. 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. All right friends, quick note. Today we are doing a little bit different type of episode, a countdown of the top stories of the week episode. That means no headlines versus main. Just diving right into the meat of the show. And the way we're going to do this is not actually counting down five stories from five to one. We're actually going to divide it into different categories and our first category is the most exciting product releases of the week. For me, this has to kick off with Midjourney, which is finally open to everyone on the web. For years, Midjourney has been a Discord only experience and over the last six months or so they've been gradually letting more and more people onto their web based interface, which is a custom designed web application for generating and editing Midjourney images. The web based experience massively decreases the barriers to entry and taking that even farther, the company is also offering free trials, which is something that is also different for them. Midjourney continues to be the AI product that I use the most and so I'm excited personally for more people to have a chance to check it out. However, Midjourney is not the only image generator that's generating conversation this week. In fact, if anything, the most discussed image generation release this week is Ideograms version 2.0. The specific reason that Ideogram is catching so much attention is how good it appears to be at handling text. Text generation has been the Achilles heel of image generators for some time. It's still something, for example, that Midjourney really struggles with, but Ideogram seems to nail it, as this thread of advertising related prompts visually shows off in this generation. A stylish backpack hanging from the edge of a mountain cliff with a breathtaking view of the valley below. The text Adventure Awaits is written in bold, adventurous letters on the top. The tagline Carrier World is placed below, emphasizing durability and style for those who seek adventure. And it looks like a professional advertising image. There are a bunch more examples of this and it really does represent a sea change moment for image generation. If this capability for text generation in images is starting to become more commonplace, one more product release which is somewhat related Luma Labs has released their Dream Machine 1.5. This is a quick update since Dream Machine is only a couple months old at this point. And already people are stacking these technologies together. Take for example this Cthulhu themed website animation, where an ideogram image with this incredibly cool text was then animated with Luma Labs. Our second category is Coolest Model Developments. And in this category, once again we have two different topics. First of all, fine tuning is now available for GPT4O. OpenAI says that this was one of the most requested features from developers and basically allows people to now fine tune the state of the art. As an additional incentive, OpenAI announced that they're offering a million training tokens per day for free to every organization through September 23rd. Now, to be fair, some people are skeptical of this. Santiago Vpino writes, fine tuning is now available for GPT4O and GPT 4.0 mini. But I need somebody to help me understand why anyone would use this. Fine tuning is hard and it takes a significant investment from a company to get it right. Why would a company spend all of that time to fine tune a model that OpenAI controls? You can't download the model from OpenAI, you can't host it yourself, et cetera, et cetera, et cetera. From what I've heard from people, and this has surprised many, the simple convenience of operating inside OpenAI's ecosystem simply overwhelms a lot of these other concerns. Whether that continues to be the case remains to be seen, but for now this is a big update that many will be excited to take advantage of. The other model development that I thought was interesting, which is something we talked about on yesterday's show, was Microsoft's release of three new Phi 3.5 models. These are all smaller models, comparatively speaking, with really impressive performance. And to me, the interesting thing about this is how much the competition in AI is not just at the far ends of the biggest model capabilities, but also in terms of finding ways to do more with less. Driving the pursuit of the small model competition is, I think, commercial concerns. Companies want to be able to run models on devices and they want to be able to offer capable models more cost effectively. These are two major considerations when it comes to model adoption, and so in many ways it's not surprising to see them become a bigger area of focus for many of the big labs. Third, we move into the biggest stories in enterprise AI, and I think the leader here has to be Salesforce announcing two new agents. The company announced the Einstein SDR agent and the Einstein sales coach. And to me this represents an example of how fast AI is changing. Even in the enterprise sector, companies haven't even really wrapped their head around generative AI that's used and maintained by their employees, to say nothing of these new agent capabilities. But that doesn't mean the technology is slowing down. Salesforce's arguments with these agents is basically that no sales team has enough pipeline, which is a fairly compelling pitch. And the purpose of these agents is then to not only increase pipeline, but in the case of the sales coach, also help people better convert. One of the interesting things to watch for with announcements like this is how providers like Salesforce position their technology vis a vis existing humans. It's very clear for Salesforce that this is not about replacing people, but but about rapidly scaling individual capacity in a context where, as they put it, there basically is no such thing as too much capacity. There are always more sales leads Today's episode is brought to you by Venice. The leading AI companies store your entire conversation history and attach it to your identity forever. That's every question you ask, every answer you receive, every image you generate, every thought you share with the machine. It's all being spied on. If you trust all the company's hackers and NSA board members that will ever have access to your AI conversations, then rejoice for you are well served. For the rest of us, Venice is an alternative. Venice is a powerful AI app for text, image and code generation that respects you as a sovereign individual and believes privacy and free speech are not only human rights but necessary for civilizational advancement. Private, permissionless and uncensored. You can try it for free without an account. AI Daily Brief listeners receive a 20% discount on Venice Pro. Visit Venice AI NLW and enter the discount code NLW Daily Brief. That's NLW Daily Brief, all one word. Today's episode is brought to you by Superintelligent, which is of course our platform that helps you learn how to use AI tools and perhaps even more importantly, gives you ideas on the best use cases that are actually going to help you achieve whatever it is you want to achieve. To recognize the end of Summer and Back to school slash back to work, we are running our best promotion ever. When you sign up for Super Intelligent between now and the end of August using code so back your first month will be 100% free. 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 superintelligent 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, our fourth topic is our biggest debate of the week, and this will be a surprise to no one. It continues to be California's controversial AI safety bill, SB 1047. Last we discussed it, a group of California congresspeople had sent an open letter to Gavin Newsom asking him to veto the bill, and former House Speaker Nancy Pelosi had added her weight to that position. Since then, we've had two developments from the big labs themselves. OpenAI sent an open letter to California State Senator Scott Wiener writing, the AI revolution is only just beginning and California's unique status as the global leader in AI is fueling the state's economic dynamism. SB 1047 would threaten that growth, slow the pace of innovation, and lead California's world class engineers and entrepreneurs to leave the state in search of greater opportunities opportunity elsewhere. Wiener bit back quickly arguing that OpenAI's letter quote doesn't criticize a single provision in the bill and also saying that the threat that AI talent might leave the state doesn't make any sense because the law would apply to any companies that conduct business in California, no matter where their offices are actually located. Meanwhile, Anthropic, which has been a little back and forth on this bill, but which of course is much more aligned philosophically with the AI safety side of the space that was intimately involved in originally drafting it, has come out in saying while they're not fully endorsing it, they think the benefits outweigh the costs, anthropic's Jack Clark wrote. You can read the letter for the main details, but I'd say on a personal level, SB 1047 has struck me as representative of many of the problems society encounters when thinking about safety at the frontier of a rapidly evolving industry. How should we balance precaution with an experimental and empirically driven mindset? How does safety get baked into companies at the frontier without stifling them? What is the appropriate role for third parties, ranging from government bodies to auditors? These are all questions that SB 1047 tries to deal with, which is partly why the bill has been so divisive. These are complicated questions for which few obvious answers exist. Nonetheless, we felt it important to give our view on the bill following its amendments in a section where they discuss high level principles for regulating AI. They write, the key dilemma of AI regulation is driven by speed of progress. AI technology continues to advance extremely rapidly. On one hand, this means that regulation is urgently needed on some key issues. We believe that these technologies will present serious risks to the public in the near future. On the other hand, precisely because the field is advancing so quickly, strategies for mitigating risk are in a state of rapid evolution, often resembling scientific research problems more than they resemble established best practices. We believe that this genuinely difficult dilemma is one important driver of the divergence in views among different AI experts on SB 1047 and in general the resolution that they suggest is very adaptable regulation. They said, we've come to the view that the best solution is to have a regulatory framework that is very adaptable to rapid change in the field. They write that there are several ways to accomplish this, including via third party auditors, frameworks that shape incentives without prescribing behavior, or procedural requirements that require a safety process without describing what is in it. Down the road, perhaps in as little as two to three years, when best practices are better established, a prescriptive framework could make more sense. I understand where they are coming from with this, but boy is that hard to instantiate in real policy. Lastly, and this is really important, they write, catastrophic risks are important to address. And once again, as I've said before with this debate, this is the central point of disagreement and why this discussion is never getting beyond first gear. By and large, the people that are most for this bill believe this, that catastrophic risks are important to address and important to address. Now for many of the people that oppose this bill, they fundamentally disagree with that. They believe that the catastrophic risks simply don't exist in the way that the proponents do. And when you don't believe in the fundamentals of a risk a of course you're not going to support regulation, even light touch regulation to deal with that risk. Now, I don't know what's going to happen with SB 1047, but to the extent that we are trying to take inspiration from this in terms of how we might want to approach this conversation on a national level, it seems to me like the clear and obvious thing here would be to separate this discourse into two different dimensions. Let the first be the risks that everyone agrees on. Build consensus around issues where there's little disagreement. For example, in this bill, whistleblower protections are something that basically everyone agrees on. I haven't seen any real disagreement with that sort of thing. Build a federal framework around the stuff where there is broader agreement and then intentionally tackle the question of catastrophic risk, instead of the two sides that have already made up their minds on this issue squawking at each other and screaming past the 99.99% of people that are in the middle, let each side actually make their case coherently and in a policy context probably too idealistic to hope for. But there it is. Lastly today, the most interesting idea of this week comes from the blog post that we read yesterday from VC Sarah Tavel where she reminds us that the incredible competition playing out between different model providers is to the huge benefit of the end users and consumers and also, frankly, startups that get to build new ecosystems. You certainly see that with the speed with which the foundation model companies are putting out new models, but even given what we talked about with Midjourney Ideogram and Luma all releasing new products this week, you're seeing it everywhere. Part of what makes this space so fun to be in is the speed at which it's changing, which is driven by competition. And so even as we have important debates around safety and the future of the world, let's not forget we're also living through an amazing capacity expanding period right now. Anyways, friends, that is gonna do it for today's AI Daily Brief. Appreciate you listening or watching as always and until next time, peace.