EP 493: ChatGPT’s groundbreaking image update, Google’s chart-topping Gemini 2.5 drop, Microsoft’s new reasoning agents and more AI news that matters

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This is one of the biggest weeks in AI development, like, ever. And I don't say that lightly. Been doing this for like two and a half years. But let's just preview what happened this week in AI news. Well, we have the world's most powerful large language model that was released and I'll tell you why. I think it's a bigger deal than you might think. We got the most capable and flexible image model we've ever seen that I think will absolutely disrupt creative Industries. One of the largest companies in the world released some breakthrough multi agentic flows and maybe even biggest yet. There's talks of a certain AI lab raising $40 billion and a separate company made a $30 billion acquisition. This is wild. This all happened in one week. Don't worry if you're scratching your head, like, what the heck is going on? I'm going to get you caught up and bring you the AI news that matters. What's going on, y'? All? My name is Jordan Wilson and welcome to Everyday AI, where your daily livestream, podcast and free daily newsletter helping everyday people not just learn AI, but how we can leverage it to grow our companies and our careers. So if that sounds like what you're doing, you're in the right place. So it starts here with this live stream slash podcast, but it continues on our website. So if you haven't already, please make sure to go to your everydayai.com, sign up for our free daily newsletter also on our website, Vina Gnomness. There's like now 500 almost episodes, so you can go. Whatever you try to learn in the world of AI, whether it's it's marketing, it's agents, it's ethics. We've already interviewed hundreds of the world's leading experts and you can access it all online for free on our website. It is a free generative AI university, so make sure you go check that out. All right? So welcome to our weekly installment of the AI News that Matters. We do this almost every single Monday. We cut through all the, the fluff, the bs, the press releases, and just bring you the AI news that matters. So it's live and unscripted and hey, live stream audience, do me a favor. Do I sound okay? I. I had a couple, you know, it was a couple minutes late getting this show started. Had some mic issues. So, yeah, hopefully y' all can hear me. Okay, let me know in the comments. Love to see everyone tuning in. Max from Chicago, Marie, Colby, Pedro, Brian, everyone else, tons of people joining on the YouTube machine. Sandra's on the elliptical. Hopefully I don't keep you too long. All right, but let's enough chit chat. Let's talk about what's happening in the world of AI news. So first, hardly no one is talking about this and I don't know why. So Microsoft has released a bunch of new very capable agents and I think that there's two in particular that our, you know, readers and listeners are really going to like. So Microsoft is solidifying its leadership in enterprise AI by unveiling major announcements to its Copilot Studio platform, including Deep reasoning capabilities and Agent Flows. So Microsoft announced two key additions to Copilot Studio. Deep reasoning capabilities for tackling complex problems with your own data and and Agent Flows that integrate AI flexibility with rule based automations. So we did have Ray Smith, the VP of AI on, sorry, the VP of AI Agents at Microsoft on the show on Friday. So make sure if you're interested in this, go listen to episode 492. We gave you a complete breakdown like the first people in the world to get it straight from Microsoft to you guys. So make sure you go listen to that episode. I think it was a great look from Ray just into the future of AI agents and everything that Microsoft is working on with these new agents. But today is actually the day that Agent Flows is being released yet. Today's March 31st. So I mean this is super new. So make sure to check if you are a heavy Microsoft 365 copilot organization. Make sure you check in on Agent Flows which should be released today. So Microsoft also announced that they've more than 400,000 AI agents were created in Copilot Studio just last quarter, showcasing some rapid adoption among enterprise users. So there's a lot of new agents. I mentioned two of them, but another one, the new Analyst Agent I think is a standout feature. So it's functioning as a personal data scientist capable of processing Excel files, CSVs and embedded tables to generate insights via Python code and visualizations. The Deep Reasoning, which I think is grabbing a lot of headlines. So the Deep Reason Agents has some new and improved capabilities that allow it to perform methodical analysis enabling use cases like generating RFP responses or conducting due diligence for mergers and acquisitions, I mean whatever you might be using it for. And then Agent Flows which should be released today's so that combines and this is Huge deterministic business logic with AI reasoning addressing customer needs for industries all over the place, from fraud prevention to operation optimization. So here's why that's important and the whole deterministic piece, right? So that means there's a piece of this new agent flow that's not generative, right? So I talk about, and I've talked in the past a lot about Notebook LM and how it's grounded in your own data and if you ask it something that's not in the data, it's just going to be like, yo, I don't know. So this is a feature of the new agent flows, it's deterministic and it lives just inside of your essential, essentially your Microsoft graph integration. So any of your live dynamic data within Microsoft 365 Copilot, that's what draws or that's what you know, this new agent is drawing from. So you know much less a lesson likelihood of hallucinations in the way that that's set up. So other industry players, including Google, OpenAI, Salesforce and Amazon are intensifying competition with their own agentic platforms. But Microsoft's approach prioritizes accessibility, offering tools for both TEC technical and non technical users to create custom agents through natural language interfaces and low code environments. That's the huge thing here, y'. All, Everything I just said natural language, right? You don't have to be a developer, you don't have to know Python, you don't have to know JavaScript or any other programming language. The language that this accepts is human language, right? So you can build these very impressive multi agentic functions, flows that use deep reasoning. So this uses OpenAI's O3 mini model, you know, to run this, which is wild, right? So a lot of these agents that we talk about, you know, through, whether it's, it's Google, whether it's OpenAI, you know, there's the new Manus, right? They're great, don't get me wrong. But one of the problems is a lot of times when you set up these agents, they're not necessarily working with your dynamic data. So you might be uploading some data, but that data changes, right? That document that, that report that, you know, that quarterly draft that you're, you know, updating a huge document, that document might change monthly, weekly, it might change every single day. So that's one of the downsides or one of the cons when you're working with some of these other agentic flows that aren't Microsoft and that don't have access to Your up to the second data and information. So I think human huge announcements from Microsoft that I don't think a lot of people were paying attention to, which is why I brought Ray on the show on Friday. So make sure you go listen to episode 492 for that. All right. What's that 40 billion dollar number I teased? Well, that's open AI is reportedly close to securing a massive record breaking 40 billion with a B. I know I kind of get the sniffles, the allergies got me today, but I. That's not a sniffle. That is 40 billion dollar funding round signaling some significant growth and investment. So this is according to Bloomberg. So reportedly SoftBank is leading this 40 billion dollar round with an initial investment of 7.5 billion followed by an additional 2.5 billion from a syndicate of investors. So a second tranche later this year expected to see SoftBank contribute another 22 billion along with 7 plus billion from other investors. So according to Reuters, OpenAI though must first finalize its transition to a for profit entity by the end of 2025 to secure the full 40 billion dollar funding round led by SoftBank. So that's huge. And failure to meet that deadline could result in SoftBank Reduc investment to only 20 billion, significantly impacting OpenAI's growth plan. So this funding round follows OpenAI's previous $6.6 billion raise in October of last year which was led by Thrive Capital and valued the company at $157 billion. So with this new round, OpenAI's valuation is projected to soar to 300 billion, showcasing its rapid ascent in the AI industry. So yeah, this one's obviously going to get very interesting with specifically Elon Musk and Xai seemingly doing everything it can to try to slow down OpenAI's plan to convert from a non profit, which it was originally set up 10 years ago as a non profit and they've been trying to transition to a for profit now for the better half of a year, but Elon Musk and some others are trying to delay their plans in doing so. So now the stakes are extremely high. We're talking $20 billion potentially that they could not receive if they do not transition to a for profit by this kind of end of year deadline. So wow, wow. I mean talk about, talk about high stakes, right? We all think that the work that we're doing on a day to day basis is high stakes. And don't get me wrong, it is right if you're saving lives, you know, helping people. But man, I'm glad that I'm not in the, you know, CFO seat over there at OpenAI. It's like, yeah, talk $20 billion in funding in the balance if you cannot complete this transition to a for profit in time. And that's according to reports. So yikes, I would not want to be in that role. Are you still running in circles trying to figure out how to actually grow your business with AI? Maybe your company has been tinkering with large language models for a year or more, but can't really get traction to find ROI on Gen AI. Hey, this is Jordan Wilson, host of this very podcast. Companies like Adobe, Microsoft and Nvidia have partnered with us because they trust our expertise in educating the masses around generative AI to get ahead. And some of the most innovative companies in the country hire us to help with their AI strategy and to train hundreds of their employees on how to use Gen AI. So whether you're looking for ChatGPT training for thousands or just need help building your front end AI strategy, you can partner with us too, just like some of the biggest companies in the world do. Go to your everydayai.com partner to get in contact with our team or you can just click on the partner section of our website. We'll help you stop running in those AI circles and help get your team ahead and built a straight path to ROI on Gen AI. Next. This little company that is a little behind in AI named Apple, right? They face so many, I mean they face class action lawsuits in the past couple of weeks because, you know, they've been promoting this Apple intelligence thing that doesn't really exist. Well now there's some new AI news from Apple and they're reportedly developing an AI powered doctor and revamped health app. So according to Bloomberg reports, Apple is advancing its healthcare technology with an AI powered doctor, a redesigned health app in a personalized health coach under the codenamed Project Mulberry. I don't know why they're always like Barry codenames, but I don't know. Anyways, Apple is creating an AI powered tool that will analyze health data from devices like the Apple Watch Watch to provide tailored healthcare recommendations such as dietary advice for users showing signs of high blood pressure. So the redesigned health app, which is right now will be unofficially named Health plus, will feature food tracking, a first for Apple, placing it in competition with platforms like MyFitnessPal and Noom. So the app may also act as a personal trainer by using iPhone's camera to access workout techniques and suggest improvements potentially integrating with Apple's Fitness plus service. So according to reports, Apple is collaborating with its in house physicians and plans to expand its team with specialists to produce educational content, possibly featuring a celebrity doctor to enhance engagement. That's just what we need, more celebrity doctors. So CEO Apple CEO Tim Cook has emphasized Apple's commitment to health and wellness for the better part of half a decade, calling it the company's quote unquote greatest contribution to mankind. We also had a story in our AI News that Matters segment last week that said Apple was reportedly trying to jam some AI powered cameras into its Apple Watch, into Apple AirPods, essentially trying to put cameras everywhere, right. Not just on your phone. And now this kind of might make a little bit more sense when we see that Apple is really just trying to prep an AI doctor and really just try to make a even bigger investment into the AI health space. Live stream audience, what do you feel about this? Right? Do you want AI powered cameras on your Apple Watch or on your AirPods or, you know, do you want all of this AI technology on every single other thing? For me, I'm torn, right. I have an Apple watch, I have AirPods. I don't want to want cameras in them because I think that's super weird and probably intrusive. But I also, like, I love this idea of an AI doctor. Right. So, you know, that's, it's, it's one of these things that we constantly have to grapple with, you know, not just as consumers but as business leaders. Right. Like how much of our data do we want to offer up for the sake of, you know, for the sake of increased productivity, for the sake of potentially increased revenue, for the sake of increased health. Right. It's, it's interesting. It's something I mean, and always personally grappling with. Right. Marie says seems like Apple is scrambling for a win. Astute observation there, Marie. Yeah. Apple has been, you know, getting crushed in the essentially the large language model race bringing artificial intelligence features to its iPhone, which has been in abysmal rollout. I do think there has to be some sort of movie made one day about how Apple potentially lost trillions of dollars in market cap by screwing up Apple Apple intelligence so badly. So, yeah, it should, it should be interesting. Yeah. Most people are just saying no, you know, Richard from YouTube says bring back the oxygen level. Max from LinkedIn says AI doctor is cool. More cameras, I don't know. Yeah, same thing, right? Yeah. Like we all want the capabilities, but yeah, do we all want, you know, 10 cameras, right. If you have a smart ring, do you want a camera on that? Do you want an AI powered camera in your tennis shoes? News, I don't know. All right, here's the multi billion dollar story that really no one is talking about. Yeah, there was so much AI news this week. Some of these stories just got no real attention. But Elon Musk's AX AI has acquired Twitter or Axe for $33 billion to strengthen its company X. AI. Yeah, confusing, right? So Elon Musk's AI company has acquired Twitter, now known as X, which is also his company. So this was a little bit more of kind of some, some paperwork and more of, you know, kind of some official acquisition, you know, legalese. But, you know, essentially now Elon Musk's AI company is the official new owner of the social media platform Axe, formerly known as Twitter. So Elon Musk's artificial intelligence company Xai has purchased Axed, formerly Twitter in a 45 billion dollar all stock deal which includes 12 billion in debt. So the social media platform itself is valued at $33 billion in this transaction, according to Reuters, which, you know, I believe Elon Musk originally acquired Twitter for $44 billion, but we saw reports previously that the valuation had dropped to about $10 billion. So this was actually some, at least for me, some, some personally shocking, you know, piece of reporting here that we had saw the valuation from the original price of 44 billion, we saw reports that it was valued, you know, earlier this year at only 10 billion. Yet in this acquisition, which is kind of an acquisition, kind of not, but definitely still an acquisition. I know it's weird, but we saw it valued at $33 billion. So the deal though, positions Musk to merge resources between XAI and X, consolidating data computing infrastructure, distribution channels and talent to enhance AI development. So Musk emphasized that integrating X with XAI will training data for its chatbot Grok, potentially accelerating advancements in AI models and capabilities. So this acquisition follows Xai's recent funding success where it raised $10 billion at a valuation of $75 billion, solidifying its position as a key competitor to OpenAI and other global AI firms. So the merger could allow X to serve as a distribution platform for xai's products while leveraging real time user data from X to improve AI training capabilities. My gosh. Too many, too many X's. I still just like calling it Twitter. To bolster AI capabilities, XAI has been expanding its infrastructure. Its Memphis based supercomputer cluster called Colossus, is reportedly the largest in the world and is designed to train next generation AI models like Grok 3. I don't know, you guys want a hot take. I know this is a new show, but it's going to take more than tens of billions of dollars and you know, all these acquisitions for anyone to actually use X AI or GROK products. So I don't necessarily understand this. Right. The problem with this, this kind of, this merger and this, you know, this beautiful, you know, partnership between Xai, Grok and Twitter is. Well, Twitter has been shown or you know, axe, whatever you want to call it in many recent studies as the number one worst platform for disinformation, for bot activities, et cetera. So when one of the biggest concerns for many companies when it comes to using large language models, it's truthfulness. It is, you know, having trust in the models that they're using. So, you know, I've been saying this on the record for, I don't know, since Grok 1 was a thing that no one's going to use, doesn't matter how powerful it is. Right. We saw Grok 3 released earlier last month. You know, from a benchmarks perspective, it did fairly well. Yet I literally do not know a single enterprise custom company that is using it as its main large language model driver, nor do I think any enterprise company should. Right. It's not yet available via the API, so you can only use it, you know, @grok.com or you know, within the Twitter platform. So I'm not really sure what the long term plan is here for profitability from Elon, Musk and Xai. Yeah, that's me. I just don't think it is a smart idea for, for enterprise companies to be using a model that now is even more tightly ingrained with the social media platform that has one of the highest instances of misinformation, disinformation in bot activities and that's been shown across multiple studies. So, you know, do with that as you may. You know, Marie says trust plus transparency equals trust equals more customers. Yeah, good, good equation there. But yeah, I mean, without more trust and transparency in your trading data, people aren't going to want to use it. So yeah, I would still, from an enterprise perspective, I wouldn't touch Grok or xai with a 100 foot pole. I don't care about the $33 billion valuation. All right, more large language model news. So. So OpenAI has updated their previous flagship model, GPT4O and it has jumped up to the number two spot in the LM arena leaderboards. So, yeah, another small story that's actually pretty big. So OpenAI announced an updated version of its GPT4O model, highlighting major improvements in coding, instruction following and creative capabilities release. So most impressive though is that this updated version of GPT4O shot up on the LM arena leaderboards from fifth place to second place, only trailing the just released an Extremely impressive Gemini 2.5 Pro from Google. So also you might be wondering, yes, that means that the now updated GPT4O model has surpassed OpenAI's newest model, which is GPT 4.5, at least when it comes to head to head human preferences. So that is what the LM arena measures. I think it's an extremely important kind of leaderboard or measurement to talk about all these large language models, especially recently. I think they're overfit. Right? So what that means is I think that the engineers building these models, especially in 2023 and 2024, really tweaked them to perform really well on certain industry benchmarks, but they weren't necessarily recognized by humans as being better. So I think it's important to look at both traditional benchmarks and these ELO scores from LM arena, which is essentially, you know, you put in one prompt, you see two outputs, you don't know who the outputs are from, and you choose which one is better. So it is the, the blind taste test, Pepsi versus Coke. But this new version, the updated version of GPT4O has shot up and it's actually really, really good. So the update has been described as making the AI more intuitive and flexible, with some users referring to its responses as unhinged due to its ability to generate less restricted content. So yeah, OpenAI CEO Sam Altman in the announcement said the new version of GPT4O is particularly good at coding, instruction, following and freedom. So yeah, there's kind of this like low key unhinged mode that a lot of people are talking about. I kind of tested it out a little bit as well, but the guardrails on the new GPT4O are down a little bit. That's not talking necessarily about the new image model, which is actually, you know, what became a little more restrictive over the weekend, which we're going to be talking about soon. But with its actual base GPT4O model, it's actually a little less restrictive. Also, OpenAI bless up, they talked about some of the updates. Better at following detailed instructions, improved capabilities to tackle complex technical and coding problems, improved intuition and creativity, and bless up. Finally, fewer emojis by default. So maybe we can stop Seeing all these social media posts and emails that have like 42 emojis. Thank you. I know I use emojis sometimes sparingly, but I'm tired at like one point on my screen seeing like a dozen emojis. It's just like y'. All. So thank you, OpenAI, for getting rid of that, since this is how everyone just writes now. Anyways. All right, so the next piece of AI news, also about OpenAI, but on the legal side. So a federal judge has ruled that the New York Times, his lawsuit back from December 2023 against OpenAI can advance. So the lawsuit accuses OpenAI of siphoning the Times articles and actually millions of them, allegedly without permission or payment to train its GPT models in violation of copyright laws. So that is according the accusations, according to the New York Times. So attorneys for the Times claim the newspaper's content is one of the large sources of copyrighted text used to build ChatGPT, alleging the AI sometimes regurgitates articles verbatim. So the judge rejected OpenAI's request to dismiss the case, but at least in a small victory to OpenAI, narrowed the scope, allowing the primary copyright infringement claims to go forward while promising a detailed opinion soon. So OpenAI argues that its data collection practices are protected by, quote, unquote, fair use, citing research and innovation. But the Times claims its reporting was neither transformed nor lawfully reused. A key legal issue is this term of market substitution, with publishers fearing chatbots summarizing news could divert readers away from their websites, which obviously impacts their ad revenue. OpenAI claims the Times manipulated prompts to force verbatim outputs, which it says are atypical for regular users of ChatGPT. Evidence gathering and pre trial hearings will now proceed, with depositions expected to remain confidential while public disputes over evidence are settled. This one could be huge, y'. All. I've been talking about this a lot since December of 2023. Another small detail of this whole case is the New York Times literally asked for the GPT technology to be destroyed in its lawsuit. Right. That's not an exaggeration. That is something they actually asked for because they said, okay, well, the New York Times and all of our paid articles were one of the big pieces that was, you know, in this data set. So I don't think that'll happen, but it's going to be interesting to see what actually happens here. It could be a monumental kind of ruling that could impact millions, millions of businesses worldwide. Right. Because so many people now, hundreds of millions of business professionals like us are using AI models in their day to day work. Right. And it's not just ChatGPT because there's probably thousands of other AI apps that use the GPT technology. So in the, I think very rare case, you know, I, I don't want to put percentages on it, but it has to be less than a 1% chance that it's, they say, okay, the GPT technology has to be destroyed because I don't even know if that's feasible. It's already out in the wild. Right. It's already been used to distill other models, so you can't exactly, you know, just take it away. But I mean, this would be a huge impact to everyone, especially in the US So it's definitely one to keep an eye on. All right. Another thing to keep an eye on is this new study from Anthropic. So researchers at Anthropic have made a significant breakthrough in understanding how large language models work, potentially paving the way for safer, more reliable AI systems. So in a new, rich, newly released study, Anthropic created a new tool akin to an FMRI scan for AI, enabling researchers to trace how large language models process information and make decisions. So yeah, this is pretty cool. It's really interesting. If you understand, if you want to better understand how large language models work, I highly recommend you go read this study from Anthropic. We shared about it in our newsletter last, last week. So this new tool that they developed, that they detailed in the study is called a cross layer transcoder or clt and it identifies circuits of neurons linked to specific reasoning tasks, which offers new insights into the internal logic of AI models. So yeah, essentially generative AI and large language models, I mean people largely call them and think of them as a black box. Right? Right. People don't necessarily understand how they work. So this new paper from Anthropic, very, very telling. So the study also revealed that multilingual models like Anthropic's own quad share conceptual reasoning across languages. So instead of reasoning separately for each language, the model uses shared neural circuits to process universal concepts and translate the output into the desired language. That's wild to think about, right? It's not that they have created their own language, but this large language model. According to this new research from Anthropic, they're essentially saying when it's thinking in a multi language capacity, it's not like, oh, so let's say it's using English, Spanish and French for whatever reason, maybe you're working on translations, it's not each time translating it back and forth, but instead it's using these kind of neural circuits to process universal concepts. It is doing the work almost outside of normal language capabilities, which is also pretty weird and wild to think about. So a little bit more about this CLT approach. So it allows researchers to trace reasoning processes across layers of the neural network. So this could improve auditing AI systems, which is huge for safety concerns, and help develop better guardrails to prevent hallucinations, jailbreaks, or just erroneous outputs. Right now, though, this technique has limitations, including its inability to capture dynamic attention shifts in large language models. So attention mechanisms play a crucial role in how models prioritize input while generating responses, which this CLT does not fully address. So scaling the method for longer prompts remains a challenge as well. Analyzing circuits for prompts of even tens of words, not even when we're talking about hundreds or thousands or millions of words, but analyzing circuits for prompts of just, just tens of words requires several hours of expert work, raising questions about the practicality for more complex outputs of using this kind of CLT methodology. But this breakthrough could encourage businesses to adapt AI more confidently by making the inner workings of large language models more transparent. Companies may feel safer integrating AI into their operations. Operations. Yeah. Sandra says, blowing my mind. Yeah, same like I've, I've read this multiple times and each time I'm just kind of silent and I'm thinking like, huh, this is weird, right? It's, it's like the more you use large language models, right. And I, like, I remember using the very early, you know, versions. Pre chat GPT versions of, you know, GPT3 pre technology in early Bert. Right. Pre, you know, Gemini in, in seeing how much they've improved and seeing these reasoning models now and then, reading this study, it was really eye opening. I'll just say that, right. I don't want to take away all the, all the goodies. I'm going to read it yourself. So, yeah, we'll make sure to link it again in today's newsletter. So if you haven't already, make sure you go sign up for that@your everydayai.com. all right? Undoubtedly, the most talked about thing, at least on the Internet this week in AI news was the new OpenAI GPT4O image generation. Yes, the new name. So Dall? E is dead. There is. Well, technically, Dolly is still around in some of the older models, if you really want to go use it. I've never really used Dall? E. It's not good at anything but OpenAI has officially launched the new native image generation capabilities of ITS multi model GPT4O model for chat GPT users, marking a major milestone in the AI technology. So the name of this is just 4O image generation. All right, I'm sure some unofficial name will catch fire and people will be calling it that, but right now, like I said, you know, this isn't a new version of $, this isn't Sora photo right now. It's just called 4.0image generation and it is bonkers. So their new multimodal GPT4O model is now capable of handling text, code and images. It is currently available for paid users. Originally it was supposed to be released to free users as well, but over the weekend the company announced that access to free users would be delayed and they also instituted rate limits on paid accounts for image generation. As they said, the new feature was quote UNQUOTE Melting their GPUs due to biblical demand. So the new feature went mega viral as the entire Internet was scrambling to create Studio Ghibli style visuals. Right. Which I don't necessarily understand, fan, right, but it's this kind of anime esque style and everyone's, you know, taking their family photos and up, you know, uploading them and you know, getting these Studio Ghibli outputs. I, I didn't do it. I don't care about that kind of stuff. But I mean literally every single, you know, AI media outlet, every single social media, even LinkedIn was being just overrun by everything Studio Ghibli from this new OpenAI's 4.0 image generation. So unlike the older Dall E3 model, GPT4O's image generation is integrated directly into the same system. So yeah, GPT4O, the O is for Omni. So it is a true multimodal large language model. Right. Whereas before how it worked when it was just GPT4 or GPT4 Turbo, even when we're talking about text to speech or voice, there was technically multiple models under the hood, right? So now with GPT 4.0, now that we have the new image generation model, it's all under this Omni model, making it more accurate in interpreting prompts and producing detailed lifelike images. So yeah, I'm curious, live stream audience, did any of you use this over the weekend? I'd love to know your thoughts. I'm personally blown away. But a couple more details so users can refine images in real time. That's huge. Through conversational edits achieving higher precision and flexibility compared to previous models. Key features of this new 4.0 image generation include accurate text rendering within images. That's big because so many, aside from models like Ideogram, which does great with text, earlier versions of things like Mid Journey, obviously Dall E, Google's earlier Imagine AI photo apps, they all really struggled with text. And that's what a lot of people, you know, sometimes want to do. Whether they want to create a photo with text on it or if they want to create infographics, if they want to create, you know, things with branding in logos and having words, you know, mixed in these images. I mean, it was pretty abysmal, you know, prior to the end of 2024. But this new model, the new 4.0 image generation is extremely, extremely good at working with text. And that really opens up the capabilities because now it can handle complex prompts, it can support different artistic styles, right? But now there's some great practical applications for it, right? So things obviously like marketing with social media, graphics, invitations, recipes, education, creating science hand scientific diagrams, infographics, game development with consistent character design, right? Things with, you know, consistent branding, you know, with logos and advertisements. So it's, it's really impressive. The other thing is it really has improved contextual understanding. So you can, as an example, upload 10 different photos and say, hey, mix these together, right? You can upload an image of a backdrop, you can upload, you know, images of three people, you can upload, upload, you know, six, you know, six products and say, hey, combine all these and it does it and it looks again, this is an early version, but it is extremely impressive. And y', all, I am, I am someone, I am not easily impressed, right? Yes, I, I cover AI every day. I've done 500 episodes. I've been lucky enough to, you know, partner with big brands like, like Microsoft, you know, Adobe and others, right? So I, I get to, you use a lot of these AI tools even before they publicly released and I'm not easily impressed, if I'm being honest, very impressed with this new GPT4O image generation right now. There's limitations still. It's obviously not perfect. It's widely been reported, there's cropping issues, aspect ratio issues, challenges with non Latin based fonts and scripts, and still difficult difficulty retaining details in small text. OpenAI CEO Sam Altman did describe the launch as a quote, unquote new high water mark for creative freedom, with the company actively refining the model based on user feedback. So this release positions OpenAI to compete with the new and also extremely impressive multimodal capabilities of Google Gemini's 2 flash model which introduced similar but not as robust multimodal capabilities earlier this month. Yeah, Pedro. Yeah, I like this. Pedro just says it's brutally good. Douglas. What's up Douglas? Douglas said, I uploaded my headshot and had it made a South park version of it. Results were spot on. So yeah, I think there's a lot of fun, you know, cutesy, you know, things that you can do with this model, right? But as someone that has, has worked in, you know, martech and comms for, for 20 years, right. I was, I was lucky enough to spend a good chunk of my career working with, you know, not just the marketing and comms departments from Nike and Jordan brand, but working with dozens of the largest creative agencies in the world, right? So I really have seen a lot of behind the scenes of how big brands, you know, essentially create their marketing, create their advertisements. And y', all, I cannot underestimate what this does right now. Anyone with a, with a 20amonth chat GPT plus account and anyone that knows how to work a computer can literally produce advertisements and marketing campaigns. Campaigns that are on par, and I kid you not, that are on par with the biggest multi billion dollar advertising and marketing companies in the world. Right? It's been very impressive like single person studios just over the weekend since this has been released, have been releasing some behind the scenes of how they're creating these campaigns and it is, they are mind bogglingly good. Good, right? Like especially I think for product advertisements, things that are you know, obviously very visual, but this new model's ability to just accurately, you know, take multiple images that you upload, work with text, but also work with the context window. That's the thing that most people aren't taking advantage of. I think right now, right when I was just playing around with this, I uploaded, you know, an entire transcript of one of my interviews from, from last week and I said hey, make me an infographic graphic that explains some of these more complex topics, right? And it did it right? Whereas previously if you're working with something like you know, Mid Journey or Stable Diffusion or some of these other diffusion based AI models, that's not how it works. You kind of had to talk in you know, prompt language and you know, describe things to a T. No, you can just dump a bunch of context, just a bunch of texts and say hey, make me something right? And if it's not good enough, you can talk to it it in natural language. That's the, the, the, the, the, the promise here and the Power of this new update, extremely, extremely impressive. Sandra is saying, can you do a show showing us how to do that? I don't know, do you guys want that? Let me know yes or no live stream audience. If you want more of a behind the scenes, you know how to do all this. Like I said, my background, I've done this. I know how this works, works. I'm personally blown away. I don't know if, if you guys want something like that, let me know here in the, you know, in the live stream. Just, you know, say yes, do a visual if, you know, if you're listening on the podcast, I always keep my email, my LinkedIn, so you can just reach out to me as well. All right, our last story of the week. I saved, I think the best for last, even though people weren't talking about this release from Google Gemini, just because of, you know, the, the power in the kind of the viral nature of open GPT4O image generation. But literally the world's most powerful large language model was released this week and hardly no one's talking about it. It doesn't make sense. But Google has introduced Gemini 2.5, its most advanced AI model yet. So Gemini 2.5 features a massive 1 million token context window, enabling it to process extensive Data sets, including 10 text, audio, images, video and even code repositories. So an upgrade to 2 million tokens is expected soon, further expanding its capabilities. So if you're not super technical, you might be saying like, okay, what does this mean in theory? Let's say you have a PDF of a book, Gemini 2.5, you can copy and paste, you can drop that thing in there and it's going to be able to go through and answer any questions you have. Even great models like ChatGPT, you know, quad has a, has a decent, you know, or has had a decent 100,000 context window. But a lot of times the more you work with a large language model, right, it might start off really great and it's like, hey, this is fantastic. This large language model is remembering everything and the more you use it, then it starts to get a little dumb. That's because a lot of the times the, some of the information that you share or if you're trying to refine a program prompt, it gets lost, right? Eventually it, it, it, you know that initial information that you share is outside of the context window. Which is why sometimes when you're using, you know, an AI chatbot, it starts out great and then it starts to just stink. It's because of the Context window. So this is Extremely impressive, a 1 million token context window for Gemini 2.5 Pro. Also, it instantly took the number one spot on the LM arena leaderboard board and it was not even close, Right. I believe it was almost a 40 point lead, so to speak in ELO scores when normally when a new, you know, large language model gets dropped and you know, oh, it's the best model in the LM arena, it might be by like 1 or 2 points, maybe 3. Right. The new Gemini 2.5 model, Gemini 2.5 Pro came in at almost 40 points higher than its nearest competitor, which is now the updated version of GPT4O from OpenAI. Also maybe even more important news related to this. Over the weekend Google again silently Google stopped, which I am impressed with, right? You know they had a bad rollout originally of Bard. I won't get into that. I've covered that a lot. But over the last six months I love what Google is doing. They're not, you know, investing heavily into the marketing. They're not making this a big show. They're just shipping, they're just shipping huge releases, shipping impressive updates. And another impressive update is over the weekend Google also made this available to free users. So like you don't even have to go into AI studio. So Google, you know, they have their AI studio which is more for developers and then they're kind of front end Google Gemini chatbot. So yeah, you can use now because previously for the first year or so of Google Gemini, they didn't put their most powerful models in Google Gemini. You had to go inside Google's AI studio, which does not protect your data unfortunately. But Google Gemini does on the front end if you are a paid users. But now you can access Gemini 2.5 Pro even if you are a free user. Also what's very important, the model now has a thinking mode. So it is more of a hybrid hybrid model, Gemini 2.5 Pro, because it allows the model to reason through its thought process before delivering responses, potentially again inching closer and closer to the ever moving goalposts of artificial general intelligence or AGI. So obviously aside from ELO scores or human preferences which Google Gemini 2.5 cleaned up on, it also did fantastically, not surprisingly on all of the normal benchmarks, including the newest kind of trending benchmark which is Humanities Last exam, which is a challenging data set designed to test the limits of human like reasoning and knowledge. So the previous high score from a large language model was OpenAI's O3 mini that had a 14% and a deep seq R1 had an 8.6%. Yet the new Gemini 2.5 Pro 18% on that. So more than double deep seq R1 and comfortably ahead of OpenAI's 03. So Gemini 2.5 Pro, like I said, is now available for both everyday users on the front end of Gemini Chatbot, as well as developers and enterprises inside Google AI Studio. And a rollout to Vertex AI is planned in the coming weeks. So according to Google, the model's advancements in reasoning, personalization and coding could significantly impact industries ranging from software development to research, offering businesses and developers tools to innovate faster and more effectively. One of the things that I was personally most impressed by gemini 2.5 pro is its ability to one shot anything when it comes to coding software development. Extremely impressive. Not that you ever should do anything one shot, right? You should always go back and refine something. But you know, I made. What did I make? Just just to see its ability, you know, I made a side runner, you know, 2D game where it's, you know, Chicago Deep dish pizza is running through the city or something like that in one shot and it got it right. It was extremely impressive. But I really think we should be paying attention to Gemini 2.5. All right, that's it, y'. All. Let me quickly recap the biggest AI news stories that matter for the week. So first, Microso released some pretty groundbreaking new agentic capabilities in Copilot Studio. So no code being able to just talk to Copilot Studio, use its new reasoning model and deterministic capabilities. Next. OpenAI is reportedly nearing a $40 billion funding round led by SoftBank, though it is determined or it could be less than that if OpenAI is not successfully able to convert from a nonprofit profit to a for profit by the end of the year, according to reports, Apple is reportedly developing an AI powered doctor and revamped health app. Elon Musk's XAI acquired the social media platform X formerly known as Twitter for $33 billion valuation, which is technically $45 billion in stock because it included $12 billion in debt. OpenAI updated its GPT4O model, which shot it up, actually passed GPT 4.5 into second place on the LM arena board. A judge A federal judge has allowed the New York Times copyright lawsuit against OpenAI to proceed. A new breakthrough study from Anthropic was released that helps everyone better understand the black box of large language models going over its new tool and technology called a a cross layer transcoder or CLT. OpenAI released their new very viral GPT4O image generation. And then, last but not least, we have the world's most powerful AI model that was also released this week. My gosh, that was a lot to cover in a very short amount of time, y'. All. The AI world is straight up in fuego. So much going on. So if you thought AI was hitting a wall, if you thought capabilities were near the ceiling, not even close. Another exciting week in AI and I hope this was helpful. If it was, please let me know if you're listening on the podcast. I'd appreciate if you hit that little subscribe button, go find it, right? If you're listening on Spotify or Apple, would appreciate you leaving us a review as well. If you're listening on social media, let me know what you want to hear more of. But also click that repost button if this was helpful. You know, a lot of people tell me Everyday AI is their cheat code. I'm like, yo, don't keep it to yourself. Share this with someone, right? I'd appreciate it if you did that. Also, I'd appreciate if you tune in tomorrow and every day for more Everyday AI. Thanks, y'. All.

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