EP 542: Apple’s controversial AI study, Google’s new model and more AI News That Matters

This is the Everyday AI Show, the everyday podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business, and everyday life. Why is Anthropic in hot water with Reddit? Will OpenAI's ChatGPT become the de facto business AI tool? Did Apple make a huge mistake in its buzzworthy AI study that it just released on large reasoning models? And why the heck did Google release a brand new version of Google Gemini when it was already on top? Yeah, a lot happening as always this week in the world of AI news. And if you missed anything or if you're just spending so much time wondering what all of these updates mean for you and your company or your department. Don't spend hours a day doing that. Instead, just spend your Mondays with us here on Everyday AI as we break down the AI news that matters. All right, what's going on, y'all? My name is Jordan Wilson and welcome to Everyday AI. This is your daily live stream podcast and free daily newsletter Helping us all not just keep up with AI, but how we can use it to leverage, uh, all this new information, all this new technology to grow your company and career. So if that's what you are trying to do, you are definitely in the right place. It starts here on the unedited, unscripted daily livestream, but you finish, you actually grow your company by reading our newsletter. It's for free on our website at youreverydayai.com. So make sure you go there and sign up. Make sure you can go check out also more than 400 and, uh, 40 now back episodes on our website, all for free, categorized. So whatever you're trying to learn to get ahead, to get that edge, it's already on our website. We've already probably interviewed a world leader in that field. So make sure you go check that out. All right. Enough chitchat. Like I said, everything from Anthropic being in trouble with Reddit to OpenAI's pretty big new connectors that I think are going to change how companies use AI. I think this new study from Apple got a lot of things wrong. And Google, yeah, we have a new version of Gemini 2.5 Pro. All right. Let's get into the AI news that matters for this week. What's up, livestream audience? Good to see you. Everyone from Al joining us on YouTube from Scotland. Georgie joining us from Jamaica. Kimberly on the LinkedIn machine from New York City. Jay woke up somehow in West Virginia. Dr. Harvey Castro. Thanks, everyone, for joining us. All right, let's start first. Probably the most recent update in terms of it's only been a couple of hours, but OpenAI has rolled out a major new advanced voice mode upgrade. So OpenAI has launched a significant upgrade to its advanced voice mode in ChatGPT, which is now available to all paid users across platforms, according to the company. So the revamped voice mode delivers much more natural speech with improved annotation, realistic cadence, and expressiveness. That can capture emotions like empathy and sarcasm. So users can now access real-time language translation as well. That one's pretty cool by simply requesting it, allowing continuous two-way translation throughout conversations. So that's an enhancement aimed at, you know, travelers, global professionals. But that one's pretty big, right? By just saying like, hey, act as a translator, you're going to hear, two different people speaking two different languages, and the new advanced voice mode, well, if it works correctly, will take care of the rest. So this new update builds on earlier improvements to accents and interruption reduction, making voice mode more reliable for diverse users. So these new features are designed to make interactions feel more human and seamless and a little less robotic, which could benefit anyone relying on voice AI for communication. So I gave this a try. One thing I think this does a little bit better on is starting out in advanced voice mode. One thing that I've, especially when I'm on the phone, one thing I never really know if advanced voice mode is like ready to go. So this new update I think helps with that just a little bit, kind of that first response. That's just my take right now. OpenAI did also note that there's some limitations, including occasional drops in audio quality and some rare instances of unintended sounds. So not quite as eerie as the one last year, right, where the advanced voice mode was like saying, help, right? Like, help, get me out of there. So nothing like that. But OpenAI did say that this isn't perfect and there's probably going to be some mistakes. So livestream audience, if you guys tested the new advanced voice mode out. And I think probably I haven't actually done a lot of kind of coverage on the show of these different voice modes, right? I think I did the original one on a show here. I think one of the reasons is it's sometimes hard to capture, to capture that on the phone. So maybe I'll just have to like grab my wife's phone because I use I use my phone to shoot the video here for the livestream. So yeah, let me know if I should do the new advanced voice mode. Google Live is obviously really good. Perplexity has theirs. I just don't know if our audience, podcast people as well, I always put my information in the show notes. Let me know if that's something you'd want to see, kind of a voice-off battle, or at least going over what these voice modes can and can't do. Let me know if that's something you want to see. Dr. Harvey Castro says ElevenLabs and Hume AI are better at emotional intelligence. Yeah, we did talk about this on the show last week on the AI News That Matters. ElevenLabs has their V3. I don't know. I'd say this new version, maybe not. I'd say obviously the ElevenLabs and Hume maybe 4 days ago were better in this regard. I don't know. I'd say right now this new advanced voice mode update that just rolled out hours ago, would at least put OpenAI in the, you know, either 1A or 1B conversation where I think maybe before there was a little bit of a drop-off in terms of quality. Cecilia says, yeah, do a voice-off show. Brian says it as well. Al here on the YouTube machine says, would like a feature where it could just listen and transcribe. Yes, my gosh, I would love that, right? Which is, you know, it's not that big of a deal. You know, generally I would just use a third-party tool, But I would love that as well to just be like, yo, just don't say anything. I'm just going to, you know, word vomit here for 15 minutes. I've tried it before and a lot of times it just cuts out. So yeah, Al, I like that idea, you know, just to be like, have a translation mode, but just to be able to talk to advanced voice mode for that. I think that would be cool. All right. Our next piece of AI news. Anthropic's in trouble. Well, because some of the other big companies like OpenAI and Google have paid tens of millions of dollars to partner with Reddit for their data. And apparently, according to a new lawsuit, Anthropic is just trying to grab it all for free. So Reddit has filed a lawsuit against Anthropic in California Superior Court, accusing the AI startup of illegally scraping Reddit user comments to train its Claude chatbots. So the lawsuit claims that Anthropic Anthropic used automated bots to collect content from Reddit despite explicit requests not to and without user consent, raising fresh concerns over privacy and data rights as AI companies race to improve their models. So unlike other lawsuits targeting copyright infringement, Reddit's case focuses on a breach of its terms of use and claims Anthropic's actions accounts to an unfair competition. So like I said, Reddit has pretty lucrative licensing agreements right now with OpenAI and Google and other companies that pay for access to its data data, enabling the platform to enforce privacy protections and user rights. So yeah, like when you are using Reddit, you're essentially being like, yo, yeah, I'm giving Reddit permission to give this data to OpenAI and Google to train their models. And these are agreements that helped Reddit prepare for its public stock market debut last year. So Infropix CEO and researchers have previously documented the value of Reddit's subject matter forums for AI training, and the company maintains its use of web data is lawful and essential for developing language models. So this lawsuit highlights growing tensions between the content platforms and AI developers, underscoring the stakes for companies relying on user-generated content and the potential impact of how publicly available data may be used or restricted in future AI advancements. So it's no secret how valuable Reddit data actually is. Right. So many times, if you're looking at the sources of information, when you're asking an AI chatbot a question, so many times it comes from Reddit. You could actually make the argument that Reddit, aside from, you know, maybe a source like Wikipedia, you can make a, you can make a claim that Reddit is potentially one of the most, or if not the most important single website for training data. One of the reasons is a lot of the information that, you know, these, these AI, uh, labs kind of just scrape on the open internet are available in kind of like there's redundancy, right? Like even with Wikipedia, right? A lot of that information, uh, especially when it's factual, exists in a handful or dozens or hundreds of different sources. Reddit, not so much because these are individual, a lot of times subject matter experts sharing their expertise, right? If you don't know a ton about Reddit, Reddit has actually been a huge part of many growing organizations' content strategy. So, you know, whether small business entrepreneurs, big business will put out original helpful content on Reddit, either asking or answering people's questions or just, you know, starting topics on, you know, news developments, etc. There's actually been a lot of companies that literally exclusively post on Reddit and don't even post on their company blog just because Reddit is so highly trafficked. So this one, might be, at least for me, the second or third most interesting kind of AI lawsuits to keep an eye on outside of the New York Times versus OpenAI and Microsoft. Because this one is huge just because of the value of the data. Again, I would even venture to say Reddit data is more valuable ultimately than data from the New York Times. That pains me as a former journalist to say, but so much of what's in the New York Times is available on dozens of other news publications, whereas a lot of time data on Reddit is exclusive to Reddit. And, you know, sometimes it's more of the nuance and human expertise that really helps make these large language models better and more capable. So, yeah, Marie saying Anthropic scraping the internet. What? So what else is new? Yeah, Reddit data is also all over Perplexity. It's everywhere. Right. And obviously people write about Reddit data and source and cite Reddit data on their own websites and other websites as well. You know, so there may be be some, some workarounds or technical loopholes on that. And this is obviously extremely hard to police, but it is one that we should all be keeping an eye on. All right, next piece of AI news seems small, actually big. ChatGPT and OpenAI making a huge play in the business sphere here with its new connectors for paid users, as well as a new ChatGPT meeting recorder. So OpenAI has introduced a new record feature in ChatGPT Teams for macOS, letting users record, transcribe, and summarize meetings on voice notes directly within the app. They've also released their new cloud connectors, which I'll talk about here in a minute. But the new record tool can transcribe up to 120 minutes per session, and it can turn audio into editable summaries and generate emails, project plans, or even code from conversations, positioning ChatGPT now as a new competitor to companies such as Otter AI or Zoom's transcription features. The OpenAI update also brings cloud connectors, and this one is big for Google Drive, OneDrive, Dropbox, Box, and SharePoint, allowing ChatGPT Business users to search and analyze documents from these platforms while respecting existing user positions, permissions. Sorry. So I did kind of a show on this, but it was technically on Claude's version of this. So if you scroll back a couple of episodes to episode 539, that show was the one Claude, the one new Claude feature that changes knowledge work and how to use it. And actually in that show I called, I'm like, ChatGPT, should be releasing this feature any day now. And funny enough, they announced it later that day. But this is pretty big. And I'm not saying that RAG is dead, right? So traditional retrieval augmented generation. And you might be wondering like, okay, what the heck is this and why is this actually important? Well, let's look at some of these connectors that I have on screen for our live stream audience. So I mentioned things like, you know, Google Drive, Gmail, I mean, Google Calendar, SharePoint, Outlook, Teams. One I'm excited to try is HubSpot, right? Being able to chat with your dynamic data is huge. The downside, at least on the OpenAI side, and maybe one reason that Anthropic's Claude still has an advantage, at least in connecting to this enterprise user data, is because right now, at least in ChatGPT, it's only available in deep research mode. So you might have to you know, wait anywhere from 3 to 15 minutes and you can select which of your connectors that you want OpenAI's Deep Research to go through. So I don't think that's necessarily a bad thing because in almost everyone's experience, you have a lower likelihood of hallucinations when you do the Deep Research mode. It uses a more powerful tool. The last we heard from OpenAI, they actually use dual O3 modes. It's actually using two versions, two separate versions of their very powerful O3 model to go through and do different things. So this one, the connectors space is booming. And I called this last week. I said, you know, even though technically Anthropic beat everyone else, I said this is going to be rolling out to all the major labs. Obviously, you know, OpenAI responded like that, that day. This one's, this one's big, right? And like I said, I don't think this kills traditional RAG, right? So what that means is if you're asking let's say you're in a, in a marketing role at a huge logistics company, right? If you're talking to ChatGPT or Gemini or Claude or anything else, right, about, let's say, industry-specific news, you don't always have a ton of control. It might bring, it might bring in things from its own internal training data, which could be extremely outdated. It could be wrong. It could not have the level of expertise that you'd expect by being a subject matter expert and being a marketer in the logistics industry, right? Or it might browse the web. And that's again, roll the dice. So by having it first look at your data, that is huge. That is essentially, you know, the promise of retrieval augmented generation, which is, you know, companies, you know, 2 to 3 years ago spent millions of dollars essentially fine-tuning models with RAG, right? Creating these embeddings in their vector databases, you know, essentially creating their own version of a large language model, but that first and primarily used its own internal data, which was a very expensive and laborious process. And now we're getting that with a couple of clicks. Right. And this is one of the reasons, if I'm being honest, I was never pushing RAG super hard because I knew that this day would come. Right. Competing on the application layer is how companies like Google, OpenAI, and even Claude are going to compete in the long run. You know, as we talk about, like, you know, knowledge being commoditized, but also that large language models could largely just be swappable, like, right, replaceable. So I think how companies are ultimately going to connect is these deep and dynamic integrations with our dynamic data. So pretty, pretty big, pretty big news here. And yeah, livestream audience, let me know if you've tried these connectors at all. I've tried them. Very impressive. I'll probably be doing follow-up shows on this either later in June and July. There's so many new kind of areas of these large language models. It's difficult to even just understand how people are using them. And yes, I talk to people aside from just being on this livestream every day. I talk to businesses, you know, from small businesses, startups, Fortune 500 companies, huge companies doing tens of billions of dollars of revenue. I'm constantly talking with them or consulting. You know, they hire us to help them, you know, learn a large language model. So it is actually difficult right now over the last couple of weeks to even understand where the interest is. Right. So please reach out and let me even know what are you interested in learning about? All right. Our next piece of AI news. For some reason, Google has just woken up chosen to dominate even more because they released a new version of its Gemini 2.5 Pro model, even though their previous version of Gemini 2.5 Pro was already by far the most powerful and capable large language model. So Google has begun rolling out a preview of its upgraded Gemini 2.5 Pro model, which will be generally available in the coming weeks. So this new version is labeled 6/05 or June 5th, right? So it's been out for just a couple of days, not to be confused with their previous version, which was actually 5/06. I kind of wait, like, I kind of wish that Google would have like maybe waited a day or roll this out a day sooner because if you're dyslexic, you're probably going to see these as the same model and you're going to be like, wait, which is this the 06/05 or the 05/06? Regardless, it's showing significant improvements in coding benchmarks, challenging tests such as GPQA and even Humanities Last Exam, which is one of the most challenging kind of AI benchmarks for large language models that assesses math, science knowledge, and reasoning skills. So this new update also addresses user feedback about performance drops from their previous model outside of coding in Google Google promised improved style and structure for more creative and better formatted responses. And yeah, in terms of ELO, right, we talk about the LM Arena pretty often here on the show. This is where you can go in, you put in input, you put a prompt in, you get outputs from two different models. You don't know which one's which, you choose which one's better, and then you get an ELO score. And Gemini 2.5 Pro, the new version, the June 5th version, actually got a 24-point jump over its previous version. So now Google, their 2.5 Pro is number 1 and number 2 on the LM Arena board. So the model upgrade is available through the Gemini API or via Google AI Studio and Vertex AI. So pretty exciting. And if you remember when I covered Claude 4, what, what episode was that? If you want to go back in and listen to it, where, where was that? Here we go. Episode 534. This was on May 28th. When we talked about Claude 4, because one of the things that Anthropic really hung its hat on is, you know, all of their scores in software engineering, web development, etc. And I said, yeah, good luck with that, Anthropic, because that's going to last a whole maybe week or two until Google updates their Gemini 2.5 Pro. Sure enough, within about 10 days, you know, they wipe out at least external benchmarks that Anthropic's Claude had. Yeah, they're gone. They're gone. So Gemini 2.5 Pro on the LM Arena now holds the top mark in every single category. It's silly. It's absolutely silly. So, all right, let's take a quick break for words from our sponsors at Google. This podcast is supported by Google. Hey everyone, David here, one of the product leads for Google Gemini. Check out v03, our state-of-the-art AI video generation model, in the Gemini app, which lets you create high-quality 8-second videos with native audio generation. Try it with a Google AI Pro plan or get the highest access with the Ultra plan. Sign up at gemini.google to get started and show us what you create. All right. And thank you to our partners at Google for sponsoring the show. All right. Speaking of Google, our next piece of AI news, well, Chinese AI lab Deepseek is accused of using Google Gemini's data to train its powerful new updated R1 model. So Chinese lab Deepseek's newly released R1, and this is the May 28th version is making headlines for its strong performance on math and coding benchmarks. But some researchers suspect it was partly trained on data from Google Gemini's family of models. So developer Sam Paik and others have published evidence that DeepSeq's R10528 uses language and thought traces strikingly similar to Gemini 2.5. Pro, fueling speculation about data sourcing and model training ethics. And if you pay attention to the show, you know this is not Deepseek's first time under scrutiny for doing this exact same thing. As last December, its V3 model was observed identifying itself as ChatGPT, further raising concerns about unauthorized use of rival AI outputs. So OpenAI previously told the Financial Times that it found evidence that Deepseek had used distillation on OpenAI's models, which is a method that extracts training data from larger models. And Microsoft also flagged suspicious data exfiltration from OpenAI developer accounts affiliated with Deepseek in late 2024. So essentially, now you have pretty serious, at least whether it's accusations or you could say solid proof that Deepseek has distilled or, you know, kind of just borrowed from OpenAI, Microsoft, and Google to help train its data. So, you know, when you read all these stories about, oh, you know, Deepseek is the future of AI because they can train their models at a fraction of the cost. Well, according to reports and executives at these exact same companies, they're doing this because they're literally just distilling from the companies that are actually paying the money to create, train, fine-tune the models. So, yeah. Hey, where are you at, all you DeepSeq people? I'm pretty sure you were in the comments back in December saying how, hey, in a couple of months, OpenAI and Google are going to be irrelevant because DeepSeq can train models for 1/100th of the cost. Yeah, no, they can't. Go look at the semi-analysis report on that. I'm going to go pull up what show was this. I did a deep dive on Deepseek a couple of weeks after all the hoopla. So go listen to episode 460 on that. And I break down the artificial analysis report that essentially looked at Deepseek and they're like, wait, they did not train this model for 5.6 $6 million, which is like 5% or 2% of what it would actually cost to train. They actually broke down their actual cost. So if you want to know the truth on Deepseek, aside from this recent news that's, you know, there are some researchers are saying, yeah, they're just distilling from other models. Go listen to episode 460 if you want the deep dive. All right. Joe here saying won't touch Deepseek. Chinese. Government surveillance, uh, worm. Yeah. So if you're using Deepseek, FYI, via the API or on their website, you are sending all of the, any information that you upload, uh, straight to the Chinese government. So this isn't me being political or me doubting open source. I'm all for open source, uh, right? I'm all for open source, open weight models, but I don't know. Do you want to send all of your data if you're using the API, if you're using the online version? Straight to the Chinese government. That's up to you. Maybe you don't care. But yeah, I would definitely be cautious, especially for enterprises that aren't reading the fine print. Yeah, you should probably read the fine print on that one. All right. Our next piece of AI news, Anthropic in even more drama. It's been the week of drama for Anthropic after last week we saw, you know, over the last 2 weeks we saw a week of releases, right? We saw Claude 4. Their Opus and their Sonnets getting Claude 4 pretty big bumps. And then we saw their version of connectors called integrations. But now it's just all the drama because like we just talked about facing a pretty big lawsuit and consequential lawsuit from Reddit and now some drama or a potential breakup with Windsurf. So open, sorry, Anthropic has withdrawn nearly all access to its Claude 3.x model. So, you know, that's 3.5 and 3.7 models from Windsurf after reports surfaced that OpenAI is acquiring Windsurf for $3 billion. So Jared Kaplan, Anthropic's co-founder and chief science officer, confirmed the move was driven by a desire to avoid enabling a direct competitor to focus and to focus on lasting partnerships. Citing limited computing resources as a secondary factor. So WindSurf users— so if you don't know what WindSurf is, it's one of these kind of AI vibe coding platforms. It's much more than that. But if you had to put it into a category, it's a vibe coding platform like Cursor, right? So WindSurf users, including both their free and pro customers, lost direct cloud access with less than a week's notice and access now requires users to bring their own API key, while Gemini 2.5 Pro is being offered at a discounted price as an alternative. So Windsurf, formerly Codium, has criticized the decision from Anthropic as anti-industry and warned it could negatively impact many other companies reliant on AI model access. The timing suggests Anthropic wants to prevent a its Claude models from supporting soon-to-be OpenAI-owned rival and possibly to protect its proprietary data from leaking into competitors' ecosystems. So a lot of people online are losing their noodles on this and they're like, oh, this is such a terrible move from Anthropic. I don't know, my two cents is I don't blame Anthropic for this. I think it was in bad taste that they cut off access to these models with, I think they said, 5 days notice. Right. We've seen reports on this OpenAI acquisition on Windsurf now for 3 weeks. So, yes, maybe Anthropic needed to do its due diligence to independently kind of confirm this rumored or reported on acquisition and to clear things internally. But still, to do this with only 5 days, even though I understand and agree ultimately with their decision, to do it with only 5 days' notice is kind of bad form, right? Especially given the fact that Anthropic, I mean, they're really only future customer base, if I'm being honest, for the most part, is software developers, web developers, people doing agentic coding, and they're using tools like WinServ and Cursor for that. So I know this angered a big portion of their current customer base. So probably not a good move, at least on the optics from Anthropic, even though I agree with it. Y'all, Anthropic has like a PR problem, right? We talked about it last week, last week on the show, kind of with their, how they talked about, oh, we found all these problems with Claude 4. They're really bad. And then they deleted the tweet. Yeah. Bad. Internal, I don't understand how a company as big as Anthropic is essentially just abysmally bad. I don't even know that's a word, but they're just very, very bad at comms, right? It's, it's, I don't, I don't understand it because this is a simple Business 101, right? Don't, don't piss off your biggest user base. And they did by doing this, even though I think ultimately they made the right decision. You probably should have given at least a couple of weeks of notice. All right. Our next piece of AI news. Speaking of kind of hot takes, I might have one on this one tomorrow. So a new Apple research paper called The Illusion of Thinking argues that AI reasoning models offer only marginal improvements only over standard language models and often fail as tasks grow complex, challenging a central narrative in recent AI developments. So according to this Apple study, standard large language models outperform reasoning models on simple tasks, while both types collapse on highly complex problems, with reasoning models regressing as complexity increases, contradicting claims that chains of reasoning yield smarter AI. So this study highlights a critical vulnerability. Introducing small irrelevant changes to prompts can degrade model performance by up to 65%, revealing the model's reliance on pattern recognition rather than genuine logic or deductive reasoning. So Apple, in their study, found no evidence that current reasoning models perform true logical problem solving. Instead, they predict responses based on statistical patterns from their training data, casting doubt on the practical value of chain-of-thought outputs or these reasoning models. Critics have accused Apple of being short-sighted or self-interested, especially as the company's own AI products like Apple Intelligence and Siri 2.0 face AI challenges, but Apple maintains its focus on privacy-preserving, efficient on-device AI aligns better with real-world use cases. And the paper's conclusion that large-scale reasoning offers limited benefits also happens to coincide with Apple's public strategy of focusing on smaller, efficient on-device models, leading to accusations that the research is just marketing designed to justify their current position. The research exclusively used uses abstract logic puzzles with a single correct answer as its benchmark. This is a terrible study, ignoring the primary real-world applications of reasoning models, which often involve creative collaboration, coding, and drafting, where the step-by-step thinking process itself is a valuable output. So let me just say it now, I'm going to not sleep a lot that today and tonight, because I read this study over the weekend and like at first I'm scratching my head and I'm like, how is this come— like, like, who approved this, right? This did not seem like a research-led initiative. This seemed like someone high up in the business development side of Apple said, hey, FYI, uh, June 9th, today, right, today is our big WWDC announcement. And we are essentially, right, according to reports, Bloomberg said that Apple is taking a quote unquote gap year on AI, whereas last year at their WWDC conference, they just said, hey, everything AI, AI, AI, Apple intelligence, Apple intelligence, right? So reports are today at Apple's WWDC, they're going to have some quote unquote AI announcements, but they're essentially being like, oh, whoops, we couldn't deliver. We're facing multiple class action lawsuits that we promised all of this Apple intelligence and didn't deliver it. They had to pull their, you know, some of their simplest AI features because they were getting it wrong, right? Like email summaries were hilariously wrong. So Apple clearly has an AI problem. So you have to question the validity of this research, even though the research itself is valid. How they framed it, I think actually is extremely disingenuous to the research field, right? I'm not a researcher by any means. I've obviously read hundreds of research papers over the last, you know, 3 to 5 years as I become more interested and more involved in artificial intelligence. And out of all the ones I read, this is probably the most questionable research paper I've I've ever read. Like I said, the observations are sound, but this seemed like marketing. This seemed like cherry-picking. Uh, this seemed like just something that, again, just seemed very disingenuous to just the AI research community, right? This, this seemed like almost Apple, uh, you know, bending over backwards to try to cherry-pick and frame certain research data to justify how they're absolutely so bad at AI. It is unfathomable that a company like Apple, many years later, after we saw reports they were spending millions of dollars a day internally on their own AI systems, couldn't roll out anything that didn't work or didn't get them sued. So instead of facing the facts and doubling down and getting it right, now instead they're taking a gap year and they're putting out out a suspiciously timed research paper that casts doubt on the future of large language models literally hours before their announcement, where their future of large language models is being swept under the rug. Interesting, right? Yeah, uh, Joe here saying Apple marketing commissioned a study to prove that AI reasoning models are overhyped. Yeah, a little tongue-in-cheek, but I'm with you there, Joe. This doesn't seem like a research-led like, survey, right? Like, even looking at the actual facts the researchers make, so the facts are sound, right? But they're also illogical, right? And the way that they're framed, I'm like, this seems like a company with a huge agenda that is trying to, uh, shift markets because they know by putting this out at this time, it's getting a ton of news coverage and news coverage which, whether you believe it or not, it shifts markets. So, uh, yeah, actually tune in tomorrow. I'm going to commit to it right now. Uh, we're going to do a Hot Take Tuesday on this paper. I know that sounds dorky, but I got takes. All right. Uh, and our last piece of AI news, Meta is reportedly in talks for a $10 billion plus investment in Scale AI. So according to Bloomberg reports, uh, and Reuters, Meta Platforms is exploring an investment in Scale AI that could exceed $10 billion. So the deal, if finalized, would be one of the largest investments in an artificial intelligence startup ever and underscores the intensifying race among tech giants to secure AI capabilities. So Scale AI was founded in 2016 and was last valued near $14 billion, specializes in data labeling, and already counts Nvidia, Amazon, and Meta as backers. The company also operates a platform for AI researchers to share information with participation from, from contributors across more than 9,000 different cities. So according to this new report on Meta's purported $10 billion investments, terms of the potential deal are not yet finalized and could still change, with Meta and Scale AI both declining to comment on the talks. If completed, the investment could further accelerate the advancements in AI technology. And provide new opportunities for professionals and companies seeking to leverage large-scale data infrastructure. It's a big move here. This is a big move. I think this is a potential deal that could catapult Meta into this one, uh, kind of tier one discussion, right? Uh, and, and I don't know, maybe it's because of, uh, Meta takes— is the only big tech trillionaire company to take this primarily open-source OpenWeights approach with their Llama models, although Google does probably have the most capable open model, at least small open small language model in Gemma 3N. But this is pretty big. I think this is something if it works out well and if Meta takes good advantage of this data, of this potential partnership with Scale AI, it could make the race at the top much more interesting because at least since quarter 4 of last year, so around November, December, it's really just been Google and OpenAI at the top, right? You could say they're flip-flopping in the 1A spot, and then you have kind of Anthropic and Microsoft in that 1B spot. But you kind of have a big drop-off, I would say, until you get to Meta and their Llama models, even after their most recent releases a couple of months ago. All right. And you all said you wanted this, this new little segment in here at the end of the AI news that matters are rumors and what's next. So like I said, what's very next is, well, in about less than 4 hours, we're going to see Apple's WWDC, their Worldwide Developer Conference, today at noon Central Standard Time. So noon Chicago time. But it's been reported they're essentially taking a gap year on AI. They're going to be opening up their 3 different internal large language models to developers and some other small AI announcements. But they're essentially tucking their tail between their legs and not saying AI every 5th word like they did last year because that blew up in their face. Still no Grok 3.5, although the Twitterverse is saying it's going to be dropping any day soon. But Elon Musk might be a little busy with his current breakup with President Donald Trump. GPT-4o is showing some tracks of thinking for some users, which is interesting. A non-reasoning model is showing traces of reasoning for many users sharing online. Google's new— I think I might have got that one wrong there. I think it's called Sparkify. Yeah, Google's new Sparkify is an invite-only creative machine that uses Google's different AI platforms to create videos up to 2 minutes long. You know what's weird, guys? I told you all that by the end of 2025, we were going to be able to create our own very high-quality bespoke versions of like Pixar movies. And y'all laughed at me. And I'm like, no, you guys, I talked to the people developing this technology. It's coming. Trust me. And a lot of you people probably thought I was crazy, but here we are. It's already starting to roll out where you can literally create up to a 2-minute video with a simple prompt, uh, in the, uh, Google Sparkify, which right now is invite only. Uh, Google VO3 has started rolling out, uh, a fast version in the Flow video editor. Uh, Google— yeah, a lot of Google, uh, what's next in rumors. Uh, Google is going to be rolling out out scheduled actions in Gemini soon, which I'm extremely excited about that one. That's one of the things I love most, and I think one of ChatGPT's most underrated features is scheduled tasks. So now looks like Google is testing that out in certain Gemini accounts. And NotebookLM in kind of an ask me anything session, they kind of laid out some of their roadmap, some things that are probably coming soon. Video over— video overviews, new source types, and even an API. A NotebookLM API is mind-boggling what that could do for the industry. All right. I hope this was helpful. So let me quickly recap the AI news that matters. So OpenAI has released an updated and more human-like version of its advanced voice mode. Reddit is suing Anthropic for allegedly scraping user data. It didn't have a licensed to do. OpenAI has launched its new Cloud Connectors and ChatGPT Meeting Recorder. Although I haven't seen the meeting recorder pop up in my Mac app yet, the Cloud Connectors are there. Google has unveiled its upgraded Gemini 2.5 Pro model, even though it was already winning the race. New reports are saying that Chinese AI lab Deepseek is using Gemini data to train its new powerful R1 model. Anthropic has cut Claude access for windsurf amid OpenAI acquisition rumors. A new Apple study is challenging the hype around AI reasoning models, but I'm going to break that down in tomorrow's Hot Take Tuesday. And last but not least, Meta is reportedly in talks for a $10 billion plus investment into Scale AI, which would be one of the largest investments in an AI company ever. All right. I hope this was helpful. If so, So please share this with your friends. Click repost if you're listening here on Twitter or on LinkedIn. I'd appreciate it. If you're listening on the podcast, as always, please click that subscribe button on Spotify or Apple Podcasts, wherever you're listening. Yeah, maybe you just listen on the live stream. This thing goes out on the podcast, FYI. So we'd love for you to follow us there. Leave us a rating if this is helpful. Please go to youreverydayai.com. Sign up for the free daily newsletter. FYI, I'm laying it out. Tomorrow, we're going to do a Hot Take Tuesday on this new Apple Paper. And break it down a little bit for you. And then on Wednesday, the new AI at Work Wednesday, you said you guys liked it. So we're going to be doing a segment called AI Magic Converts Outdated Content into Engagement Gold. You're not going to want to miss that one. I've been planning it for like 3 or 4 days. It's going to be really good. You're going to want to join. Thank you for tuning in. Go to youreverydayai.com, sign up for the free daily newsletter. I'll see you back tomorrow and every day for more everyday Everyday AI. Thanks, y'all. And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going. For a little more AI magic, visit youreverydayai.com and sign up to our daily newsletter so you don't get left behind. Go break some barriers and we'll see you next time.