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AI Business News: Legal Risks, Model Milestones, and Industry Dynamics
Recent developments in artificial intelligence are not about flashy launches or viral headlines, but present practical challenges and strategic shifts for business leaders watching AI’s impact on workforce management, competitive positioning, and regulatory preparedness.
This summary translates key themes from a recent industry round-up into direct, actionable insights—touching on AI-driven HR decisions, new open-source benchmarks, and strategic differences among the sector’s largest companies.
AI in HR Management: Legal Exposure and Process Controls
A new federal lawsuit filed by 26 current and former employees of a major technology company signals increasing risks when implementing AI-powered HR decision systems. The suit alleges that AI was used to target employees on protected medical, parental, or family leave for layoffs, citing the use of keystroke monitoring, in-activity metrics, and token usage dashboards as contributing to indirect discrimination 02:29.
Legal filings reference violations of the Family and Medical Leave Act, Americans with Disabilities Act, and Pregnancy Discrimination Act 03:49. The core accusation is that legally-protected absences were not accounted for algorithmically, and the company allegedly failed to pause for individualized review.
Business Value:
Internal AI systems that monitor employee productivity or attendance may unintentionally sideline individuals on protected leave, creating grounds for significant litigation.
Process audits and cross-system checks are critical; integrating exceptions for protected absences and human review steps is essential before AI-based HR tools are deployed at enterprise scale 05:06.
Business leaders should model compliance scenarios before automating workforce reductions or performance tracking.
Unified AI Regulation: Industry Push for Predictable Oversight
A high-profile executive proposed the creation of a FINRA-style industry watchdog to pre-screen advanced AI models for national security risks such as cyber warfare and bioweapons 06:13. The proposed framework requires AI labs to submit frontier models for pre-release vetting, with the power to halt or slow launches crossing risk thresholds 07:11.
Industry leaders from the largest American labs have publicly endorsed these principles, with the notable exception of one major company advocating for open-source AI and drafting a separate regulatory response 07:57.
Business Value:
A standardized external review or “permission slip” process for new AI releases would deliver clarity on compliance and national security, reducing risks of sudden regulatory interventions that could affect product roadmaps 08:54.
Early participation or alignment with emerging oversight bodies may mitigate the risk of business disruption or rushed compliance in case of regulatory crackdowns.
AI Hardware Innovation: Consumer Data and Home Integration
Insights emerged regarding development of a new consumer AI device, reportedly a mobile, screen-free smart speaker with mechanical mobility and integration with leading language models 11:22. This device is designed to synthesize a user’s digital life, including emails, and aims to proactively personalize in-home experiences 12:02.
Business Value:
The move indicates a trend toward AI companions providing tailored value in home and work settings, beyond traditional voice assistants.
Consumer data access and privacy practices associated with such devices must be made explicit, as business adoption (e.g., in home offices) could expand.
Early awareness of hardware advances may create partnership or integration opportunities in sectors such as productivity, health, or smart home ecosystems.
Open-Source AI Models: Parameters, Access, and Operational Challenges
A Chinese AI startup, backed by major technology investors, has announced a 2.8-trillion parameter open-source model (set for weights release on July 27), marking a new milestone in model scale 13:52. Third-party benchmarks position the model close to—though not ahead of—the most powerful US proprietary models 15:33.
Business Value:
Large open-source models at trillion-parameter scale require massive infrastructure—far beyond consumer-grade hardware 17:06. Only enterprises with significant in-house compute can utilize such assets directly.
Despite “open-sourcing,” API-driven access may be expensive, sometimes exceeding costs for established commercial offerings 19:39.
Potential regulatory changes in China could limit further export of these tools, constraining mid- to long-term access for global businesses 19:08.
Businesses with existing large-scale AI investments should evaluate the ROI of fine-tuning or integrating such models, weighing ongoing compute costs and possible export restrictions.
Delayed AI Model Debuts: Competitive Consequences
Reporting confirms that a major US technology company’s anticipated Gemini 3.5 Pro model remains delayed past its initial June target, due to ongoing shortcomings in coding performance relative to internal benchmarks 20:19. With competitors shipping new, high-performing models, the delay has led to public market losses and uncertainty in the enterprise AI landscape.
Business Value:
Companies waiting for next-generation models from specific providers may face extended timelines that disrupt planned upgrades or proof-of-concept work 21:41.
Diversification in model sourcing and readiness to pivot to alternative suppliers are risk reduction strategies in fast-moving segments of AI development.
Large Vendor Alliances and Friction: Control, Data, and Investment Dynamics
New reports indicate internal tensions between coalition partners, with large investors criticizing partner AI models as excessively editorially controlled—limiting usability for creative tasks 25:21. Additional industry commentary points to the dangers of “paying twice” for AI: once in subscription or API fees, and again through the transfer of proprietary company data required to unlock maximum utility 28:04.
One major vendor is cited as uniquely requiring enterprise data retention, suggesting differentiated compliance and data risk exposure for customers 28:41.
Business Value:
Decision-makers reviewing enterprise contracts need to scrutinize not only explicit pricing and model quality, but also underlying data retention policies.
There is growing recognition that data sovereignty and institutional knowledge retention are as critical to value extraction as model performance.
Vendor management strategies must include the flexibility to renegotiate or switch providers in light of changing editorial or data retention stances among AI suppliers.
Expanded AI Capabilities: Productivity and Cost Management
Other market moves include:
New integrations enabling cloud AI tools to connect with third-party platforms for creative and productivity tasks 30:52.
New features for automated code execution in document-based AI notebooks 32:41.
Launches of auto-drafting email tools that maintain brand or personal voice, and personalization features for digital avatars 34:20.
Business Value:
The proliferation of productivity-focused AI features presents immediate pathways to incremental efficiency gains in document management, communication, and digital marketing.
Business owners and decision makers should assess the incremental cost vs. benefit of integrating such tools, particularly as improved memory, user experience, and workflow support become more widely available.
Conclusion: The AI Business Landscape in Transition
Behind headline-grabbing releases, AI leaders are navigating lawsuits, regulatory proposals, infrastructure constraints, and data policy challenges. For those steering company strategy, vigilance in compliance, supplier diversification, and readiness to adopt new, practical productivity tools is essential. The industry’s trajectory in the coming months will shape how value—and risk—are distributed across the business landscape.
Topics Covered in This Episode:
- Meta AI Layoffs Lawsuit: Discrimination Claims
- Google DeepMind Proposes Unified AI Watchdog
- OpenAI Smart Speaker Hardware Leak Details
- Kimi K3 Trillion-Parameter Open Source Model
- Kimmi K3 Benchmarks vs GPT-5.6 Soul, Fable 5
- Google Gemini 3.5 Pro Model Release Delayed
- Microsoft CEO Nadella Criticizes Anthropic Fable 5
- Anthropic Fable 5 Data Retention Enterprise Policy
- Quinn 3.8 and Inkling AI Large Model Launch
- Suno Data Scraping Leak and AI Music Training
- Google AI Mode Integrates Canva, Instacart, YouTube
- Anthropic Extends Fable 5 Access to Max Users
- Apple Testing PrismL Model Compression on iPhones
- Perplexity Rolls Out Self-Improving AI Memory
- ChatGPT Universal Search and Work Features Update
Episode Transcript
Jordan Wilson [00:00:16]:
There was no Blockbuster AI story this past week. No landmark AI court case or chart breaking AI model. Although there were plenty of new updates, developments, and stories that you need to know for your company to keep pace, this was one of those rare quiet weeks in AI news and developments. You know what that means though. Right? We're likely in for a doozy of new news this week, like a sharpshooter that never misses twice from the three. I'm guessing we're going to be in for a big week of AI updates this coming week. Regardless, we did get enough to keep up with the past seven days. I mean, we have the world's new best open model, some juicy AI lawsuits, and the Microsoft CEO calling out not just one of his biggest competitors by name, but also one of the companies that he's invested $5,000,000,000 in.
Jordan Wilson [00:01:13]:
Yeah. Still plenty you need to know to keep up, and that's what we're gonna do on today's AI news that matters. What's going on? Welcome to Everyday AI. If you're new here, my name is Jordan Wilson, and we do this every day. It's your daily livestream podcast and free daily newsletter helping business leaders like you and me keep up with AI developments, use that information to grow your company and career. So if that's what you're trying to do, sweet. Me too. It starts here with the unedited, unscripted livestream podcast, but please make sure you go to our website at youreverydayai.com.
Jordan Wilson [00:01:46]:
We're gonna be keeping you up to date with the highlights from today's story and everything else that's happening in AI world. So let's just jump straight into it. First, Meta, after having an amazing July so far with their new Muse Spark 1.1 that we talked about last week, their new Muse, image in video models, well, they got, maybe a little bit of a black eye this week. That's because a group of 26, current and previous meta employees has filed a federal lawsuit claiming the company's use of AI in layoff decisions unfairly targeted workers on medical, parental, or family leave. So according to the Associated Press, the lawsuit was filed in Oakland and involves 26 anonymous META employees who say they were selected for layoffs after taking protected leave or requesting disability accommodations. So the employees are among the 8,000 workers or about 10% of Meta's workforce who were notified of layoffs in May. So the lawsuit alleges that Meta used internal AI systems, keystroke in activity monitoring, and algo performance rankings in AI token usage dashboards, dashboards to determine who would be laid off. So the plaintiffs claim that these AI power system penalize employees who are on protective leave as their output was automatically reduced, making them more likely to be selected for termination.
Jordan Wilson [00:03:21]:
Many of the affected workers were on pregnancy or parental leave, while others took medical or family caregiving leave. Eight are women who had been who had taken maternity or pregnancy related leaves, and four are men who took parental leave. So the lawsuit argues that Meta Systems failed to account for legally protected absences and did not pause for individualized review as required by law. The complaint cites violations of several state and federal laws, including the Family and Medical Leave Act, the Americans with Disabilities Act, and the Pregnancy Discrimination Act. So Meta responded saying that those claims lacked merit and are not based on facts and stated that workforce decisions were made by people, not AI. So not exactly the week that Meta wanted to follow-up with after their hot start to July that saw their stock really just rebound from, like, a year of lackluster performance and losses. So, Meta honestly had the best start, I would say, to July outside of OpenAI. Right? If you look at kind of the the big six of AI, alright, which is the big four model makers, that's OpenAI, Anthropic, Google, Microsoft, and then you put in Meta and SpaceX into the equation.
Jordan Wilson [00:04:47]:
Right? If I talk about the big six in AI, right, it's kind of the big four plus Meta and, SpaceX. So Meta actually had one of the best Julys, you know, so far, until this happened. So not a good look. This one's gonna be interesting to see how it plays off. And if nothing else, a good takeaway for business leaders here is you always have to make sure that your systems are talking to each other. Right? If this is truly the case, this is absolutely horrible. Right? If women that were on pregnancy leave, were, you know, essentially, decided an AI decided that they were going to be up for termination because they weren't hitting their keystrokes or their, you know, token, you know, targets, which is absolutely asinine if this is true. I hope it's not, but regardless when it does break one way or the other, we'll let you know in the newsletter.
Jordan Wilson [00:05:43]:
I'm guessing this will eventually just be settled out of court. Alright. Our next one, which could end up being a big joint agreement for US tech companies, which you don't really see a lot. That's because the Google DeepMind CEO is pushing for a unified AI watchdog after the anthropic ban has led to kind of this staggered and what I'm calling the permission slip AI reality that we're all living in. So Google DeepMind CEO, Demis Hassabis, is calling for a FINRA style industry funded watchdog to oversee advanced AI, aiming to prevent the chaotic kind of government crackdowns like the one that halted Anthropic's Fable five and Mythos five models in June. So the Trump administration's abrupt ban on those model models when they were citing national security risks triggered a tense two and a half week negotiation enforced last minute changes, exposing the lack of a formal review process for powerful AI systems. So this is what, Demis' proposed body would require. So it would require, AI labs to submit their Frontier models for pre release vetting up to thirty days before launch, focusing on threats like cyber warfare, bioweapons, and nuclear misuse.
Jordan Wilson [00:07:11]:
So the framework would also include emergency powers to slow or halt industry wide AI development if a model is found to cross critical risk threshold. So the reason why this is important because this is the first, kind of initiative that's picked up steam across all of well, not all of the big six, but I think five of them. That's because major tech leaders, including Microsoft's Satya Nadella, OpenAI's Sam Altman, Google's Sundar Pichai, and others have publicly endorsed the core principles of the proposal, marking a rare show of unity in the competitive sector. Anthropic's Dario Amodi supports binding regulation, but has called for an even stricter government led agency with authority to block unsafe model releases outright. So Meta, led by Mark Zuckerberg, remains the notable holdout here continuing to advocate for open source AI in drafting its own regulatory response. That one there is pretty, I don't wanna give it a certain name, but, you you know, the fact that Meta cited open source AI being an advocate for even though they are the company that has famously shifted away from open models in their previous, llama series to now the Muse, which are proprietary closed source. So I don't really know why Meta's response was was, well, hey, we care more about open source. Anyways, all of the other major US labs have already signed voluntary agreements to submit their models for government safety testing, but the industry the industry wants a predictable standardized process instead of the ad hoc intervention that we've seen.
Jordan Wilson [00:08:54]:
So the White House is currently reviewing the proposal as a potential compromise to keep America competitive in AI while managing security risks. So if you didn't see this, we did share this in our newsletter last week. I think this is sorely needed. Presumably, you would have probably liked this, to come from the government and not necessarily a private company, but maybe that's what might make this stick. Right? Similar to the FINRA style, you know, having a private public, sector agreement that says, hey. We're essentially the experts in AI. You probably don't know government, exactly what you should be doing when it comes to regulating our industry, which I absolutely agree with. That's not me saying that there's not smart people in AI in the government.
Jordan Wilson [00:09:52]:
There's obviously absolutely brilliant people, you know, who have both backgrounds, at these big six tech companies working in government now. But for the most part, when it comes to, like, the bleeding edge technology, I don't think the White House really has a clue. And that's not a political statement. That's just any government. I don't think any government would have the clue how to regulate The United States acceleration in AI right now. Right? But that's because, you know, sixty days ago, you know, six months ago, the capabilities that we have today, no one probably could have predicted them, especially six months ago. So it is good, that, you know, Google DeepMind's, Demis Hassabis is kind of calling for this and taking, this step forward. Demis obviously has one of the deepest and, most respected backgrounds in AI in the entire world.
Jordan Wilson [00:10:48]:
So we'll see if Sir Demas can get it done. Alright. Moving from one, kind of compromise, I guess, of US big tech companies, to a leak that could maybe impact millions of people. That's because we just got a report from Bloomberg that says OpenAI is working on its first hardware device. So finally, we get some details on what this, you know, much reported on device. You know, we've been hearing about this thing for, almost nine or ten months now. So according to Bloomberg reports, it is a mobile smart speaker that integrates AI and syncs with chat GPT. So according to reports, the device is designed to be a screen free device, and it acts as a human like AI companion for the home offering proactive learning and a personalized service.
Jordan Wilson [00:11:45]:
So unlike traditional smart speakers, OpenAI's model reportedly features mechanical elements that can move on their own, aiming to feel, more like a living companion or one that can at least kind of wander maybe from room to room with you. So the speaker is intended to access a user's digital life, including emails to deliver highly tailored assistance. So development is being led by formal former Apple engineers who played key roles in creating products like the iPhone and Mac. So the project comes amid legal friction as Apple recently sued OpenAI, accusing it of stealing trade secrets and warning of more revelations during discovery. OpenAI denied any wrongdoings on that. Sources told Bloomberg the new device veers significantly from anything Apple has on the market today and is unlikely to violate trade secrets. So OpenAI's push reflects the growing industry excitement about consumer AI hardware, with startups like HARC raising around $700,000,000 to build personal intelligence devices. So the reported OpenAI devices form factor hasn't been revealed highlighting how much investor interests exist before these products are even unveiled.
Jordan Wilson [00:13:05]:
So I'm all for anyone that's listening to the show for a long time. I don't really care about my data. I know. Right? If you want to know all the random AI stuff I've been searching and, if a OpenAI smart speaker wants to follow me around and help me with that, sweet. Sounds good. Right? Anything to get rid of, Alexa and Siri sooner, the better. Like, please sign me up for this. Put me on a wait list.
Jordan Wilson [00:13:33]:
Alright. Next, you don't have to get on a wait list because this is out. This is the new king of the open well, soon open source hill. Alright. More on that here in a second, but we do have a new open source king in Kimmy k three. So Moonshot AI, a Chinese startup backed by Alibaba and Tencents, introduced Kimmy k three, a absolutely massively monster open source model with nearly 3,000,000,000,000 parameters. Yes. Three almost 3,000,000,000,000 parameters.
Jordan Wilson [00:14:12]:
So moonshots revealed Kimi three at the World AI Conference in Shanghai, touting it as the world's first open source model in the 3,000,000,000,000 parameter class. So Kimi k three is not technically open source yet, but the company says they will release the weights on July 27. So at 2,800,000,000,000 parameters, Kimmy k three puts it in direct competition with leading American proprietary models from OpenAI and Anthropic. So the announcement comes just weeks after The US temporarily forced Anthropic to withdraw its its mythos, and fable five models due to cybersecurity concern, highlighting the growing not just national security focus on advanced AI, but also the interest on potential open source AI projects that can live in the frontier or, like, frontier point five sector. Right? So and this is why it's actually important because third party evaluations by artificial analysis and arena show Kimmy k three performing, on par ish, right, with, GBD 5.6 Soul and Fable five. So in some benchmarks, they're a little bit better actually. But right now, I would say that you have, GBD five six Soul and Fable. They are class one a, and now, well, you might have an open source model in Kimmy k three, technically, one b.
Jordan Wilson [00:15:50]:
So at least right now, I wouldn't even say it's the second tier. It's you know, we have a tie for one a and, yeah, we have a Chinese open source model that has closed the gap, to be one b. So Kimmy k three's open source approach stands in contrast to, obviously, the closed proprietary systems of American firms throwing a wrench in the AI strategy game plan for some larger enterprises. So the model itself is designed to operate with minimal human supervision, handling complex tasks like engineering and software development. The release immediately impacted global markets with shares in Chinese competitors, z AI and MiniMax, dropping sharply in Hong Kong after the announcement. So I'll cut it to you straight on this, because I think people, for the most part, when they look at open source models, they usually think of two things. They think, well, if I have a powerful enough computer. Right? Like, as an example, I have a very beefy Mac studio, sitting here on my desktop.
Jordan Wilson [00:16:58]:
People think, oh, if I have very expensive hardware, I can run the best open source models. No. We are past that. Unless you literally have a rack of NVIDIA GPUs and a cooling, center in your basement, you can't run this. Right? This is for 0% of consumers out there. You can't run a 3,000,000,000,000 parameter model on any consumer hardware. So that's number one. So, yes, this is really for those enterprises that have access to compute at scale.
Jordan Wilson [00:17:30]:
Number one, especially if you can host it, which is not a lot of companies. But if you do have a couple of racks, and maybe you have a large AI bill, you know, maybe you're paying, $8.09 figures in AI spend with, you know, a bunch of GPUs, which, again, not a lot of companies. But for some companies, yes. In, this week or sorry. In, like, ten days or so, on July 27. So that's, like, in seven days. You'll technically be able to download this model, and if you want to fine tune it because it's open source. So for a very, very, very, very few companies, this is actually could be fantastic news if you have, the resources and, the the the human, skill needed to make that happen.
Jordan Wilson [00:18:18]:
That's one thing people think. Oh, I can just download this and run it. No. You can't. Number two, they think it's extremely cheap. Also not the case. Right? So if you're not using this, you know, downloading it and running it locally, people think, well, oh, open source models are super cheap. Previously, yeah, they were.
Jordan Wilson [00:18:37]:
Not really with this one. Right? We we we see this Kimmy k three. We also saw, that Quinn will be releasing their next big multiple trillion parameter model, here any minute or any hour. So I don't think this next tier of frontier ask open models are gonna be open in the sense that we thought of them previously. Right? And the other thing is there's no real guarantee that we keep getting these open source Chinese models for much longer. We saw reports which we talked about on last week's AI news that matters that China may start, restricting the export of their models. Right? Specifically, not wanting, maybe The US to get a hold of these, which is obviously ironic considering that these models have largely just been distilled from US models. So regardless, there's a little bit of background.
Jordan Wilson [00:19:33]:
You can't go download this. And if you're paying API prices, it's not like they're super cheap. Right? They're actually, in many cases, more expensive than GBD 5.6, Sol. You know, they're probably a little cheaper, than Fable five and Mythos five since those are the most expensive models on the market when it comes to price per performance. Alright. More model news, but this is not we get one. This is just we're waiting longer. So Alphabet, parent company of Google, its shares fell 4% Thursday after news broke that the highly anticipated Google Gemini 3.5 pro, yeah, months behind schedule, not coming out anytime soon.
Jordan Wilson [00:20:19]:
So according to a new Bloomberg report, the delay is due to Google's efforts to improve the model's coding performance, which currently falls short according to their own internal expectations. So the setback comes as competitors like OpenAI, Anthropic, and, Meta have all launched AI models recently that outperform Google's current offerings in software cogeneration. So Alphabet first teased Gemini 3.5 Pro in May after releasing Gemini 3.5 Flash. So in May, at their IO conference, they said that the model would be coming out in June. Obviously, June has already passed, and we're near the end of July. And now the latest report says Google's next model in Gemini 3.5 pro could still be months away. So an alphabet spokesperson told CNBC that the company is shipping quickly across a wide range of models and continues to test Gemini 3.5 pro and other upgrades with partners and the US government. So, yeah, if you were, you know, holding your breath or if you were, you know, trying to decide between GBT five six soul and Fable five, and you're like, wait.
Jordan Wilson [00:21:41]:
Let's just wait until, you know, Google Gemini 3.5 pro because it was supposed to come in June. Surely, it's coming in July. Well, no. And if this report holds to be true, we might be heading into the fall without even Gemini 3.5 pro. And at that point, I mean, presumably, we're gonna be getting a a fable five one soon. We may be getting a GPT, six around the horizon. We'll see. So, you know, it's it's gonna, be worth following to see just how big of a jump this 3.5 pro could be, or maybe, I don't know, if Google comes out with another flash model in the interim.
Jordan Wilson [00:22:26]:
Because if they're still working on the same pre train that they were previously, that can might be concerning. And, I mean, we'll see if for the first time in a long while, at least two plus years, if Google is not able to compete on the model front, which to me, I would be shocked because I've always been a big believer in that Google at any point whenever they want can drop the world's most powerful model. So I don't know. Maybe when I said that a year or so ago, maybe I was biting off more than I could chew and believing in, the big g a little bit too much. So, yeah. We'll we'll see if that holds true. I still think they'll be able to, you you know, Google 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 Jenna AI. Hey, this is Jordan Wilson, host of this very podcast.
Jordan Wilson [00:23:33]:
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 chat g p t 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 build a straight path to ROI on GenAI. It's they have their own. Right? They have their own, the, you know, GPUs, TPUs. They can they can train these things quickly, without having to, you know, pay their competitors billions of dollars like Anthropic is having to do right now, for inference and to train these models.
Jordan Wilson [00:24:43]:
So alright. Speaking of big tech companies, we're moving from Google to Microsoft for our last big AI news story of the week. That is the juicy one. Here we go. So Microsoft CEO Satya Nadella recently, according to reports, started to kind of seemingly shift his public stance on mainstream AI, moving from an aggressive investor in closed source Frontier Labs to a vocal critic of their current trajectory. So the shift, it began with Nadella's leaked criticism of anthropics Claude Fable five. So according to reports, Nadella slammed the flagship model as being two, quote, unquote, editorially controlled, arguing that its rigid guardrails and refusal protocols don't make sense for a creative utility. So reports also said that Nadella questioned anthropic's limits on user requests to its high end Fable AI model, calling the editorial controls on creation tools nonsensical during remarks to Microsoft's Copilot engineers.
Jordan Wilson [00:26:03]:
So Anthropic's fable model sometimes rejects users' queries or responds with older versions of the model with essentially falling back to Opus 4.8, leading to a lot of frustration and criticism on social media. Right? You've seen many examples, and I've tried some myself even asking Fable five about certain types of cancers or, you know, hey. What are the biggest, you you know, in certain medical fields? What are the biggest unanswered questions? And it will say, essentially, you can't ask this. And it's gonna roll you back, to an older model like Opus 4.8. So this is extremely noteworthy as Satya Nadella is, at least according to these reports, publicly criticizing Anthropic. That's because Microsoft has invested $5,000,000,000 in Anthropic, with Anthropic agreeing to also spend $30,000,000,000 in future years on Microsoft's Azure cloud infrastructure. So this is, right? You normally wouldn't hear shots fired like this, you you know, slamming a company in their flagship model, especially when said company is, well, gonna be reportedly paying you $30,000,000,000 over the next few years, and you have a large ownership in that company. But that wasn't the only, kind of shot at anthropic that Nedella took.
Jordan Wilson [00:27:39]:
That one was, again, according to reports, direct. The second one, a little indirect, but most industry in it, you know, insiders are connecting the dots. So in a seemingly somewhat related long form online post last week, Nadella coined the term reverse information paradox to explain that businesses essentially just pay for AI twice. They pay for it once with actual money. Right? So they're buying subscriptions for their employees or paying for tokens. And then he said they're actually paying for it a second time. And the second time is more dangerous because they're giving away their proprietary knowledge and institutional know how that they're essentially forced to hand over to make the model useful. So in his post, Nadella didn't name names on who does this, but well, everyone's looking at the fine print here and being like, wait, the only company that actually forces you to do that right now is Anthropic.
Jordan Wilson [00:28:41]:
Because if you're a at least for paying business customers at least, Anthropic is the only one that has a requirement that they're going to retain your data, and there's nothing you can do about it. Right? So with the new Mythos five and Fable five, Anthropic essentially throws zero, data retention or z d r. You know, Anthropic's just throwing zero data retention out the window. So, again, although Nadella didn't mention Anthropic by name, everyone's, you know, reading his post and being like, okay. This is also definitely about Fable. So for all you people out there that, you know, sometimes say, oh, Jordan's being so hard on anthropic. No. I'm not.
Jordan Wilson [00:29:27]:
My gosh. Like, the fact that anthropic still has that required, data retention. Again, I don't have $5,000,000,000 invested in Anthropic, and Anthropic hasn't agreed to pay me $30,000,000,000 over the next couple of years. So if Sadia Nadella is number one, again, according to reports, calling them out by name in one, you you you know, breath. And then in the next breath, he's essentially describing them because that's the only company that truly fits that description for enterprise customers. That's not a good sign for anthropic. Just saying that. So, yeah.
Jordan Wilson [00:30:07]:
Yeah. Many attributed that second half of the statement to anthropics mythos five and fable five data policy, which forces that data retention even for enterprise customers. Alright. That's a wrap on our big stories, but let's quickly go into the what's new and what's next. So these are some still important happenings. Some maybe some leaks in here, but let's just quickly go into our what's new and what's next rapid fire. Here we go. So the Trump administration launched Gold Eagle Hub to accelerate cybersecurity patching for critical infrastructure.
Jordan Wilson [00:30:46]:
Meta reportedly entered talks to lease up to $10,000,000,000 of compute to anthropic. Google AI mode added actions through Canva, Instacart, and YouTube music. Yeah. If you didn't check that out, pretty cool. If you have a paid personal Gmail account, check that out. Next, I referenced this earlier, but Quinn 3.8 is launching soon. And the company says it is a 2,400,000,000,000 parameter model, and they are reporting benchmarks near Fable five, G P D five six, Seoul, Kimmy K three levels. Alright.
Jordan Wilson [00:31:20]:
Thinking Machines released a 975,000,000,000 parameter open weight inkling AI model. New York halted any data center construction more than 50 mag, MW. Is that mega I always forget that what what that is. MW is is mega megahertz. Is that right? Mega megawatts. My gosh, y'all. Sometimes I read too much AI news, and I just forget things. Alright.
Jordan Wilson [00:31:49]:
Anyways, New York halted, construction for one year on any of those, new data centers. Next, more than 200 experts, including 15 Nobel laureates, called for urgent preparation for AI's economic impact. Anthropic permanently extended Fable five to max users, but, yeah, it's only at about one third of the original limit. So, yeah, I talked about this on last week's show. I said there's no way Anthrapic is actually taking away Fable five because they would lose most of their subscription revenue. So, unfortunately, for most people, it is only if you're on that $100 or $200 a month paid plan. Google renamed notebook l m to Gemini notebook, and they added cloud code execution, for paid users. I think that's only out, to ultra users, but it will be coming out to pro users soon.
Jordan Wilson [00:32:46]:
So, yeah, let me know if we should do a Gemini notebook, episode when that drops. I'm gonna accidentally still call it notebook l m all the time. Next, a hacker leaked Suno's secret data, reportedly showing that millions of songs were scraped from YouTube and Deezer. Alright. Next, OpenAI released GPT Red, an automated system to detect prompt injection vulnerability in AI agents. Amazon Bedrock added support for OpenAI's new models, g p d five six. Apple is reportedly testing prism l, prism l's, AI model compression, which would essentially allow them to run 27,000,000,000 parameter models on iPhones, which would be pretty sweet. Please just fix the Siri Apple if you're listening.
Jordan Wilson [00:33:37]:
Thanks. Anthropic added in in app browser to Claude code on desktop, enabling site in dock interaction. So, yeah, I tried it out. It's pretty good. It's not quite as good as codexes, but it does the job. Next, perplexity rolled out self improving memory, faster models, and one click website publishing. ChatGPT rolled out their universal search, that helps you more easily find projects, images, documents, chats from one sidebar, a much richer and better search experience. Email program, Superhuman, released their new auto draft feature that writes email replies in your voice, using better models, and then you can go send them from your drafts.
Jordan Wilson [00:34:20]:
Next, Spotify released a new feature where you can talk to Spotify by voice or text to control music and see listening history. Gemini rolled out personal avatars, so allow you to generate AI videos starring your own face and voice. And then last but not least, Chad GPT work, which I don't know if it's called just Chad GPT now. I noticed that in the dropdown that used to say Chad GPT work and codex, now it just says chat g b t and codex. So I'm not sure if we're still calling it chat g b t work or not. But regardless, it actually makes it easier. That's funny. One of my, AI is just, shouted out at me.
Jordan Wilson [00:34:59]:
But it actually makes it much easier, to show your conversation history. So, essentially, they brought your chats from chat g b t into a place that made more sense inside of the desktop app. Whereas before, you know, users were a little bit confused. Also, it brings your projects in, which a lot of users were complaining about. So, essentially, if you tried out CHED GPT work when it came out, about ten days ago and we're like, wait. Some of this isn't adding up. Where's all my CHED GPT stuff? Well, now it's all there. Alright.
Jordan Wilson [00:35:29]:
So I hope this was helpful. All of the AI news that matters for this week, but like I said to start the show, I can almost guarantee we're gonna get a ton of new releases. Right? Word on the street is we'll probably be getting an Opus five from a tropic that could be near that to GPT five six or, Mythos level, you know. And who knows? It is still hot AI summer. And I think that once the steam starts to pick up, it is going to be a hot one. So, I get it. It is hard. If you are a busy business leader and you're trying to implement AI in your company, and you're like, how do I keep up? Well, it starts here with the daily podcast, but make sure you also go to our website at youreverydayai.com.
Jordan Wilson [00:36:16]:
Thank you for tuning in. Hope to see you back tomorrow and everyday for more everyday AI. Thanks, y'all.