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Navigating the Rapid Evolution of AI: Key Insights for Business Leaders
In the ever-shifting landscape of artificial intelligence (AI), it's crucial for business leaders to stay informed about the latest technological advancements and their implications. Below, we explore significant developments covered in a recent episode of the Everyday AI podcast, focusing on the potential impact on businesses.
Emerging AI Controversies: What Business Leaders Need to Know
The evolution of AI models continues to stir both innovation and controversy. Recent developments include the launch of a new AI model by a prominent startup, which claims superiority over existing competitors. However, this rollout hasn't been without its challenges, facing allegations of misleading benchmark results and concerns about content censorship. For business leaders, understanding these dynamics is essential to making informed decisions about adopting new AI technologies. Transparency in AI performance and ethical considerations should remain top priorities.
AI Safety and Regulations: Navigating a Shifting Policy Landscape
Recent political decisions threaten to disrupt AI safety and regulatory frameworks, posing challenges for companies relying on AI model testing and regulatory guidance. Significant cuts are proposed for a US Safety Institute responsible for overseeing AI safety, potentially derailing efforts to balance AI growth with regulation. As business decision-makers, staying abreast of political shifts and advocating for robust regulatory frameworks is crucial for maintaining ethical and safe AI deployment.
Quantum Computing: A Quantum Leap in AI Processing Capabilities
A recent breakthrough in quantum computing, introducing a new quantum chip, holds the promise of transforming AI processing capabilities. Although practical applications remain a few years away, the potential for quantum computing to accelerate AI development should be on the radar of forward-thinking business leaders. The ability to process large datasets more efficiently could revolutionize industries, offering competitive advantages to early adopters.
AI-Powered Video Creation: Redefining Content Production
The introduction of a new AI video generation model by a leading tech giant signifies a shift in how businesses might approach content production. This development offers a cost-effective alternative to traditional filmmaking, opening doors for companies to create high-quality video content. For business leaders, this means the potential for enhanced storytelling and engagement strategies without breaking the bank.
Strategic Implications for Business Leaders
As AI technologies continue to evolve rapidly, business leaders face both opportunities and challenges. To navigate this landscape effectively, it is imperative to:
Monitor ongoing developments and controversies within the AI sector.
Advocate for clear and ethical AI regulations while preparing for potential shifts in policy.
Explore the integration of advanced technologies, such as quantum computing, into strategic planning.
Leverage AI-powered tools to enhance content strategies and internal processes.
By staying informed and adaptable, businesses can harness the power of AI to drive growth and innovation while mitigating risks.
Topics Covered in This Episode
1. Grok 3 Controversies
2. AI Censorship and Political Stances
3. OpenAI and Chinese AI Misuse
4. Advancements in Robotics
5. Google's AI Co-Scientist System
6. Launch of Mira Murati's New AI Startup
7. Google's VEO 2 AI Video Model
8. Microsoft's Quantum Leap
Podcast Transcript
Jordan Wilson [00:00:16]:
Elon Musk's grok three is already facing multiple controversies. Google's v o two state of the art AI video model has been released, but not in the way that you would think. And Microsoft is going quantum and apparently discovered a new type of matter. Like, I don't know. Like, it's it's Monday, and it already feels like we're at the end of the week in terms of the amount of AI news that is just hitting us. And that's not all. We might also see a new update, a new model from Anthropic, from Claude after, I don't know, waiting, like, seems like thirty years. Alright.
Jordan Wilson [00:00:57]:
We're gonna be covering those stories and a whole lot more in today's AI news that matters. So welcome to Everyday AI. What's going on y'all? My name is Jordan Wilson, and I'm the host of this show, and, this is for you. So we do this every single weekday, Monday through Friday, bringing you the real updates that matter. So on Mondays, we do our AI news that matters, but we do the everyday AI show every single weekday. So if you're looking to grow your company or grow your career by understanding, the latest in GenAI, you are in the right place. The other right place for you to be your BFF is going to be our website. That's youreverydayai.com.
Jordan Wilson [00:01:42]:
You can go there. You can, number one, sign up for our free daily newsletter where every single day we recap not just our podcast, which is usually bringing you some exclusive insights with interviews and everything like that. But on there, you can go listen to, like, now 450 episodes, all sorted by category from the world's leading experts all for free. So make sure you not only go sign up for that free daily newsletter where we'll where we will be recapping today's show. But also go check out, I don't know, one to 20 episodes and be the smartest person in AI at your company. That's what we are here in trying to get you to do. Alright. And also, make sure go listen to episodes four forty three through four forty seven.
Jordan Wilson [00:02:22]:
Some people are asking recently like, hey, Jordan. Where do I start? This looks intimidating. You have, like, 500 episodes. Go listen to those. That's our twenty twenty five AI predictions and road map series. So if you have not listened to episodes four forty three to four forty seven, please go do that. Alright. Enough chit chat y'all.
Jordan Wilson [00:02:39]:
Let's get into the AI news that matters for the week of February 24. And, also, thanks for joining us live. If you're normally on the podcast, come hang out. It's fun. Michael and Michelle, Sandra, Philip, lot of people joining on the YouTube machine this morning. Love to see it. Samuel, Bethany, Lauren, Jackie, big bogey face, Alan, Natalie. Too many to name this morning.
Jordan Wilson [00:03:03]:
Thanks for thanks for tuning in y'all. Alright. Let's get into it. Let's start at the big story, what everyone is talking about. Elon Musk's startup, XAI, has launched its latest AI model, GROC three, claiming that it surpasses competitors like OpenAI, Claude, Anthropic, and Google and others. So GROC three is said to be significantly more capable than its predecessor GROC two and is available to premium users of the social media platform, Axon. It's rolled out to free users as well. It's actually been a confusing rollout, from the Grok team, because, when it first rolled out, you had to have a premium plus, and then you had to have a premium, and then they doubled the price of premium, and then they made it, you know, somewhat available to free users, but with not a lot of, you you know, communication.
Jordan Wilson [00:03:56]:
But it is available, and the model has been tested on standardized exams in everything from math, science, and coding, reportedly outperforming existing AI models. More on that reportedly, here in a bit. So Musk described GROC three as scary smart with enhanced reasoning abilities and noted that it is trained on synthetic data, allowing it to reflect on its mistakes and improve logistical consistency. So the launch of GROC three also includes a new product called deep search. Alright. You know, GROC had to go against the grain and not name itself deep research like the other, deep research tools from Google perplexity and OpenAI, so that you have the deep search mode, in Grok three, the new voice mode, and people are going wild about the unhinged mode. So I don't know if you're 13 and, you know, giggle at profanities, maybe it's for you. And as well as a kind of a think deeper mode.
Jordan Wilson [00:04:57]:
So similar how you can kind of control, certain models to use a little more, compute or to, use a reasoning model. You have that with the new GROC three as well. So the models rollout is part of the beta phase with ongoing improvements expected and the voice assistant features slowly, rolling out already. I do believe the latest. I haven't used the new voice features, but I did see it, was released to many users as of late this weekend. So XAI has expanded its GPU cluster, doubling the size to support the training of GROC three. So, originally, it was reported that they had 100,000 of NVIDIA's most powerful GPU chips. Well, turns out they actually reportedly have 200,000 of NVIDIA's most powerful, GPU.
Jordan Wilson [00:05:49]:
So they really just willed, GROC three into, existence. So you have to tip your cap, to the XAI team. Right? Going from essentially zero to GROC three in, like, a little more than a year. And the GROC the release of GROC three comes amidst intense competition in the AI market with previous models from OpenAI and Google setting high benchmarks that GROC three has now either topped or has at least caught up to in almost all benchmarks. So, you you know, I'm curious for our livestream audience if you, are using Grok. Alright. Michael says, hey. I'm 35 and giggle at the profanities.
Jordan Wilson [00:06:34]:
So, you know, let me know if you're actually using Grok, if you wanna hear more about it. I don't know. It's it's gonna be grabbing a lot of headlines, I think, the first couple of weeks. And speaking of that, yeah, we actually have two more grok stories to start off with, and they're pretty significant. I think we kinda have to talk about here. So, speaking of those benchmarks, there is a controversy that has erupted online between OpenAI and XAI concerning those exact benchmarks. So, OpenAI accused XAI of presenting misleading benchmark results, which XAI cofounder Igor Babushkin defended highlighting a broader debate about transparency in AI performance reporting. So here's here's the gist, and I'll try to break it down, hopefully simply.
Jordan Wilson [00:07:27]:
So XAI published a graph showing GROC three outperformed OpenAI's o3 mini high model on the AIM. That's the AIME twenty twenty five math benchmark, a test whose validity as an AI benchmark has been questioned by some experts. So the dispute centers around the omission of OpenAI's o3 mini high score at consensus 64. So, cons 64 or consensus 64 is a method that allows a model 64 attempts to answer each question, potentially inflating performance scores. But when measured at, at one, which is the first attempt, Groc three's performance was lower than OpenAI's o3 Mini high. Contrary to xAI's claim of Groc three being the world's smartest AI. So, essentially, if you gave Groc one attempt, it did not beat OpenAI's o3 Mini and some other models, and they use this o or sorry, this, Cons 64, which essentially gives a model 64 attempts to see if they can get the right answer. So parts of this, I understand.
Jordan Wilson [00:08:44]:
Right? Because large language models are generative. They're not deterministic. So they are like a controlled roll of the dice. Right? So you could do the same prompt 10 times, get nine different answers. You can get one different answer. It depends on what you're asking and if there is a, definitive answer or not. So, I personally, though, think it's worth noting this whole cons 64 method because, you know, it's essentially now what he said, she said. OpenAI said, no, Grock.
Jordan Wilson [00:09:11]:
You guys lied on these benchmarks, and Grock's like, no. You use Khan's sixty four as well on your benchmarks. Here's the thing that I didn't really see anyone else talking about. Yes. OpenAI use Khan's sixty four or, you know, the best of 64, but only when comparing its own models. Right? And and kind of going to show that when you gave a model like o3 Mini high extra compute, that is what makes it the high variation of that. Right? They they were essentially showing how much extra juice you can squeeze out of the model, you know, on this high mode or giving it 64 attempts, to get an answer right. But I haven't seen anyone except now Grok and XAI use this cons 64 benchmark to compare itself to different models.
Jordan Wilson [00:10:04]:
That is not something that OpenAI did. Right? In this instance that they're talking about, OpenAI was just comparing, its own internal models with the cons 64, not external models. So a bunch of geeky, benchmark drama going on in the AI world, but that is not the only controversy that Grok is already facing. Yeah. I would love to say I'm surprised, but I'm not. Alright. And, y'all, I I'm not trying to get things political here. I know people are gonna you know, people sending me hate mail.
Jordan Wilson [00:10:37]:
This is just what happened. Alright? I don't know why people get so mad, like, at me. And they're like, oh, Jordan, you're making this so political. I'm like, no. This is just facts. This is just facts. This is what happened. So save your grumbling for someone else.
Jordan Wilson [00:10:49]:
Alright. So, XAI's Grok three chatbot has been reported to have its search capabilities censored, sparking controversy over free speech and the truth seeking promises made by Elon Musk. So this is according to reports in recent users. And when I saw this, I did replicate this and, yes, this is actually or was actually true. So again, Igor Babushkin from XAI confirmed a system prompt update was reversed after user feedback indicating internal misalignment with company values. So users noted that Grok three's search instructions, had previously told the model to disregard anything that it saw online. Right? Because, Grok has, access to the Internet and obviously has access to Twitter. So there was a system instruction that told Grok to ignore anything that said Elon Musk or Donald Trump spread in, spread misinformation.
Jordan Wilson [00:11:55]:
Right? So a couple online sleuths, you know, it's whenever new models come out, people try, you know, thousands of different things to see, you know, what's maybe not correct, what's maybe, misaligned in a model, and this is something that was obviously pretty bad. Right? If you're trying to be the free speech platform and you are giving specific system instructions saying, hey. If anyone asks about misinformation and, you know, who spreads it, don't mention Elon Musk or Donald Trump. Yeah. Right? Not at all. So, the the move, like I said, contradicts Musk's previous assertions that x, the platform hosting Grok, is dedicated to free speech. So Grok three has taken unexpected political stances, Also, listing Donald Trump first when asked about who deserved a death penalty. Yeah.
Jordan Wilson [00:12:44]:
That's not good. And labeling, like we said, Musk as a major misinformation source. XAI has responded by adding a prompt to prevent grok from commenting on death penalty cases. Yeah. So people were actually saying, hey. Who deserves the death penalty? And it came back naming names, including US president Donald Trump, so that's not good. So the team has said that there is a permanent fix. And since I'm not putting those type of, prompts out there into existence, but, since people have shown that that has been kind of fixed.
Jordan Wilson [00:13:21]:
So this behavior highlights the challenges Musk face in balancing free speech with controlling narratives, especially as GRAC three continues to express views contrary to Musk's apparent political preferences. And that's just the beginning of it. There's a whole other, very serious issues with grok. It was readily giving out instructions on how to make drugs, how to make chemical weapons of mass destructions, things that large language models should not be spitting out. So I guess we'll have to keep an eye and hope GRAC becomes a little less unhinged, because that's not good. Alright. Moving moving on, moving on. Yeah.
Jordan Wilson [00:14:09]:
Now we have more AI misuse. Who would have thought? Alright. So OpenAI has identified and disrupted attempts to misuse its AI tools in Chinese influence campaigns, including spreading Spanish language anti US disinformation. So according to reports, this is, so according to OpenAI, one of these campaigns was called sponsored discontent, and it used chat g b t to generate anti American Spanish language articles and English language comments. So these articles were distributed across various Latin American news sites, sometimes as sponsored content, while comments appeared on platforms like x. Yeah. You know, all the time when I say, you know, people ask me like, hey. Are you gonna use Grok? Should businesses use Grok? And I'm like, absolutely not.
Jordan Wilson [00:15:05]:
And this is one of the reasons why. I told you a couple of them and some of the controversies that Grok is facing right now. But the other thing is Grok relies heavily on x, and it has been widely shown, that the x formerly known as Twitter platform not only has the highest rate of disinformation and misinformation versus other social media platforms. No social media platforms are perfect. Right? And Meta also, you know, uses, its platforms and its training data for its llama models, but not at the level in the frequency that Grok does and that Grok uses x a, you know, x content. So this is just another reason why you gotta be careful and it's there's a lot of bots. Right? There's a lot of bots. So, you know, OpenAI found that, it's, GPT technology was being used to spread, you know, kind of, this pro Chinese and anti American, disinformation on platforms like x.
Jordan Wilson [00:16:05]:
I already said that couple weeks ago. I believe I said that in my, AI predictions and road map series. Right, that AI was gonna be used in a lot of bad ways, by, China. So Ben knee Ben Nemo from OpenAI's intelligence team noted this is the first known instance of Chinese influence operations targeting Latin America with translated articles. So there was another campaign called peer review, and it involved using ChattyPT to create marketing materials for a tool allegedly used to report protests to Chinese security services. So OpenAI has banned the involved accounts, citing violations of policies against using AI for unauthorized surveillance. Alright. Let's get to robotics.
Jordan Wilson [00:16:59]:
So figure, a robotics startup from Silicon Valley has introduced Helix, a new AI model for humanoid robots. So the Helix model allows robots to handle objects, collaborate with other robots, and control their upper bodies more smoothly. So this new launch of the Helix platform follows Figur's decision to end its collaboration with OpenAI and raise $1,500,000,000. So, yeah, Figur, made made some headlines about three or four weeks ago when they said, hey. Yeah. We're ending our partnership with OpenAI, because in their first figure o one model, it was using, Chad GPT's or OpenAI's models, both their vision, their speech to text, and just their full four o model was using it for the figure o one. So now we saw this, kind of what figure decided to do instead, and it did look fairly impressive although the demos were extremely, limiting, but Helix could represent a significant step toward integrating humanoid robots into everyday home environments. So unlike previous models, Helix does not require extensive training on specific tasks, enabling interaction with unfamiliar objects.
Jordan Wilson [00:18:20]:
So in the demonstration video, Helix powered robot successfully put away groceries, showcasing their practical applications. So, figure did say in this demo video, essentially, it was giving them groceries to put away in a simulated kitchen. There were two of these new figure robots presumably running the helix, kind of model or the helix system, and it was said that they hadn't been trained on these items. Right? So there were some grocery items and some other things that were placed on a counter. And then these two, figure AI robots silently put away the groceries and worked with each other, so they handed each other things, which I thought was both pretty cool. Right? Because there's times like, I got home late last night. I didn't wanna put away the groceries. Alright? But I had to.
Jordan Wilson [00:19:10]:
Would I want two humanoid robots putting away the groceries? I don't know. Maybe. Maybe in the future, but a little weird. I actually found it a little unsettling that the robots weren't talking. Right? Like, I think figure was was trying to show, like, oh, look how, you know, smart these AI, these these humanoid robots are. They can you know, first, they haven't been trained on these models. Like, oh, the apple goes in the dish and, you know, the cold thing goes in the fridge. Right? So, Figure said that they weren't trained, specifically on all of these, items, but they weren't communicating, which I don't know.
Jordan Wilson [00:19:50]:
At least when I think about it, when and if there's a humanoid uprising, I would like for them to be talking to each other so at least I can understand what's going on. So although it shows some pretty, emergent capabilities, I don't know. Personally, I found it a little disturbing that they did that they were collaborating silently. So Figurs founder, Brett Adcock, highlighted a major breakthrough in robot AI, like I said, achieving this helix model entirely in house. So the company is reportedly in talks to raise another $1,500,000,000, valuing it at nearly $40,000,000,000. So, yikes. I don't know. Are you guys excited, about this? Angie from LinkedIn says silent grocery agents are creepy, and asking, are they just listening and watching us? I don't know.
Jordan Wilson [00:20:47]:
Joe says, I don't want chatty robots putting away groceries away when I'm trying to sleep. So I don't know. Maybe people want, multiple humanoid AIs, you know, silently going around and, doing things. I don't know. I would I would prefer hearing actually what they're saying, but that's just me. That's just me. Alright. Some other big, big AI news, not necessarily on the large language model side, but Google has introduced an AI system called AI co scientists designed to help scientists formulate new hypothesis, potentially accelerating scientific and medical research.
Jordan Wilson [00:21:23]:
So this AI system uses unique methods involving AI agents that generate, debate, and refine ideas before presenting them to human scientists. So unlike other AI models, AI coscientist produces new ideas rather than summarizing existing ones, setting it apart from reasoning models like OpenAI's o3. So the system has been powered by, by Google's Gemini two point o, but can work with any large language model offering flexibility across various fields. So the AI coscientist comprises several specialized agents that work together to generate, review, and refine medical hypothesis, simulating a team of research assistants. So during testing, the AI coscientist successfully generated a hypothesis about antibiotic resistance that match findings from an independent study demonstrating its potential effectiveness. So while the AI coscientists can perform complex tasks, it is designed to collaborate with human scientists, not replace them. So The US and UK have initiated fellowships to study AI's impact on scientific research with funding from the Alfred p Sloan Foundation and The UK Government. So according to researchers, these advancements in AI could significantly augment biomedical and scientific discovery, ushering in a new era of AI empowered scientists.
Jordan Wilson [00:22:52]:
So I've been saying this for many years. Right? I've always said the future of large language model is many small language models. Right? And we're kind of seeing that here, with Google's co scientists. Instead of just, you know, having 10 different versions of Gemini two point o, and each of them just take a small section of the task. These are specially, developed essentially small agents, and these agents just have one role. So it's think of it as a narrow focus. You know? Sometimes we talk about, you know, ANI, artificial narrow intelligence versus AGI, artificial general intelligence and write these large language models are trying to tackle artificial general intelligence, which means they're trying to be the best at everything. But, you you know, and we're we're not just talking from a, an LLM perspective.
Jordan Wilson [00:23:44]:
We're talking from an agentic perspective as well. Right? That's why I think early on, the early buzz of agents in, you know, late twenty twenty two, early '20 '20 '3, at least LLM powered, agents. It was these agents. It was like one agent that was trying to do absolutely everything, where I think what we just saw here, from Google with coscientist is going to be the larger trend, throughout the industry is you're just gonna have, at first, maybe a handful, but then dozens, but eventually, hundreds of, agentic, AIs working with each other, but really just fine tune for one very specific task. Why? Well, narrow intelligence, is much easier, to achieve than general intelligence. Right? So if you train a model or if you fine tune a model, specifically on one area, let's say, medical or, you know, researching, potential reasons, antibiotics fail as an example. Right? If you train one model on just that, it is going to perform much better than the larger model that it was distilled from that was not, trained specifically on that. So pretty exciting stuff, there from Google.
Jordan Wilson [00:24:55]:
Alright. Our next piece of AI news, some unsettling one. But the Trump administration is planning to cut almost 500 roles at The US Safety Institute housed within the National Institute of Standards and Technology or NIST. So this is according to reporting from Axios. So these cuts are significant as they may deeply impact AI safety and regulation efforts, potentially leaving the a AISI as gutted. So the AISI has been instrumental in overseeing AI model testing and collaboration on regulation efforts with companies like Anthropic and OpenAI. So, yes, for the last year or so, the big AI labs have been working, with the US AI safety institute to make sure, to make sure new models that they release are safe. Well, might not be happening anymore, with this new, with this recently, created USAI Safety Institute now reportedly being gutted.
Jordan Wilson [00:26:04]:
So the cuts also affect semiconductor production, including quote, unquote, from Axios, seventy four postdocs, fifty seven percent of CHIPS staff focused on, incentives, and 67% of CHIPS staff focused on r and d. So, the decision seems contradictory to the Trump administration's goal of achieving AI dominance over China, especially consider considering the national concert, national security implications of the CHIPS initiative. So the anticipated firings follow the exclusion of AISI staff from the recent AI action summit in Paris and the resignation of AISI director Elizabeth Kelly reportedly due to political pressure. So this development is part of Trump's broader AI agenda, which prioritizes AI dominance over safety and regulation. Alright. New news. I guess we have a name now from Mira Mirati's newest, company. So Mira Mirati, the former CTO, the chief former chief technology officer of OpenAI, has officially unveiled the name of her new AI startup called Thinking Machine Lab, aiming to address significant gaps in advanced AI systems.
Jordan Wilson [00:27:34]:
Sorry. Thinking Machines Lab. So the startup's mission is to make AI systems more understandable, customizable, and generally capable according to a blog post shared on Tuesday. So it's not just her at the top of the ticket. There's some other big names, from OpenAI and other, big tech companies. So John Shulman was a cofounder of OpenAI, will join Mirati as the chief scientist after he left Anthropic. Yeah. So Shulman went OpenAI, Anthropic, now going over, to Thinking Machines Lab.
Jordan Wilson [00:28:12]:
Also, Barrett Zoff, previously OpenAI's vice president of research, will serve as the chief technology officer, and at least seven former OpenAI staff, have joined the team. The team also includes researchers from top AI companies like Meta, Google DeepMind, Character AI, and Mistral. So Mirati left OpenAI in September to explore new opportunities and was reportedly in talks to raise over $100,000,000 for her new startup. So, well, what is it all about? Well, the new venture is significant for the AI industry as it highlights a trend of key talent moving to new projects and potentially, shaping the future this direction of AI research and applications. So it should be, interesting to see what Murati and, her teammates cook up at Thinking Machines Lab. So we don't have a ton of new information about what they're gonna be working on aside from addressing the gaps in advanced AI systems and to make AI systems more understandable, customizable, and generally capable. So not exactly sure what that is actually going to mean yet, but, Mirati did assemble a pretty impressive, roster of talent, to get Thinking Machines Lab off the ground. 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 GenAI.
Jordan Wilson [00:29:58]:
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 GenAI. 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 build a straight path to ROI on GenAI. Michael says he's excited for Mira's company. Yeah.
Jordan Wilson [00:30:54]:
I'm excited to see, what they cook up as well. Alright. Speaking of cooking up, you can now cook up some new AI video with Google's VO two. So Google DeepMind has announced the cost structure and availability for its v o two video generation model, which is now accessible via its cloud API platform. So, creating a video using v o two is priced at 50¢ per second, translating to about $1,800 per hour on the Vertex cloud as noted by Google DeepMind researcher John Baron. For context, the blockbuster film Avengers Endgame cost approximately $32,000 per second to produce using traditional methods. So, yeah, $32,000 for a very highly visual blockbuster film, like avengers endgame, where right now it's 50¢ per second, for v o two. Obviously, those two things are not the same.
Jordan Wilson [00:31:58]:
Right? Don't think they are. I'm not trying to draw a comparison, but, you know, you might be thinking 50¢ a second. Is that expensive? You you know, how much do well, there there you go. $32,000, per second for high end cinema. Yeah. I called Avengers Endgame high end seminar. That's I like it. I watch Marvel movies.
Jordan Wilson [00:32:19]:
I I have hobbies. Right? It's almost like I'm arguing with myself as I don't sleep and just read and talk about AI all day. I'm like, yes. I'm a real boy. I have hobbies. Alright. So, although Via two is more expensive than OpenAI's Sora, which charges $200 per month with no usage cap, it remains a more affordable alternative to conventional filmmaking. So the pricing only covers the AI generation process, but additional cost obviously for human labor and multiple iterations to achieve desired results should be considered.
Jordan Wilson [00:32:55]:
Yeah. So, you know, obviously, a human still needs to go in there and work with this. So that's not the total cost. Right? This is just the cost to actually produce it. So AI enthusiasts and professionals could consider the potential of AI models like v o two to completely change video productions and its implications for cost savings and efficiency in creative industries. So aside from the API, v o two has also just been released across a variety of platforms. So we talked about it last week. It was released in a limited capacity, in YouTube shorts.
Jordan Wilson [00:33:32]:
You couldn't use the full v o two model, but now you can. So you don't just have to, you know, cook it up, you know, with your own developers using the API, because now FreePik and FAL, I don't know if that's Fall AI or FAL AI. Right? But Free Pick and FAL, also have this service baked into their video generation platform. So, this is pretty exciting news because, well, number one, I'm surprised. Right? I'm surprised that Google did not make this a video on its front end or did not make this v o two available on its front end for the general public yet. I'm assuming that will come, at some point once they figure out pricing, but they did make it available via the API. And what that means is just about any video generation company out there that uses, multiple APIs, as an example, free pick and fall or FAL. Right? They can start using v o two.
Jordan Wilson [00:34:30]:
And why is this important? Well, v o two is hands down the best AI video model out there. It is better than OpenAI's Sora. It is better than Cling, out of China. It is better than Adobe Firefly. Right? And I'll say it's not even necessarily close. So the v o two model is extremely impressive. And I will say this, Sora, we got a a a tease of it first. Right? And then we, had to collectively wait like eight months, but at least it's now available for anyone inside OpenAI's platform, when you go to Sora.com.
Jordan Wilson [00:35:08]:
So it's interesting that Google didn't release this on its own platform first. Right? Where you can, like, log in and use it. Right? You have to use it via the API or one of these other third party service providers, or you can use it in a very limited capacity, in the YouTube shorts section. But it is by far the best AI video model, and I will say it is the first AI video model that I think will confuse the general public. Right? Because I think with even with OpenAI's Sora, which I would say is probably in second place, I think there's, you know, some some competition there for who's next best after Google's v o two. But I'll say with Sora and a lot of these others buying for second place, for the most part, you can tell. Right? If you just take your first shot out of Sora, you can usually tell it's AI generated. Right? It struggles a little bit with physics.
Jordan Wilson [00:36:01]:
It struggles with understanding real world simulations. Google, not as bad. Right? It's not perfect. Right? I think there is one kind of viral example, that, you know, once all these platforms were, released because there are some, trusted testers, that did get early access to VO and can go use it inside Google's platform. But there was one kind of famous, or viral, comparison video. It was someone, cutting tomatoes. Right? A close-up of someone cutting tomatoes and and and Sora and and all the other, you know, some of the AI video, video generators from from China and, you know, Runway and and all these others really struggled. Right? And and sometimes it was cutting a finger and sometimes, the the tomato just kinda cut itself or, you know, you keep chopping the tomato and it just wouldn't come out into little slices.
Jordan Wilson [00:36:50]:
And then the v o one was extremely impressive. Right? So I do think this is the first video that will confuse the average, human viewer, in terms of it's real. Right? And, yes, you can start with an image as well. So you can get a you you know, use some of the best platforms out there like MidJourney. Get a get a still image, and then create a video that looks very realistic. So there's obviously some great upsides to this. Right? Like, maybe corporate training videos are gonna get updated, the ones that haven't been updated since 1997, and they're still, like, a three by three aspect ratio. Right? And they're terrible.
Jordan Wilson [00:37:32]:
Right? So maybe there's there's good use cases, like, old you know, companies are gonna be able to create more engaging content. They're gonna be able to update more videos at a cheaper cost, and smaller companies are gonna be able to produce high quality videos that just didn't have the budget or the talent or the expertise to create before. But, obviously, there's a ton of downsides with this because I think people are not going to be able to realize what is real and what is fake, especially when the next version comes out. But I do think with enough generations and in the hands of a skilled, person, it is it can be hard at least in short little bursts to tell if v o two is real or not. Alright. Our kind of our last piece of AI news, well, Microsoft has a quantum leap. So micro Microsoft has announced a significant milestone in quantum computing with the unveiling of its Majorana one chip, which could revolutionize industrial scale problem solving. So, also, they said they discovered a new state of matter, but we'll leave that sign that discussion for, like, the scientists.
Jordan Wilson [00:38:39]:
This is an AI podcast. Right? I don't I I don't understand that part. But the announcement led to a boost in shares, for quantum computing companies, with D Wave Quantum up nearly 10% and Riggette, computing rising 2.5%. I got that wrong. Righetti computing. Right? So the the whole quantum computing industry, with this Microsoft announcement just went boom over the weekend. So, Majorana, one is a quantum computing unit or a QPU. Yes.
Jordan Wilson [00:39:13]:
I know. Now we have CPUs, GPUs, NPUs, TPUs, and QPUs. I guess we're just gonna p u everything until we run out of other letters in the alphabet. So, my around one is a quantum processing unit or QPU that utilizes a new type of qubit to the topological qubit described as small, fast, and digitally controlled. So Microsoft claims its architecture can potentially fit a million qubits on a single chip, surpassing IBM's goal of a 100,000 qubit quantum supercomputer by 2033. So yeah. Microsoft said, IBM hold my QPU, and they just said we're gonna 10 x it. So the development marks a transition from scientific exploration to technological innovation after Microsoft has been researching this for, apparently, more than seventeen years.
Jordan Wilson [00:40:16]:
So quantum computing is expected to transform, well, all fields, and that's why it's important if you're following generative AI. But, it's especially, expected to transform fields like pharmaceuticals, cybersecurity, and supply chain optimization, although mainstream applications are still years away. But despite enthusiasm, industry leaders like NVIDIA's Jensen Huang and Meta's Mark Zuckerberg caution that practical quantum computing is still a long way off. So quantum computing is expected to revolutionize field revolutionize fields such as, like I said, pharmaceuticals, cybersecurity, and AI, although it's gonna be a while until we actually see this, into fruition. So we don't cover quantum computing a ton on the show. We did cover it, once, but here's why it's important for AI. Think of it like this. It will make everything thousands times faster.
Jordan Wilson [00:41:15]:
Right? So think of all the the the the power in the compute that is needed right now, to train new models and when we actually use them. If quantum computing comes to fruition, right, and if this new, Majorana one chip, does help in that quest, everything will be like I mean, according to reports, up to a million times faster. Because, again, I'm not an expert in this, but how traditional computing works is you essentially have one part of a computer, working on one task at a time. Right? It can't work in parallel. You know, one part of a computer works on one part of the task, then the next part of the computer works on another part of the task. Whereas this, with this, new Majorana one, reportedly, it'll just have, like, a million, qubits working on every single possible explanation or part of a problem in parallel. Right? So things that would literally, in theory, take thousands of years could be done in seconds when and if quantum computing is achieved. So this does not mean we've achieved quantum computing, but, this is a pretty big milestone in a quantum leap on the, quantum quest from Microsoft.
Jordan Wilson [00:42:39]:
So, we probably won't be covering this too much as it's not, like, super generative AI, but it is something that impacts literally everything because, you know, then instead of, you know, having, you know, to use a hundred thousand GPUs or 200,000 GPUs over the course of a year. Right? It's a very time consuming, energy consuming, costly process. In theory, you could do all of that training async. Right? You could run it simultaneously and probably get it done in, I don't know, like a minute or something like that. Right? Again, is is that science fiction? Maybe a little bit, but it's starting to look like more near term science fact than science fiction. So pretty interesting. Alright. So let's wrap it up and say there might be some new announcements maybe as soon as this week.
Jordan Wilson [00:43:33]:
So according to the grapevine and the grapevine is, you know, just, people on on Twitter and, reporters on the Internet, Anthropic may be releasing a new version of Claude this week because tipsters online are saying that they've seen references of Claude three point seven SONNET, which would be Anthropic's newest model, which come on, Anthropic. Like, everyone was saying, you know, they updated, SONNET 3.5, and they just called it SONNET 3.5 new. And everyone's like, yo, just call it SONNET 3.6 or something. Right? But apparently, we may be seeing a an announcement on Claude three point seven SONNET, which would have reasoning capabilities, and kind of that extended thinking for detailed step by step problem solving. And it would offer users reportedly offer users the choice between quick responses and a thorough analysis, making it ideal for AI agents, complex workflows, and customer interactions. So according to rumors, claw 3.7 SONNET is, Anthropic's most intelligent model to date and the first to offer extended thinking. So kind of this hybrid, model, situation, right, where it uses a little bit of the quote unquote old school transformer, but then it also uses a reasoning model. So, it is reported that, Amazon could be, announcing this or anthropic could be announcing it in step with Amazon Wednesday, at the Amazon AI Alexa event.
Jordan Wilson [00:45:04]:
So we'll be covering that this week. And, also, there's rumors that, you know, whether it's right around the same time or in the weeks after, OpenAI might be releasing their new GPT 4.5, technology shortly after, Anthropic releases their new hybrid version of Claude. So, again, this is all rumors and rumblings, but we are beginning to see some, kind of snippets or breadcrumbs of this in code. Right? So I believe this was spotted on, Amazon Bedrock system showing, Claude three point seven as a model choice, and then was reportedly, taken down. So we'll see its rumors and rumblings for now, but AI does not sleep. And maybe I should start sleeping a little more. Alright. I hope this was helpful y'all.
Jordan Wilson [00:45:53]:
If it was, please repost this. Right? So if you're listening, on YouTube or Twitter, please don't just keep everyday AI as your secret cheat code. Right? Our team spends so much time every single day making sure you, dear listener, are the smartest person in AI at your company. So when someone's like at your company is like, hey. Should we be using Grok? Right? We've been using, OpenAI for three years, and they're like, let's get off Grok. You at least know, hey. There there's a couple things we should we should be considering, right, in this conversation. Right? Our goal is to make you the smartest person in AI at your company so you can grow your company and grow your career with generative AI.
Jordan Wilson [00:46:32]:
So if that is you and if this was helpful, please consider sharing this. If you're on the podcast, thank you for listening. Please subscribe to the show. Leave us a rating. We'd appreciate that. Also, go listen to episodes four forty three through four forty seven, our twenty twenty five AI predictions and road map series. Thank you for tuning in. Go sign up for the, newsletter, youreverydayAI.com.
Jordan Wilson [00:46:55]:
See you back tomorrow and every day for more everyday AI. Thanks, y'all.