Ep 210: OpenAI’s Sora, Gemini releases Ultra 1.5, NVIDIA’s Chat with RTX – AI News That Matters

Exploring Large Language Models

In a digitally convergent world where copyright infringement is a major concern, a potential solution has been suggested - a legal system approach. This method, that advocates resolving IP conflicts in courts encourages a constructive dialogue between content creators and users, thereby ensuring a balanced enforcement of watermark attributions and policy for fair educational use. As we advance technologically, an increase in judicial proceedings related to copyright infringement, IP, and watermarks is anticipated.

Benchmarks and Emerging Software

The continuous race to produce top-performing AI tools has resulted in notable achievements such as the Gemini Ultra 1.5's 87% increased performance on benchmarks. Yet, access for smaller workspace accounts and understanding of product releases remain valid concerns. In a similar context, NVIDIA has released new software "Chat with RTX" with specifics about PC and GPU requirements. These tools aim to support file searches and data incorporation, opening new avenues for efficient data management.

Subverting Misinformation

Generative AI has been plagued by misrepresentation and misinformation. These issues hinder its advancement and adoption by the masses. Awareness and understanding of the actual facts surrounding this technology can help businesses utilize it effectively. Across the digital landscape, tech companies are making unofficial agreements to curb the spread of mis/disinformation, particularly as the 2024 elections approach, and the specter of generative AI meddling becomes a real fear.

AI Content and Legal Implications

AI content agreements are creating a shift in how AI companies gather data from platforms, highlighted by the recent $60 million annual AI content deal by Reddit. These agreements have ignited debates about the futures of content providers who could potentially exit the business, initiate legal action, or form partnerships and unions with AI companies. These considerations are reshaping the roadmap for the future of generative AI.

Generative AI Developments

Developments in generative AI are mirrored in innovations like OpenAI's new text-to-video model, SORA. High-quality results and longer video generation distinguish this model from available ones, albeit it's not yet publicly available. However, future application is also an area of hot discussion within the tech community. Opportunities to delve deeper into SORA and its prospective impact are inspiring much curiosity.

AI Agents and the Future

Speculation is rife about the future of AI assistance with models possibly evolving to become more interactive and efficient. We've already seen the announcement of the development of AI agents designed to control devices and complete tasks across websites and applications. Such advancements pose interesting implications for businesses and professionals alike, as these tools streamline tasks and improve productivity.

Rising Investments and Collaboration Against Misinformation

The announcement of mammoth investments into AI development, upward of $7 trillion, indicate the significant belief in the future of this technology. Simultaneously, there is an increasing commitment among tech giants to combat AI misinformation and disinformation, particularly ahead of election seasons. Agreement on collaborative measures among these companies has become essential in today's political climate due to the lack of AI-related legislation.

Deceptive Content and Election Integrity

The emergence of deep fakes has raised concerns about their potential impact on US elections, adding to the urgency for strategic measures to maintain election integrity. Collaborative measures to combat AI-generated deceptive content highlight the shared responsibility among tech companies, governments, and lawmakers to curb the misuse of such progressive technology.

AI Outlook

The future of generative AI holds exciting advancements and important implications for businesses. Ensuring factual understanding of these developments is essential. A proactive approach towards learning and adapting to this rapidly evolving landscape can help businesses leverage generative AI effectively, fostering growth and prosperity.

Topics Covered in This Episode

1. OpenAI's Sora
2. Google Gemini 1.5
3. NVIDIA Chat with RTX
4. Andrei Kapathy's departure from OpenAI
5. Reddit's AI content deal


Podcast Transcript

Jordan Wilson [00:00:16]:
Even if you were trying to keep up with the AI news this week, good luck. When it comes to the generative AI space, the last 7 days have been absolutely nutty. There's been so much happening, so much news that actually matters to all of us. So, that's what we're going to be talking about today on Everyday AI. Welcome. My name is Jordan Wilson, and I am the host in Everyday AI. It's for you. Well, it's for all of us.

Jordan Wilson [00:00:46]:
To help us all keep up with what's going on in the world of generative AI and how we can use it to actually grow our companies, grow our careers. Alright. So, we do this once a week. On Mondays, we go over the AI news that matters. So you don't have to spend 3 hours each day trying to keep up. You can just spend about 20 to 30 minutes on Monday morning, and we'll sift through all the nonsense, and we'll tell you what actually matters to growing your company and to growing your career. And there was a lot this week. There's a lot.

Jordan Wilson [00:01:18]:
Alright. So, we're gonna get into it, but before we do, as a reminder, if you haven't already, make sure to go to your everydayai.com and sign up for the free daily newsletter because, yes, we're gonna be going over the news that matters over the last week, but, man, we still have a lot of other daily news that you should be looking at as well. SoftBank looking to raise a 100,000,000,000, a new Mistral model, Apple building an AI coding assistant to compete with Microsoft GitHub, 11 Labs with some new announcements. So much late breaking news. But, if you haven't already, make sure to sign up for that free daily newsletter so you can keep up. And I tell people we have what I think is one of the greatest and largest resources of free generative AI information on the entire Internet. We've had more than 200 and, I think, 10 episodes now, and you can go back, read, the newsletters for each and every one. You can go back and listen to the podcast.

Jordan Wilson [00:02:10]:
You can back on our website and watch the livestream and learn from, more than a 120 different experts that we've interviewed, so make sure you go do that. Alright. And if this is helpful, please consider reposting this and sharing it to keep your network in the loop. Alright. Enough. Let's now talk about the AI news that matters for this week. So, 1st and foremost, even if you've been sleeping under a rock, you somehow probably heard wind of OpenAI's new SORA text to video model. Alright.

Jordan Wilson [00:02:43]:
So let's go over high level what this is and what it means. Alright. So, so OpenAI has announced their new text to video model called SORA. So a couple highlights that I think separate this from other, text to video models out there. Some of the big players you've probably heard of are Runway and PEKA Labs. Also, the big players have been, announcing their own models as well. Google has announced Lumiere. And then you also have Meta that has announced emu video.

Jordan Wilson [00:03:19]:
But at least the publicly available models right now kind of leading the space are Runway's, Gen 2 and Picolabs 1.0. So here's kind of some some things that you need to know about OpenAI's new model, SOARUP. The biggest differentiator is the quality. Y'all, like, when I first saw this, I I posted a comparison video, and I'll I'll leave that in the show notes, today as well. But if I'm being honest, I could barely believe it. I could barely believe it. I'm like, is this real? Right? Which to tell you the truth, I never really do that with GenAI. You know, I've used 100.

Jordan Wilson [00:03:58]:
I should probably keep track somewhere because it's probably getting near a1000, but I've used hundreds, personally used hundreds of generative AI tools. Some are like, oh, okay. Yeah. That's that's nice. That's useful. This is one of the few. Again, it's not open to the public yet, but this is one of the first that I've looked at. I've looked at the results and I've said, there's no way.

Jordan Wilson [00:04:20]:
You know, there's no way. But it's, you know, apparently true. Right? So originally, I I was even hesitant to share about it, you you know, on LinkedIn or to even tell people about it because I'm like, alright. There's there's no way this could be a ruse. Right? And I waited because eventually, Sam Altman was the CEO of, OpenAI and, obviously, their popular product chat g p t. Sam Altman, was sharing new videos in real time based on what people, were kind of talking about on Twitter or requesting on Twitter. So, you know, you saw mister beast asked for, I think it was a monkey playing chess in a park and, you know, within minutes, there was a video posted. So it was so good.

Jordan Wilson [00:05:04]:
The quality was so good. I didn't believe it at first, which, again, for the hundreds of generative AI products that I've seen and I've used and we cover them, you know, we cover, you know, a handful of new products every single day in our newsletter. I couldn't believe it. The quality was that good. It's it's in another category. It's in its own category right now. Right? Like, I I wouldn't, you know again, we do have to wait until the model becomes publicly available, but it's in its own category right now. So another big thing that I think separates, this new model from others is it can go up to a minute long for video generation.

Jordan Wilson [00:05:43]:
So put in a short text prompt and you get a video that is up to a minute long versus normally, you know, these other platforms are normally around 4 to 5 seconds. And, you know, some you can kind of extend them, up to maybe 16 seconds. So a couple other things that are important to keep in mind, it's not publicly available yet. And then also, it's, right now, it's only available to red teamers, which are people who check it for safety, and a select group of artists and designers. But, like I said, so far, the results so far out exceed everything, and it's not even close. It's not even close. Yeah. I, I I I definitely agree, with doctor Harvey Castro here in the comments saying, the SOAR infrastructure hints that we are closer to AGI.

Jordan Wilson [00:06:29]:
Yes. You know, there's some interesting concepts, in SORA. And, you know, we'll make sure to share, more in the newsletter because this is one of those things that you just kinda have to see to believe. It is very hard to describe, on a podcast or even on a live stream showing you screenshots, but it is extremely extremely impressive. So impressive we are having a dedicated show tomorrow. So if you do want to know more, about the new, text to video model from OpenAI, the SORA model, make sure to tune in tomorrow because we're gonna be talking about the larger impact that I think no one's talking about because I think this model from, OpenAI hints at something much larger than text to video. Alright. So make sure to join us tomorrow for that one.

Jordan Wilson [00:07:19]:
Alright. Our next piece of AI news that matters is Gemini Ultra 1.5 is released. Well, it's kind of released. Alright. So we'll get to that. But, this is the new model from Google. So right now this is why I said it's kind of released. Right now, it's only developer and enterprise customers have access to a limited preview of Gemini, Gemini 1.5 pro via the AI Studio and Vertex AI.

Jordan Wilson [00:07:50]:
So if you are a, kind of a Gemini advanced customer right now, you do not have access to Gemini 1.5 unless you are a developer or enterprise customer accessing it through their, AI studio or Vertex AI. So, a couple of things that are important to keep in mind here, some of the improvements, of of of the model, let's talk about that. 1st and foremost, it's the context window. Okay? So, this is from Google, again, you know, it's not really out there in the wild, so not a lot of people are able to test this yet, but, a 1,000,000 token context window for enterprise customers. And then your normal commercial customers are gonna get 128 k tokens. Okay. So what that means, a million token context window is huge. So the way large language models work, and this is the most basic way that I can explain it and hopefully it makes sense, you know, if you're if you're driving, to work in your car or walking your dog right now without showing you a visual.

Jordan Wilson [00:08:55]:
But if you think of, you know, back in the day, the old star wars credits. Right? And you kind of saw how they came on to the screen, you know, kind of at an angle. You can see a pretty big chunk, of the, kind of the opening sequence, the words, you know, in a galaxy far, far away. Right? And eventually, you know, you'll have a couple paragraphs on the screen, but eventually, that top paragraph will disappear as new text comes on. Okay? That's essentially how large language models handle memory. Right? It can't remember, literally everything that you put in. Right? So as you have a conversation back and forth with a large language model, it'll start to forget things, right? And that's what you get into, these memory windows. So everything is a token.

Jordan Wilson [00:09:42]:
So I like to tell people this, right now, ChatGPT is probably one of the more popular, large language models out there. It has a 32 k, token memory, which is about 26,000 words. So after 26,000 words back and forth, it starts to lose its memory. So you can see how 1,000,000 tokens might be great because one of the, I think, one of the largest downsides of working with a large language model is that memory. And so many people, I would say 95 to 99% of people who are using large language models don't use them correctly. And one of the biggest things is they don't understand the memory context. So this is a big pretty big announcement here from Google, pushing to 1,000,000 for enterprise, for enterprise customers and developers. Also, this is from Google's own reporting is they said that, there is a 87% increase on their own benchmarks.

Jordan Wilson [00:10:39]:
So essentially an 87% increase, from Gemini 1.5, Gemini Ultra 1.5 versus Gemini Ultra 1.0. So 87 87% increased, performance on these different benchmarks. However, you still shouldn't go ask what Gemini is. Still is not very aware. Right? So even this morning, I have Gemini advanced right now. It is, 2 months free, and then it's $20 a month after that. But you should keep in mind, most workspace accounts. Right? So as an example, my business, we have our, you know, what used to be called G Suite, but we have our Google Workspace.

Jordan Wilson [00:11:21]:
We can't access, you know, Gemini, advanced. You have to have a Google One subscription. And, for whatever reason, Google makes it very hard, right, for people small businesses that are using Google Workspace to pay money and to use their AI products. I don't know why. So, you know, I think so many people, myself included, when we're using Gemini, we have to use our personal Gmail accounts. So we can't really test it in a real world scenario where we're working, you know, with our connecting. I think one of the best, the best prospects of of Gemini is connecting with your Gmail. Right? With your work Gmail, and your work calendar, and your work Google Drive, and your docs, and your spreadsheets.

Jordan Wilson [00:11:59]:
Right? But you can't right now, for whatever reason because so many smaller workspace accounts do not have access to Google's AI products. I don't understand it. Google, can someone reach out to me and tell me what what's what's going on here? But, anyways, even even as of this morning, Google is not aware. You know? I'm asking Google, are you Gemini Ultra 1.5 or Ultra 1.0? And it doesn't give me a straight answer. It says, I'm not either Gemini Ultra 1.5 or 1.0. That's another thing. Hey. New large language model companies, when you release updates, you need to be more clear about what it is, who gets access, and your model itself in its system prompts should know specifically because otherwise there is confusion and people aren't going to adapt to your products if you are confusing the majority of customers.

Jordan Wilson [00:12:41]:
Alright. Now some more large language models. Hey. I like this here from Woosie. Woosie, thanks for the comment. So joining us live says, I feel like at 1,000,000 context window, it's gonna start being me that forgets what I'm working on in these long chats and not the model. Absolutely. A 1,000,000, token context window is so much.

Jordan Wilson [00:13:06]:
Right? It's it's it's more than, yeah, It's more than I think most human beings can remember. So that's a great point. Alright. So we have more large language model news. So NVIDIA has, publicly released chat with r t x. So they did announce this last month, but just, I believe it was Tuesday of last week, so just under a week ago, they did now publicly, NVIDIA publicly, unveil its new, I'll say software, called chat with RTX. Alright. So let's talk a little bit about what this is, what it does, and why you might wanna use it.

Jordan Wilson [00:13:46]:
K. So right now, chat with RTX from NVIDIA is a free local model that you can download on GitHub. So if you don't know what a local model is or a small small language model, don't worry. Literally just did a whole episode on this last week, so we'll make sure to link to that in the show notes. However, you do need a PC right now to take advantage of chat with RTX. You cannot access it on, at least out of the box. You can't access it on, Apple Computers on a Mac. So, it also does require a PC with an NVIDIA GeForce RTX 30 or 40 series GPU with at least 8 gigabytes of video RAM.

Jordan Wilson [00:14:27]:
So there are some, some technical minimum requirements for your PC. So for the most part, if you have an old PC from a couple years ago, probably not gonna be able to use, chat with r t x. You will need a much newer PC with specifically one of those 2 NVIDIA GPU chips, the GeForce RTX 30 or 40 series chips. And as well as 8 gigs of video RAM. So, the chatbot can use a couple different models including Mistral or Llama, those open white large language models, and you can search through local files to provide answers. That's the big thing right now. So this is, one of the first, kind of popular models, from at least, you know, your your your household names. You know, when I'm talking about that, I'm saying you know, Microsoft, OpenAI, Google, etcetera.

Jordan Wilson [00:15:19]:
This is one of the first models that brings, you know, RAG or retrieval augmented generation front and center to this new chat with RTX software. What that means is you can essentially interject, your data and have it live and stay within the model. Right? There's kind of, you know, workarounds that you can do this in chat g p t, also in Bard, and in Microsoft Copilot where you can just upload, some of your some of your documents in certain chats. But depending on which model we're talking about, they handle that differently. So a little bit differently with chat with RTX, it does kind of lead with a retrieval augmented generation or RAG approach first. So what that means is you can interact with the AI model using local files as a permanent data set and it can support various file formats like like .text, .pdf, .doc, XML files, as well as you can incorporate, which this is what I'm excited about, you can incorporate information from YouTube videos and playlist. So it should be pretty, pretty exciting. And I'm sure I'll be covering this more actually, a lot more in March.

Jordan Wilson [00:16:24]:
I will be at the, the NVIDIA GTC conference. NVIDIA is actually bringing me out there to partner with them, to broadcast from, San Jose live that week. So if you're gonna be in San Jose, in March at the GTC conference, make sure to reach out to me and let me know. We'll meet up. We'll say what's up. We'll we'll go talk. We'll go talk dorky stuff, at the conference. Alright.

Jordan Wilson [00:16:47]:
Another piece of AI news. Man, this has been a such such an action packed week. It's so much, I have to take a sip of water. Oh, man. Here we go. Another big piece of AI news that matters. And here's why it matters. Andrei Kapathy is leaving OpenAI.

Jordan Wilson [00:17:10]:
So if you don't know, Andrei is one of the most, well, like, I would say one of the most well respected and prominent figures in the field of artificial intelligence, and he just announced his departure from OpenAI for the 2nd time. So he did have this, kind of announcement on Twitter, this, tweet that he put out that I'm sharing on my screen. He said, hi, everyone. Yes. I left OpenAI yesterday. First of all, nothing happened, and it's not a result of any particular event, issue, or drama. But please keep the conspiracies coming as they are highly entertaining. And then Andre went on to say, actually, being at OpenAI over the last year has been really great.

Jordan Wilson [00:17:48]:
The team is really strong. The people are wonderful, and the road map is very exciting. And I think we have a lot to look forward to. My immediate plan is to work on personal projects and see what happens. Those of you who followed me for a while may have a sense of what that might look like. Cheers. So little bit more about Entre. So he's was a founding member of OpenAI, and he initially left in 2017 to join Tesla leading their AI teams there, and then he just came back to OpenAI just a little more than a year ago.

Jordan Wilson [00:18:19]:
So founding member, then he left to lead kind of Tesla's AI efforts for about 5 years, and then he just came back to OpenAI for about a year. So a couple other things, and I'm gonna tell you here why this matters to everyone. Well, it's right here. So Kuparthy had been hinting at his involvement via Twitter. He had this, kind of as his bio, that he was working on projects related to AI assistance, mentioning his work on, and I quote, building kind of a Jarvis at OpenAI, end quote. And then he's kind of reflecting on his vision for creating helpful and conversational AI systems. So the timing of this, I think, is particularly interesting. So it was just about a week prior to this that the first kind of, initial or official reporting came out about OpenAI's assistants or their agents that they were working on.

Jordan Wilson [00:19:18]:
So, new reporting. Again, this was about 2 weeks ago, about a week and a half ago, just before, Entre's announcement came out and said that OpenAI was officially working on 2 different types of AI agents. So one of the agents, can take over and control your device, right, you give it access to. So whether that's, you know, your your desktop or your phone, we don't know yet, but one of their agents or one of their agent functionalities is taking over and controlling a physical device. That's number 1. And the 2nd kind of agent or the 2nd agent function is being able to complete tasks for you, across websites and apps. Okay? So that sounds kind of like a Jarvis type model. Right? And the the the Jarvis, if you're unaware, that kind of stems from, the Marvel series and Iron Man and Tony Stark where he had his JARVIS assistant that could do anything.

Jordan Wilson [00:20:10]:
Right? He could talk to it, and JARVIS can perform actions on his behalf. So this is what Andre had been hinting at in his Twitter bio. And, again, the news of this preceded Andre's announcement by just 1 week. So I don't like to speculate a whole lot on everyday AI because I like to always be a fact based. Right? Fact based, media company that's bringing you the news. We bring receipts. But it is interesting, and you do have to think, are these 2 things related? Maybe Andre was not fully on board with, you know, this kind of pseudo announcement. Maybe he had a different direction for AI agents.

Jordan Wilson [00:20:49]:
I'm not sure. Or maybe everything's just great, like he said. But the timing of these things was I'd say it had to, have played into this decision. Yeah. And I agree with, Svatlana. Really intrigued what he's up to. Yeah. So you have to keep your eye on on what Andre may may be working on.

Jordan Wilson [00:21:12]:
You have to keep your eye on OpenAI and what's happening with their agents. Also related to this, it has to be related to this, is Sam Altman's out there raising 7 trying to raise $7,000,000,000,000, for GPU chips. Yes. That is a trillion with a t as in mister t. I pity the fool who doesn't understand what can be done with $7,000,000,000,000 to build, essentially an NVIDIA competitor to create these GPU chips that all these generative AI companies need to power their AI. But, also, combine that combine that $7,000,000,000,000, building your own chips, which right now, they're, very limited in availability, and then combine agents. Right and then let's talk about the future of work and talk about future versions of gpt 5 and talk about oh, when you have sora right now, you can kind of see yeah, something pretty big is gonna be happening around the corner. So you gotta keep your eyes on whatever Andre may be working on.

Jordan Wilson [00:22:14]:
You gotta keep your eyes on what OpenAI is doing with agents with this, $7,000,000,000,000. Wow. Yes. Can agree. That's a huge huge arms race. Yeah, something something's definitely going on well, here's something that's going on that's I'd say positive Alright. Another piece of AI news that very much so matters. Ready? So big tech is banding together on AI, to combat election related misinformation, disinformation.

Jordan Wilson [00:22:48]:
Alright. So, this this story kind of just kind of broke over the weekend, so we're gonna we're gonna dive into it a little bit here. And, hopefully, this will make sense on why it matters, but I'll still explain it to you. Alright. So a group of about 20 tech companies have come together to fight AI miss misinformation in elections. So some of those companies include this is not an exhaustive list, but your big names of who's who in AI and social media. So we're talking about Microsoft, Meta, Google, Amazon, OpenAI, Anthropic, Snap, TikTok, X, IBM, and others, all coming together. And kind of their goal of this is to focus on combating AI, misinformation and disinformation as well as deep fakes.

Jordan Wilson [00:23:37]:
Because according to this report, that we kind of, flashed on screen here from CNBC, That we've seen a 900% increase year over year in deep fakes. And this is obviously raising serious concern about election related misinformation and disinformation. Alright. And if you maybe aren't from the US, let me kind of bring you into where we are right now. Alright? In the next coming weeks, we're gonna start to see a lot of primaries here in the US election cycle. So what that means is over the next, you know, couple of months, the 2 major parties, democrats and republicans, go through a series of primary elections. And, essentially, these elections, determine who each, you know, 1 candidate from each party that will be representing their respective party in the November 2024 general elections. Alright.

Jordan Wilson [00:24:34]:
So for the most part, you know, it's everyone kind of knows who the candidate is, but this is, you know, still a process, that we go through here in the US. The primary election and the general election. So you have already started to see the amount of deepfakes and AI that have already been used. You know, probably one of the most prominent ones was when there was a deep fake version of president Joe Biden, that was on a robocall, and it was telling, voters in the New Hampshire primary, which already happened a few weeks back, not to go out and vote. Right? So that was obviously a deepfake. It wasn't authorized. You know, and there's a lot of investigations still ongoing. And since, the FTC has banned the use of AI robocalls.

Jordan Wilson [00:25:21]:
So companies that do that can obviously face, you know, prison, imprisonment as well as some pretty large fines. So kind of 2 separate issues, but now we have the big tech companies coming together and they're, essentially, you know, creating this accord, kind of like an unofficial, agreement between these large companies. So here's a little bit more on what this agreement means and why I think it's important to talk about. And, also, it is a very timely announcement, especially considering what we just saw was possible. This this announcement came hours after OpenAI's sorta text to video model. Right? Again, I don't think this one was a coincidence because when you have 20 companies coming together to agree on something, presumably, it's been weeks or months in the work. But still pretty interesting that this, kind of alliance, was launched just hours after we saw the, unfathomable unfathomable capabilities of OpenAI's new SLA model. So this accord, these members agree to 8 high level commitments, which we're gonna share about more in the newsletter.

Jordan Wilson [00:26:28]:
But they're mainly aiming to protect the integrity of elections and combat the risk of AI generated deep, deceptive content reflecting the industry's commitment to safeguard democracy. This is a pretty huge deal, y'all. Like, especially here in the US, it's unlike other unlike other countries or groups of nations. We do not have any legislation around AI. Yes. We have an executive order from the White House, from the Biden White House. We have an executive order on AI. We have, you know, these, kind of new, I won't even call them laws necessarily, but you have these new guidelines from the FTC, as an example, banning AI robocalls.

Jordan Wilson [00:27:12]:
But there is no actual legislation. Right? This is something that people don't fully understand about the, the legislative process here in the US. It moves slower than a snail. There is technically not even legislation. Right? So, again, we have to say there's there's rulings from governing bodies such as the FTC. There's executive orders, etcetera. But we don't even have legislation that has gone through our congress and has passed out on social media, right, which has been around for 20 years. You know we're still debating section two thirty of a law that was passed in 1996 about the internet right so I do think that this is a huge announcement from these tech companies.

Jordan Wilson [00:27:59]:
This is essentially, an unofficial handshake of sorts. Right? And they're saying, Hey. We all understand that it's important, for for the future of democracy here in the United States to to come together and say that we're gonna do certain things. We're gonna make sure we're gonna do what we can, what's in our control, to make sure that our systems are not used explicitly to create disinformation, misinformation around elections. Because here's the thing, these texts to image models like Midjourney V six, you can't tell the difference between that and a real photo. You can't. I used to be a photographer of sorts, I've taken, you know, probably 250,000 photos. I have a bunch of DSLRs sitting in a closet somewhere.

Jordan Wilson [00:28:44]:
You can't tell the difference. I don't care what anyone says. You can't tell the difference between someone that's really good at Midjourney and if if if they're creating, political images, you can't tell the difference. Especially the average person can't. Text to voice, you can't tell the difference. The models are too good, dangerously good. Right? And now we're seeing the first, what I think is a usable model for text to video in Sora from OpenAI. Can you still tell it's it's AI generated? Yeah.

Jordan Wilson [00:29:14]:
You can. Right? But, I mean, if we were talking about models that existed last week, you know, Runway and Pika, I don't think you would ever look at, what comes from those programs and think that it might be real. Right? Whereas, Sora, you might. Right? So, again, we're not sure when that's gonna become publicly available, but I think it's it's very timely. This agreement between these 20 companies, I think, is extremely important for keeping the elections here in the US as safe as possible, but don't get me wrong. It is still going to be sheer and utter chaos. I've been saying this for more than a year, that the 2024 elections, I still think, is gonna be people's a lot of people's first experience with generative AI. Because even though they're banning these, you know, these these use cases, people are still gonna use it.

Jordan Wilson [00:30:06]:
Right? And this is gonna be hard to track down, and this is gonna be hard to police, their mismanagement. So I still think this is gonna be extremely problematic for the 2024 US elections. However, huge steps, so you have to give credit where credit is due to these large companies all putting aside competitive differences. Right? Because one of these companies could have said, nah. You know, we're not gonna, you know, sign on board with this. And that, in theory, could have given them a competitive advantage. Right? Even if people were using it for bad purposes. You know? So I do love that all big companies, in social media and intact came together, as part of this agreement to protect the elections here in the US.

Jordan Wilson [00:30:48]:
Alright. Our last piece of AI news that matters this week. Reddit has just reportedly inked a new AI content deal. This is huge. Alright. So let's talk about this. So according to a Bloomberg, a Bloomberg report, Reddit has entered a new licensing deal with an undisclosed large AI company estimated to be worth about $60,000,000 annually. Alright.

Jordan Wilson [00:31:18]:
So this move reflects a shift in how AI companies are acquiring data, moving away from using open web, scraping without permission to establishing formal agreements with platforms like Reddit. Right. I talked about this a couple months ago. The, the ongoing, legal dispute between The New York Times and OpenAI and Microsoft. So, the in this lawsuit, The New York Times alleges that OpenAI has used millions of its pieces of copyrighted materials to train its models. Right? And to oversimplify this, right, because I don't have an hour to explain the intricacies, but, essentially, so many generative AI models are just trained off the history of the open Internet, which does, obviously, include a lot of copyrighted work. So it is very hard for any company out there to make an argument that their, large language models or their generative AI models are not trained on copyrighted works because most of them are. Don't get me wrong.

Jordan Wilson [00:32:21]:
I think there are companies that are taking a a much more cautious approach. You know, I think Adobe is taking a much more cautious approach approach than others. But I think what we're going to see is a lot of deals like this. A lot of deals like what Reddit just saw, where you're gonna have these companies signing what looked like man, is this this looks like professional athlete contracts. But if I'm being honest, I think whatever company signed this deal with Reddit, got a great deal. Got a great deal. $60,000,000 annually. It might seem like a lot, but when it comes to reliable information, and when it comes to SEO value even, if if if you use the Internet, Reddit, I think, has become, a lot of times, if you wanna save time and if you wanna get reputable information, a lot of times, people find that on Reddit.

Jordan Wilson [00:33:16]:
Right? The SEO world has become a mess, so you might read 10 articles, you know, when you do a Google search or you do a Bing search, you might read 10 articles and 7 of those might just be, you know, companies that have just gained the SEO system and it's just a bunch of unrelated garbage. So the content on Reddit is extremely valuable. Right? So I think a $60,000,000 deal is actually a great deal, for whichever large language model company signed this. So it could be OpenAI. It could be Google. It could be Microsoft. It could be, Amazon. It could be Anthropic.

Jordan Wilson [00:33:56]:
I would say it's one of those, but I'm I'm I'm sure we'll find out in the coming days weeks. One other thing to keep in mind about this is it's gonna set the stage. Right? Whatever happens both in this New York Times, versus OpenAI lawsuit, which I assume will be settled out of court, I don't think, it'll actually, you know, go to a judge or a jury trial. I do believe it'll be settled. But I think that's gonna set the set the tone for what large language models look like in the future because, yeah, you're gonna whatever happens between that, you know, case and what's happening here, with this agreement between a large language model company and Reddit, I think that's gonna be what it looks like going forward. So so many publishing companies, I've talked about this on the show before, there's essentially very limited options on what happens. Right? Either companies will just go out of business because they're losing traffic, because instead of people going to their website, they're just using AI search engines like Perplexity, like Google's search generative experience, SGE, using Copilot, or using ChatGPT. So people aren't visiting these websites as much.

Jordan Wilson [00:35:06]:
So either 1, these publishing companies are online, you know, information providers will either go out of business. Number 2, they'll sue, they'll sue all these large language model and big tech companies for scraping and using, their copyrighted data. Or number 3, they're going to see partnerships like we just showed here with this, with this partnership, this reported partnership, between Reddit and whatever company this is. So I think there's gonna be a lot of individual partnerships like this as well as I I've called I've called for this. I don't know if a company's out there doing it. Hey. If you wanna make a bunch of money, go do this. Create a union for the tens of thousands of high quality websites that are putting out great content online and create a union.

Jordan Wilson [00:35:49]:
Create a union of, online content producers in there. That's, you know then you can work out large agreements with these, companies to use all of this data. Alright. That's it. As always, there's a lot more in our newsletter, so make sure you go to your everyday a I dot com. Sign up for that do, daily newsletter. As well as, if this was helpful, which I hope it is, y'all, sometimes we spend 2, 3, 10 hours, researching and producing 1 single episode, which you can probably guess that's a lot for a daily show. So we would really appreciate it if you would repost this, share this if you're, you know, tuning in on social media.

Jordan Wilson [00:36:31]:
Repost this. Retweet it. Tag your friends. Keep them in the know. Because here's the thing. I think with generative AI, there's a lot of bad information out there. So many people do not care about the facts. They don't care.

Jordan Wilson [00:36:44]:
Right? They just say, hey. Here's, you know, 500 chat g p t prompts to make you rich and then they try to sell you some some crappy software. That's not what we're about here at Everyday AI. We care about you understanding generative AI. We want you to know how to use it, how to understand it to grow your companies, and to grow your career. So if you could share this, we'd really appreciate it. And, also, make sure you tune in tomorrow. I think there's something, a big impact on this new OpenAI SOAR model that people aren't really realizing.

Jordan Wilson [00:37:15]:
Yes. The quality is amazing. It's gonna change the text to video. It's gonna change storytelling, but there's something much more than that. So thank you for tuning in. Thank you for listening, watching, reading, and we hope to see you back tomorrow for that show and more on Everyday AI. Thanks

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