111 | OpenAI could be on the brink of bankruptcy, Nvidia chips delay impacting the entire AI eco-system, Google acquirs Character.AI and more AI news

0:00Hello and welcome to a weekend news edition of the Leveraging AI podcast, the podcast that shares practical, ethical ways to improve efficiency, grow your business, grow your business, and advance your career. This is Isar Maitis, your host, and every week it's jam-packed with news. If last week was the week of releases of new models, this week has actually a very wide variety of topics of news. Interesting from M &A topics to valuation topics to interesting delay topics in the deployment and interesting delay topics in both NVIDIA chips as well as Apple's AI deployment. So basically, every week we have a lot to talk about.

0:38So let's get started.

0:46The first piece of news comes from OpenAI and its financial challenges. What that means is a report on the information is stating that OpenAI is expected to lose$5 billion by the end of 2024. for. That puts them at bankruptcy risk, and they might run out of cash in the next 12 months unless they raise additional money. They state, based on their sources, that OpenAI currently spends about $700 ,000 daily just to keep ChatGPT running. Basically, all of us and everybody around the world using it, they're projecting to invest about$7 billion in training of their next model, GPT-5 or anything in between, like they've been deploying so far, like GPT-4-0 and GPT-4-0-mini and so on.

1:35They are allocating about$1.5 billion for staffing. So in the current extreme competition on talent, I'm sure they're paying some interesting salaries to interesting people. And their income is expected to only be$3.5 to$4.5 billion coming from about$2 billion from ChatGPT subscriptions and about$1 to$1.5 billion from people accessing the API. Now, the company raised about$11 billion so far from seven funding rounds. Most of the money comes from Microsoft, either in means of straight cash or in means of access to its servers to train and run ChatGPT and so on. Now, obviously, this business model is not sustainable.

2:17You cannot make$3 to $4 billion a year. And that's, by the way, extremely impressive. I don't think any company in history got to make three to four billion dollars a year so quickly from the launch of his first product, which was Chachapiti at the end of November of 2022. And in the beginning, it was completely free, so they didn't even start making money at that point. So their growth in revenue is incredible, but their growth in expenses is even more incredible. Now, what does that mean? It means a few things. First of all, they're a very different company than some of their competitors. So Google, Meta, Amazon, and even Microsoft has billions to spend on training and growing new models and the infrastructure that is required in order to run it.

3:00OpenAI does not have the revenue to do that, at least not yet. So that puts them at a position where they continuously have to raise significant amounts of money. That being said, there's a pretty clear consensus both on the side of the tech companies as as well as the investment side of the world, of the potential incredible impact of AI, which tells me that most likely OpenAI will raise a stupid amount of money in its neck rounds, an amount we've never ever seen before, probably in the tens of billions of dollars, to keep OpenAI running and keep them at the lead, or at least in competition with the other companies.

3:40But what it shows us, it also shows us the stupidly high costs that is associated with developing frontier models, which tells us all that there is going to be a very short list of companies that will be able to continue to do this moving forward. And we're going to talk about the consolidation in this market in some other news today. There's a lot of other news about OpenAI today. One of them is they just introduced a new GPT-4.0 model. So GPT-4.0 was introduced not long ago. Then they introduced GPT-4.0 Mini. was actually doing very well in comparisons to other models. On some aspects, it's actually doing better than GPT-4.0.

4:21So the mini version, which is significantly smaller and significantly cheaper to use, is ranking very closely on the LMSYS leaderboard to the GPT-4.0, even though it's about 16 times cheaper to actually use. So I think we're going to talk more about this, but that's the direction that everything is going. We're going to get cheaper, faster, and better models all the time. But going back to the new GPT-4O model, the new experimental GPT-4O model has a long output model. What does that mean? So models are being measured by their context window. What is the length of information you can put in a single chat?

5:00So you run out of memory basically at a certain point, and that is usually measured by tokens. And tokens is just a unit that all these large language models of work at, but every token is about 0.7 words, meaning if you have 128 ,000 tokens context window, it means you can fit about 100 ,000 words, both the stuff that you write in your prompts and the information you provide the chat, as well as what the chat is spitting out. So the current limit of ChatGPT for always 128 ,000 tokens, and that is not changing in this new experimental model. So what is changing is the length of a single response.

5:42So far, GPT's 4.0 limit for a single response it could give you to whatever prompt you give it was 4 ,000 tokens, which is about 3 ,000 words. This new experimental model extends the output capacity in a single response to 64 ,000 tokens. Basically, half the length of the information that can be in a single chat can come out in a single answer. That's a 16x improvement from the current model that allows to obviously ask a lot more complex and sophisticated questions and get a lot more detailed information. This is extremely useful in data analysis and detailed business use cases, as well as research and so on.

6:26So a huge improvement in that particular case. And this model comes cheaper, as I mentioned, like everything new that we're going to get, than the existing GPT-4 variants other than GPT-4 or Mini. So the pricing right now is$6 per 1 million tokens of input. So the prompts that you're putting in and$18 per 1 million output tokens, basically the inference, what the outcome that you're getting from ChatGPT. This is currently in alpha with being tested just by a few users, but they're expecting this to be just a few weeks and then they're going to roll it out to everyone. I would like to interrupt the news for a few seconds and tell you about the new course we recently launched.

7:08As you probably know, we have our flagship course called AI Business Transformation Course. We have been teaching it since April of last year and hundreds of companies have already taken the course, both privately by approaching me and building private courses for them, as well as publicly with courses you can sign up for. But there's been a huge demand and a lot of people approached us to create an offline self-paced version of that course. And we have. So that course is currently available on our website. Multiple people has already signed up since we launched it just a couple of weeks ago. So if you want to take a course with me personally as an instructor with a cohort of people that can learn from one another, other business leaders who are taking the course, that's one option.

7:51And you can find that on our website. Or you can also take it as a self-paced course, which you can do online. on your own time, and do it at your own pace. As I mentioned, it's available right now. The link is going to be in the show notes, so you can open your phone or computer right now, wherever it is you're listening at, and find the link and click it and get all the information you need. I would love to see you there and hear your feedback about the course if you're taking it. That's it. Let's go back to the news. Now, in the past few months, we had a lot of negative news about OpenAI and safety issues between multiple significant figures departing the company or changing positions.

8:28And so this week, there are news about multiple steps that OpenAI is taking in order to potentially at least change our view of their approach to safety. But one of them is that OpenAI Sam Altman just announced that the company is working on an agreement to provide early access to each major new models to the US AI Safety Institute for testing before they release it. They have announced a similar deal with the UK's AI safety body just not too long ago. And this comes again in the wake of a lot of criticism of OpenAI's approach to safety. This is obviously very good news. And I wish that there's going to be some international group that's going to monitor this.

9:11I'm going to talk more about the international approach to this and potential implications in the next few news pieces. But right now, at least submitting models to a third independent party to evaluate it for safety before release is a very good step forward. And I hope that every company before it releases its models will do the same thing. And if we're already talking about safety and regulations, then the EU AI Act is now finally in force. So the official effective date of the EU AI Act was August 1st, so just earlier this week. And just as a quick reminder, because we talked about this in multiple previous episodes, it takes a real risk-based approach to how to evaluate AI risks, low or no risk, which is most applications, and then it's not regulated, high risk, which include biometrics and medical and education and employment implications and applications that requires compliance with high risk quality management obligations.

10:11And then there's limited risks like chatbots and deep fake tools and so on that must meet different transparency requirements. The penalties for not meeting that are very severe. So it could be up to 7 % of global annual turnover for doing releases that break these rules. What does that mean? First of all, it does mean a lot immediately because most of the provisions will only be fully applicable in mid of 2026. So companies have time to do this. But there's already multiple companies who said they're not going to deploy their models in the EU for now, which is good from one perspective because it means it is keeping the safety of the EU's people from getting access to potentially harmful AI tools.

10:54The flip side of that is it's obviously dramatically slowing innovation for companies in the EU who want to harness the capabilities of AI tools. And so it's a double-edged sword where on one hand, yes, it's keeping you safe. But on the other hand, it's dramatically slowing your ability to compete in the world. And I think the EU will have to make some adjustments to its current set of rules or come to some agreements with the companies with more specific details on what's allowed and not allowed. So it will enable them to at least deploy some of their capabilities for EU members. In another move to show its commitment to safety, OpenAI announced a new development method to increase safety of models that they call rule-based rewards or RBR.

11:41are. They've made that announcement on July 24th. And the key components is that it uses clear step-by-step rules to evaluate the model's output for safety standard. And it's designed to balance between the potential harmfulness and harm prevention of the model. So going back to what I said about the EU, it's trying to find a balance between the good and the bad that can come from the model. They've already implemented that into GPT-4 and GPT-40 mini. And they're obviously planning to use this methodology in future models as well. And I'm going to quote from their announcement to tell you what they shared specifically about this.

12:18And I'm quoting now, to ensure the AI systems behave safely and align with human values, we define desired behaviors and collect human feedback to train a reward model. This model guides the AI by signaling desirable actions. However, collecting this human feedback for routine and repetitive tasks is often insufficient. Additionally, in our safety policies change, the feedback we've already collected might become outdated, requiring new data. So that's them describing the problem. So again, the problem is that it's just not good enough and probably not scalable with the amount of data that they're putting in to use only human feedback for these models.

12:59So now the solution that they're suggesting. Thus, we introduce rule-based rewards, or RBRs, as a key component of OpenAI's safety stack to align model behavior with desired safe behavior. Unlike human feedback, RBRs uses clear, simple, and step-by-step rules to evaluate if a model's output meet safety standards. This continues on and on with more details, but then they are stating that there's also obviously potential drawbacks. And now I'm quoting again, shifting safety checks from human to AI can reduce human oversight of AI safety and might amplify potential biases in the models if biased models are used to provide RBI rewards.

13:43In other words, if they don't get their equations right and their specific rule base, that will continue to go really bad because the models will continue to evolve without human supervision. So what does this tell us? It tells us that probably there needs to be some, again, external tools to evaluate the safety of these models. Hopefully, these tools will come from an international alliance that will do this, kind of like the nuclear weapon oversight that is done by the global community to monitor the development of nuclear weapons in other places. I really hope that's the direction it's going to go, even though it's not clear whether that's actually happening or not.

14:21There's been a few attempts to do that, but so far there's nothing practical out there that actually moves in that direction. Specifically about OpenAI, I don't know if that is done only because the amount of pressure that they have on them right now, both from Congress and from media, as far as reducing their investment in safety. I don't know if that's actually a good thing or a bad thing, what they're doing right now. All I can say is that we'll keep on watching and I will update you as this thing progresses. And since we're already talking about AI safety and we're talking about potential global aspects of this, Sam Altman this week had a very interesting announcement.

14:58He's stating that the urgent question over time is who will control AI dominance in the world between the democratic side of the world and authoritarian models controlled by countries like Russia and China and so on. He's saying that U.S. is currently in the lead of the development, but that lead is not guaranteed. Other governments may overtake the democratic nations in its AI capabilities. As an example, Vladimir Putin, the president of Russia, stated that the AI race winner will become the ruler of the world. China has set up clear guidelines and investments in order to have the lead in the AI race by 2030, which is not that far out.

15:43In this article, Altman warns around the potential negative consequences if these authoritarian regimes get the lead in AI. They could force companies to share data. They could develop new types of weapons and cyber weapons that nobody has ability to fight. And he goes on and gives some other examples. But he also states what he suggests or proposes that a US-led global coalition will do in order to prevent that and make sure that what he's claiming is democratic approach to AI prevails. So four things that he mentioned. One is develop robust security measures to maintain the coalition's AI lead, basically preventing these other parties from getting access to the models and AI technology that is developed in the West build significantly more AI infrastructure, meaning data center, power plants, and so on, in order to support the growth.

16:37And we talked about before, they are not in a great position from a cash perspective. And basically what he's saying that the government needs to step in, in order to provide infrastructure to make sure that the West stays ahead on this process. I tend to agree. The numbers it's starting to come to when it comes to tens of billions and hundreds of billions of dollars to train and run the future models is not something a company can do on its own. And the only way to do this is either through a large government body that's going to finance that or a international coalition that's going to finance that to keep the infrastructure in the West.

17:17He also adds that there needs to be a commercial diplomacy policy, meaning export controls on what AI capabilities can be shared outside of the US or the Democratic Alliance, and putting limitations or some kind of oversight to foreign investments in Western companies that are developing AI. And the last component is established global norms for AI development and deployment, which ties back to what we talked about earlier, just having more control on what everybody's doing and deploying and so on. Now, a couple of months ago, when Leopold Aschenbrenner left OpenAI and did his open interview talking about the current status in OpenAI, he talks about this topic a lot.

17:56So if you didn't listen to that interview, go and look it up. I'll put the link in the show notes. It's an incredible interview that talks a lot about the global risks and powers trying to get access to advanced AI and what might be the implications. So it's not a new thing, but the fact that Sam Altman took the time, and he's a pretty busy guy, I'm sure, to outline this in an article tells you that he has serious concern. It also shows you that there's a deeper and deeper involvement of politics in this power game of AI control. And I think part of Sam Altman's move is to potentially relieve the needs of his own company to raise the amount of money and resources that are required in order to achieve the goals that they're trying to achieve.

18:46That being said, I'm sure his concerns are real and that we all need to pay attention to that, especially governments in the West. And from OpenAI to two companies that are tied to and related to OpenAI with some interesting news. One of them is Figure. Figure is a humanoid robot company that is backed by OpenAI and some other interesting players like NVIDIA and Microsoft and Intel Capital and Jeff Bezos Expeditions Funds. Lots of really big players invested a lot of money in this company. They just announced their new version of their robots. Their next version is going to be called Figure 2, and they're planning the formal reveal on August 6th.

19:28If you're listening to this podcast as it comes out, you can still catch the release. They're claiming it's going to be the most advanced humanoid robot on the planet. Now, that comes after they've announced a partnership with BMW Manufacturing that already is testing figure one in some of its manufacturing facilities. This obviously is another step in the race of humanoid robots, and this race is definitely intensifying. And there are several big players in that, but figure is just one of them. And the expectation is that these robots will show up more and more in 2025 and definitely into 26 and 27 in more and more places initially in public places like factories and hospitals and so on.

20:12But over time, it will make its way into our homes as well. But the really interesting news that comes that is related to OpenAI from one of its partners actually comes from Microsoft. So Microsoft just listed OpenAI as a competitor in its 10K SEC filing. This is the first time they've been doing it. And that's another step in the weird relationship between OpenAI and Microsoft. So going back to the beginning, for those of you who don't know that, Microsoft invested or committed to invest about$13 billion in OpenAI. As part of that process, OpenAI started their for-profit arm that is controlled by their nonprofit board, which is a weird thing to begin with.

20:54And Microsoft owns 49 % of that. But despite all of that, they've been competing on multiple things. Microsoft has been developing its own models to potentially in the future not be dependent on OpenAI. OpenAI in parallel are developing things that are competing directly with Microsoft tools. And one of the immediate recent examples is that, as I mentioned last week, just announced GPT Search, which directly competes with Bing. So in the taken filing, OpenAI is listed alongside Anthropic, Amazon, and Meta as competitors in the AI development. and they're also mentioned as a competitor next to Google as far as search competition.

21:37Now, why are they doing that right now? Maybe because of the recent news from OpenAI as far as GPT search, but also maybe because they are under investigation for antitrust by the government because of their big stake in OpenAI. As part of that process, they also gave up their observer board seat that they had in OpenAI because of the same concerns. So do I think it changes anything in the actual relationships between OpenAI and Microsoft? No, I don't think so. I think Microsoft is continuously hedging its dependency on OpenAI. That doesn't mean they're not going to invest additional X number of billions or maybe tens of billions in OpenAI to keep the relationship going for now.

22:19But as I mentioned, there are other forces such as government oversight that is impacting these decisions. And we had enough, I think, from OpenAI for one day. So let's move to some M &A news. Two very interesting M &As happened this week. One, Canva acquired Leonardo.ai. Those of you who don't know Canva, Canva is a design tool that's been around for a while. It's a highly successful company. I use it all the time. Me and another 180 million monthly users use Canva regularly to create designs for multiple things. They have about a$2 billion revenue and they just acquired Leonardo.ai, which is another tool I really like.

23:00It's one of the more advanced AI graphic generation tools. The reason I'm saying more advanced is that they took the approach of instead of using it as a regular chat and just using prompts to create new images, they built an entire set of tools that makes it feel more like a professional tool for designers, integrating a lot of AI tools and using using a lot of open source libraries that allow you to have a lot of really cool extensions that allows you to do stuff that is impossible to do on any other platform other than open source tools. In that deal, all of 120 Leonardo AI employees, including the executive team, will join Canva, but they will continue running dependently as their own platform.

23:44So Leonardo.ai is not going away, at least for now. So if the question is, why is Canva doing this? They're doing this because Canva has committed already to a lot of AI capabilities. They've been pushing this very hard with their Magic Studio features, which are really cool and very helpful if you're using Canva regularly that allows you to create new images or manipulate or change existing images and so on using AI. And now with the access to Leonardo's technology, they'll be able to provide significantly more AI capabilities within the Canva platform. As a Canva and Leonardo user, I'm really excited about this particular one.

24:23There are a lot of really amazing features that I currently use in Leonardo that will be incredible to have within the Canva platform. Now, the second interesting M &A news comes from Google. Google just acquired Character AI. So if you don't know Character AI, they're a really unique company. And what they've created is a chat platform that allows anybody to chat with known characters, whether historical figures or sports stars or actors and so on. Any person can pick a character to talk to and have conversations with these people. They've had conversations with other companies or potential acquisitions like Beta and X and so on.

25:03But eventually they landed in Google, which is not surprising because both co-founders, Noam Shazir and Daniel De Freitas, the CEO and the president, were both Google employees and left to start Character AI. So now them plus the other employees of Character AI are all going to become Google employees. Character AI is going to continue running as a separate platform, but they're going to use a lot of the knowledge that these people have in developing these kind of tools in the Google AI development. Also, it's been mentioned that Character AI itself will transition from developing its own AI models like they did so far to use alternatives from open source, such as Lama's 3.1 to run behind the scenes in its products.

25:50Both these news, as well as stuff we mentioned earlier today, is showing you a very clear trend of consolidation in the AI market. It's happening because it's impossible to finance the amount of money that is required to run frontier models and to develop really advanced companies in this field, which means more and more smaller or mid-sized companies that are really successful, like Character AI, will get picked up by somebody who has the ecosystem to support them and the distribution to support them. I will not be surprised if one of those next companies is going to be Perplexity. So those of you who don't know Perplexity, Perplexity is an amazing platform that combines search capabilities like Google Search together with chat capabilities like ChatGPT and Claude and so on into a very powerful search and research platform.

26:38I use Perplexity daily, probably as much as I've been using Google in the past few months, but they are going to face some very fierce competition, both from OpenAI with their new GPT search, as well as from obviously Google and Bing. And I don't think they have the funds to compete with the companies I just mentioned, meaning it's not going to be surprising if some other company picks them up and rolls them into their own technology. But since we're talking about Google, they've released a new experimental model. It's a new version of Gemini 1.5 Pro, dubbed Gemini 1.5 Pro Experimental, version 0801.

27:16And it's available for testing, meaning You can get access to it through the Google AI Studio, as well as the Gemini API. It's already at the top of the LMSYS chatbot arena leaderboard with a score of 1300, which is the best score on there right now. So those of you who don't know the LMSYS chatbot arena, it's an open platform that anybody can get access to where you can run a prompt and you get two results and you get to vote which result is better and fulfills your needs better. So it's a real world testing of a lot of people that are ranking without knowing which models they're actually ranking.