Amazon Goes All-In On AI

Welcome back everyone. Today on the Joseph Carlson Show, Amazon, the company that competes with everyone, is once again competing with seemingly everyone. They launched Amazon Nova, our new generation of foundation models. This is a direct competitor to ChatGPT. It's advertised to have many different versions. You have Nova Micro, Nova Lite, Nova Pro, Nova Premiere, Nova Canvas, and Nova Real. This model has all different capabilities, and you can pick which one best serves your needs.

But this is a clear attempt from Amazon to match Chat GPT's capabilities and surpass them with distribution. Amazon has deepened their partnership with Anthropic to accomplish these goals, and some of the things that they're accomplishing are pretty impressive even by modern AI technologies. Amazon looks like it's closed the gap with its closest competitor.

The stock is now at 220, up another 2.39% today because investors are being reminded that Amazon is a dominant, aggressive combative technology company. Not only do we have the report that Amazon launched Nova competing directly with Chachi PT, closing the gap with generative AI, but we also have another report at the same time that Amazon's creating its own homegrown AI supercomputer will, quote, lower the cost of AI as it seeks to build an alternative

to NVIDIA. So Amazon is now competing with Chachi BT at the same time that they're competing with NVIDIA. This is a reoccurring theme in investing. Investors forget about established companies and chase whatever is the flashiest object at the moment. In this case, investors have forgotten that Amazon is a dominant player in AI. We have examples here of them now using their AI analytic skills to partner with Moody's to make Moody's Analytics more powerful.

During the keynote presentation, Jassy, the CEO of the company, goes through a litany of examples of how Amazon is using their generative AI and practical applications. Some of these are literally game changers for Amazon. They have incredible practical applications that are going to be implemented over the next year as Amazon continues to climb. I think it's good to put this in context. What is all of this AI stuff mean for the future of this company?

How will it bolster Amazon's earnings capability? We're going to be going over all of it in this episode. Now, of course, we have a lot of news to get to today. We have Salesforce rising 9% on the day after reporting earnings yesterday. Why is the stock up 9% when the company reported earnings that are mostly in line and the guidance they gave was also mostly in line? Well, I'll give you a hint. It's another story that has to

do with a changing AI narrative. We also have Texas Roadhouse receiving free advertisement from former NFL players. And we have United Health executive, not the CEO, but an executive of the company, Brian Thompson, that was shot dead near Manhattan Hotel. This was a premeditated targeted attack and we'll be looking at all the details in this episode. Now, as we jump into this episode, I first want to point

out that if you try Qualtrim today, you'll get the entire month for free. We offer a free month trial through the month of December. You can join by going to Patreon dot com slash Joseph Carlson. Once you join the Patreon, Qualtrim is included along with a lot of other content like exclusive episodes, portfolio updates, all sorts of different goodies. So if you want to try that out, you can as well. There's nothing to lose now. We start off with the main story, which is Amazon's huge

push into artificial intelligence. It seemed like it was going very slowly and then all of a sudden it's happening very quickly. But for those of us paying attention, this should not come as a surprise. When I look at Amazon, it's not a company that I hold in my passive income portfolio. So I don't hold Amazon in the tech category or the financial category.

I own a lot of Amazon in my secondary portfolio, which is the Story Fund. The Story Fund's a portfolio I track primarily on my secondary channel, which is Joseph Carlson After Hours. Amazon is the second largest position. It's a $92,000 position with $34,000 in the green. This is one that I've been saying for over a year now is undervalued. I believe that Amazon has been perpetually undervalued for quite some time, especially coming out of 2023.

This company was not getting a lot of credit, but it seems like that's starting to change and that's typically what happens with narratives. Stocks are driven by cash flows in the long term and narratives in the short term. Narratives can give you opportunities to buy into stocks at good prices when there's a negative narrative on a good stock that will generate good cash flows in the future.

That was the case with Amazon. This is a company that had an ongoing narrative that it was not a major AI player. Over the past two years, Amazon has been answering that question of what are they doing in artificial intelligence? And part of their answer is Amazon Nova. They call it the new generation of foundation models.

Our new Amazon Nova models are intended to help with these challenges for internal and external builders and provide compelling intelligence and content generation while also delivering meaningful progress on latency. Inside Amazon, we have around 1000 Gen. AI applications in motion and we've had a bird's eye view on what application builders are still grappling with. Our new Amazon Nova models are intended to help with these challenges for internal and external builders.

That's a lot of very area they covered there. They're building all these Gen. AI applications and they put it into this model called Nova Nova's being broken up into four main categories. You have Nova Micro, the text only version that's very low cost, low latency. You have Nova Light. It's one step up, a very low cost multi model that is lightning fast for processing

images, videos and text inputs. Then you have the step up from that Nova Pro, a highly capable multi model with the best combination of accuracy, speed and cost for a wide range of tasks. Then you have the most powerful 1 Nova Premiere, the most capable of Amazon's multi models for complex reasoning tasks, for use of the best teacher for distilling custom models. It's going to be available early next year. And then you have Nova Canvas and Nova Reel. Canvas is for generating images,

Reel is for generating video. So they also have those video and image generation as well. Overall, what Amazon created with Nova is a comprehensive model for generative AI. They had one part of the keynote where they actually put in the text prompts so you could see what the prompt was and what the reels have generated. They still look AI, but they

look pretty impressive. Many of these are just as good as I'd see in ChatGPT, and Amazon is offering these at much lower or more competitive prices than existing competition to power all this generative AI. Amazon isn't working by themselves. They continue to deepen their relationship with Anthropic, which has so far been considered 2nd place to Chachi BT, but over time, at least right now, it seems like many of the capabilities from Anthropic are

a very close second place. The relationship is pretty simple. Amazon is giving them credits to run all of their processing on Amazon's web services. Amazon in return gets equity and influence over Anthropic. So they're they're both swapping different services they use. Now all of this is really cool. Amazon's going to gain a lot of additional customers with Amazon Nova.

There's already so many companies using Amazon Web Services. So leveraging that already existing platform and then pushing Amazon Nova seems like a no brainer. But one part of this that I think needs to get highlighted again is that inside of Amazon, they're already using 1000 Gen. AI applications. They're already in motion. And this is the AI story that's

being left out. Amazon so far by investors has been considered a second tier, third tier AI company, one that doesn't really get included in the conversations of companies that will benefit dramatically from artificial intelligence.

This narrative is changing and it will continue to change rapidly in 2025. How I know this narrative is going to change is because if you've been following Amazon very closely, you'll know that they've been migrating AI into every single aspect of their company. Every part of it, from the movie business, Amazon Prime, to their retail business, to their servers to their advertisement. It is transforming Amazon, and this isn't some vague promise of the future without any specifics.

Amazon gives detailed specifics of how this is transforming the company, starting with customer service. So take customer service. We have a retail business with a few 100 million customers they occasionally need to contact. Customer service, he mentions we have a retail business with a few 100 million customers. He throws out a few 100 million customers. Like it's just a side note, but just take that into account. Amazon's retail business has a

few 100 million customers. They own 40% of online shopping. So anything that moves a needle with customer service at all, increasing customer service response time, customer satisfaction, lowering cost of customer service, that is massive for Amazon's business. Occasionally need to contact customer service. The vast majority of them prefer to do it in a self-service way so they can do it quickly and

take care of it themselves. And we had built a chatbot many years ago and it of course used machine learning, but it had static decision trees and the customers had to enter a lot of words before you got answers. So a couple years ago we rebuilt this using generative AI and so now it's much easier for customers. So imagine I ordered an item a

couple days ago. I get on the chat bot, the new chat bot, we know who you are, that you ordered a couple days ago, what you ordered, where you live. And we can predict in this model if you're contacting us just a couple days later that you might be contacting us about a return. And so when you start to tell us that, we quickly can tell you where the nearest physical location at a Whole Foods or somewhere else is that you can return that item.

And then the model is also smart enough to be able to predict when you're getting frustrated with it and you might need to be connected to a human for resolution. Now this chatbot before we re engineered it already had very high customer satisfaction. But since we added the generative AI brain to it, 500 basis points better customer satisfaction, that's practical AI. Increasing customer satisfaction by 500 basis points. When you scale that out on Amazon's full retail business,

that is incredible. The amount of savings and time and hassle for Amazon, the amount of money saved scales across hundreds of millions of customers. So even these little incremental changes from Gen. AI have massive impacts on the margin of Amazon. And of course, this doesn't just end with customer. Service or take sellers, we have about 2 million sellers who sell in our retail store worldwide. It's over 60% of the units that

we now sell. And the way they get a product onto the website is they have to fill out this very long form. And the reason there are so many fields is we're trying to make it easy for our customers to navigate and understand what the products are. But it's a lot of work for sellers. And so we rebuilt a tool. We basically built a brand new tool using generative AI such that now sellers only have to enter a few words or they can take a picture, or they can point to a URL.

And then the the tool fills in a lot of those attributes. It's much much easier for sellers and we have over 500,000 sellers now using our generative AI tools. So we have AI integration with the customers. We also have AI integration with the sellers, making their job easier, making it so that more people want to sell on Amazon. This continues on with practical example after practical example. The amount of scale that Amazon has whenever they make one of these iterative changes is massive.

And of course this also has different applications like their warehousing. Look at inventory management. So think about the scale of problem we have to solve. In our retail business, we have over 1000 different buildings or nodes as we call them. And everything we do is optimized to get the right product in a fulfilment centre or building close to the end customer to save on transportation time, which means we get it to you faster and we

do it for lower cost. And so that means anyone point we have to understand what's in that fulfilment centre, what's the inventory levels of each item, which items are being ordered and at what rate do we have more capacity in that fulfillment center? Do we need to move inventory around to other fulfillment centers to balance the network? And so we've used transformer models to solve these problems

and make forecasts. And already our long term demand forecasting transformer models has improved that accuracy by 10%. And then we've also improved the regional prediction accuracy by over 20%. Those are big gains at our scale. He mentions that these are big gains at their scale, and again, scale is a meaningful word here. If Amazon was a very small shop, then 10 or 20% gains doesn't really hit margins quite as much

as a company at their scale. But they're already using Gen. AI and the logic behind it to help solve these tough questions behind logistics. Any efficiency in logistics means cheaper prices for customers. They're more competitive than the competition. It means a bigger market share for Amazon, better returns for the investor. Or think about robotics. We have over 750,000 robots roaming our various fulfilment centres and they have all sorts of AI in them.

But I'll, I'll give you the example of Sparrow, which is a robotic arm that does resorting. And so if you got a chance to zoom out of our fulfilment centres, it's really an operation that's constantly taking items from lots of different disparate parts and aggregating them into containers. So we optimize the capacity we have and the conveyance that we have. And So what Sparrow is doing is it's taking items from one bin and it's aggregating them into another bin.

And So what the generator of AI needs to do in Sparrow is it has to tell them what's in the first bin, what item do we want them to go pick up? It has to discern which item is which. It has to know how to grasp that item given the size of it and the materials and the flexibility of that material. And it has to know where in the receiving bin it can put it. And so these are, these are all inventions that are critical to us changing the processing time and the cost to serve our customers.

So we have about 5 of these brand new robotics inventions that we've pulled together in our Shreveport, LA fulfilment center just a couple months ago that we launched. And already we're seeing 25% faster processing times. And we believe we're going to have 25% lower cost to serve during the holidays because of these AI inventions and our robotics. Amazon already has the best online retail customer experience by far of any

company. They are the easiest to work with, the fastest to ship, the best return policy. Overall, they treat their members the very best out of any company online, and this is only going to get better. The distance between Amazon and their secondary competitors is going to widen. But we're also seeing altogether brand new shopping experiences that we're able to generate and invent with generative AI. So a few examples. I'll start with some agents. Let's start with Rufus, which is

our shopping agent. So if you're going to buy an item and you know what you want, I would argue that there isn't a better experience than ordering it on Amazon, having it shipped very quickly to your home. However, if you don't know what you want and you're trying to decide, you can obviously do it at Amazon. Many of you do bless you and

thank you for doing that. However, you can know it's, you know, and you do it through browse nodes and you do it through recommendations that we make and you do it through customer reviews. But there's something nice when you don't know what you want about going into a physical store and asking the salesperson, you know, telling them what you're thinking about and having them ask narrowing questions and then pointing you to maybe the couple items that

you want to consider. And then you look at those items and you don't have all the data in front of you and you ask that salesperson, well, what about this? What about that? They could answer it quickly if they don't walk away. And then you know you have the ability to make those decisions and what you want quickly. And what we're trying to do with Rufus is we're trying to make

that experience even better. So with Rufus, you can go to any product detail page and instead of going through the plethora of information on that detail page, you can ask any question and Rufus will answer it really quickly. Rufus will make comparisons for you across products and categories. It'll make recommendations you can make really, you can ask really broad questions for recommendations and it'll ask narrowing questions. So it gets it really what your intent is.

If you say to Rufus, hey, I want that same golf glove that I always get, can you find that for me? The one I've ordered, Rufus will find it for you. You can say to Rufus, give me the order status of, of the items that haven't been delivered yet and you'll get that too. And one of the nice things about Rufus relative to to physical salesperson is that Rufus is not going to take another job at another retailer or it's not going to start working in another profession.

Rufus is going to be there with you all this time, getting to know your intent and your interests and what you want better and better. Rufus was something that was launched that at first seemed unclear. It seemed like a little helpful tool, but I at first did not really understand the intent of this product. But it's clear that Amazon is designing Rufus to be an AI agent, to simply be a place where you can have a mini version of ChatGPT or Amazon Nova within the Amazon app.

And again, these examples with Amazon implementing AI are literally nonstop. They just go on. And we're just talking about the retail business here. Jassy continues on giving examples of how generative AI is being used in Alexa. Of course, this is going to be dramatically improved. They're intertwining all their aspects of their business with Alexa. But it doesn't end here. He gives more and more practical

applications. He moves on from discussing the impact of agents to now discussing different features on Amazon's app. There's a. A feature we have called Amazon Lens. So let's say that you're at a friend's house and you see a planter they have that you admire because this happens to be very often and you want to know where that planter is from. And you ask your friend. My friend doesn't know.

What you can do today is you can plug into a search engine like Amazon or somewhere else, planter, hanging macrame, maybe you'll get a decent answer. Probably not. Instead, you can use Amazon Lens and you can take a picture of that item. And what Amazon Lens is doing is using computer vision and then a multimodal model underneath it to do a search query that leads you right to the right search result on Amazon where you can buy it easily.

It's really magical and cool. These are features that are going to become standard practice in the future as customers learn about them and become, I'm convinced that they actually work well, they will adopt these new features. Shopping behaviors have changed over the past five years dramatically. They're going to continue to change with the advent of AI, and Amazon is leading this online shopping AI integrated future.

We've all had this experience where, you know we're buying a shirt and you don't really know if that brand runs large or small, whether you'd be a medium or large in that shirt. What we've done is we've built a large language model that takes all the sizing relationships between in the many, many brands that we have and compare which ones run like each other, which

ones run larger or smaller. And then we're able to look for customers, what you've bought before and when you're at a new brand, we can make the right recommendation for what size you really should order. Very handy, very practical. This is something that I've already used on Amazon and it works perfectly. They already know based off of your order history what size you are, and then they know exactly what size of this product is going to fit you based on

different reviews. So this is another pain point from ordering clothes online is getting the sizing right. So if Amazon can cut down on the massive cost associated with large amounts of returns by getting the size correct, that's another thing that can improve the margins of the retail business. And then if you look at what we're doing in Prime Video, we have a very deep partnership

with the NFL. We've built something together over the years called NextGen Stats and we collect 500 million data points every season and then. We've built AI models on top of that and so you can see some of the features we've built. We've built something called defensive alerts, which shows you which defensive player might blitz the quarterback, puts a circle around it, changes the viewing experience. Or we can look at different formations and sets and detect where the defence may be

vulnerable. And so we have a defensive vulnerability feature where we can highlight for viewers where the offence should attack. These change the experience for fans. And so these are by the way. This is actually astonishing, what they're doing. They look at the layout and formation of the football players, and then they kind of identify what the most likely

play is to occur. They're predicting the future with generative AI and then sharing that with the viewer so they know where to better pay attention to. If Amazon gets this right, this is another thing that separates them from the competition. This will be difficult for other companies to implement at the scale that Amazon's already at. Amazon Prime Video is already a world class asset.

In fact, now there's reports that 70% of the people that sign up for Amazon Prime sign up because of Amazon Prime Video. So as they're adding more value to this, they'll get more customer acquisitions as well. The applications that Amazon has to implement AI into their business are enormous. The opportunity here is larger than most other companies. So when investors disregard Amazon or don't consider it an AI company, I leave confused. I don't understand that thought

process. Amazon has every reason to be considered one of the top AI companies in the world. Not only are they intermingling AI into all of their business, they're competing with Chachi, PT with Amazon Nova. They have massive cloud scale with Amazon AWS, but they're also competing on the hardware front. Amazon announced that they're building a supercomputer, a new server powered by homegrown AI chips.

This is under Amazon Web Services and it's going to be called the Ultra Cluster, a massive AI supercomputer made-up of hundreds of thousands of homegrown Tranium chips. This means that Amazon is the one designing these chips. This means that Amazon is the one designing these chips. The chip cluster will be used by the AI startup Anthropic. It'll be located in the US. It'll be ready in 2025.

It'll be one of the largest in the world for training AI models. When the AWS CEO was talking about this new chip cluster, he also mentioned that Apple is using it. Apple's one of the biggest customers of Amazon's custom AI chips. Apple said that we have a strong relationship and the infrastructure is both reliable and able to serve our customers

worldwide. Now, of course, when Amazon announces that they're creating their own chips and customers like Ale are choosing them, this pits them a little bit against NVIDIA, a company that is a current partner of Amazons. Quote Today. There's really only one choice for the GPU side, it's just NVIDIA. That's what Matt Gurman, the chief executive of Amazon Web Services, said. We think that customers would appreciate having multiple choices.

Amazon's trying to break Nvidia's monopoly to become a duopoly. A key part of Amazon's AI strategy is to update its custom silicon so that it can not only bring down the cost of AI for its business customers, but also give the company more control over its supply chain. That could also make AWS less reliant on NVIDIA. NVIDIA, of course, has made a fortune by selling their GPU's to mostly big tech customers, which make up over 50% of their

current revenue. And Amazon's motto of your margin is my opportunity seems to be at play here. They want to drive down the margins of NVIDIA. It's going to take time for Amazon to make a lot of gains in the GPU market. Even though the use of Amazon's GPU's is much more narrow, the scope is smaller and the application is more specific. This will drive down costs for GPU's overall. When Amazon starts creating alternatives in any capacity to NVIDIA, that's going to drive

down costs. So whether we're looking at the hardware aspect or the software aspect, something that I've been saying for over a year now with Amazon is that it is one of the leading AI companies. It is going to be a force to be reckoned with and investors are starting to recognize this. This is a narrative that has been changed. Amazon has been branded as one that's behind an AI or not really part of the conversation. And over the next year, we're going to continue to see that change.

And as that happens, I'm going to be remaining fully invested in this company. Now moving on, another stock in My Portfolio that's going through a bit of a transformation is Salesforce. I purchased into Salesforce over the past six months and this one continues to rise. Today being the best day since I bought it. Salesforce stock is currently up 9% on the day after reporting earnings yesterday after close. There's banks raising their

price targets. Analysts across the board are all becoming more excited about this company. Salesforce basically did exactly what they said they were going to do. If we look at their EPS and revenue estimates, they actually missed narrowly on the EPS. If we look at the estimate compared to dismissed, they missed by two or three pennies. And if we look at the revenue, they did be on their revenue estimates. So they reported 1/4. That was in line with

expectation. We can turn to the guidance, but the guidance was also roughly in line with expectations. So why is Salesforce up 9%? The majority of this gain is because of a shift in narrative, A Salesforce similar to Amazon. Investors are getting more on board that this company is an AI company. Salesforce just released their new product called Agentforce, and within the first week of business, Salesforce's CEO said that they had over 200 customers

sign up for the service. Agent forces Salesforce's new branding for their AI agents. These are better than chat bots. They're chat bots that can do very complex tasks. In fact, they can kind of do entire human tasks. The big selling point for Agentforce is that it will lower the intensity of work required for their company's customers. They're promising remarkable efficiency gains through Agentforce. We've gone through a phase of generative AI and we've seen what that has done, the

efficiencies it's gained. But agents are this entire new concept. It's like the next level of AI. And in an interview today, Sam Altman described what he thinks is going to be the biggest change in 2025, the next iterative development that will change people's perspectives to what AI is capable of. Sure. I expect that in 2025 we will have systems that people look at, even people who are skeptical of current progress and say, wow, that I did not expect that.

That does change what? Like what? Agents are the thing everyone is talking about, I think for good reason. You know, this idea that you can give an AI system a pretty complicated task, like a kind of task you'd give to a very smart human that takes a while to go off and do and use a bunch of tools and create something of value. That's the kind of thing I'd expect next year. And that's like a huge deal.

We talk about that like, oh, you know, this thing is going to happen, but that's like, if that works as well as we hope it does, that can that can really transform things. And Sam Altman is right. If this is correct, if there are agents that can accomplish these complex tasks, that's going to be incredibly transformative and it's going to be very valuable for the companies that have the distribution system to sell

these agents to their customers. Well, what company has a massive amount of existing customers, maybe over 150,000 customers? Salesforce does. What company has customers data in almost every segment of their business, in sales, in service, in platform, in marketing and integration? Salesforce does. Salesforce as a company has more customers and more customer data than almost any company on earth. They are the CRM, the customer relationship management tool for hundreds of thousands of

companies. They already have all of that data. They already have all of those connections. They have all the sales funnel existing. All they need to do is press a button and sell agents to them. That is exactly the vision that Marc Benioff sold in this latest earnings report. He gave practically a 20 minute dissertation on what agents are. If you want the most in depth, comprehensive view of agents, just go listen to the last Salesforce earnings call.

He goes on and on for well over 20 minutes describing this transformative technology. His opening remarks, I actually believe may have set a record for the longest opening remarks of any CEO in an earnings call. Although out of everything that he said in the opening remarks, I believe the most illustrative example of agent force was given during the Q&A. He gave an example of healthcare. Let's go ahead and listen to the story that Marc Benioff shares

about healthcare. I just got a call. From my hospital telling me that I'm coming in to get scheduled for another MRI and incredible service. You know, Ruben knows that this great relationship with UCSF and they're, they, they pay a lot of attention to me. I pay a lot of attention to them.

Incredible organization. And they had a lot of questions for me about getting me ready for my next MRI and, and at the end of the call and this kind of preoperative care and there'll be another call post operative and so forth. And I, I was just saying to myself, wow, what did that cost them? And they just don't have enough people as it is. Their doctors are already burned out, their nurses are burnt out. I've talked to the folks all the

time. You know, there's a lot of pajama time for all these doctors is what they call it, because they're all working late at night with their families trying to get through all of their messages. Everybody's maxed out at UCSFI. Mean it's an incredible org, but I, I, I can't believe, you know, the amount that they have to do with such a actually limited workforce. And then, you know, I got this call.

I said, you know, they kind of know all of this already about me. They've got all of my data, they have all of my care, they have my family history, they've got all my scans. They can have an agent do this work. And that call probably cost them $100 and it didn't have to happen. And I think that we could have done the call for probably about $1.50. And I think that that is the message to our customers. That's the sales pitch. It's that simple. Right now, humans are doing

things that cost $100 per call. When you factor in a human salary, they're scheduling their healthcare, everything you need to do to hire a person to return calls, to answer all these different inquiries. There's a lot of cost associated to it. Salesforce created a product, these agents that they can distribute with their massive customer base and the sales pitches, It's going to save them a lot of money, a lot of money on returning monotonous calls

that agents can figure out. The technology is finally here to solve it. When you have a margin difference between costing $1.50 or $100, that is an easy pitch. The only thing that remains is for customers to be convinced that this product is worth it. That's why they're implementing things like calculate your ROI right on Salesforce's website. This is a tool they developed to help customers understand their

potential savings. They can put in the number of customer service employees, the average annual salary of those employees. You can punch in the number of conversations those employees take on everyday, and then you have a dial here to calculate the percentage of support conversations shifted to Agentforce over three years. If you get to 50%, here's a chart of the savings. Year 1 you save $200,000. Year 2 you save $283,000. Year three you saved $405,000 with only a small team of 20

customer service agents. After three years, you've saved $886,000. Salesforce is also changing the way the customers are paying for this product. Instead of paying a flat license or a fee or a per seat license, customers pay for it through consumption.

The customer doesn't pay for Agentforce unless they're saving money with Agentforce, but this also is beneficial for Salesforce. Salesforce knows that AI is replacing many different seats or different employees at companies, so having a consumption based model protects them from that dynamic change. Every single customer in Cory they can complete, they can get a dollar or $1.50 and that's a savings for their customer and its money directly in

Salesforce's pocket. All Salesforce has to do right now is push this product to their customers. They have to run the sales pipeline. That is why Salesforce is hiring 1000 people to sell this product to their customers. They want to get the word out. They want to let their customers know we have this new product that can stand to save you a lot of money.

Marc Benioff also noted that within the first week of this product being launched, they already have 200 customers signed on and they have conversations with thousands more. So if you're wondering why Salesforce is bouncing up after earnings that seem to be in line with expectations, it's because investors again, are getting more on board that this company is not going to be destroyed by artificial intelligence. In fact, it's going to be one of

the biggest beneficiaries. Unlike Amazon, the biggest benefit that Salesforce currently has is their already established distribution system. This knowledge and data that they have around hundreds of thousands of customers is incredibly useful for when they they want to sell a new product like Agentforce. Now moving on. I saw something that I thought was funny.

In fact, I was sent this by a couple people, but it's JJ Watt, a former NFL player and he gives a huge endorsement for Texas Roadhouse on Twitter. He tweeted Texas Roadhouse simply does not miss ever with a picture of the meal that he ordered. Now this tweet with this picture got 1500 comments, 1100 retweets, 37,000 likes and it got viewed 2.4 million times. This is what they column business earned advertisement meaning that Texas Roadhouse.

In order to make this incredible endorsement from a former NFL player, probably the best person that you could partner with to endorse a company a restaurant like Texas Roadhouse. He endorsed it for free. He just went out and he enjoys the meal. He said that he got the meal in under 20 minutes. He was in and out of the door. The service was incredible. He gave it this glowing endorsement. This is one of the examples of a company that just offers a great product.

The endorsements are in the customers themselves. The reason that we don't see any national advertisements, it's the same reason you don't see Costco advertising. The product sells itself so well through the word of mouth. I think things are going to continue on for Texas Roadhouse. There's so many people that love this restaurant. They're opening up new locations. Even though the valuation is a bit higher, it's traded up some. I'm still along the ride for this one.

Now moving on, we get to some news that's rather shocking.

A United Health executive, Brian Thompson was just killed. He was shot down in a premeditated attack. Now there's video of this clear assassination. I'm not going to show it on this channel. It's all over X and Twitter and online you can find if you really want to watch it. But it is disturbing. It shows him being gunned down in a premeditated fashion by someone that looks like a professional. The assassin has a jacket on with a hood up covering his

identity. He pulls out a handgun with a silencer and shoots at point blank range multiple times, ensuring that he's dead. This is a clear cut assassin fascination. Now the Wall Street Journal is reporting that a manhunt is underway for the suspect, who is lying in wait for the executive. So as of right now, they haven't caught this assassin. He's still on the loose. In fact, they don't even know his identity.

He fled on foot after shooting outside the Hilton Hotel and then the suspect rode on an E bike to Central Park where he was last seen. Police said that he planned the attack, but they don't know why. So as of right now, we don't have a clear motive. An important thing to note here is a small caveat. A lot of different news organizations are reporting that Brian Thompson was the CEO of United Health. He wasn't the CEO of the entire

company. He was the CEO of a smaller business owned by United Health. So he was an executive at the company, but he wasn't the CEO. Thompson, who was 50, was believed to be going to United Health Annual Investor Day early to help set up. So to get this straight, this executive that works for a company that works for United Health was just going to an annual investor day to help set things up and he was targeted by an assassin early in the morning in broad daylight in New York City.

This is truly shocking and disturbing. Now the police, of course, are trying to find this guy. They've already put up a bounty for the assassin offering $10,000 for anyone that has any type of information. This whole event is just tragic and unsettling. Ryan Thompson, From every bit of information we can gather on his history, at least now it's hard to find any possible motive for

someone wanting to hurt him. There's already news organizations that have dug through his public history, looking at every challenges he's faced, everything that he's done with his work and private life. There's nothing distasteful, objectionable, questionable. It seemed like he was all around a good person, his mother-in-law said. The only thing I can say is that he's a good man. I can't say anything else. We're still in shock. This seems like a totally meaningless, senseless attack.

The family must be devastated as well. He's also married, so his wife must be completely devastated right now. All around a completely horrific event and hopefully we find the scumbag that did this. That's going to be it for now. See you in the next one.