NVIDIA Massive Earnings vs New Groq AI Chip LPU Breakthrough SHOCKS Everyone! 🤖💾 (Not Grok AI)

In this video we're going to be talking about Nvidia and what is behind their massive market cap as well as a potential new player in the AI chip manufacturing game grock no not grock with a K elon's grock grock with a Q let's dive right into [Music] it so we'll also be going over Nvidia versus Gro what's the difference and makes grock unique now what we'll cover in today's video we'll go over nvidia's recent rapid growth the latest AI news regarding

Nvidia the new AI chip startup Gro and how Gro actually works grock's key features grock's lpu versus nvidia's GPU as well as we'll go over some clips on the Allin podcast from chth who was one of their earliest investors on Gro Rock So nvidia's recent rapid growth as of February 2024 nvidia's market capitalization is approximately 1.95 trillion making it the world's fourth most valuable Company by market cap this valuation reflects nvidia's significant growth and dominance in the AI and graphics processor

Markets driven by strong demand for its products and strategic positioning in key techn technology sectors here is a graph of the market cap of Nvidia you can see here this is as of February 2024 you can see how it skyrocketed and you can see the timeline at the bottom only a few years ago it was not nowhere near as high as we're seeing it in today's time now you can see here the different years and the endof year market cap right

Here as well as the percentage change so uh 2024 4 we're at 1.95 Trill 2023 we were at 1. 1223 Trill and then 2022 we were at just 364 Bill and then 2021 735 bill and if you go down a few more years you'll see 2018 81 billion so it's completely had insane growth like if you look at from 2022 to 2023 it had a 235.68 88% % change and that is absolutely insane here's another graph showcasing nvidia's uh price compared

To the S&P 500 all right and their Nvidia reports a 21% increase in net income year-over-year for q1 of uh FY uh 24 profits fueled by increased demand for AI Tech of course all right now nvidia's results for their Q for filing basically just to sum everything up uh you know you don't have to know all these numbers but if you do want a quick gist of what everything is I'll give you the rundown here so they made 22.10 billion this

Quarter which is a lot more than the 6.05 billion they made at the same time last year people thought they would make about 20.41% centers like servers and other Tech to store and process data they made 18.4 billion up to up from 3.62 billion from last year beading the guess of 17.21 billion Gaming revenue they earned 2.9 billion from gaming which is 58% more than last year and more than 2.72 billion people thought they would make uh professional visualization Revenue this

Is the money from selling Tech used for things like Graphics and Design they made 463 million up from 226 uh Million last year and did better than the expected 435.214 per than last year but still more than expected of 272.50 and then adjusted growth uh grow gross margin this is measure is a measure of how much money they make after covering the cost of goods but before paying off other expenses and that it it's uh 76.7% up from the 66.1% of

Last year which means they're making much more profit on each sale they did better than the expected 75.4% and then R&D expenses they spent 2.47 billion on research and development 26% more than last year but close to the expected 2.43 billion this money is invested in developing new products and Technologies and then adjusted operation operating expenses uh they spent 2.21 billion on operating expenses like salary marketing Etc and that's up from a 25% from last year but slightly less than the

Expected 2.23 billion and then adjusted operating income this is the profit from their business operations after deducting operating expenses but before taxes and other costs and they made 14.75 billion which is a huge jump from the 2.22 billion last year and more than the expected 13.14 billion and then free cash flow they had 11.22 billion left over after covering all their costs which is a lot more than the 1. 74 billion last year and also more than the expected 10.82 billion

This is good because it means they have a lot of cash available for things like paying off debt investing in new projects or returning money to shareholders so in summary nid absolutely crushed it this quarter uh making more money than last year and more than most people thought they would in almost every area of their business right now if you don't know too much about Nvidia you may be wondering how do they do this well it's through their gpus and the

Massive boom of the AI industry and we'll get into kind of that in a second and what that means for NVIDIA what that means for the AI industry and what that means for potential competitors like Gro right so latest AI news regarding Nvidia Nvidia introduces new laptop gpus for AI on the go Nvidia has launched two new graphics cards designed for running AI applications on laptops expanding the accessibility of AI technology to mobile user users Micron begins mass production of memory

Chips for nvidia's AI semiconductors Micron Technology has started mass production of high bandwidth memory hbm semiconductors for NVIDIA nvidia's latest AI chips the h200 gpus which are expected to start shipping in the second quarter and these chips are designed to consume 30% less power than competitors and then nvidia's AI Revolution Ai and gpus nvidia's Graphics processing unit AKA gpus are the heart of the AI boom these gpus originally designed for gaming are now crucial for training AI models because of their

Ability to handle complex calculations quickly generative AI demand the launch of chat GPT and other AI Technologies has led to a surge a massive surge of demand for nvidia's gpus companies are racing to incorporate AI into their products and services requiring powerful chips that Nvidia specializes in all right and if you don't know we talked about this many times on the channel the way you scale these models and the way you actually make them more powerful is one of the main

Ways one of the most important ways that we've seen is through compute so that's why you see all the big AI companies looking for compute either trying to develop their own chips or trying to get more Nvidia chips or other competitor chips um new chips are arising right that we're seeing new chips are being developed major Investments are being made into to these companies so we're going to continue seeing this trend uh over the next few years and nvidia's Competitive Edge

And pricing power so right now Nvidia has a huge Competitive Edge and they have dominance in the AI chips and Nvidia is poised to dominate the generative AI chip Market with significant market share its gpus especially the newer models like the hopper h100 are much more powerful in AI task compared to previous versions and competitors's offerings at and pricing power so nvidia's AI chips command a premium price selling for much more than its gaming chips and this pricing power is a

Testament to the value and performance of nvidia's AI technology so you can see here in an article nvidia's h100 AI gpus cost up to four times more than amd's competing Mi 300X amd's chips cost uh 10 to 15K a piece and nvidia's h100s have peaked at $40,000 all right so these chips are not cheap and the future of nvidia's growth so sustained demand for AI the generative AI Market is expected to grow exponentially driving continued growth for nvidia's chips as well

As any other competitors that you know are on the up and up and this growth is not just a short-term Trend but a part of a longer term shift towards AI driven Tech and stock valuation and investment potential so despite High valuation multiples analysts believe invidious stock has room to grow and the company's revenue and earnings are expected to increase significantly supporting a much higher stock price and here is the global artificial AI Market size which was valued at uh 45412

Billion US in 2022 and is expected to hit around 25756 billion by 2032 progressing with a compound annual growth rate a a of 19% from 2023 to 2032 the North America artificial intelligence Market was valued at 16730 billion in 2022 now this is just an estimate right and we've seen with AI and exponential growth and if you look at previous you know experts predicting you know where we'll be when we'll achieve AGI it's completely changed over the years so yeah this

Is probably bare minimum but I wouldn't doubt if it's much more of a exponential growth curve than what we're seeing here especially you see someone like Sam mman you know and the $7 trillion investment and of course we've seen clips now where he's kind of explaining that that's not just what you may think what maybe some of the headlines made it seem where he's just asking for 7 trillion he's basically saying that's what it would take on a uh much bigger

Scale for for the whole infrastructure in order to achieve AGI thanks so much for joining us yeah of course and uh Hey a couple of quick questions you know the first one is 7 trillion what's this all about anyway look uh as as I'm sure you all know you shouldn't believe everything you read in the Press really we do think the the kernel of Truth is that we do think that uh investing a lot of money in AI compute energy data

Centers is going to be important to deliver the the amount of services people want and the tools that we all are going to really I think get a huge amount of value out of to help create better Futures so there's a lot of investment to be made here I think so but it's across a lot of stuff it's not I mean it's a this is like a worldwide investment to help many many different efforts many different people and not just chips

Of course but sort of the whole infrastructure stack around it and um so yeah I I would say this is probably bare minimum what we'll see with the growth I think it's going to be a lot more and I think you it's really hard for experts or really anyone to predict things when it comes to AI because it's just something that we haven't seen and as it's progressing we start to see emerging properties and all these different things that we cannot

Predict and it's really just a level of intelligence that us as humans we're not going to be able to understand so it's hard to predict but anyways I want to give you an an analogy between kind of with what Nvidia and what we're seeing and their massive growth and it's basically nvidia's AI chips within the gold rush so imagine Nvidia as a gold miner during a gold rush but instead of gold Nvidia mines for AI capabilities just the best the best

Tools and equipment were in high demand like shovels and whatnot during the Gold Rush nvidia's gpus are in high demand for the AI boom this demand has made nvidia's tools more valuable leading investors to bet big on the company driving up its stock price Nvidia success is not just about being in the right place at the right time it's about having the best tools in an era where everyone is rushing to find AI gold in summary nvidia's increasing stock price is

A reflection of the central role in the AI Revolution its financial performance and the Market's confidence in its future uh growth prospects right and this also goes kind of hand inand with any potential um competitors or other companies that are coming out with these new Chips there's going to be a lot some of them aren't going to be you know these unicorn companies these ones that actually take off or gain traction but one that in particular especially recently that has been

Going viral and basically gaining traction is this new AI chip startup Gro and we're going to dive all into um pretty much everything about this so you get a really good understanding and grock Inc is a Silicon Valley based startup and has made significant strides in the field of AI chips technology AI chip technology focusing on developing high performance low latency chips for AI applications their approach to chip design is fundamentally different from traditional methods emphasizing a software first mindset that

Allows for greater Simplicity efficiency and performance in processing AI workloads roock has released an lpu chip so instead of a GPU a graphics Processing Unit it's a language processing unit that is taking the AI industry by storm with its Lightning Fast computation speed this chip generates output at a speed beating both chat GPT Gemini um as well as uh you know Nvidia and allows you users to use multiple AI models quickly it can generate 500 tokens a second AKA a novel

In just 500 seconds they've partnered with Samsung to develop gamechanging solutions for AI machine learning and high performance Computing applications and you can check it out at gro.com so once you go to gro.com you'll be greeted with welcome to gro we created the lpu inference engine the first and fastest of its kind serving the realtime AI Market our solution for inference not training makes us the AI performance leader in regards to speed and Precision in the compute Center unlike other providers

We are aren't brokering a cloud servers we buil our own chip compiler and software systems and Gro Cloud our first gen Gro chip a language processing unit lpu is a pro a new processor category that's one part of our secret sauce our performance enables a greater potential for AI across multiple Industries it's about realtime AI low latency low batch size Solutions try grock chat for yourself so you can actually log into grock chat you can either do it through email or

Through Google if you're looking for API um you can go to here and get that as well you'll have to apply for it um once you actually sign in here is what it will look like you will be able to enter your prompt here um right here you can see a drop down where you'll see your settings over here you can change the actual speed you can change the maximum tokens the temperature the top P the top K all right you

Could select default and you could also change the system prompt so please try to provide useful helpful and actable answers of course you could change change this and then of course you can log out but over here is where you would enter your prompt here you can select one out of two models at the moment you can select llama 270b 496 or mistal 8X 7B 32768 and depending on you know what your what type of output you would want you can

Go through select these open models so right now it's only using open source models and in the future you know they're going to obviously get more open models as well as um you know different maybe private companies um but the whole thing here is using their Rock Chip it's a lot faster so let me just show you an example write a compelling article on what on the new rock aiip so look how fast it is writing this you can see that

I'm not going to read it here but um it's lightning fast it's a lot faster than chat GPT chat gpt3 4 whatever um so imagine using this on some of the more powerful models right now it only has these open models right here but imagine using it with something like chat G bt4 or chat G bt4 turbo leveraging the gro AI chip that would be something very powerful how do I get started you have to request access for the API to

Run llm applications in a token based pricing model so you can go ahead check out the white paper read some of the FAQs read about us you can see the different team here the leadership the CEO founder Jonathan Ross as well as the whole team down here and you can check out some of their stuff and their Solutions right there so how does Gro actually work so grock's technology is centered around the tensor streaming processor tsp architecture which is designed to

Handle the specific demands of AI and machine learning applications this architecture is characterized by its ability to perform tasks in parallel significantly enhancing the processing speed and efficiency the tsp architecture includes matrix multiplication units which are crucial for AI applications and features a high degree of parallelism through its storage units for weights one of the key Innovations of grock's chips design is the elimination of Trad additional Hardware components such as cores threads and on chip networks which are common in CPUs

And gpus instead grock's design focuses on simplifying the chip architecture to reduce complexity and improve performance this approach allows for a more efficient silicon design maximizing the use of transistors and computation and grock's chips are designed with a softwar defined architecture where the compiler plays a central role in controlling the hardware this means that all the EX execution planning happens in software bringing up silicon real estate for performance enhancing features the compiler has a comprehensive view of the hardware at every

Given cycle enabling precise control over data movement and processing this deterministic approach uh processing approach ensures predictable and repeatable performance which is crucial for AI applications and we're going to break this down in yes I'm going to give you kind of the technical stuff but we're also going to make it easy for you to understand and you'll get a really good sense of barck and what this chip is and how it's different once you actually watch this whole video as well

As will include a chip of the actual CEO going over some specifics with grock which is very very uh educational all right and here are some clips of the CEO of grock going over the grock AI chip Jonathan Ross is the brain behind grock the world's first language processing unit now before I lose you in the technological jargon of AI let me put it this way what Ross created is a chip that can run programs like meta's llama 2 model for

Example faster than anything else in the world 10 to 100 times faster in fact and he's here with me now to explain how that is possible before I ask you that grock why grock thank you Becky uh it's grock and we spell it with with a Q and it's because it comes from a science fiction novel and it means to understand something deeply and with empathy of course it does tell us about your chip and what makes grock chip lpu different

From other AI chips and accelerators I have to tell our viewers the Nidia uh CEO was here of course uh this week at the beginning of the week so we've uh we've had all the greatest Minds in here what's your story well asking me how the chip Works before I show you what it does is a bit like asking how a magic trick works before showing you the magic trick you're going to get bored but I'll give it a shot cool

So most chips they they don't have enough memory inside of them sort of like if you were building cars and you use a giant Factory and you need about a million square feet of assembly line space well if you don't have a building that's large enough to fit that then you need to set up part of the assembly line tear it down over and over again right and that's slow and it takes a lot of time and that's what happens with

The GPU you have to read from that memory so thousands of times for every word that comes out it's as if you're setting up the assembly line over and over right you talk about the wow moment people have when they first experience the speed of your Tech you are breaking performance records almost every week how fast is your processing today and why is speed so crucial to coin a phrase so what why do I care about the speed the reason you

Care about the speed is it's about engagement imagine if I spoke if I spoke that slowly you just drift off you You' go away most certainly so the statistic is if you improve the speed by 100 milliseconds on a website on desktop you will get about an 8% increase in in user engagement on mobile it's 34% people have no patience on mobile and we now set a speed record where we can do what's called 500 tokens per second that would be

A novel in about oh somewhere around 100 seconds I'm going to get to this I just got to ask you one other question before I actually try this out cuz clearly that's the only way to really kind of reveal what we're doing here what makes you better than other large language models so we don't make the large language models we just make them fast and so we take open source models we run them so it's the same model everyone else has

But you will have a very different experience because of the speed right now ai is unnatural all right and then grock's Market impact so grock's entry into the AI chip Market challenges established players like Nvidia AMD and Intel by offering an alternative that promises higher performance and efficiency for AI and machine learning workloads the company's Innovative approach to chip design and its focus on simplifying the architecture could potentially reshape the landscape of AI Hardware as AI applications continue to evolve and

Demand more from underlying Hardware Rock's technology is well positioned to meet these needs the company's focus on a software first design and its ability to deliver high performance low latency processing for AI workloads make it a notable player in the high performance AI chip market and grock's impact on AI cool calling and customer support call centers so this is something I wanted to talk about because this is one thing I saw the potential of Gro right now if not if you

Don't know there's different tools leveraging you know typical AI Solutions where you can you know have ai coold callers or AI customer support centers where you know an AI would either call call a prospect or a pro or a customer would call in to a support center and the AI would be trained on the knowledge base and be able to ask questions or book appointments or all these certain things and this type of technology and this type of business model or

This type of use case is picking up more traction and it's going to keep progressing thing right but what I've seen and we've used this in you know different clients businesses as well as our business and whatnot and for example AI cool callers or customer support centers the the latency and the the speed of which these um these models or these uh agents can respond to a prospect is very slow it's it's it's okay it's not terrible but in terms of

An actual human having a conversation with you like if someone called me I would EAS be able to tell it's an agent and I would say Gro is definitely a huge step closer and you'll see in a second I'll show you a demo video of grock actually talking someone talking to grock the founder actually doing this and it's a lot quicker and that is key when it comes to actually um having an agent that is like a humanlike agent right so

Um faster respon response times grock's lpu significantly reduces the lag time in AI models enabling real time conversations that closely mimic human interactions enhanced personalization the speed and efficiency of grock's AI chips enables AI systems to quickly analyze customer data and tailor conversations making cool calls improved customer experience Gro technology can significantly enhance the customer support experience by reducing weight times and enabling AI systems to provide immediate accurate responses to in inquiries and then costeffective operations with its high-speed processing capabilities

Grock's lpu can handle a longer volume call of calls with fewer resources potentially reducing operational cost for call centers and then scalability rocks chips are designed to efficiently scale with the needs of AI applications making it easy for customer support centers to expand their AI capabilities without compromising performance I asked you that question but why don't I actually just ask rock all right let's do that so we're going to turn it on let's do it I know the answer to this

Gro but what makes you different well first to another hey I'm Gro you can talk to me like I'm a person all right I will do what makes you different from a large language model that i' may have used in the past sure I'm a bit different from those big language models you've used before I'm a language user interface or Louie designed to have more natural and engaging convers how Sim you to a human brain well I'm not a human brain

But I'm designed to understand and respond to you like one yeah I can process and generate human language in a natural way but I don't something most people don't know um here's something interesting did you know that octopuses have three hearts two pump blood to the gills while the third pumps it to the rest of the body and when an octopus swims the heart that delivers blood the body stops feeding which is why o prefer crawl rather than swim unless necessary

Write me a poem it's Val Val's day a very short one very very very very very short but lovely oh I see oh I see Happy Valentine's Day I'm glad you're having a lovely day I hope you get to spend time with someone special or do something fun is there anything you'd like to about or I'm not I'm I'm I'm I'm giving up on you you've done everything that I asked and more thank you so much I feel as if I'm

Talking to a human being it's worrying me how worried are other chip manufacturers by you well we've been contacted by a few of them the speed is definitely a differentiator and people notice it and should I so thank you very much oh sorry how rude of me yes oh we just interrupted again thank you very much you're welcome more relevant and engaging for the Prospect and here is the grock chip scalable architecture so we have SRAM memory massive concurrency 80 TBS

Per second of bandwidth stride insensitive and then networking 480 gigb per second bandwidth extensible Network scalability multiple topologies and then grock true Point Matrix four times engines 320 * 320 fuse dotproduct integer and floating point and data switch shift transpose perter for improved data movement and data reshaped programmable Vector units 5,12 20 Vector alus for high performance and then instruction control multiple instruction cues for instruction parallelism now what is the difference between grock's lpus versus nvidia's gpus so deterministic performance grock's

Lpus offer deterministic performance meaning that it can ex execute operations with predictable timing which is crucial for applications that require consistent and reliable processing speeds efficiency and language processing the lpus specifically optimized for language processing tasks potentially offering greater efficiency and faster performance when running large language models compared to General processing models gpus power uses so grock's lpu is designed to be more power efficient which is important an important consideration for data censors looking to reduce energy consumption and operational costs

And then simplified Hardware design the lpu simplified Hardware design which eliminates traditional components like chors threads allows for more efficient silicone layout and maximizes the use of transistors and computation software defined architecture the defined architecture the software defined nature of grock's architecture means that the compiler has a centralized role in controlling the hardware which can lead to more efficient use of resources and better performance for specific tasks and then High utilization for large language models rocks LP GRS lpu system is

Designed to achieve High utilization when serving thousands of users which which is particularly beneficial for large scale systems that deploy large language models and here is the comparison between the grock Chip And nvidia's GTX 1070 and on the left you can see grock with Simplicity enables compute performance and on the right we have complexity leads to more compute costs and here we have a letter from Gro with a Q to Elon Musk saying hey Elon it's time to cease and de

Grock hey Elon did you know that when you announ the new a xai chatbot you use our name your chatbot is called roock and our company is called grock with Q so you can see how this may create confusion among people Gro with a Q AKA us sounds like a lot uh sounds a lot like identical in Brackets to grock with a k aka U and the difference of one constant q k only matters to scramblers and spell Checkers plus we

Own the trade Mark we can we can see why you might want to adopt our name you like fast things Rockets hyper loops on letter company names and our product Gro with a Q lpu inference engine is the fastest way to run large language models llms and other generative AI applications however we must ask you to please choose another name and fast I stand by my recommendation to name it startart fast it's both on message with your idea of sarcasm bought

Inspired by Hitchhiker's Guide to the Galaxy and sounds sufficiently distinct from any other AI company or product which is why I wouldn't recommend calling it giggle or open XI win-win but your call and making this request we're thinking about you as much as us it must be annoying having all those people hitting you up on X asking how the gro lpu inference engine is able to deliver 10x better performance and precision at scale or how it is 10 times more energy

Efficient and 10 times more cost effective that's plenty of x's even For You especially when it's not your grock I get it it was annoying when my great aunt asked me about my new spark snarky bought over Thanksgiving dinner but I passed the mashed potatoes anyways # grock on so you can see the grock team has a bit of sense of humor here and uh I'm excited to see how they're going to grow and let me know what your thoughts are

On grock with with a Q even grock with a K and as well as Nvidia their recent growth do you think grock actually stands a chance with competing with them do you think anyone stands a chance with competing with them or do you think the Market's still at a point where you know it's new enough you know inv Vias had this huge growth Spike and yes they're going to continue growing but there is room in the market for competitors I mean

There are so much you know there's so much opportunity to develop new Chips new Innovative chips the AI Market is com is scaling you know at a rapid rapid rate and you know in turn the chip Market is going to scale with it let me know your thoughts what your thoughts are in the comments down below and then here is a clip of chamoth from the all-in podcast one of my favorite podcast going over grock and he was one of the

First Investors in grock's lpu and uh you'll be able to hear what he has to say and some of his thoughts on the future grock also had a huge week that's grock with a Q not to be confused with elon's grock with a K shth you've talked about grock on this podcast a couple of times obviously you were the I guess you were the first investor the seed investor you pulled these lpus and this concept out of a team that was

At Google maybe you could explain a little bit about grock's viral moment this week in the history of the company which I know has been a long road for you with this company I mean it's been since 2016 so again proving what you guys have said many times and what I've tried to live out which is just you just got to keep grinding 90% of the battle is just staying alive in business yeah and having oxygen to keep trying things and

Then eventually if you get lucky which I think we did things can really break in your favor so this weekend you know I've been tweeting out a lot of technical information about why I think this is such a big deal but yeah the the moment came this weekend combination of Hacker News and some other places and essentially we had no customers two months ago I'll just be honest and between Sunday and Tuesday we've just we overwhelmed and I think like the

Last count was we had 3,000 unique customers come and try to consume our resources from every important Fortune 500 all the way down to developers and so I think we're very fortunate I think the team has a lot of hard work to do so it could mean nothing but it the potential to be something very disruptive so what is it that people are glomming on to you have to understand that like at the very highest level of AI you have to

View it as two distinct problems one problem is called training which is where you take a model and you take all of the data that you think will help train it and you do that you train the model you learn all over all of this information but the second part of the AI problem is what's called reference which is what you and I see every day as a consumer so we go to a website like chat GPT or Gemini we ask

A question and it gives us a really useful answer and those are two very different kinds of compute challenges the first one is about brute force and power right if you can imagine like what you need are tons and tons of machines tons and tons of like very high quality networking and an enormous amount of power in a data center so that you can just run those things for months I think Elon publishes very transparently for example how long it trains

To to train his grock with a K right model and it's in the months inference is something very different which is all about speed and cost what you need to be in order to answer a question for a consumer in a compelling way is super super cheap and super super fast and we've talked about why that is important and the gro with a Q chips turns out to be extremely fast and extremely cheap and so look time will tell how big

This company can get but if you tie it together with what Jensen said on the earnings call and you now see developers stress testing us and finding that we are meaningfully meaningfully faster and cheaper than any Nvidia solution there's the potential here to be really disruptive and we're a meager unicorn right our last valuation was like a billion something versus Nvidia which is now like a $2 trillion company so there's a lot of market cap for GR to gain by just

Being able to produce these things at scale which could be just an enormous outcome for us so time will tell but a really important moment in the company and very exciting and talking about the record-breaking speeds as well as giving a demo of the actual audio of talking to grock which is relevant to what I was speaking about when it comes to Rock's potential to help disrupt Ai call centers and AI um you know AI co- calling and whatnot and this

Is on CNN so let's play that right now for grock all right guys so that is it for this video thank you for watching make sure to subscribe like this video If you enjoyed it appreciate any support I'm really trying to go hard on providing you guys up-to-date information with all the latest AI news and Trends so I really appreciate your support as well as uh being a viewer here at and uh you know subscribing I welcome you to the channel

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As our client's business uh businesses we've set up multi-million dollar infrastructures with Ino high level for our clients businesses so you can use it whatever size of business you are whether you're just starting out or whether you're a multi-million dollar business and uh I would highly recommend checking out go high level if you're not using it already and we actually have a custombuilt snapshot a master snapshot with all the automations all the forms all the websites put into that snapshot that

We're giving away for free it's at ghost Rd level.com you'll see the link right here and you can get a 14-day free trial signing up through our affiliate link and if you sign up through our affiliate link it doesn't cost you anything else uh and there's no you don't pay for X to your users or anything like that it's literally the cheapest CRM that has the most features and capabilities and if you sign up through our affiliate link um just let

Me know message me shoot me an email Josh executive stride and we'll shoot over that free snapshot so if that's interest to you just go check out ghost.com watch the video it explains everything that doesn't interest you don't watch the video it's cool just you know enjoy these free videos and uh that's it for the for all the free stuff guys as well as the value that I want to um you know let you guys know about other than that I

Will see you in the next video I will be doing consistent videos so make sure to subscribe and I will see you guys very soon keep hustling keep grinding and of course accelerate your stride take care guys