fbpx

NVIDIA, AMD, & the future (and present) of tech

Nvidia and AMD are companies that create graphics cards, processors, and some other components for computers. Graphics cards have come to the forefront of the “Third Industrial Revolution’ because they do the calculations that make machine learning possible. In this context, Nvidia is the gold standard, and AMD is like silver. 

AMD also make CPU, like Intel, with their line of processors called Ryzen. Never heard of it? Does that make it undervalued, or worthless? You’ve probably heard of Nvidia because that’s what’s in your computer if you have an Apple or Windows GPU. In some cases AMD is equivalent in performance, or better. Certainly, many people consider AMD a better value.

All speculations aside about the differences in the difference between the inherent and perceived value of AMD and Nvidia’s components, let’s talk about the vale of what they are making.

Theoretical Underpinnings of Bullish Sentiment for GPU Market

So let’s get specific about why GPUs are important in the economy today. What sorts of products are they necessary for? To understand this, a good example is the screen that you are looking at. Each one of the pixels that you see in front of you has to be controlled, and a graphics card transmits this information as an instruction onto the screen. 

In a graphics card, each core can do a simple calculation, such as controlling a pixel on a screen or performing a mathematical calculation. The beauty and power from these components (GPU) comes from the way that they work together to perform a greater, and often times extremely complex, task. 

This is much different than a CPU. Consider that, at the low end, an Nvidia GPU will have at least a thousand cores. Compare that to the latest highest end Intel $7k CPU, which has only 24 cores. CPU cores can do many more different things than the cores of GPUs, but because GPU cores are more specialized they can be more quickly or efficient, and there can be more of them used by the computer successfully. 

Now that it’s clear what a GPU is, let’s talk about the applications for the hardware. GPUs are necessary for machine learning, augmented reality, virtual reality, gaming (e-sports), and cryptographic calculations (crypto mining). Let’s break down the value a little more.

Artificial Intelligence, Gaming, & AR/VR in the Workplace

How does breaking down the limits of time and space to tell the future sound? What about abating the risks of superbugs like Covid 19 while maintaining close connections. As in, having a group of co-workers in your living room, and being in their living room, while also being on the plant floor. All this happening while cloud infrastructure is pushing gaming powered by the same GPU’s that are making this possible. Therefore, behemoths are spreading the cost of super-powered (and super profitable?) chips across the population and increasing investment into GPUs. Add 5G into the equation and it looks like investment into GPUs will increase, even as the cost to consumer increases, but probably through a subscription service.

What are the risks, though, especially in the short-term? How do we know that these stocks will go up in the short-term, especially in a hyper-globalized JIT world with fragile supply chains. So what if China got a hold on the new corona virus and they’re ramping production back up if the supply chain has kinks in other places in the world with no backup plan. Are supply chains too fallible at the expense of cutting expenses? There are some new risks that need to be integrated into the supply chain from corona virus or other low probability catastrophic events. These are real risks, especially because in Nvidia’s most recent report they state: 

“We do not directly manufacture semiconductors used for our products. Instead, we utilize a fabless manufacturing strategy, whereby we employ world-class suppliers for all phases of the manufacturing process, including wafer fabrication, assembly, testing, and packaging. This strategy uses the expertise of industry-leading suppliers that are certified by the International Organization for Standardization in such areas as fabrication, assembly, quality control and assurance, reliability, and testing. Additionally, we can avoid many of the significant costs and risks associated with owning and operating manufacturing operations. While we may directly procure certain raw materials used in the production of our products, such as substrates and a variety of components, our suppliers are responsible for procurement of the majority of the raw materials used in the production of our products. As a result, we can focus our resources on product design, additional quality assurance, marketing, and customer support.”

Even if demand increases because of the importance of remote work, remote school, increases in game sales (especially subscription services in this area, with consumers iffy about making big purchases with lower income expectations), will Nvidia be able to source the stuff? Will innovation be stifled by the fact that it does not have it’s necessary building blocks; is AR/VR in the workplace too nascent for white-collar workers to realize that it is what they need? Will investors consider the future income from these possibilities, or is that too Silicon Valley-esque, and they have too bad a hangover from the threat of negative interest rates.

Are we in survival mode, or is it time to find real(ly awesome) solutions? Nvidia has exposure to AI, gaming, VR/AR, driverless cars, and bitcoin. I believe that it is a good bet in the corona economy because remote work is more important, and fiat currency may lose value with unemployment insurance in some cases SIGNIFICANTLY exceeding income from jobs. Will employers find automation solutions previously thought too expensive attractive as workers gain market power and demand wages in excess of what seems to be the emergence of a Universal Basic Income?

Will a check from the government, in fact, solidify income expectations, as opposed to the current belief that job loss will shake consumer confidence, resulting in similar or even increased momentum of money? Inflation could be on the horizon, and one place I would rather not be is in cash because inflation obviously devalues cash. Bitcoin may be a good short-term solution, and Nvidia provides that exposure as well because their equipment can be used to mine the cryptocurrency.

Moreover, with most of it’s supply chain in Asia, where governments have a more tyrannic hold, resulting in ability to quarantine citizens under threat of fines or worse, the supply chain may be surprisingly resilient (that’s the important thing: surprise). Supply chains may not be as nimble as previously thought, but supply is not thought to be the problem. Demand is, and governments are taking care of that by putting money in the hands of people out of work with nothing to do but play video games or work on hobby projects. This, however, is where AMD takes the stage.

AMD’s graphics cards are cheaper than Nvidia’s, but have similar or in some cases better performance, especially when it comes to tasks that don’t require perfect calculations, such as gaming computers. For people working on hobby projects with uncertainty about future income, they might choose AMD over Nvidia to cut costs, as they dabble in their garage building that computer that’s been sitting there for years while they trudged to and from work. While Nvidia’s cards are preferred for industrial applications like AI or AR/VR for Microsoft’s HoloLens, hobbyists will prefer AMD’s GPUs and associated CPUs. The bottom line is these people are going to have to do something while they are cooped up in the house, and people love video games.

However, my bet, and I agree with analysts that Nvidia is better positioned to benefit from the Corona economy, is that we are even going to see increased government investment into a way to leverage technology to make remote work less remote. Increasing innovation in the remote work, remote education, remove everything is now a matter of national security. The technology is increasingly here (5G, AI), but the reason to switch has not been evident until we entered the Coronavirus economy.

The company that most stands to benefit from this hype is Nvidia, but AMD may post strong numbers in the face of a shitty economy.

About Data

Data Analytics Offering

Machine learning is transforming industries, but businesses should be afraid of it. Transferring systems or integrating systems can lead to losses instead of gains. In some cases, businesses crumble when trying to innovate because their operations come to a screeching halt.

Implementation is Everything

There are a thousand offerings that can be sold to a business. Promises of automating expensive workflows sound great. Remember that when you are messing with important workflows there is much to lose, however. Businesses today know the importance of technology, but it’s good to keep in mind the importance of business as usual. Implementing new systems takes careful planning. Serving the customer today ensures the business will continue to serve customers tomorrow.

Start for tomorrow.

Futuristic Products

That being said, there is much to gain from implementing the technology that already exists. Amazon has many awesome tools that, with that careful planning mentioned earlier, can maximize the potential of your business.

Now is time to talk about a few of them, and the implications that they bring. Keep in mind that this business (Sage Market) is all about innovating to use existing technologies to their maximum potential. I hope you will contact us through any of the channels below the header image to talk more about this.

Amazon Kendra

When I first heard about NoSQL databases, I was grateful that I had found a reason to slack off about learning SQL (I am happy to say I understand SQL databases).

Basically, a NoSQL database is a distributed database that is supposed to make it easier to query data, and I was taught in business school that it would have implications when it comes to unstructured data.

I think that a good analogy for this is Google. Google indexes and organizes lots of unstructured data and then decides what you mean when you search for something. When I took my second business analytics class they said that NoSQL was supposed to allow querying of data without using SQL, like Google.

Unstructured Data?

Let me back up a bit. What is unstructured data, and how does it differ from “structured data”? I back up like this because this is a very important point not only to the idea of NoSQL, but to the application of machine learning to querying databases. Extracting the truth from the data is easy when the labels give you the answer, but becomes much more difficult when the algorithm has to label the data itself.

"BUSINESS HAS
ONLY TWO FUNCTIONS
MARKETING AND
INNOVATION"
-MILAN KUNDERA

Sage Market Technology Consulting

The real reason I got so excited when I heard about NoSQL was that it seemed that to create a NoSQL database (as the hype misinformed me), the unstructured data would need to somehow structure, or label itself. Otherwise, how could you query the data in a number of different ways and receive the same information? The query would need to contain a kernal of truth that the system could search for in the data.

Enter Amazon Kendra... (again)

So my interest in NoSQL has really just manifested itself in Amazon’s Kendra product. Instead of putting a bunch of effort into labeling and organizing your data so that it is available to the people who need to communicate it, gain from Amazon’s machine learning algorithm. Let it do as much heavy lifting as possible, and only after you find out what the tech can do should you invest more time and energy.

Clarify with an Example

I used to work for a Credit Union, answering the phone and talking to customers about their accounts. Surprisingly, customers would ask me, being paid close to minimum wage, about esoteric financial regulation. We were supposed to say, “Sir/Mad’am, I am not a financial advisor/accountant, and therefore cannot advise”, but I like to talk about esoteric financial regulations, strangely enough.

One day, a woman called and asked me about the title on a boat that she was going to purchase. It was different from a normal loan, however, because it had been owned by the Coast Guard. It had a special lean on it, called a Ship’s Preferred Mortgage, or something like that. You might think, there is no way anyone could know about that, but my boss pulled it out of thin air. I was jealous, but impressed. I found out later that he had just entered a slightly different search into our internal intranet, and it was written there in plain English.

Ok?

You might be thinking to yourself, Hayden how does this relate to using machine learning to improve business processes? I’ll tell you how. When that person asked that question, a voice recognition software could have triggered a search into the internal database, using Amazon Kendra’s artificial intelligence to query and return the right information. Then, it could have just popped up on my screen.

I want to stress that this sort of technology could be possible for your application, too! With a little imagination and the right research, any business can implement these awesome tools with little to no risk. Then, benefit from the profits, give back to the community, and go down in history as generally awesome.

Who are you?

Thanks for reading this! I hope that you contact me to talk about how machine learning can be used to improve you business effectively and ethically. Also like us on Facebook and Instagram, or e-mail me directly.

Sage Market is Growing

We want to create a network of entrepreneurs to spread the goodness of technology. If you are added to the e-mail list, I will reach out to you personally. To be added to our automated Facebook Messenger list & receive personal communication from me, click the button.

Opt-In Button
Artificial Intelligence Intuition Header

Artificial Intelligence Neural Networks Intuition Introduction

Intuitively Understanding Machine Learning

Artificial Intelligence. The buzzword if the decade. Some people are scared of it, others are scornful. Populist voices angrily express their fear of being automated or worse deny the possibility. Is it denial or misunderstanding?
 
One thing is for sure: artificial intelligence is misunderstood for good reason. The same mentality from Einstein’s famous quote about quantum mechanics applies: “if you think you understand [artificial intelligence], you don’t understand [artificial intelligence]”. 
 
This is especially true for artificial intelligence that is a “black box”: we actually can’t explain the predictions, but we can measure the accuracy of them. 
 
We can measure the accuracy of a prediction by pretending we don’t know the answer and then comparing the predicted value to the actual value. In order to increase the accuracy of our predicted accuracy, we can split the data up as many different ways we want, training on the one section and testing on the other, ten, twenty, or even a hundred times. This is called cross-validation.
 

Neural networks are famously hard to model. When I say model them, I mean explain why they come up with the prediction that they come up with. This is because they use something called  automated feature selection. This means that the variables that make the prediction are automatically chosen by the neural network from the data.

Each one of these ‘features’ is called a perceptron, and they can be layered, each layer and link between representing the relationship between the features/perceptrons.

These are exactly like the associations that we have baked into our brains, and that’s the analogy to our brains that the “neural network” represents.

Slope Intercept Form (Yawn...) for Neural Networks (Yay!)

Remember slope-intercept form from basic algebra?  y=mx+b shows the relationship between y and x, which are both variables. In this equation, b is the constant
 
*eyes glaze over* – “WAKE UP!”
 
Okay, so now think really hard. We have two variables that we are trying to show a relationship between. Sound important? If we can model the relationship between two variables, we can make predictions and provide insight into why there is a relationship! 
 
So the m in this equation is called the coefficient and it is important because it quantifies the relationship. It allows us to model the relationship! Things get more complicated though, and then much more complicated (we’ll talk in a bit how to use generalize this idea of slop-intercept form to think about neural networks). 
 
Think about adding more variables. Instead of a relationship between two variables, such as height and weight, now we add other features of a person, such as hair color. Some of them won’t have an impact on what we are trying to predict (height), in which case the coefficient will be zero. So then we have multiple m’s/coefficients. 
 
Now’s the kicker. Take each one of those m’s/coefficients and put another equation inside of it, with it’s own m’s/coefficients. Now consider that maybe there’s a relationship between the m’s/coefficients in that m/coefficient and the m’s/coefficients of the other m’s/coefficients. Mmmm.. M&M’s.

Neural Networks Simplified for Intuition

There are many different types of neural networks, and one thing that differentiates them from each other is the relationship between the perceptrons, or the m’s. This is the more simple way to understand them that provides the intuition. When one perceptron’s impact on the prediction is visualized, it seems disjointed and random, but together they make the prediction. 
 
A great example is a number recognition system. AI’s are famously good at image recognition. For example, one of the features might be the way that a four has a horizontal line in the middle, and that’s all. The prediction power comes from the way that this relates to other lines, parts of numbers, or other types of features.
 
Thanks for reading this! Stay tuned and follow us on Twitter or Instagram for more.

Elasticity & Agility on AWS

Value is a Value Prop

Sage Market is about adding value to your business by first applying existing technologies. This article is going to talk about a couple of the value proposition that Amazon Web Service’s technologies offer: agility and elasticity. More importantly it is going to discuss why these value propositions are important. By the time you finish reading this, I hope it will be clear why Sage Market is worth your time.

The plan for Sage Market is to become part of the Amazon Partner Network, among other things. This means Sage Market will be an Amazon affiliate, being knowledgable of the Amazon product catalog and experienced in deploying the solutions. Additionally, it will bring a breadth of knowledge about how to apply technology in other ways to grow and improve the business.

Amazon Products

Amazon Web Services is a suite of tools that allow businesses to take advantage of technology in some important ways. It allows you to serve your customers better because it offers agility and elasticity. Agility means that you can experiment quickly and cheaply. Elasticity means you can scale your business to meet surges in demand that might otherwise cause your system to crash. Let’s talk a little more about what this means, starting with agility.

Agility: Smart R&D

Businesses today face a seemingly insurmountable challenge: innovate or be squashed. You might say to me, “that’s all good and fine, but I’ve been around for 70 years. I have got nothing to worry about. Besides, I couldn’t put people out of work by innovating. That would be heartless.” To this, I shake my head and grimace.
 
Both political parties are growing tired of free trade and globalization, fueled by fear of the masses. They have a secret, though. As populism rises and manufacturing is incentivized in future legislation, state of the art plants will increase production.
 
These plants will, much to the dismay and surprise of the populist movement that hates losing their jobs, use automation and hire a fraction of the workers.

 

There will be new entrants that come into the market and compete with this state of the art capital, even if you don’t. They won’t even have employees that they would lay off with the new technology. They’ll sure have an incentive to automate your manufacturing business cheaply, though.
 
Any incumbent business owner who has benefited from competitive advantage to profit for years should be investigating how the recent tech boom will affect them. If they have even a shade of foresight they will be researching and experimenting with how they can use technological advancement to fend off the future of specialized labor that will be AI.
 
What is the best way to do this? Cheaply and with minimal risk, of course. This is what agility is. It is the ability to experiment with your finger on the pulse of your business, reading and analyzing your data in real time to pivot or embrace whatever it is your are experimenting with.
 
Amazon has tools to optimize this process. Now, agility is important, but how can this be possible? Elasticity and agility are so related it can be confusing to decouple them in the mind.
SAGE logo

Elasticity Universal Truth

Elasticity is being able to react to market activity in real time. It means scaling your activities in direct response to what your customers are doing. This is simply good customer service, but it is also cost effective.

Just as important to the bottom line as increasing sales by being responsive is to minimize costs. It is also great for the environment, so by being responsive to your customer you will save the planet and attract more customers.

Any business savvy individual knows that a dollar saved is a dollar earned. If you are chasing dollars for your business, whether that be for society’s good or to buy a new car to show off to your neighbor, there is no difference between a dollar from cost-cutting or sales-increasing. This is a universal truth.

Get Involved

If you are serious about staying relevant in the changing landscape, it is cheap to get started. I will work with you and create a quote for you and your business for free. If I can’t add value, I would not even think of charging a dime.

Additionally, I am looking for people that are ambitious about applying technology to change the world in a positive way. Sage Market is in it’s infancy, but it has a positive future, just like us. Check out our social media channels, or e-mail us at support@sagemarket.info.

Theme BCF By aThemeArt - Proudly powered by WordPress .
BACK TO TOP