Bitcoin Mining and the Race for AI Power | FRED THIEL

I'm great. Glad to be here.

The AI industry, similar to Bitcoin, needs a lot of energy to operate. If you go back to the late teens in Bitcoin, the challenge was turning on power to sites so you could deploy miners. And that was the big challenge back then. And granted, Bitcoin miners use a lot less energy than AI does. Though, if you go back again, the WEF said that Bitcoin was going to burn up the planet and use all the available energy that ever existed. Still hasn't happened. Now it's AI. But essentially, AI needs power. And if you look at the dynamics in the AI marketplace, it's about market share. It's not dissimilar to Bitcoin. It's how much energy can Anthropic versus OpenAI versus CoreWeave versus whomever Microsoft, AWS, etc. get so they can plug in their compute, so they can deploy their models, so they can operate inference for their clients, so their clients can get benefit of AI. To be fair, up until not too long ago, training was the primary use of AI data center. Now clients are doing inference. Inference is when you're chatting, when you're running agentic frameworks, that's inference. You're getting an answer from AI. That's what generates value out of AI. Training doesn't give you any real value as a customer. And so as agentic frameworks were launched earlier this year, you saw a huge uptick in token demand. And you just look at Anthropic sales numbers. They have surpassed OpenAI at this point. Huge uptick. And they are all capacity constrained because every model they released requires a lot more capacity to operate as the number of enterprise customers grows and as the growth within each enterprise customer grows, you have an exponential curve on the demand for tokens. And just look at all the news headlines about tokens or companies are spending way too much money. 3 months earlier it was about token maxing. Then they got their bills and it was like, oh my goodness. We got to watch out for this. And all that's being driven by a constraint in capacity. And so if you have constraint in capacity, it means all of a sudden, where is the constraint point? The constraint point is energized capacity. It's locations where you have land, you have water, you have energy, the energy is turned on and you just need to build a data center building. And the AI industry, just like Bitcoin, has always been constrained by what we call the three C's: capital, capacity, and compute. It was no different in 2019 when Mara was busy growing to become the biggest miner in the world. It's the same thing today in the AI industry. You go raise money, you go find capacity, and you go buy a bunch of GPUs and plug them in, compute. And that's the basis of what's going on now. So the challenge is if you were to go do greenfield sites, like some of our peers have chosen to do, then you get into queue for power. You have to get permits. It can take you 3 to 5 years. That is too far out from what the AI industry is thinking about today. They need capacity to come online in the next 2 years, or they will lose market share. And so it's a battle, and they're willing to pay fairly high prices.

From the hyperscaler perspective, the issue is do you have power connected today and available? Can you draw electrons today?

If you can draw electrons today and there's easy access to internet, and you have water for cooling, then all I have to do is build a building. And that's an 18- to 24-month process. That's why I'm online in 2 years. If what you're talking about is a site where you have submitted a request to ERCOT or whichever other utility or grid operator you're talking to for power, that may take you 3 to 5 years to get that power turned on.

No, because in a way, yes. If you own the power, you have the power available today. If you have a PPA, you have the power available today, too.

If you look at the way Mara operates, most of our sites are operating with some form of PPA. But we have the power turned on today. We're drawing on it today. And so one of the strengths in our portfolio, these over 1 GW of energized power today with capacity running up now, potentially close to 2 GW of power, is that power is available today. So a hyperscaler can come in and work with us and build a site and the energy is available today.

Do you have electrons?

Who controls the electrons is very important today.

Inference has driven an exponential growth in demand for compute. And so if you look at the ecosystem of the AI industry, it's not just hyperscalers, but it's people like Nvidia, AMD, Broadcom. That's all compute. Then you have cooling infrastructure, Vertiv, et cetera. You have power infrastructure, Schneider Electric, and others like that. And what happens is if there's only so much capacity available, all of those companies' revenues are constrained by the lack of available power. Because if you don't have power that's turned on, you can't build a data center. You can't plug in the compute and use it. You can't have a need for cooling, etc. And so Nvidia, for example, is very interested in ensuring that they get access to power for their customers because they can't sell more compute if there isn't more power to plug that compute into.

Think about it this way. If you're a producer of something and there's a constraint to your customers buying what you're selling and that constraint isn't money, that constraint is somewhere to plug it in. Then you're going to do whatever you can to remove that constraint. And so you have a lot of actors today, not just hyperscalers, but also compute vendors and neo clouds who sell to the hyperscalers, who are all actively looking for available power. And if you think about Mara's shift more recently towards AI, as we've said publicly, we've always felt inference was going to be the attractive market. We've also said that most hyperscalers won't want to work with a Bitcoin miner because Bitcoin miners haven't developed tier four data centers. They don't know how to build that level of redundancy, resiliency, cooling, etc. And so we felt that it wasn't right for Mara to go in the market and try and do this ourselves. This is why it was so important to find a partner like Starwood because with Starwood, we have a partner who has built and delivered and operated over 70 gigawatts of hyperscale capacity for the tier one operators in the space. And it's somebody who has a captive construction EPC arm who knows how to build these and deliver them on time, within cost, and to the level of service needed by the hyperscaler.

Think of it this way. They do not have a reputation for having ever done this before. So if Mara goes to Google and says, I have a site I want you to come in. I'm going to negotiate a lease with you. I've never negotiated a lease with a hyperscaler. They have never worked with me before. So they're going to put in every single little protection they can to make sure that they get what they want and that I have to deliver everything. Working with Starwood, who has delivered already to people like Google, Microsoft, etc., you already have that relationship. There's a certain amount of trust. The whole process goes a lot faster, a lot less friction. When you then look at construction, again, same thing. You have an experienced partner who's delivered before. And so there is a higher degree of trust from the end tenant that the site's going to be online and available and operated according to spec when it was planned to. And lastly, with Starwood, the big advantage for us is that they have the ability to credit wrap the project financing. Which makes it more attractive for us in that regard. Versus our peers, you read announcements about delays to sites coming online. That's because a lot of our peers have never actually built these sites before. And so now is when they're discovering that that lack of prior experience is starting to impact their ability to deliver on time. And there are huge penalties in these lease agreements for not delivering on time. In some cases, they're so big that they can remove a lot of the profitability of these deals. So now you've gone and raised all this money, gone and done everything you can to deliver this, and you deliver it 6 months late, and all of a sudden the profitability of that site is severely diminished.

Business development is really more managing tenant relationships, design and construction, and then operating and stabilizing the asset.

We are really the land and power bank, if you would,

in the relationship.

And because we have this portfolio of land and power available today, we were a very attractive partner for them. Because they now all of a sudden had inventory they could go and take to their clients and say, here's available land and power. Let's look at getting you in. And so what we've seen is since we signed the agreement, and we've been working with Starwood for over a year on this, and we had been out talking to tenants already late last year. So we're now seeing a very accelerated pace of conversations with tenants where you're starting to see a lot of activity around the sites, and it's more a question of allocating the right capacity to the right tenant, so that you're not overly dependent on any one tenant, which is risky because the economics of their business has changed. Look at OpenAI, they've gone from we're going to own and operate sites to we're going to lease sites to whatever their model is today. And so you have to be very careful as to how you do that. But I think we chose a great partner and I think this is going to be a great way of clearly generating a lot of value out of these sites that we have. And best of all, we get to keep mining Bitcoin the whole time up until these sites turn on and then we pick up our miners and move them to another site.

We look at power and land assets through the lens of what we call an economic triad. Is the power low enough cost and of a type that you can mine Bitcoin? Is the land and power and access to potentially water and internet sufficient to use it for a hyperscaler or an inference or a neo cloud site, colocation site? And then is this something that's really attractive for critical IT load potentially? Critical IT load versus AI HPC is more private cloud, the stuff we do with Xion, where it is smaller scale sites, but where the primary service you're doing is providing highly resilient, secure private cloud where an enterprise may want to run its own models. They're running their critical applications as well as their AI compute.

Exactly, and it's not multi-tenant. It's single-tenant. So if you think about it this way, Exaion was born inside EDF, which is the largest electrical energy producer in the world. A French company that operates a lot of nuclear capacity, 56 nuclear reactors today with more coming online every year. Their whole reason for existence was to operate the AI infrastructure for these nuclear sites in a way that was highly secure and in no way dependent on any outside third party who could shut off access to some technology, some component for those sites because at the end of the day EDF is a French state-owned company. And so it's a strategic player. If you look in Europe today, there is a high degree of concern regarding reliance on US, Chinese, or Russian, or any non-European technologies and technology companies because of the fear that they could shut something off. And now all of a sudden you can't operate. And the perfect example of this is what the US government just did with Anthropic and Fable. If you had been running as a company anywhere in the world, Fable, and the US just directed Anthropic to shut it down, you're now SOL.

It's what we call technically sovereign.

Yeah, so it's technologically sovereign. If you use the term straight up and down sovereign, the ownership of the company would have to be clearly sovereign, which is very hard because most of the technology components that come into these systems comes from somewhere outside of Europe. But at the end of the day, what you want to ensure is that no non-European actor can pull a plug on you.

No, it's not a new idea. Simply look at the fact that look at your bill from Anthropic or OpenAI or Gemini or Amazon and look at what you're spending per token and then say do I really need to use them to do review and edit drafts of emails? Do I really need to use those models to do analysis of a financial spreadsheet? You need to apportion the type of tasks to the model that is best suited to it and has the most appropriate token cost. You can today run your own models and there are lots of different models and I think even Exaion today in their infrastructure operate over 12 different model systems that you can easily switch between. You can easily shift all of that basic bread and butter AI use to your own models and run those in-house at dramatically lower cost.

No, they're absolutely starting to do this. We have spoken to enterprise customers who are moving their AI processing and their AI infrastructure out of Amazon AWS and into proprietary private cloud infrastructure because it's a 10x savings.

Realize your private cloud infrastructure provider has to have full secure infrastructure, etc. And so you need to ensure that again, another reason for Exaion. That's what they do. If they can do it for the nuclear systems in France, you have to assume that they have a very high level of security in what they're doing. Can you ensure that the data can't be taken by anybody? Can you ensure that the data is always safe, meaning it's encrypted whether it's at rest in flight or in use? Can you ensure that people can't access the sites? Can you ensure that no foreign actor can do something that shuts the site down? The big issue in Europe is also the Cloud Act, which is a US law that essentially says that if you're running on Google infrastructure in Europe, your data is accessible under the US Cloud Act. So all of these things are driving people to really look at running their own infrastructure. It's not necessarily efficient for you to build your own data centers, but you can operate with somebody like Exaion who can operate private cloud on your behalf and provide all the services that you need. So you get all the benefits without necessarily having to build that infrastructure yourself.

Longridge is unique in one way in that A, we already had a 200-megawatt substation or site with 200 megawatts allocated to it called Hannibal, which was adjacent to Longridge. Longridge had 1,600 acres of land and a 500 megawatt dual cycle gas-fired plant. And we were very interested in the land. Because the land we had at Hannibal wasn't sufficient to build a hyperscaler site. And we also wanted to have access to more power. And while Longridge today sells the vast majority of its capacity into the grid and we're not going to change that, there is the ability for us to add more capacity to the site from a generation perspective as well as applying for more load for the Hannibal site. That can get us to 600 megawatts available to build a significant hyperscaler site on the land that we would control as soon as we close the Longridge deal.

It depends on the application. Hyperscalers today are typically looking at things north of 250 megawatts. But there are lots of neo clouds who want things north of 50 megawatts. And the neo clouds service the hyperscalers predominantly. CoreWeaves of the world, Nscales, etc.

A neo cloud is essentially CoreWeave's the perfect example. They essentially are running GPUs as a service on behalf of a hyperscaler. So if you're Google, Microsoft, whoever, and you want to grow capacity, you can do it using your own capacity or you can do it asset light, which is you contract with a neo cloud. I'm going to take 100% of your capacity for the next 5 years. You're going to buy the GPUs, you're going to build the site, you're going to operate it, and I'm going to pay you a fee per megawatt.

That's a fixed amount. If you think about how we grew as a Bitcoin miner, we did the same thing. We grew initially by being asset light. We didn't own and operate sites, we just contracted for capacity so that we could grow as fast as possible. We then vertically integrated to own the sites, which we were able to do at lower than replacement cost, and then we started buying power assets to fully vertically integrate. It's exactly the same thing the hyperscalers do. They own and operate a certain amount of capacity themselves. They contract with neo clouds so that the neo clouds have to take the risk of buying the GPUs and doing all of that. This isn't on the hyperscalers' balance sheet, it's on the neo clouds' balance sheet. And so that gives them extra flex capacity. And then over time, they will build more of their own sites. And the neo clouds just become middle men.

Essentially.

And so it's going to be very interesting to see how this business evolves over time, but I think there's going to be more than enough demand for inference capacity that the neo clouds will eventually shift their business from servicing hyperscalers to servicing enterprise customers because it's a much higher margin business.

Yes, than servicing a hyperscaler. I mean, negotiating with Google, granted, it's great to get a 10-15 year contract with Google for something, but if you can service enterprise customers, there are more services you can bake into what you're doing, which makes it a higher margin business.

From bells and whistles, basically, that you're able to offer enterprise high end.

Security is definitely a bell and whistle. Other bells and whistles are the ability to do load shaping, load balancing, the ability to run multiple different models, the ability to automatically route traffic based on the cost of a token, based on the latency that your use case provides, so quality of service.

Yeah, so I think it what you're really going to get to is where essentially it's going to be a little bit like the internet where you are essentially going to just take it for granted and you're going to say okay, I'm going to run my model and I need to run it within kind of sandboxed safe architecture and I'm not going to worry about what models being run or where physically it's running or anything like that. That is all going to be hidden behind a control plane that I operate with and I'm going to work with my trusted vendor who's going to ensure that the data is secure, that the models are all updated continually, that the infrastructure operates, it's fully resilient, etc.

Well, the capital required is much more different. In Bitcoin mining you're at about a million dollars a megawatt all in between infrastructure and compute. In the hyperscaler game or in the large-scale AI, your infrastructure, just the building power to the building cooling to the building is anywhere from 10 to 15 million a megawatt.

So, right there you're at 10 to 15x. And that's even before you consider the compute, which is most probably 40 to 50 million a megawatt. Right? So, now you're talking 50 to 60 million dollars a megawatt, which is 50 to 60 times higher than what it costs to do Bitcoin.

Well, you obviously are charging a fee that is giving you a good return on that capital, but you have to have access to the capital to be able to do it.

Now, granted, Mara is not going to be in the business at least initially of renting GPU capacity. We're building buildings for data center operators like Google, Microsoft, and others to come in and deploy their own compute in those sites. Almost more like a real estate development play where we control power and assets, and we allocate those accordingly. Over time, we may very well, especially at the lower end of the marketplace, build and operate actual token factories, if you would, as capital is available, as the market continues to develop.

Essentially. And if you look at what Xiyan does today, I mean, they are a buyer, they're a partner of Nvidia. They buy GPUs, they deploy GPUs for their enterprise customers. Again, Xiyan is the high-value, high-margin end of the spectrum, low scale. All right, a typical Xiyan data center may be 5 to maybe max 25 megawatts. All right, your Neo Cloud site is typically 50 to 200 megawatts, and a hyperscaler site is 250 and up.

Absolutely. There are very few companies out there today that require more than one NVIDIA cluster to run their models. Inference is much more efficient from a compute perspective than training is. Training is very GPU intensive. Inference doesn't really require GPUs. You can run it on a mix of A6 and CPUs. And so, this is why NVIDIA went out and did this deal with Groq. Because it enabled them to release an inference system that costs about 1/30th per token of what it would cost if you just ran it on the latest GPUs.

Well, similar to Bitcoin mining, there's technology obsolescence risk.

So, now think you have a tenant who is leasing GPU capacity from you. GPUs don't last 15 years. Just like Bitcoin miners don't last 15 years.

Every 3 years you're swapping out and upgrading your Bitcoin miners. Every 3 years, think about it. What was NVIDIA selling 3 years ago? What are they selling today? What are they talking about selling in 3 years? Hugely different technology in the sense that it's much more efficient, much more powerful. If you're a hyperscaler and you're renting capacity from a neo cloud, for example, 3 or 4 years down the road, are you going to want to be paying that price for infrastructure that's three or four years old?

Think what you're going to see is the hyperscalers and the large companies like putting the balance sheet risk of all those GPUs on the neo cloud vendor.

If you were to sit down with a financial analyst and look at all these credit deals that have been done by the neo clouds and the credit backstops and who's actually ensuring that these guys can get the credit they need to go buy all these GPUs. The question is what happens when those GPUs reach the end of their economic life? Where in the calculus of all this, where in the performer projections of all these neo clouds is the technology obsolescence risk taken into account?

They're hoping that the profitability is such from the contract that they will be able to afford to upgrade.

Yes, you can project the revenues, but the question is you now have to make a decision about at what point do you refresh the infrastructure? And what's that going to cost at a point in time in the future?

No idea. And most of the performers, if you look at them in a 15-year contract, maybe include one technology refresh, which I think is a pipe dream.

It could be three. I mean, and the other thing is today as people are looking at GPU rental rates and saying, 'Well, H100s are still renting at attractive price. Well, that's because there's limited capacity. Right? As more and more capacity comes online and as machines become more and more efficient, you start getting a growth in actual capacity. Again, similar to Bitcoin mining. You take a machine that operates at 30 joules the terawatt

A terahash, sorry. And now you replace it with a machine that operates at 15 joules a terahash, you've just doubled your capacity on the same amount of power.

So, same thing. You take GPU / ASIC / CPU solution that uses X amount of power to generate a certain amount of compute. And you make those machines super energy efficient, then all of a sudden you're increasing capacity without having to increase your physical plant.

Absolutely. Well, it's going to be, can you deliver a site on time? To spec. With the operational resilience the customer wants. That's the first thing. Second thing is, can you over time operate the site such that it's profitable? And then this is in the case of a neo cloud where you're having to worry about infrastructure and you're operating the site and you're hands-on. In the case of our business model, at least with Starwood, we are essentially building a powered shell for a customer. They're coming in bringing their GPUs, they're operating it. We don't run that risk. Right? We are really in that sense a true asset manager. We're investing in an asset. We're underwriting to a certain fixed return. And then, that's what makes the deal so attractive.

I think if you look at the legacy of Bitcoin mining, it's been a business of wildcatters.

Not many wildcatters ever end up creating big oil companies.

I think it's going to be a combination of consolidation and just expertise. I mean, if you look at our team on that side of the business, while on the one hand you have deep operational expertise around Bitcoin mining and Bitcoin mining sites and how to operate hundreds and hundreds of thousands of machines around the world to generate Bitcoin.

We also have people with deep expertise out of the energy generation industry, out of the energy banking industry, out of the credit and finance industry who know how to underwrite and look at these models, get them financed, etc. So, I think it takes a much broader set of experts on a team to really be successful at this versus what it took to be successful as a Bitcoin miner. Remember, Bitcoin miners don't have customers. Start there.

To be a Bitcoin miner, you had to have money, you had to be able to find a plot of land, get access to some power, and cut a deal with a hardware vendor so you could get miners and plug them in.

And then you just had to run them as hard as you could.

It's a very different game here. It's not bandits and rubber bands. It's doing things to a very high degree of quality, high degree of security, high degree of resilience.

Yeah. It's like going from very much bush league to major leagues. And not all players make it to the major leagues.

So, Bitcoin mining has a number of advantages as a developer of AI HPC assets. For one thing, you can plug in Bitcoin miners tomorrow and take power immediately, which is really important for the power companies because they don't want to allocate power if you're not able to use it because they want to generate revenues.

So, Bitcoin miners can come in, operate, we build modular sites, they're fully containerized, we can build them and move them very quickly and easily. So, it gives us the ability to immediately take and use power while we're designing and getting ready to build the hyperscaler or the AI HPC site. And then as we build that site, we can shift power over to that site over time and remove the miners and move them to the next site. So, it gives us an ability to monetize electrons much faster. The other thing that it gives us is the ability to continue to go look and explore parts of the world where power pricing and the need for flexible load are such that it makes sense to still mine Bitcoin. And there are lots of places in the world where there is excess power today, where there is a need for flexible load, where Bitcoin mining plays a role. And I go back to a speech I think I gave at Mining Disrupt in 2021, which was basically the power companies are going to be the Bitcoin miners of the future. Why? Because they're the ones who own excess power. And they're the ones who have a need for load balancing over time. And I think that will continue to be the case. I think Bitcoin miners will partner with power companies or they will become power companies in their own right.

So, we have a load balancing technology called Vertebrae, which we have deployed within our own infrastructure. There's a lot of interest from third parties to deploy that in data centers as a way to essentially take any excess capacity, power capacity, that the data center has and monetize it in a way. You also have to look at it from the power company side. Power companies now want AI HPC data centers to become flexible loads. They want them to be curtail-able. Right? So, that means you have to have backup power, but it also means you need to be able to load shape. And their data centers today aren't designed to load shape. They're designed to just use power and use it in whatever way they want to. They need a fixed amount of power. The problem is the utility wants, if they're going to have use a fixed amount of power, they want them to actually use the fixed amount of power. They don't want them to say, I'm giving you 100 MW, but you're using 66, 72, 85, 99, 97 all within the course of a day. Because now the power utility, again, think about the grid. It's like plumbing, right? You have to balance it continually to make sure that you're not putting too much power, too little power anywhere. They're having to essentially adapt to your load. So, if you can create a steady load profile, the power company will give you a lower rate. Right? And then if you can make that load somewhat curtail-able, so say you have 2/3 of your power is AI HPC and a third is Bitcoin mining potentially, then you can always curtail that Bitcoin mining and give that power back to the grid when they need it. And it gives you the ability to scale up and the Bitcoin mining to scale up when your power needs are lower.

No, I mean at the end of the day you have to get to zero cost power.

And even then you're not halvening-proof.

Because you still have to buy the infrastructure, you still have to buy the miners, right?

And you still have to get a return on them. So I think while today it's Bitcoin, it may very well in the future just be flexible load AI HPC.

It will be a thing.

Again, I think power companies who have a net zero cost of power for Bitcoin mining, any power they're generating that they can't sell is viable for Bitcoin mining. They will potentially view Bitcoin mining as a way to monetize excess power. So, I think again, as I said now 5 years ago, the power companies are going to become the Bitcoin miners of the future.

Potentially. Yeah, listen, Satoshi designed the subsidy and transaction fee mechanism under the premise that Bitcoin was going to be used for transactions. That is not how Bitcoin is used today. And so, until you have a transaction fee or other fee basis that supports the so-called security budget, the halving cycle is going to make it less and less profitable to operate Bitcoin mining.

I don't think on a dollar per terahash basis, prices have ever been this low. And that calls into question a couple of things. One is how long will Bitcoin mining ASIC manufacturers continue to produce ASICs if they can't sell them? As they begin to give up their allocations with the foundries for wafer capacity, and by the way, the foundries want that capacity back because the AI ASIC vendors need that foundry capacity. Then the available amount of hardware in the market starts decreasing, which may just lead to prices going back up again. And so I think long-term global hash rate will decrease. I think long-term it's going to become a marginal business. And there will be very few people who can affordably operate unless they're using Bitcoin mining to gain a subsidy somewhere else.

Revenues off of the byproduct of Bitcoin mining. So, either your load balancing is a service you are charging for or your heat is being sold and you're charging for it or something like that.

Correct.

Any cost of energy is going to potentially make Bitcoin mining unprofitable.

Well, I mean think about it this way. So,

All of this old inventory of AI because I mean in the Bitcoin world we're used to major refresh cycles every 3 years. In the AI world, Nvidia's obviating machines every 6 to 9 months. So, that infrastructure hits the market and somebody's going to buy it and somebody's going to figure out a way to take those old machines and make them flexible load and operate them on a part-time basis just like we do with our wind sites. So, we move our old machines off of grid attached sites and we put them on a wind farm. Why? Wind energy is marginal cost zero. Right? You run the machines. If they only run 6 hours a day, it doesn't matter. Right? The machines are already written off. The energy's almost free. Any production is good production.

I think it's a combination of things. A, we have a very unique portfolio of sites. Right? There are not a lot of people who have as much capacity as we have in the locations that we have it.

No, just across the

And now I'm excluding the sites where we are hosted. So, we have a site in Texas and a site in Nebraska where we're hosted. And those contracts roll off in the next year and two years. So, at that point we won't have any hosted capacity at all. But as you look at our business, we have sites in very attractive locations that have energy available today. And you will continue to see us acquiring more energy and land assets that are very highly attractive to hyperscalers where that power is available if not currently, in the very near future. And we're going to continue to build that portfolio and we're going to continue to work with Starwood, the synergies of our relationship with Starwood are very unique and don't exist anywhere else in the industry. It makes it much more capital efficient for us to do sites. Most of our peers can only do one site at a time and they're having to spend huge amounts of capital to do those sites. And the nature of our relationship with Starwood makes it much more capital efficient for us.

You can't do AI, HPC, or Bitcoin without electrons.

Acquire electrons and then generate maximum value per electron.

Anytime. Thank you.