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Ben Fielding: Decentralizing Machine Intelligence

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2 месяца ago

2 апреля, 2025

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It started with a noisy desk. The desk was a wooden cubicle in a lab at Northumbria University, in northern England, where a young AI researcher began his PhD track. This was in 2015. The researcher was Ben Fielding, who had built a large machine stuffed with early GPUs to develop AI. The machine was so loud it annoyed Fielding’s lab-mates. Fielding crammed the machine beneath the desk, but it was so big he had to awkwardly stick his legs to the side.

Fielding had some unorthodox ideas. He explored how “swarms” of AI — clusters of many different models — could talk to each other and learn from each other, which might improve the collective whole. There was just one problem: He was handcuffed by the realities of that noisy machine beneath his desk. And he knew he was outgunned. “Google was doing this research as well,” Fielding says now. “And they had thousands [of GPUs] in a data center. The things they were doing weren’t crazy. I knew the methods… I had lots of proposals, but I couldn’t run them.”

Ben Fielding, CEO of Gensyn, is a speaker at Consensus 2025 in Toronto.

Jeff Wilser is the host of The People’s AI: The Decentralized AI Podcast and will host The AI Summit at Consensus 2025.

So a decade ago, it dawned on Fielding: Compute constraints would always be an issue. In 2015, he knew that if compute was a hard constraint in academia, it would absolutely be a hard constraint when AI went mainstream.

The solution?

Decentralized AI.

Fielding co-founded Gensyn (along with Harry Grieve) in 2020, or years before Decentralized AI became fashionable. The project was initially known for building decentralized compute – and I’ve spoken with Fielding about this for CoinDesk and on panel after panel at conferences – but the vision is actually something wider: “The network for machine intelligence.” They’re building solutions up and down the tech stack.

And now, a decade after Fielding’s noisy desk annoyed his lab-mates, the early tools of Gensyn are out in the wild. Gensyn recently released its “RL Swarms” protocol (a descendant of Fielding’s PhD work) and just launched its Testnet — which brings blockchain into the fold.

In this conversation leading up to the AI Summit, at Consensus in Toronto, Fielding gives a primer on AI Swarms, explains how blockchain snaps into the puzzle, and shares why all innovators — not just tech giants — “should have the right to build machine learning technologies.”

This interview has been condensed and lightly edited for clarity.

Congrats on the testnet launch. What’s the gist of what it is?

Ben Fielding: It’s the addition of the first MVP features of blockchain integration with what we’ve launched so far.

What were those original features, pre-blockchain?

So we launched RL [Reinforcement Learning] Swarm a few weeks ago, which is reinforcement learning, post-training, as a peer-to-peer network.

Here’s the easiest way to think about it. When a pre-trained model goes through reasoning training – like DeepSeek-R1 – it learns to critique its own thinking and recursively improve against the task. It can then improve its own answer.

We take that process one step further and say, “It’s great for models to critique their own thinking and recursively improve. What if they can talk to other models and critique each other’s thinking?” If you get many models together in a group that can all talk to each other, they can start learning how to send information to the other models… with the overall goal of improving the entire swarm itself.

Gotcha, which explains the name “Swarm.”

Right. It’s this training method which allows many models to kind of combine, in parallel, to improve the outcome of a final meta-model that you could create from those models. But at the same time, you have every single individual model just improving on its own. So if you were to come along with a model on a MacBook, join a swarm for an hour and then drop back out again, you would have an improved local model based on the knowledge in the swarm, and you would have also improved the other models in the swarm. It’s this collaborative training process that any model can join and any model can do. So that’s what RL Swarm is.

Okay, so that’s what you released a few weeks ago. Now where does blockchain come in?

So the blockchain is us moving forward some of the lower-level primitives into the system.

Let’s just pretend that someone doesn’t understand the phrase “lower-level primitives.” What do you mean by that?

Yeah, so I mean, very close to the resource itself. So if you think about the software stack, you’ve got a GPU stack in a data center. You’ve got drivers on top of the GPU. You’ve got operating systems, virtual machines. You’ve got all this stuff going up.

So a lower-level primitive is the closest to the bottom foundation in the tech stack. Am I getting that right?

Yes, exactly. And the RL Swarm is a demonstration of what’s possible, basically. It’s just a somewhat hacky demo of doing really interesting large-scale, scalable machine learning. But what Gensyn’s been doing for the past four-plus years, realistically, is building infrastructure. And so we’re in this period now where the infrastructure is all at that v0.1 sort of beta level. It’s all done. It’s ready to go. We have to figure out how to show the world what’s possible when it’s quite a big shift to the way people think of machine learning.

It sounds like you guys are doing a lot more than decentralized compute, or even infrastructure?

We have three main components that sit underneath our infrastructure. Execution – we have consistent execution libraries. We have our own compiler. We have reproducible libraries for any hardware target.

The second piece is communication. So assume you can just run a model on any device in the world that’s compatible, can you get them to talk to each other? If everybody opts into the same standard, everybody can communicate like TCP/IP from the internet, basically. So we build those libraries and RL Swarm is an example of that communication.

And then, finally, verification.

Ah, and I’m guessing this is where blockchain comes in…

Imagine a scenario where every device in the world is executing consistently. They could link models together. But can they trust each other? If I connected my MacBook to yours, yes, they could execute the same tasks. Yes, they could send tensors back and forth, but do they know that what they send to the other device is actually happening on the other device or not?

In the current world, you and I would probably sign a contract to say, yes, we agree that we’ll make sure our devices do the right thing. In the machine world, it needs to happen programmatically. So that’s the final piece we build, cryptographic proofs, probabilistic proofs, game theoretic proofs to make that process entirely programmatic.

So that’s where the blockchain comes in. It gives us all of the benefits of blockchain you can imagine, like persistent identity, payments, consensus, etc. And so what we’re doing with the testnet now is taking RL Swarm and the primitives of the other infrastructure and we’re adding in the blockchain components and saying, ‘Hey, when you join a swarm now, you have a persistent identity, which exists out there on a decentralized ledger.’

In the future you’ll have the ability to make payments, but right now, you have that trust consensus mechanism where we can terminate disputes. So, it’s kind of an MVP of the future Gensyn infrastructure, where we’re going to add in components as we go.

Give us a tease of what’s coming down the pipeline?

When we reach main-net, all of the software and infrastructure is live against blockchain as the source of trust, payments, consensus, etc., identity. This is the first step of that. It’s adding identity in and saying when you join a swarm, you can register as the same person. Everyone knows who you are without having to check some centralized server or website somewhere.

Now let’s get wild and talk further in the future. What does this look like one year from now, two years from now, five years from now? What’s your North Star?

Sure. The ultimate vision is to take all of the resources that sit under machine learning and make them instantaneously programmatically accessible to everyone. Machine learning is heavily constrained by its core resources. This creates this huge moat for centralized AI companies, but it doesn’t need to exist. It can be open-sourced if we can build the right software. So our view is Gensyn builds all of the low-level infrastructure to allow that to get as close to open-source as it possibly can. People should have the right to build machine learning technologies.

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Bitcoin Is the Asset, Ethereum Is the Platform

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1 час ago

19 мая, 2025

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Blockchains are a technical marvel, but in this vastly competitive landscape, I’ve come to see the social consensus and ecosystem around blockchains as by far their most important strategic asset. The social layer matters, but for different reasons depending on the chain.

Specifically, I have the hypothesis that the “Layer 0” for any blockchain ecosystem can only excel at one primary mission. When I say “Layer 0,” what I am really talking about are the communities of people that sustain these networks. They are everyone from enthusiasts to engineers, developers, investors, venture capitalists and volunteers. As public networks that are built with open-source code, the strength of each ecosystem is primarily the community around it.

Despite their superficial similarities, the communities and the ecosystems that underpin bitcoin and Ethereum are radically different. I have long said that “bitcoin is the asset. Ethereum is the platform.” In both cases, the social consensus around these blockchains is what keeps them together and makes each one ideally suited for its mission.

Bitcoin first. Bitcoin is a scarcity-based store-of-value. Better than fiat currency. More reliably scarce than gold. Immune to politics and protected by a vast proof of work infrastructure. Bitcoin is in a constant battle for mindshare with other crypto-assets and, even more so, against traditional fiat currencies and central-bank-issued assets.

This is not the same as other stores-of-value. There can be many kinds of government and corporate debt, and their values are all tied to the likelihood of repayment. The closest analogy for bitcoin is with gold, which does not pay interest or generate any cash flow. Nor is there any meaningful industrial demand for gold. The value of gold is simply that it is scarce and getting more of it is not easy.

One particularly important feature of this crypto ecosystem is that it is a zero-sum game. If you admit that there can be more than one cryptocurrency used as a store of value, you are on a slippery slope because technically, there can be an infinite supply of identical copies of bitcoin. If there can be two, there can be a thousand. If that happens, the value of bitcoin is uncertain and likely low.

Right now, there are no other cryptocurrencies that have a value even remotely close to that of bitcoin. Assets like litecoin, bitcoin cash, dogecoin and others represent a tiny fraction of bitcoin’s market capitalization. The only asset in the same general league is ether, and I would argue that it should be seen less as a cryptocurrency and more as a stake in a computing ecosystem.

The result of this logic is a uniquely aggressive approach to mindshare. The value of bitcoin must be sustained by constant memetic warfare against other cryptocurrencies. Scroll through r/bitcoin, and you will find a stream of memes that aim to reinforce the value of bitcoin. Typical content includes dire warnings about the U.S. dollar’s debasement with quantitative easing, the serious U.S. federal debt, the horrors of inflation, and rapturous predictions for future prices. That quantitative easing did not cause inflation and that low to moderate inflations inflict no measurable economic harm does not matter in that context: Political harm, yes, economic harm no. (See here and here)

A typical bitcoin meme includes a reminder that a long, long time ago, a dollar would buy you a full bag of groceries. The implication is that you are being robbed through gradual printing of money. This meme has never stood up to the most basic examination. Moderate inflation is fine, necessary, and infinitely better than deflation. We are vastly better off than we were when a dollar could buy a bag or groceries, but acknowledging that would undermine the narrative. It does not matter, however. Never let the facts get in the way of a good story.

To sustain its value, bitcoin needs a very assertive social consensus. And that has to continue for an exceedingly long time. Gold’s use as a shared global store of value dates to 650 BCE in ancient Türkiye, so they have a significant head start. And while there are other precious metals, none of them have ever approached gold in terms of total market capitalization. The market cap of gold is 10 times larger than the market cap for silver.

The social ecosystem that underpins Ethereum is different. First and foremost, Ethereum is the world computer. Ethereum is a positive-sum ecosystem where people are encouraged to build and extend. The discussion and tone of r/Ethereum is, again, a good proxy for the whole ecosystem: it is focused on engineering, development, and new applications.

Ethereum, like bitcoin, has an equally passionate Layer Zero ecosystem and is as dominant compared to other “smart contract” blockchains as bitcoin is to other pure crypto-assets. Ethereum’s dominance is visible in the market cap of the asset but also in its share of tokenized assets. Ethereum is the dominant ecosystem for most “real-world” assets and the majority of stablecoins as well. With over 100 Layer 2 networks in operation, Ethereum has 20 times more “network extensions” than any other ecosystem, including bitcoin and Solana.

Both the Bitcoin and Ethereum ecosystems have ardent believers that see things differently from the dominant narrative. There is a small, but resilient application layer being built upon bitcoin. Bitcoin will soon have its own layer two networks, including some that are EVM- compatible.

Similarly, there is a passionate group of Ethereum believers who think Ethereum should be both the network computer and a scarcity-based asset. EIP-1559 (Ethereum Improvement Proposal), which was adopted in August 2021, reduced the rate at which new ETH was issued and shifted the gas fee model so some ETH is burned with each transaction. The result is that the amount of ETH in circulation is increasing at a slower pace than bitcoin and, in some cases, even decreasing.

Neither of these is necessarily a bad idea and, at least in theory, either ecosystem could be a host to both types of activity. In practice, the cultural requirements of each ecosystem are so different that they cannot really excel at more than one function at a time.

In the real world, currencies like the U.S. dollar are most effective as a means of exchange, but not necessarily as a store of value. You can use dollars to buy things, but a deflationary system that increased the value of the dollar, over time, would be catastrophic for the economy as it forced up real interest rates. As Ben Bernanke discovered, trying to stimulate an economy when inflation is low is very difficult. The same problem makes bitcoin unsuitable as a currency even while it may excel as a store of value.

With Ethereum, we’ll see how well the current blockchain boom plays out over the next few years. If the ecosystem retains its dominant share of new asset tokenization and smart contracts, I think we can declare it a winner on the primary mission. Bitcoin has a longer game to play, but if we see increasing correlation with gold, that may be an indicator that real-world investors are buying into the argument for digital scarcity.

Either way, it could be several more years of real world experience before I can prove (or disprove) my theory. This also means that memetic warfare on Twitter between ecosystems isn’t going away anytime soon.

The views reflected in this article are the views of the author and do not necessarily reflect the views of the global EY organization or its member firms.

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XRP Futures Start Trading On CME

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2 часа ago

19 мая, 2025

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XRP futures started trading on the Chicago Mercantile Exchange’s (CME) derivatives platform on Monday, becoming the first regulated futures tracking the price of XRP in the U.S.

Traders can trade two contract sizes: 2,500 XRP and 50,000 XRP, which will both be cash-settled and based on the SME CF XRP-Dollar Reference Rate, which tracks the price of XRP daily at 4:00 p.m. London time.

CME already offers bitcoin BTC, ethereum ETH and solana SOL futures as well as bitcoin and ethereum options. The Group’s SOL futures, which launched in mid-March, had only booked $12.3 million in notional daily volume on the first day and closed with $7.8 million in open interest, a much lower number on an adjusted basis compared to the debut of the ether and bitcoin futures.

The price of XRP was down 3.45% over the past 24 hours.

The existence of regulated futures could mark a big step in the right direction as it relates to a spot XRP exchange-traded fund which is currently under review to be approved or denied by the Securities and Exchange Commission (SEC). Several U.S. issuers have filed to launch such a fund but have yet to receive a decision.

«CME-traded XRP futures are now *live*,» wrote ETF Store President Nate Geraci on X. «CFTC-regulated contracts on XRP. Spot XRP ETFs only a matter of time.»

The former SEC under Chair Gary Gensler had previously told issuers that one of the reasons it approved the spot bitcoin and ethereum ETFs was that it already had an existing regulated futures market in the U.S.

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Dogecoin Finds Support After Sharp Drop as Bulls Regain Momentum

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2 часа ago

19 мая, 2025

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Dogecoin’s recent price movement shows a classic battle between bears and bulls, with the meme cryptocurrency finding stability after a significant downtrend.

The coin experienced a 9.7% drop from $0.237 to $0.214 before buyers stepped in at key support levels. This buying pressure has created what analysts describe as a «panic zone retest» around the $0.215 mark, which has so far held firm against selling pressure.

Market structure indicates DOGE is currently navigating a falling wedge pattern, typically considered a bullish reversal formation when broken to the upside.

The Ichimoku cloud on short-term charts shows price lodged in equilibrium territory, with multiple technical indicators converging to create tight reference levels between $0.212 and $0.225.

For traders, the immediate focus remains on whether DOGE can break above the descending trendline resistance near $0.219-$0.220. A decisive move above this level could target the $0.235-$0.244 range, while failure to hold current support might see prices retreat toward $0.20 or even $0.185 in the near term.

Technical Analysis Highlights

DOGE formed a descending channel with clear resistance at the $0.235 level, where selling pressure consistently emerged.
A notable support zone developed around $0.215-$0.217, confirmed by increased volume during the 13:00 hour.
V-shaped reversal pattern formed with the bottom at $0.215 around 13:14, followed by steady accumulation.
Volume significantly increased to over 10 million units around 13:30, triggering a sharp upward movement.
New support zone established at $0.218, with multiple high-volume candles confirming strong buying interest.
Overall price action suggests bearish momentum with intermittent consolidation phases.

External References