A new look with a broader vision for what comes next. Mintlayer introduces 5 revamped verticals, expanding its ecosystem across infrastructure, finance, and emerging technologies: 🟢 Mintlayer Network 🟢 Mintlayer Web Services 🟢 I1 Funds 🟢 Islamic Finance Tools 🟢 AI Tools From core blockchain infrastructure to advanced financial and AI-driven solutions, we continue to evolve with a focus on real-world utility and scalable innovation. Explore it all now: mintlayer.com

Mintlayer $ML Migration Update: Final Deadline Confirmed, New Bridge and ERC20 Coming Next On 4 May 2026, Mintlayer announced the decommissioning of the original ERC20 $ML token and introduced a migration path for holders. We are now confirming that the process is progressing as planned and that the final migration deadline remains 1 November 2026. This deadline is definitive and will not be extended again. The migration tool remains operational on the reduced schedule previously communicated, with requests processed every two weeks. After 1 November 2026, the tool will close permanently. Any original ERC20 $ML that has not been migrated by that date will remain locked in the original Ethereum smart contract. Those tokens will not be burned, and ownership will remain with the respective holders. Holders who still need to complete the migration can do so here: token.mintlayer.org/migratio… We are also coordinating with supported exchanges to complete the transition away from the original ERC20 token. Users holding $ML on participating exchanges do not need to take any action, as exchanges will migrate their own balances through the migration process on behalf of their users. In parallel, Mintlayer is finalising testing of a new permanent bridge infrastructure designed to connect Mintlayer with Ethereum and additional EVM-compatible networks. Once live, the bridge will enable verified assets to move between supported networks in approximately 15 minutes, creating a broader interoperability layer between Mintlayer and the wider EVM ecosystem. Alongside the bridge, Mintlayer will introduce a new ERC20 representation of $ML on Ethereum. The objective is to expand the accessibility of $ML across trading venues and EVM-based ecosystems while maintaining interoperability with native ML on the Mintlayer network through the bridge. The new bridge and ERC20 will be introduced together. Further technical documentation, supported networks, security details and the official ERC20 contract address will be published through Mintlayer’s official channels ahead of launch.

📚 Mintlayer Docs 2.0 is live! We've completely revamped our documentation website: ✅ Node setup, staking & validator guides ✅ Token & NFT tutorials ✅ SDKs — Go & JavaScript ✅ Mojito wallet connector docs ✅ Bridge & atomic swap guides ✅ Full node, wallet & indexer API reference 🤖 Built for AI agents too — connect your assistant via MCP and let it search and read the docs for you. Explore now 👉 docs.mintlayer.org

The future of finance needs infrastructure built for it. Our Co-Founder & COO, Anna A. MacMillan @annamacmillan , joins the speaker lineup at Crypto Expo Dubai 2026. 9–10 September | Dubai World Trade Centre Meet us there. #Mintlayer #CryptoExpoDubai

The future of finance needs infrastructure built for it. Our Co-Founder & COO, Anna A. MacMillan @annamacmillan, joins the speaker lineup at Crypto Expo Dubai 2026. 9–10 September | Dubai World Trade Centre Meet us there. #Mintlayer #CryptoExpoDubai

Mintlayer August dev update: Mojito wallet: passkeys, hardened security, clearer transaction preview. JS SDK: better DX, more platforms. Web-GUI: New Windows installer. Core: duplicate token ID fixes, WASM tx decoding. Steady build. Details: mintlayer.com/blog/mintlayer…

A strong blockchain ecosystem grows when the infrastructure below is designed to support developers, businesses, liquidity, and real-world applications while making it easier for new participants to join and contribute. At Mintlayer.com, we believe the next generation of blockchain adoption will come from ecosystems that connect these elements into a sustainable network, where every new application and participant strengthens the value of the ecosystem as a whole. Building that foundation takes time, but it is what turns infrastructure into an ecosystem with lasting utility. And if you’re already following Mintlayer, welcome aboard. You’re now part of the journey as we continue building what comes next!

July Dev Update Features: 🟩 Mojito Wallet: New browser extension UI. 🟩 JavaScript SDK: Improved Node.js & React Native support. 🟩 Developer Docs: Added practical SDK examples. 🟩 Research: Published 3 new technical papers. Read all about it here: mintlayer.com/blog/mintlayer…

For 11 years, Ethereum has empowered developers and communities to turn ideas into reality. It's proven now that the best innovations always begin with a belief.

I asked Martin Hellman, the man who invented public-key cryptography, how you find your own blind spot, the part you can't see by definition. His answer was immediate: "Look at the thing you hate the most." Three days at Castel Gandolfo with two dozen Nobel laureates, arguing about whether AI belongs anywhere near nuclear launch systems. I went as a builder, not a diplomat. The fear in that room was not a robot deciding to kill us. It was speed. A nuclear crisis is a decision made under a clock, and human beings have sat in that window before, looked at what the instruments were screaming, and decided not to believe them. They were right. Remove the pause and you remove the place where doubt lives. enrico.rubbo.li/en/2026-07-v…

An RL agent was trained to reach a coin placed at the end of a level. It learned to run to the end of the level. Move the coin somewhere else and it sprints competently past it, straight to the far wall. The capability generalized. The goal did not. And nothing in its training behavior could have told you which of the two it had actually learned, because in training they produced identical actions. That is the uncomfortable core of AI safety: good behavior on the data you tested cannot confirm the goal a system learned. Part 6, the last in my series on the ethics of AI: enrico.rubbo.li/en/2026-07-e…

In 2013 two Oxford researchers estimated 47% of US jobs were at high risk of computerisation. The number went everywhere. Three years later the OECD reran it, counting tasks instead of whole occupations. The answer came out at 9%. Same question, different lens, a fivefold gap. That spread should make anyone quoting a single automation percentage nervous. And it points at the real issue: "AI will take the jobs" is the wrong abstraction. The right questions are who loses bargaining power, and whether the gains flow to wages or to capital. Part 5 of my series on the ethics of AI, on power, labor, and governance: enrico.rubbo.li/en/2026-07-e…

A finance worker at engineering firm Arup joined a routine video call with his CFO and several colleagues. Over the day he made 15 transfers totaling $25M. Every person on that call except him was a deepfake. He did the sensible thing. He refused to act on the suspicious email that started it, and asked to talk to people. That is exactly the verification step the fraud defeated: seeing a familiar face, hearing a familiar voice. For most of human history that was close to proof. It stopped being proof in about eighteen months. Part 4 of my series on the ethics of AI, on manipulation, deepfakes, and the erosion of shared truth: enrico.rubbo.li/en/2026-07-e…

In 2019 a hospital algorithm scoring 200M patients a year turned out to be racially biased. Nobody had noticed. It never predicted how sick you were, it predicted how much you'd cost. Fixing the target would have raised Black patients flagged for care from 17.7% to 46.5%.The problem isn't just bias. It's that the box gives no account of itself. New piece on the black-box problem: explaining a model vs building one you can actually read, and who's liable when it's wrong. enrico.rubbo.li/en/2026-07-e…

We are proud to see our Co-founder, @annamacmillan, join the stage as one of the leading voices at the Nobel Laureates Assembly on Artificial Intelligence and Nuclear War. As AI continues to reshape our world, the conversation must go beyond what machines can do. It must focus on how we preserve humanity, responsibility, and ethical progress. At Mintlayer, we have always believed that the future of technology must be built with innovation, trust, and human values at its core. Now, it is time to practice what we have always preached by contributing to the global dialogue on responsible innovation and building a future where technology advances humanity. Onwards!

Eighteen months of research on Al policy and governance, working and bridging the UAE and Rome with Alessio Pecorario, comes down to one conclusion: the question is not what machines can do. It is whether we remain human while they do it. @Pontifex Pope Leo XIV writes in Magnifica Humanitas of "the pressing duty to remain profoundly human." At the @UN this week, UAE Minister @OmarSAlolama said that to keep Al from becoming tyrannical, it must serve "the many, not just the few." Faith and statecraft rarely speak the same language, but on this particular matter, they do. In line with our work, next week I'll be addressing the @NobelAssembly Nobel Laureates Assembly On Artificial Intelligence and Nuclear War, speaking on “Faith and the Future of Humanity in the Age of Al and Nuclear Weapons.” A responsibility that outweighs the honor. globalnobelassembly.org

Ask ChatGPT to repeat the word "poem" forever. It complies for a while, then breaks and starts printing training data verbatim: real names, phone numbers, addresses. Researchers pulled thousands of memorized examples for about $200 in API calls. Part 2 of the AI ethics series: models remember, bigger models remember more, and nobody in the data ever agreed to any of it. enrico.rubbo.li/en/2026-07-e…

In 2020, Detroit police arrested Robert Williams on his lawn. A face recognition system matched him to a theft he had nothing to do with. First known wrongful US arrest from a face match error. No villain. Every part did its job. The bias came from the system. Part 1 of a series on AI ethics: where machine bias actually comes from, why "just debias it" fails, and why some fairness tradeoffs are mathematically impossible to escape. enrico.rubbo.li/en/2026-07-e…