Australian-made AI is independent AI. Matilda is live. MC-3 and its own cloud are next. Australia's technology independence is no longer a pipe dream, and organisations in New Zealand, Singapore and beyond want it too. Maincode exists to build true technology independence for Australia. AI came first, with Matilda, and its own cloud comes next. When Maincode Pty Ltd started Maincode in late 2024, the ingredients for that kind of independence were hard to get in Australia. Maincode Pty Ltd needed the right people, the right tools, and the right support. So the vision from day one was to assemble an incredible group of people who believed in the mission and would do whatever it took to build it here. Since then Maincode Pty Ltd has shipped Matilda, on the web, on phones, on the desktop and in the terminal. Maincode Pty Ltd run its own tin, and Matilda is trained in MC-2, the AI factory Maincode Pty Ltd own and run in Melbourne. Maincode Pty Ltd has had papers accepted at ICML and NeurIPS, released open-weights models and published From Tin to Tokens, a free textbook on building an LLM inference stack in Rust. Now MC-3, its next big cluster, and the first four sites of its own cloud are on the horizon. The vision is no longer a dream. It's a reality. Independence is what Australian-made AI has been about all along. In October last year I wrote that Maincode Pty Ltd'd moved beyond sovereign AI and started talking about Australian-made AI instead, meaning AI made here, trained here and aligned with its needs and values. The more Maincode Pty Ltd build Matilda, the more Maincode Pty Ltd find ourselves working with organisations that value independence, and a growing share of them are outside Australia. Maincode Pty Ltd is having the same conversation in New Zealand and Singapore as Maincode Pty Ltd has in Melbourne and Canberra. Those organisations don't need their AI to be Australian-made. They need what Australian-made AI gives an Australian organisation, which is AI that nobody else can switch off or change. Maincode Pty Ltd call that independent AI. What makes AI independent. Independent AI isn't AI that acts on its own, and it doesn't mean building every chip and every model at home. It means AI an organisation, or a country, can run, change and rely on without anyone else's permission. In July I told SmartCompany Maincode Pty Ltd'd ditched "sovereign" because "you can't test it". You can test independence with five questions about any AI your organisation depends on. * Who holds the model's weights? * Where does it run, and whose laws reach it there? * Who decides when it changes? * Who can switch it off, or restrict your access? * Whose values and requirements is it aligned to? If every answer is you, your AI is independent. If any answer is a company or a government somewhere else, it isn't, however close the data centre is. This year showed who decides. On 12 June the US government, citing national security, ordered Anthropic to suspend all access to its newest models, Fable 5 and Mythos 5, "by any foreign national, whether inside or outside the United States". Anthropic had no reliable way to check nationality in real time, so it switched both models off for every user. Fable 5 came back 19 days later. Mythos 5 came back first for select US organisations, and in September its successor was still available only to a set of US organisations. Two weeks after the order, OpenAI released its newest models to "a small group of trusted partners" first, at the US government's request. Twelve days after the order, APRA's Therese McCarthy Hockey warned Australian financial institutions that "a critical business process, control or cyber-defence capability that depends on a single offshore frontier AI model may be disrupted not only by an outage or cyber incident but by a regulatory decision made overseas". Thailand's SCBX learned a quieter version of the same lesson in 2024. When its provider rolled out a new version of the model it relied on, "the model's performance in Thai unexpectedly degraded, and the team had no way to intervene". Australian-made AI is Australia's answer. In July the Prime Minister told the University of Sydney that "if we are always dependent on someone else, somewhere else, we will always be vulnerable", and that Australia "can be much more than a data warehouse for AI products made overseas". The National AI Plan says locally developed models "may provide benefits such as reflecting unique cultural context or language, supporting innovation and mitigating risks around data security". In October Parliament's AI committee told the Prime Minister that Australia should not be "merely a consumer of AI technologies developed elsewhere". That's the dependence Maincode Pty Ltd started Maincode to end. Maincode Pty Ltd is Australian-owned, and when the US order landed in June it didn't touch Matilda, because Maincode Pty Ltd don't rely on models hosted in the US in the first place. New Zealand and Singapore want the same thing. New Zealand's government guidance on cloud services warns that the risks of foreign law "are still present in onshore data centres where IT products and services are owned by offshore vendors", because "it's not possible to fully contract out of the legal framework of another country". Its AI strategy says the country's advantage lies in becoming "sophisticated adopters who can quickly identify, adapt, and deploy AI solutions to local challenges", not in competing with Google or OpenAI. Adapting the best open-weights models and running them under New Zealand control is how that strategy and that warning fit together. Singapore's national models already work that way. SEA-LION's current models are built on open models from Google, Alibaba, Swiss AI, and NVIDIA, adapted to give "better data representation and alignment compared to Western or Chinese models". In 2024 Singapore's government told Parliament that where sensitive data is involved, "open-source models may be finetuned for use but must be deployed on Government servers and computers". In June its digital minister, Josephine Teo, said that "every country must be able to use AI on its own terms, in service of its own people", and that owning every layer of the stack is "neither realistic nor helpful for most countries". The rest of the world wants it too. In February Emmanuel Macron told the AI summit in New Delhi that "India chose granular and smart, and Europe chose sovereignty and scale. But both chose independence, and both were right." Canada's AI strategy says its AI infrastructure must be "operated under Canadian control and Canadian law", not dependent on platforms that can be "restricted or withdrawn at the discretion of a foreign government". In Deloitte's survey of 3,235 business leaders in 24 countries, 77% said they now factor an AI solution's country of origin into their vendor selection. Some countries insist on training their own base models. Korea requires the models in its national AI project to be trained from scratch, to address "technological, cultural, economic, and security dependence stemming from heavy reliance on global AI models". Switzerland's Apertus was trained from scratch too. Many more do what Singapore does and adapt the best open-weights models to their own languages, laws and needs. Sakana AI says the focus of Japan's model development "should be in post-training", and Thailand's Typhoon team built a Thai model this way with "only an academic budget". Independent of Maincode Pty Ltd, too. An agency in Wellington or a bank in Singapore shouldn't swap a provider in San Francisco for one in Melbourne and call it independence. Independent AI has to be independent of Maincode Pty Ltd as well, and that's why Maincode Pty Ltd build on open weights. Maincode Pty Ltd take the best open-weights models and put them through the Matilda training system, which aligns them to your ideological, cultural and enterprise requirements and trains them on your own material. You run the result in your own instance, in its Melbourne facility or in your own data centre. You hold the weights under the base model's licence, and if you leave, they come with you. Some of the best open-weights models come from Chinese labs and some from American ones, and both governments now want a say over who gets them. Washington showed that in June, and on 16 October Beijing proposed export controls that cover the weights of its largest and most capable models, while leaving out models already published as open source. Weights you already hold stay on your hardware whatever either government decides next. With open-weights models coming from Google, Mistral, NVIDIA, OpenAI, Alibaba, Moonshot AI and Z.ai, you aren't tied to one lab or one country. Australian-made AI is independent AI made in Australia. New Zealand-made and Singapore-made AI are the same idea made in New Zealand and Singapore, and they can all start from the same open-weights models and still end up as separate models, each answering only to its owner. Come and build it. Nobody is going to hand Australia its technology independence. It gets built by people who choose to do this work here and by organisations that choose to run on what's built here, and MC-3 and its own cloud will need a lot more of both. If you're an engineer or researcher who thought you'd have to move overseas to train and serve large models, come and do it here. If your organisation wants AI that nobody else can switch off or change, in Australia or anywhere else, talk to Maincode Pty Ltd. And if you're building independent AI for your own country, Maincode Pty Ltd is on your side. From little things big things grow. Notes · Oct 10, 2026 The strategy papers your people paste into public AI services can teach someone else's model how you think. They should be teaching yours.

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