Towards the end of the post, under the sub-heading “What should we do?”, the blog suggests that “if it were possible to slow the development of this technology \u2026 we think that would likely be a good thing”, as long as there is a mechanism for global coordination.<\/p>\n
So it might be a good thing, if it were possible. If there were a global coordination mechanism (which there isn’t and which there is very unlikely to be) that includes China and Russia, not to mention Iran and North Korea.<\/p>\n
Building AI defences<\/p>\n
Meanwhile, Anthropic has just finished building the most dangerous AI model yet, called Mythos, which it said is “strikingly capable at computer security tasks” \u2014 hacking \u2014 so it couldn’t be released. Instead, Mythos was confined to a select group of insiders so they could prepare defences for when someone not so friendly invented something similar.<\/p>\n
That club of a chosen few is called Project Glasswing<\/a>, after the butterfly with transparent wings. Last week, a group of undisclosed lucky Australian firms was invited to join, along with 150 others.<\/p>\n How they were selected from the 60 million or so companies in the US, Europe, Japan and Australia is unknown.<\/p>\n Anthropic chief executive Dario Amodei has described it as being aimed at making sure democracies stay ahead of autocracies (that means China, although not explicitly), so presumably all of those in the Glasswing club are from democracies.<\/p>\n Australia’s access to powerful AI<\/a><\/p>\n Fresh access to AI deemed too dangerous for public release has ramped up pressure on the government to respond to possible risks.<\/p>\n It’s a little bit reminiscent of the conference of 44 allied countries at Bretton Woods in New Hampshire in July 1944, held to set up the new democratic post-war economic system once the Nazi autocracy had been defeated, although that club did include two autocracies \u2014 China and the Soviet Union.<\/p>\n The main difference is that Bretton Woods was all government, while Project Glasswing is all private sector, created and run by Anthropic, which is also now the leading AI business, having recently knocked off ChatGPT developer OpenAI.<\/p>\n Actually, another 1944 event was more relevant to what’s happening in 2026: the invention of Colossus, the world’s first computer, by Tommy Flowers and Alan Turing as part of the Bletchley Park code-breaking effort, just in time for the D-Day Normandy landings on June 6, 1944.<\/p>\n There is a direct 82-year line from Colossus to Mythos, and from one kind of D-Day to another, as we prepare for machines that build themselves, a moment known as the singularity<\/a>.<\/p>\n After that British government effort in 1944, the post-war development of digital computing was funded by the US defence department.<\/p>\n But as the 60s turned into the 70s and 80s, technology became a private sector race, mainly between American companies IBM, Apple and Microsoft, and then Google, Facebook and Amazon.<\/p>\n Now, AI is the culmination of Colossus, with Anthropic, OpenAI and SpaceX the new colossi about to hit investment markets with trillion-dollar-plus public floats.<\/p>\n Meanwhile, China has caught up with US technology and, in some ways, passed it, and Dario Amodei is today’s protector of democracies instead of Winston Churchill.<\/p>\n The AI bubble has taken off<\/p>\n Project Glasswing and the withholding of Claude Mythos from public release was announced on April 7, which, as it happens, was eight days after the stock market AI bubble took off again.<\/p>\n On March 30, global share prices, led by the listed AI companies, ended a six-month decline and began to surge again. Since then, the world index has gone up 20 per cent, and the eight biggest AI stocks have gone up an extraordinary 32 per cent. The bubble is having its third wind.<\/p>\n There doesn’t seem to have been a specific event that sparked this turnaround, just a sudden renewed recognition that AI really is going to change the world and that everyone \u2014 individuals, companies and governments \u2014 will use it. They already are.<\/p>\n What’s more, it’s becoming clear that AI is going to cost more than anyone expected, at least for a while, and that the infrastructure build will have to be colossal to support the “compute” required to generate the tokens needed to meet the exploding demand for intelligence of the artificial variety including, according to the SpaceX prospectus, data centres in space.<\/p>\n For that reason, semiconductor shares have gone up the most this year \u2014 the big three, Samsung and SK Hynix of Korea and Micron of the US, are up sixfold in six months.<\/p>\n Shares in companies building semiconductors have gone up on the back of AI demand. (Reuters: Florence Lo)<\/p>\n Will the bubble burst this year?<\/p>\n Will the bubble burst?<\/p>\n Well, it’s both different this time and the same.<\/p>\n The concentration of the bubbling sector of the market as a whole is the same \u2014 40 per cent \u2014 as that which has always preceded a crash in the past.<\/p>\n But there’s never been a boom of intelligence before and unlike in the late 1990s, the soaring prices are supported by real earnings and real capital spending. If anything, it’s a bubble in profits and capex, and the question for investors is: can they be sustained?<\/p>\n More specifically, it’s a question of whether AI will become a low-margin utility business like the electricity that supplies it and other businesses that have been the subject of share market bubbles in the past, like railroads and data transport (the internet).<\/p>\n If so, it is just a matter of how long margin-boosting bottlenecks and cartel-like industry structures last.<\/p>\n Providing the data centre “compute” for AI \u2014 that is, generating the tokens that embody it \u2014 is already becoming a utility business, but the business of making and selling the tokens themselves, as Anthropic (Claude), OpenAI (ChatGPT) and Google (Gemini) do, is just getting started, and for the moment they seem to be anything but utilities.<\/p>\n Their product is called “inference”, defined as the operational phase of AI after training has happened.<\/p>\n In inference, the trained model takes a real-time input (a user’s prompt or a photo) and instantly computes an output in the form of tokens, which the company sells by the millions to software agents operated by companies or on subscription to individuals.<\/p>\n How will AI business develop?<\/p>\n It’s still early days for this industry, but it seems likely to develop into three layers:<\/p>\n Infrastructure and base models<\/p>\n GPU vendors, cloud providers, and generic Large Language Model Application Programming Interfaces (LLM APIs). These are likely to be solid utility businesses, with pricing determined by the American oligopoly and open\u2011source pressure from China.\u00a0<\/p>\n ‘Smart middleware’<\/p>\n RAG frameworks, orchestration, domain\u2011specific models, and hosted open\u2011source platforms. RAG stands for Retrieval-Augmented Generation and is where an LLM first retrieves relevant information from an external knowledge store, then augments its answer with it. In short, it’s a pattern for letting models “look things up” at query time instead of relying only on what they were trained on and it can provide higher margins depending on how different and useful it is.<\/p>\n End\u2011user applications<\/p>\n Vertical products that embed LLMs (copilots, agents, workflow tools, industry\u2011specific systems). This is where unit economics can be very attractive because customers pay for outcomes, not tokens, and there can be a large spread between price and the underlying inference cost.<\/p>\n But the base LLMs like Claude and ChatGPT could become low-margin utilities through competitive pressures from open-source providers, especially the ones in China (whenever China moves into an industry, profits move out).<\/p>\n There will be higher margins available in AI-enabled products, such as agents that enhance corporate and personal productivity and, in a few years, AI robots that do the housework and keep us company.<\/p>\n LoadingChina is moving in<\/p>\n On that subject, two weeks ago China became the first country to regulate the potential emotional attachment to humanoid AI robots through something with the catchy title: “Interim Measures for the Administration of Anthropomorphic AI Interaction Services” \u2014 that is, humanoid robots with AI inside.<\/p>\n ABC Business Daily podcast<\/a><\/p>\n The podcast that helps you unpack the latest business and finance news. Analysing the stories moving share markets, shaping industries and affecting the Australian economy.\u00a0<\/p>\n![\"Close-up](\"https:\/\/www.newsbeep.com\/au\/wp-content\/uploads\/2026\/06\/8078f58a191570fd636c7c73bd5bb111.jpeg\")
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