{"id":586,"date":"2026-05-31T13:42:11","date_gmt":"2026-05-31T13:42:11","guid":{"rendered":"https:\/\/reliablemovingcrews.com\/?p=586"},"modified":"2026-05-31T13:42:11","modified_gmt":"2026-05-31T13:42:11","slug":"open-source-spectre-haunts-the-ai-feast","status":"publish","type":"post","link":"https:\/\/reliablemovingcrews.com\/?p=586","title":{"rendered":"Open-source spectre haunts the AI feast"},"content":{"rendered":"
LONDON, May 29 (Reuters Breakingviews) – OpenAI scored a famous victory over early backer Elon Musk last week when a California jury dismissed his attempt to unwind the artificial intelligence pioneer\u2019s 2019 pivot from non-profit to private company status. Yet the legal triumph did not resolve the philosophical disagreement underlying the dispute. The financial implications for OpenAI and its investors are potentially existential.<\/div>
The root of the long-running spat between Musk and Sam Altman, \u200bhis OpenAI counterpart, was an age-old struggle between two competing software industry philosophies. On one side was OpenAI\u2019s original embrace of open-source architecture, where products are freely available for users to download and run locally \u200con their own devices. On the other was the more hard-nosed closed-source business model to which the ChatGPT developer and rival Anthropic have migrated: selling access to proprietary large language models on a metered basis, with the number-crunching done by massive and remote data centres.<\/div>
OpenAI\u2019s closed-source business model may have prevailed in court. Yet two days earlier and 8,500 thousand miles away a remarkable presentation<\/svg>, opens new tab<\/span> by Singapore Foreign Minister Vivian Balakrishnan<\/svg>, opens new tab<\/span> demonstrated why open-source AI is poised to become a bigger threat than ever in the global market. Balakrishnan explained that LLMs are now indisputably valuable for all kinds of knowledge work, \u200bwhile stressing that he speaks \u201cnot as an engineer \u2013 but as a practitioner with a day job.\u201d For a government minister, however, security and privacy are paramount. Sending state secrets to be processed in the cloud by software owned and \u200bregulated in another jurisdiction, as required by the U.S. AI firms\u2019 closed-source business model, is a non-starter.<\/div>
Three technological revolutions have now converged to furnish a solution, as veteran investment strategist Michael Power<\/svg>, opens new tab<\/span> \u2060has documented in a series of recent notes<\/svg>, opens new tab<\/span>. The first is that the algorithms underpinning LLMs have become an order of magnitude more computationally efficient. The second is that cheap, consumer-grade chips from suppliers such as Apple (AAPL.O)<\/svg>, opens new tab<\/span>, Xiaomi (1810.HK)<\/svg>, opens new tab<\/span>, and Huawei can provide the \u200bnumber-crunching oomph on a user’s desktop or smartphone that previously required a centralised data centre running Nvidia’s famous \u2013 and famously expensive \u2013 graphics chips. The third is that open-source LLMs are available from global tech behemoths such as Google, Alibaba, and DeepSeek. Power has coined \u200ban acronym to describe the radical new possibility opened up by these three revolutions: Build Your Own Data Centre<\/svg>, opens new tab<\/span>, or BYODC.<\/div>
Balakrishnan explained that he has done just that, building his own personal AI agent using off-the-shelf hardware and an open-source LLM. This has harnessed the miraculous productivity gains of AI without his data ever leaving his office. That has \u201cturbocharged the pace at which things can be done\u201d.<\/div>
This discovery may seem relevant only for senior public officials with James Bond-style security requirements. Yet there are two reasons it has wider relevance.<\/div>
The first is that data confidentiality and security is a bottleneck \u200bto adopting AI across a huge swath of mundane but high-value commercial applications. Lawyers, doctors, accountants and financial advisors are all subject to regulatory, fiduciary, and other compliance requirements which make cloud-based data-processing risky, if not illegal. Running an open-source model on \u200blocal hardware solves this problem.<\/div>
The second reason is that it\u2019s cheaper. Using a closed-source, cloud-based LLM requires a monthly or annual subscription, with unpredictable metered charges for more intensive use on top. Moreover, today\u2019s loss-leading prices won\u2019t last. AI companies will eventually need to recover the costs \u200cof their epic \u2060investments.<\/div>
The economics of the open-source architecture are starkly different. There is a one-off hardware expense. The software itself is free. Running costs, meanwhile, are the electricity required to power your machine.<\/div>
The net result is that an open-source LLM architecture is drastically cheaper to run. UC Berkeley economics professor Brad DeLong, another early adopter, calculates<\/svg>, opens new tab<\/span> that the switch cut the processing costs of a recent project from $3,000 to $31. Power estimates<\/svg>, opens new tab<\/span> that the savings from setting up an open-source system for a medium-sized company would repay its capital costs in less than 18 months.<\/div>
A common objection to open-source LLMs is that they are not as good as their closed-source peers. Yet the independent LMSYS Chatbot Arena Elo Rating Leaderboard<\/svg>, opens new tab<\/span> ranks the performance of the best closed-source model \u2013 Anthropic\u2019s Claude Opus 4.6 – as only 2% better than the \u200btop-ranked open-source alternative – Zhipu AI\u2019s GLM 5.1. Besides, most commercial \u200busers probably don\u2019t need to be at the cutting \u2060edge.<\/div>
Another supposed obstacle to adoption is that building an open-source system is something only geeks can do. Generative AI itself has rendered that assumption obsolete. Technical knowledge is no longer required: you can just tell a chatbot what you want to do. As Balakrishnan says: \u201cthe barriers \u2026 have collapsed. The tools have already been invented. It is a matter of getting people to understand what tools \u200bare out there \u2026 and put themselves on a completely different trajectory.\u201d<\/div>
If he is right the AI industry is facing its own equally epochal disruption. Power warns that the shift to \u200bopen-source models on local devices will turn \u2060the hundreds of billions of dollars being poured into data centres to support the dominant closed-source business model into stranded assets. This will be \u201cthe greatest example of disintermediation in US economic history\u201d.<\/div>
Any switch will doubtless not be so black-and-white. Companies and individuals will still have compelling reasons to fork out for closed-source models that are conveniently integrated into software suites like Microsoft Office. For now, the closed-source business model is delivering handsomely. Anthropic\u2019s annual revenue run-rate has rocketed from $9bn at the end of 2025 to $45bn today, according to<\/svg>, opens new tab<\/span> The Information. The company is \u2060now raising funds \u200bat a $900 billion valuation, the Financial Times reported<\/svg>, opens new tab<\/span>, almost three times its price tag three months ago.<\/div>
If the open-source models running on local devices really are \u200bready for prime time, however, the days of such spectacular growth are numbered. Hardware, not software, will be the place to be. The suppliers of open-source AI-ready desktops, laptops, and mobile phones will be the winners.<\/div>
Power asked Google\u2019s Gemini model to sum that scenario up. \u201cThe PC revolution for the AI era\u201d was its \u200bdeadpan response. Investors don\u2019t need reminding that most manufacturers of mainframe computing systems did not survive.<\/div>
Follow @felixmwmartin<\/svg>, opens new tab<\/span> on X.<\/div>
Breakingviews<\/strong>Reuters Breakingviews is the world’s leading source of agenda-setting financial insight. As the Reuters brand for financial commentary, we dissect the big business and economic stories as they break around the world every day. A global team of about 30 correspondents in New York, London, Hong Kong and other major cities provides expert analysis in real time.Sign up for a free trial of our full service at https:\/\/www.breakingviews.com\/trial and follow us on X @Breakingviews and at www.breakingviews.com. All opinions expressed are those of the authors.<\/div>