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Living in the world of LLMs often makes me wonder about the details of how they work and how they have developed over the years. This article is an extensive (600 pages) reference that includes LLM theory, training, benchmarking, all the way up to how to set up agentic systems. I like to open a (…)

The recent autonomous cyber intrusion by OpenAI against Hugging Face underscores AI’s dual-use risks. In response, the US House is weighing a bill to empower the Department of Homeland Security to shut down or slow AI models that the government deems too dangerous. The bill’s implications for non-US AI models remain ambiguous. Unlike a June (…)

It always stuns me how companies can invoke ‘consent’ when almost no one reads the pages-long terms and conditions, and even those who do probably won’t understand much of it anyway, and still it’s considered legally valid . What’s new here is that this so-called consent isn’t just meaningless to users; this article documents how (…)

Here is a chronological top-30 (well, top-27) of research articles showing how modern LLMs developed – from the first convolutional neuronal networks for image classification all the way to transformers and how to optimise them. If you’re wondering how this technology developed, what some of the shortcomings are, and what the most active development topics (…)

This article is interesting because Schneier, writing primarily about AI safety and the futility of model bans, incidentally reframes the entire AI sovereignty debate. Everyone is fighting over frontier models: the expensive, inaccessible layer. But the harness, the code that orchestrates and directs AI models, is where power actually lives. It is buildable today, and (…)

While I generally agree with this nuanced discussion about how use of ‘AI’ in a plethora of government processes is neither new nor necessarily bad, I think an important point that it only indirectly addresses is that we should avoid using these systems as a panacea for overrun and underfunded public services.

A slightly morbid example of how you never know what your data might eventually be used for. Although this is not exactly a classical case of your privacy being violated, I have some doubts that everyone who enthusiastically chased cute virtual monsters in their neighborhood would also have volunteered to collect data to train military (…)

Canada’s new AI strategy treats AI as critical infrastructure and targets all layers of the sovereignty stack, from cloud infrastructure and semiconductor capacity to data ownership and talent development. Notably, the strategy includes support for SMEs as a key lever toward AI sovereignty. I’m eager to see what AI sovereignty will look like in five (…)

The rise of powerful large language models (LLMs) such as Mythos and ChatGPT 5.5, alongside agentic AI systems like MDASH, has sparked concern in cybersecurity due to their ability to identify and exploit large numbers of zero-day vulnerabilities, prompting calls for significantly stronger IT defenses. This shift also presents an opportunity: by democratizing access to (…)

In case you want to start a small project, but want to avoid the US or Chinese hyperscalers, here are some EU-owned solutions for you. I like this list, not because I want to promote these services, but rather because it shows that the EU is gaining traction on providing credible and competitive basic services. (…)

It’s encouraging to see digital sovereignty discussions beginning to bear fruit, though much of that fruit is still unripe. The more closely the non-US community examines the issue, the more complex it becomes: ‘sovereign’ cloud computing means little if the underlying hardware is produced in the US or China. A server is not just one (…)

What makes Stanford HAI’s AI Index valuable is its data-driven, long-term perspective, which provides a welcome antidote to sensationalist headlines. Key signals: AI capabilities are not plateauing, the US-China gap has closed, and responsible AI is not keeping pace with AI capability. As for Switzerland, it ranks #1 globally in AI talent per capita, yet (…)

This is a very thorough description of a bug detected in a Zero Knowledge Proof (ZKP) library used by a blockchain. If you are interested in how modern ZKPs work, this article gives a condensed overview of what is happening in a ZKP, and what the security guarantees are. As always, the devil is in (…)

I think this take on the state of AI adoption is spot on. Since ChatGPT made its public debut, we’ve been promised large-scale transformation of the workplace and society at large. But a little over three years in, apart from very specific tasks, we’re still unclear what this supposed revolution will actually look like, and (…)