Longer translated texts for readers who want to understand what AI is doing to work, industry, institutions and everyday life.
The 28 essays available in Swedish, English and Norwegian.
On the Anthropic result where one line of reframing reduced broad misalignment, and why who sets the frame is the real alignment question.
How AI may pull up both the industrial and service ladders for the countries that still need them most.
On the night two frontier models were switched off by an export-control order, and what it says about trust, sovereignty and dependence.
On the gap between Anthropic's economic policy framework and its own report on recursive self-improvement: the staircase, the curve and the Swedish question.
On the trajectory where AI capability rises quickly while access, control and bargaining power are distributed unevenly.
On why a scenario is not a forecast, and why the distinction between evidenced and guessed determines whether one thinks honestly about AI.
On why the most important AI question for 2026–2040 is not an AGI date, but the threshold where agent tasks become long enough to shift knowledge work.
On the contradiction between AI job forecasts, Swedish tech founders' policy wish list and the labour market their own products transform.
EWMC is now open source: a local, weighted memory store for AI assistants where not everything weighs the same.
Two signals in one day: superintelligence on the policy table and a model too sensitive to release.
On the AI Act, a sixteen-month delay and whether regulation can catch an exponentially moving technology.
When more visible output hides thinner quality, weaker responsibility and less real intelligence.
Why AI, robotics, cheap energy and automation together drive a larger civilisational shift.
On the distance between the actual pace of technology and the self-image of institutions.
Why the question of general intelligence becomes practical before it is philosophically settled.
An opinion piece on why AI should be treated as a system shift for work, administration and competitiveness.
Why AI policy needs clearer responsibility, higher pace and more shop-floor implementation.
On the practical voice missing from the AI debate: where technology meets operators, lines and decisions.
Why a few minutes with a free chatbot is not a serious test of what AI can do.
Why AI is not another office tool, but a different kind of capacity inside an organisation.
What AI means when technology meets industrial environments, processes and practical responsibility.
How AI begins to move from screens and text into machines, logistics and physical environments.
On the gap between playing with AI and making the technology work in real professions and environments.
On why memory, context and continuity matter when AI becomes part of real workflows.
How persistent AI systems change the emotional texture of interaction with machines.
On meaning, identity and the institutions that can carry a society with less necessary wage work.
On what remains to be allocated when AI makes intelligence cheap but land, energy, water and materials remain finite.
What happens when capacity becomes cheap enough to change the assumptions behind scarcity.
Why the first years of the AI shift are likely to be uneven, confusing and politically difficult.
An interactive map of AI, work, demography, energy and development paths.
Possible development paths for the AI shift through 2050 and what they demand from society.