AI makes it cheaper to create working fragments. It does not automatically make those fragments part of a maintainable system. In practice it may make the canonization step more important not less
Everything depends heavily on the segment. Open-weight models already look good enough for a ton of internal tasks right now but there is always gonna be that small percentage of workloads where the last few percent of quality are totally worth the money.
I feel like the market is just gonna become way more mixed. Not like "everyone is switching to open" or "everyone is staying on frontier" but a mix of multiple models for different scenarios
The weakest part of the article is that the forecasts up to 2029 assume the current market structure will barely change. In three years literally everything can change, like prices, models, hardware, and how we actually use LLMs
That is exactly why big clouds never put all their eggs in one basket, even if it is a super cheap and cold basket. The cost of protecting and backing up network lines for an isolated island quickly eats up any benefits from geothermal energy. Physical security for terabit lines is way more expensive than air conditioning these days
Iceland and Norway are part of the EEA so the AI Act and GDPR will reach them just like Germany or France. Running away there from regulators makes no sense. But running from bureaucracy to get land permits and substation connections - yeah maybe municipalities work faster there
I feel like this is way too binary. I don't have to write every line of code myself to understand the system. I don't write my own compiler HTTP stack or database either
It's more about the level of abstraction. If AI handles 80% of the grunt work and I spend my time on architecture and reviews that's still a win
I feel like the author is jumping way too fast from "OpenAI is losing money" to "the whole AI economy is broken." A company being in the red during aggressive scaling doesn't automatically mean the unit economics don't work.
That's why a hybrid approach is needed. The agent shouldn't be making up dimensions based on an image. It should use OCR to extract the size table from the datasheet, feed it into a parametric table, and only then map it onto the base enclosure template.