Oil is a global market and these corporations have a legal fiduciary responsibility to stakeholder. I doubt the legality of them providing fuel at a lower cost to American's if it can be sold abroad for more. Ignoring any refining realities.
For anyone else wondering, the companies are not named in the article, and the models mentioned are Claude Opus 4.7, Claude Mythos 5 and an internal research model. There is little other detailing outside of a timeline.
Much of the stress I see from people who are struggling with stress from online is caused by “the news” at large. Could this same result be said if these same individuals read the NYT everyday? I wish you could study this and control for politics, or even - government. I am skeptical that the technology itself causes this, I am doubtful that “brain rot” content causes stress.
My understanding is that models can suffer “context limit anxiety” and a higher context limit will make it perform better especially as the context expands
I follow the New York Times, as well as being an avid news follower and have found them to be of poor reporting quality a handful of times over the past year.
My usage of GLM 5.2 has been defined by slow throughput and flaky providers, in many (definitely not all!) applications a dumber, faster, and more consistent model makes more sense to me.
In a corporate setting yes Opencode all the way. However in a non corporate setting I am getting $3000 of api usage a month for $100 at Anthropic and only use open code for the smallest cheapest tasks
The canadian government will provide lots of historical data for curious citizens, many of which are recordings of interviews from decades and decades ago. For a book project this allows me to make a hours of audio searchable through a GUI application I have developed that has a voxtral backend.
Subagents are quite inefficient and the lossy context transfer between them does lead to more cost and more waiting. However I have found it to produce more reliable output, whether that is worth it for a given task has been a consideration.
It was real here in the US for a great deal of time, and its decline of 'realness' seemingly coincided with the universal push for youth to attend it. The culture of college in the US i'm sure is quite different than germany or asian countries.
Fable has seen an increase of at least 3x daily spend on my part, but it is also easier for me to reach my limit on my plan, so maybe I am just making more use of my limits?
I use GLM 5.2 through Opencode Go, but find it to be quite slow when you get to higher contexts (80k+) through their provider so I have not been able to test too much.
Very expensive, not sure how it fits in with many companies seemingly trying to get employees using models at about Sonnet tier pricing. I certainly would never pay API rates for it, using ccusage I am seeing myself "use" $150-$400 worth of fable per day. (https://www.theinformation.com/articles/tesla-caps-employee-...)
I feel like the times of AI generated profile pictures are long behind us and we are just beginning to see the widespread disdain for AI use specifically in a personal setting. To many it seems tacky and I think this is the biggest issue meta faces for AI in products outside of facebook itself. Though I suppose there is plenty of time before their target demographic ages out of existence for them to reap the rewards of the increasingly socially disconnected boomer/late genx and millenial/genz.