FWIW, you're comparing a training-specialized chip to an inference-specialized chip. It'd be more apples to apples to compare to TPU v4 lite, but I can't find that chip's details anywhere beyond some mentions in the TPU v4 paper: https://arxiv.org/abs/2304.01433
Too late for what exactly? Majority of climate scientists agree the situation is dire, but there are many actions that can be taken to reduce the short-term and long-term impact, via both adaptation and reducing carbon emissions.
We're up against massive loss of biodiversity, loss of habitable space on the planet, and an enormous amount of human suffering and loss of human life due to the current and future effects of climate change. A smaller population will not solve these problems alone, but it will buy us more time to solve them.
FWIW, I'm not trying to promote anything extreme like population control policies, just pointing out that the current trend of population leveling off is generally a good thing.
I feel like this happened to Gitlab / GitHub as well. Gitlab was gaining a ton of popularity and momentum with their free private repositories and built-in CI testing infrastructure. Then GitHub swooped in and offered all the same things, taking the wind out of Gitlab's sails.
Thanks Isaac. How do I reach that page? I expected it on one of the informational pages such as the home page or benchmark programs page, but had no luck.
I can't find the documentation for it, but you can see here that they measure the size of the source file after gzip compression, which reduces advantage of code-golf solutions:
Not exactly what you're looking for, but here are some 2D plots of code size vs. execution time with geometric means of fastest entries and smallest code size entries of each language:
Strict immigration policies during the previous presidency combined with the pandemic have led to record low immigration. Census projections generally expected immigration levels to remain constant. However, immigration plummeted from a net gain of ~1000k/year in 2016 to ~250k/year in 2020[1].
Tangentially, I am amazed at the data in your source about how fast population growth is leveling off in the US. In 2020, the census projected US population to continue growing and cross 400 million by 2058 [1]. This projection accounts for the observed trends in falling fertility rate and assumes relatively constant rate of immigration:
>By 2030, immigration is projected to become the primary driver of population
>growth: more people are projected to be added to the population through net
>international migration than from natural increase. The projected shift to net
>international immigration as the primary driver of population growth is the
>result of falling fertility rates and the rising number of deaths in an aging
>population, not because of a projected increase in international migration.
I guess the pandemic broke a lot of those assumptions. We will see if they hold in the long run though.
The post focuses on countering the strawman-like argument that resource shortages are the primary threat with overpopulation. However, it is overwhelmingly clear that climate change is the biggest threat related to overpopulation, unless we are able to get carbon emissions per capita below 0 globally.
Where did you find this feature? As a beta user, I have a hard time finding documentation for the features in Kagi. Ironically, searching about Kagi in Kagi is not helpful.