Yes, there is a whole host of problems behind wanting data to be the main driver of understanding social structures. This is in fact a mask for the neoliberal agenda.
OK, this is an interesting way for the Darwin Award to branch. Some of the 2025 nominees are indeed funny. Now I wonder which ones will win the award!
We can expect more misleading papers to be published by the big LLM providers. Don't fall in the trap, wait for actually peer reviewed papers from academia. Unsurprisingly the results aren't as good there.
Long but interesting chapter which shows how GPUs architecture works and the differences with TPUs. This is unsurprisingly written in the context of large models training.
Really captures well the ethos of the moment...
Honestly, it took much longer than I expected. Now you know that GitHub has really become a conduit for Microsoft's AI initiatives.
Good thinking about LLMs and why it's not necessary to run after them.
The business model is still not here... There won't be an LLM company making money, it'll be bundled with something else.
Sounds very expensive... But maybe an interesting use of LLMs for code reviews.
Interesting thinking on how the tools should be designed to avoid killing learning abilities. Now I doubt they'll ever be designed that way. That said, this gives good insights on how to use them better for programming.
Running interesting models locally gets more and more accessible.
Don't forget who so called productivity gains are for. Maybe it'll deliver (although I doubt it), and if it does we can draw the consequences from the past.
ETH Zurich spearheading an effort for more ethical and cleaner open models. That's good research, looking forward to the results.
Those companies still don't make any economic sense... It's really just a ploy for fake growth.
Interesting comparison, indeed would a clock like this be useful?
And one more... it's clearly driven by an architecture pattern used by all vendors. They need to get their acts together to change this.
There's always been disinformation in time of wars. The difference is the scale and speed of producing fake images now.
Good reminder that professional translators aren't gone... on the contrary. There's so many things in languages that you can't handle with a machine.
I recognize myself quite a bit in this opinion piece. It does a good job going through most of the ethical and practical reasons why you don't need LLMs to develop and why you likely don't want to.
OK, this is a serious and long paper. It shows quite well how over reliance on ChatGPT during the learning phase on some topics impacts people. It's mesurable both from their behavior and through EEG. Of course, it'd require more such studies with larger groups. Still those early signs are concerning.