We must assume that Europe is becoming the world's last democratic major hub. Imperfect, perhaps, but democratic.
As such, Europe is the prime target of the new American administration.
Everything this administration will do will be aimed at harming us.
Washington's primary objective is now to hamper Europe's ability to exert a counter-power, even if it means joining forces with the worst tyrants.
We still have allies in the United States, but not within the administration.
I don't know much about large language models, but this new Chinese one sounds interesting:
"DeepSeek-R1 scored as high as or higher than OpenAI’s o1 on a variety of third-party benchmarks (tests to measure AI performance at answering questions on various subjects), and was reportedly trained at a fraction of the cost (reportedly around $5 million), with far fewer graphics processing units (GPU) that are under a strict embargo imposed by the U.S., OpenAI’s home turf.
But unlike o1, which is available only to paying ChatGPT subscribers of the Plus tier ($20 per month) and more expensive tiers (such as Pro at $200 per month), DeepSeek-R1 was released as a fully open-source model, which also explains why it has quickly rocketed up the charts of AI code sharing community Hugging Face’s most downloaded and active models.
Also, thanks to the fact that it is fully open-source, people have already fine-tuned and trained many variations of the model for different task-specific purposes, such as making it small enough to run on a mobile device, or combining it with other open-source models. Even if you want to use it for development purposes, DeepSeek’s API costs are more than 90% lower than the equivalent o1 model from OpenAI.
Most impressively of all, you don’t even need to be a software engineer to use it: DeepSeek has a free website and mobile app even for U.S. users."
https://venturebeat.com/ai/why-everyone-in-ai-is-freaking-out-about-deepseek/
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@pbloem this sounds an awful lot like "no true AGI" kind of argument...
I agree that we do not have this kind of generalization, yet, but, on the other hand, we do have waymo stats saying they're generally safer where they operate than humans.
Basically, "nowhere near" feels way too strong, given that waymo miracles do exist. We have self-driving cars (under some limited conditions), that's pure magic, and it's far closer to self-driving cars everywhere than to self-driving cars nowhere.
This is quite a neat demonstration of the counter-intuitive dangers of using current ML tech in critical situations.
You'd think that more reflective = more visible, but visibility is a problem for humans. For ML more reflective means more unusual, which means the system doesn't know what to do.
This creates a whole host of problems. For example when fashion rapidly changes, systems will get less good at recognizing people.
@pbloem the current paradigm is of the "train on more data until nothing is out of distribution", and while it's not "true" generalization, with enough capital this approach can and has yielded wonders.
What we see above is perhaps just the effects of not enough data...
Nicolas Henin 🇪🇺💙💛
John Carlos Baez
Peter Bloem
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