Black holes, white holes, wormholes, anti-universes, and all kinds of awesome relativity weirdness:
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Continue reading “Something Strange Happens When You Follow Einstein’s Math” »
1/ Researchers have found that AI models can solve complex tasks like “3SUM” by using simple dots like “…” instead of sentences.
Researchers have found that specifically trained LLMs can solve complex problems just as well using dots like “…” instead of full sentences. This could make it harder to control what’s happening in these models.
The researchers trained Llama language models to solve a difficult math problem called “3SUM”, where the model has to find three numbers that add up to zero.
Continue reading “Meaningless fillers enable complex thinking in large language models” »
Dive into RNNs, the backbone of time series, understand their mathematics, implement them from scratch, and explore their applications.
Generally, it’s advised not to compare apples to oranges. However, in the field of topology, a branch of mathematics, this comparison is necessary. Apples and oranges, it turns out, are said to be topologically the same since they both lack a hole – in contrast to doughnuts or coffee cups, for instance, which both have one (the handle in the case of the cup) and, hence, are topologically equal.
In a more abstract way, quantum systems in physics can also have a specific apple or doughnut topology, which manifests itself in the energy states and motion of particles. Researchers are very interested in such systems as their topology makes them robust against disorder and other disturbing influences, which are always present in natural physical systems.
Things get particularly interesting if, in addition, the particles in such a system interact, meaning that they attract or repel each other, like electrons in solids. Studying topology and interactions together in solids, however, is extremely difficult. A team of researchers at ETH led by Tilman Esslinger has now managed to detect topological effects in an artificial solid, in which the interactions can be switched on or off using magnetic fields. Their results, which have just been published in the scientific journal Science, could be used in quantum technologies in the future.
If you do the math, it means CATL is offering an impressive charging rate of roughly 1 km/sec in a 10 minute quick charge.
Sir Roger Penrose proposes that the universe undergoes repeated cycles of expansion, decay, and rebirth, challenging the traditional notion of a singular Big Bang origin.
Renowned physicist Sir Roger Penrose, hailing from the University of Oxford and a co-recipient of the 2020 Nobel Prize in Physics, posits a fascinating theory regarding the universe’s cyclical nature. Contrary to prevailing notions, Penrose suggests that our universe has undergone numerous Big Bang events, with another impending in the future.
Penrose’s Nobel-winning contributions revolve around advancing mathematical frameworks that not only validate but also extend Albert Einstein’s general theory of relativity. Moreover, his investigations into black holes elucidated the phenomenon of gravitational collapse, wherein excessively dense entities converge into singularities, infinitely massive points.
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The Future of Humanity Institute announced last week that they have shut down. Located at the University of Oxford in the UK prior to its demise, the institute was one of the few places worldwide studying the risk of human extinction and a few other controversial research areas. Let’s have a look at the events leading to the institute’s closure.
Continue reading “Institute for Extinction Risk Shuts Down: What We Know” »
Mathematicians have the tools to explore worlds of 2, 3 and 5+ dimensions. But the fourth dimension remains mysterious and elusive. Topologists are trying to change that, one problem at a time.
Topologists prove two new results that bring some order to the confoundingly difficult study of four-dimensional shapes.
👉 Researchers have developed a method called Selective Language Modeling (SLM), which trains language models more efficiently by focusing on the most relevant tokens.
Researchers introduce a new method called “Selective Language Modeling” that trains language models more efficiently by focusing on the most relevant tokens.
The method leads to significant performance improvements in mathematical tasks, according to a new paper from researchers at Microsoft, Xiamen University, and Tsinghua University. Instead of considering all tokens in a text corpus equally during training as before, Selective Language Modeling (SLM) focuses specifically on the most relevant tokens.
Continue reading “Selective language modeling: New method allows for better models with less data” »
