Thomas Rueckstiess @tomonezero
AI researcher | productivity | board games | juggling | coffee tomr.au Melbourne, Australia Joined January 2013-
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Seems more like a cost or system complexity trade-off than a sensor fusion issue. Especially if you deep learn end-to-end, more data is better. Sensor fusion can happen implicitly in the net with multi-modal architectures.
Seems more like a cost or system complexity trade-off than a sensor fusion issue. Especially if you deep learn end-to-end, more data is better. Sensor fusion can happen implicitly in the net with multi-modal architectures.
The (true) story of development and inspiration behind the "attention" operator, the one in "Attention is All you Need" that introduced the Transformer. From personal email correspondence with the author @DBahdanau ~2 years ago, published here and now (with permission) following…
It depends on your use case. If your data is flat and has a strict schema (i.e. is tabular), CSV works well. If your data is nested, or contains arrays, or your schema changes across objects, you need a semi-structured format like JSON, which contains the schema in each object.
It depends on your use case. If your data is flat and has a strict schema (i.e. is tabular), CSV works well. If your data is nested, or contains arrays, or your schema changes across objects, you need a semi-structured format like JSON, which contains the schema in each object.
BREAKING NEWS The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in Physics to John J. Hopfield and Geoffrey E. Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural networks.”
In 2019, OpenAI announced GPT-2 with this post: openai.com/index/better-l… Today (~5 years later) you can train your own for ~$672, running on one 8XH100 GPU node for 24 hours. Our latest llm.c post gives the walkthrough in some detail: github.com/karpathy/llm.c… Incredibly, the…
Ollama 0.2 is here! Concurrency is now enabled by default. ollama.com/download This unlocks 2 major features: Parallel requests Ollama can now serve multiple requests at the same time, using only a little bit of additional memory for each request. This enables use cases…
visualization of what a neural network does
A shift is coming, I can see it. Apps that ship with their own LLMs (small, quantized, optimized for the app to run on your own GPU or CPU). These models will not completely replace your usage of the large models you already pay for, instead they will add a sprinkle of…

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