#attention-mechanisms

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fromZDNET
1 week ago

DeepSeek claims its new AI model can cut the cost of predictions by 75% - here's how

The Chinese artificial intelligence startup DeepSeek AI, which stunned the world in January with claims of dramatic cost efficiency for generative AI, is back with the latest twist on its use of the technology to drive down the price of computing. Last week, DeepSeek unveiled its latest research, DeepSeek-V3.2-Exp. On its corporate blog, the company claims the new model can cut the cost of making predictions, known as inference, by 75%, from $1.68 per million tokens to 42 cents.
Artificial intelligence
fromHackernoon
1 year ago

Defining the Frontier: Multi-Token Prediction's Place in LLM Evolution | HackerNoon

Dong et al. (2019) and Tay et al. (2022) train on a mixture of denoising tasks with different attention masks (full, causal and prefix attention) to bridge the performance gap with next token pretraining on generative tasks.
Artificial intelligence
Science
fromHackernoon
1 year ago

In Cancer Research, AI Models Learn to See What Scientists Might Miss | HackerNoon

Multi-instance learning with attention mechanisms effectively identifies tumor regions, but TP53 mutation detection remains more complex and less accurate.
#large-language-models
fromHackernoon
4 months ago
Artificial intelligence

Issues with PagedAttention: Kernel Rewrites and Complexity in LLM Serving | HackerNoon

fromHackernoon
4 months ago
Artificial intelligence

Issues with PagedAttention: Kernel Rewrites and Complexity in LLM Serving | HackerNoon

#transformers
fromMedium
6 months ago
Artificial intelligence

Multi-Token Attention: Going Beyond Single-Token Focus in Transformers

Multi-Token Attention enhances transformers by allowing simultaneous focus on groups of tokens, improving contextual understanding.
Traditional attention considers one token at a time, limiting interaction capture among tokens.
fromMedium
6 months ago
Artificial intelligence

Multi-Token Attention: Going Beyond Single-Token Focus in Transformers

Multi-Token Attention revolutionizes transformers by enabling simultaneous attention to groups of tokens, enhancing contextual understanding.
Artificial intelligence
fromMedium
6 months ago

Multi-Token Attention: Going Beyond Single-Token Focus in Transformers

Multi-Token Attention enhances transformers by allowing simultaneous focus on groups of tokens, improving contextual understanding.
Traditional attention considers one token at a time, limiting interaction capture among tokens.
Artificial intelligence
fromMedium
6 months ago

Multi-Token Attention: Going Beyond Single-Token Focus in Transformers

Multi-Token Attention revolutionizes transformers by enabling simultaneous attention to groups of tokens, enhancing contextual understanding.
Artificial intelligence
fromMedium
6 months ago

Multi-Token Attention: Going Beyond Single-Token Focus in Transformers

Multi-Token Attention allows transformers to attend to groups of tokens, enhancing model performance in natural language processing.
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