Efficiency
The AI Community Splinters: Could geopolitics drive a wedge in the AI community?
Will international rivalries fragment international cooperation in machine learning? Countries competing for AI dominance will lash out at competitors.
Efficiency
Giant Models Bankrupt Research: Will training AI become too expensive for most companies?
What if AI requires so much computation that it becomes unaffordable?The fear: Training ever more capable models will become too pricey for all but the richest corporations and government agencies. Rising costs will
Efficiency
Giant Models Bankrupt Research: Will training AI become too expensive for most companies?
What if AI requires so much computation that it becomes unaffordable?The fear: Training ever more capable models will become too pricey for all but the richest corporations and government agencies. Rising costs will
Efficiency
Getting a Charge From AI: How battery developers are using AI
Machine learning is helping to design energy cells that charge faster and last longer. Battery developers are using ML algorithms to devise new chemicals, components, and charging techniques faster than traditional techniques allow.
Efficiency
Getting a Charge From AI: How battery developers are using AI
Machine learning is helping to design energy cells that charge faster and last longer. Battery developers are using ML algorithms to devise new chemicals, components, and charging techniques faster than traditional techniques allow.
Efficiency
More Efficient Transformers: BigBird is an efficient attention mechanism for transformers.
As transformer networks move to the fore in applications from language to vision, the time it takes them to crunch longer sequences becomes a more pressing issue. A new method lightens the computational load using sparse attention.
Efficiency
More Efficient Transformers: BigBird is an efficient attention mechanism for transformers.
As transformer networks move to the fore in applications from language to vision, the time it takes them to crunch longer sequences becomes a more pressing issue. A new method lightens the computational load using sparse attention.
Efficiency
Toward 1 Trillion Parameters: Microsoft upgrades its DeepSpeed optimization library.
An open source library could spawn trillion-parameter neural networks and help small-time developers build big-league models. Microsoft upgraded DeepSpeed, a library that accelerates the PyTorch deep learning framework.
Efficiency
Toward 1 Trillion Parameters: Microsoft upgrades its DeepSpeed optimization library.
An open source library could spawn trillion-parameter neural networks and help small-time developers build big-league models. Microsoft upgraded DeepSpeed, a library that accelerates the PyTorch deep learning framework.
Efficiency
Dropout With a Difference: Reduce neural net overfitting without impacting accuracy
The technique known as dropout discourages neural networks from overfitting by deterring them from reliance on particular features. A new approach reorganizes the process to run efficiently on the chips that typically run neural network calculations.
Efficiency
The Transformation Continues: Technique boosts transformer performance on long sequences.
Transformer networks are gaining popularity as a high-accuracy alternative to recurrent neural networks. But they can run slowly when they’re applied to long sequences.
Efficiency
The Transformation Continues: Technique boosts transformer performance on long sequences.
Transformer networks are gaining popularity as a high-accuracy alternative to recurrent neural networks. But they can run slowly when they’re applied to long sequences.
Efficiency
Dropout With a Difference: Reduce neural net overfitting without impacting accuracy
The technique known as dropout discourages neural networks from overfitting by deterring them from reliance on particular features. A new approach reorganizes the process to run efficiently on the chips that typically run neural network calculations.
Efficiency
Experience Counts: Research proposes an upgrade to experience replay.
If the world changes every second and you take a picture every 10 seconds, you won’t have enough pictures to observe the changes clearly, and storing a series of pictures won’t help. On the other hand, if you take a picture every tenth of a second, then storing a history will help model the world.
Efficiency
Experience Counts: Research proposes an upgrade to experience replay.
If the world changes every second and you take a picture every 10 seconds, you won’t have enough pictures to observe the changes clearly, and storing a series of pictures won’t help. On the other hand, if you take a picture every tenth of a second, then storing a history will help model the world.
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