Extra-condensed knowledge

Researchers hope that bringing deep learning techniques to cell imaging and analysis could turn messy biological problems into solvable computations.

The deep learning algorithms that power computational microscopes require large datasets to train them to perform independent tasks, but such datasets are not always readily available. Then the performance of these algorithms must be assessed to compare it to the current standard of analysis.
Building bridges

Introducing AI into the daily practice of microscopy, whether you’re looking at cells or rocks, is to ensure that the technology can be used by any scientist, regardless of their knowledge of deep learning techniques.

The future of AI

Across the board, researchers working in academic and commercial settings see the greatest barrier to adopting AI into scientific life as fear of the unknown. Yet its increasing influence is undeniable.
There’s a sense that while change is inevitable, society needs to make a stronger commitment to ensuring all scientists can benefit from these new technologies.

Genioux knowledge fact condensed as an image

Condensed knowledge

CONTEXT

Researchers hope that bringing deep learning techniques to cell imaging and analysis could turn messy biological problems into solvable computations.
The deep learning algorithms that power computational microscopes require large datasets to train them to perform independent tasks, but such datasets are not always readily available. Then the performance of these algorithms must be assessed to compare it to the current standard of analysis.
Building bridges
Introducing AI into the daily practice of microscopy, whether you’re looking at cells or rocks, is to ensure that the technology can be used by any scientist, regardless of their knowledge of deep learning techniques.
The future of AI
Across the board, researchers working in academic and commercial settings see the greatest barrier to adopting AI into scientific life as fear of the unknown. Yet its increasing influence is undeniable.
There’s a sense that while change is inevitable, society needs to make a stronger commitment to ensuring all scientists can benefit from these new technologies.

Category 2: The Big Picture of the Digital Age

[genioux fact deduced or extracted from AAAS]

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Type of essential knowledge of this “genioux fact”: Essential Deduced and Extracted Knowledge (EDEK).

Type of validity of the "genioux fact".

Inherited from sources + Supported by the knowledge of one or more experts.

Authors of the genioux fact

Fernando Machuca

References

Small images, big picture: Artificial intelligence to revolutionize microscopy, Sarah O’Meara, April 23, 2021, AAAS.

ABOUT THE AUTHORS

Sarah O’Meara

Sarah O’Meara is a freelance writer who specializes in life sciences.

Extracted from LinkedIn

About

I am a creative team manager who has lead editorial, audience development and technical teams in the UK and China for startups and established companies. I specialise in problem-solving, research, delivering to a deadline and motivating staff. I like to work with optimistic, intelligent teams with progressive goals.