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Why ‘open source’ AIs could be anything but, the derailment risks of long freight trains, and breeding better wheat

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Treść dostarczona przez podcast@nature.com and Springer Nature Limited. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez podcast@nature.com and Springer Nature Limited lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.

00:31 How open are ‘open source’ AI systems?

Many of the large language models powering AI systems are described as ‘open source’ but critics say this is a misnomer, with restricted access to code and training data preventing researchers from probing how these systems work. While the definition of open source in AI models is yet to be agreed, advocates say that ‘full’ openness is crucial in efforts to make AI accountable. New research has ranked the openness of different systems, showing that despite claims of ‘openness’ many companies still don’t disclose a lot of key information.


Nature News: Not all ‘open source’ AI models are actually open: here’s a ranking


06:12 Why longer freight trains are more prone to derailment

In the US, there are no federal limits on the length of a freight train, but as companies look to run longer locomotives, questions arise about whether they are at greater risk of derailment. To find out, a team analysed data on accidents to predict the chances of longer trains coming off the tracks. They showed that replacing two 50-car freight trains with one 100-car train raises the odds of derailment by 11%, with the chances increasing the longer a train gets. While derailments are uncommon, this could change as economic pressures lead the freight industry to experiment with ever-longer trains.


Scientific American: Longer and Longer Freight Trains Drive Up the Odds of Derailment


11:44 How historic wheat could give new traits to current crops

Genes from century-old wheat varieties could be used to breed useful traits into modern crops, helping them become more disease tolerant and reducing their need for fertiliser. Researchers sequenced the genomes of hundreds of historic varieties of wheat held in a seed collection from the 1920s and 30s, revealing a huge amount of genetic diversity unseen in modern crops. Plant breeding enabled the team to identify some of the areas of the plants’ genomes responsible for traits such as nutritional content and stress tolerance. It’s hoped that in the long term this knowledge could be used to improve modern varieties of wheat.


Science: ‘Gold mine’ of century-old wheat varieties could help breeders restore long lost traits


Subscribe to Nature Briefing, an unmissable daily round-up of science news, opinion and analysis free in your inbox every weekday.



Hosted on Acast. See acast.com/privacy for more information.

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Artwork
iconUdostępnij
 
Manage episode 425743096 series 3137
Treść dostarczona przez podcast@nature.com and Springer Nature Limited. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez podcast@nature.com and Springer Nature Limited lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.

00:31 How open are ‘open source’ AI systems?

Many of the large language models powering AI systems are described as ‘open source’ but critics say this is a misnomer, with restricted access to code and training data preventing researchers from probing how these systems work. While the definition of open source in AI models is yet to be agreed, advocates say that ‘full’ openness is crucial in efforts to make AI accountable. New research has ranked the openness of different systems, showing that despite claims of ‘openness’ many companies still don’t disclose a lot of key information.


Nature News: Not all ‘open source’ AI models are actually open: here’s a ranking


06:12 Why longer freight trains are more prone to derailment

In the US, there are no federal limits on the length of a freight train, but as companies look to run longer locomotives, questions arise about whether they are at greater risk of derailment. To find out, a team analysed data on accidents to predict the chances of longer trains coming off the tracks. They showed that replacing two 50-car freight trains with one 100-car train raises the odds of derailment by 11%, with the chances increasing the longer a train gets. While derailments are uncommon, this could change as economic pressures lead the freight industry to experiment with ever-longer trains.


Scientific American: Longer and Longer Freight Trains Drive Up the Odds of Derailment


11:44 How historic wheat could give new traits to current crops

Genes from century-old wheat varieties could be used to breed useful traits into modern crops, helping them become more disease tolerant and reducing their need for fertiliser. Researchers sequenced the genomes of hundreds of historic varieties of wheat held in a seed collection from the 1920s and 30s, revealing a huge amount of genetic diversity unseen in modern crops. Plant breeding enabled the team to identify some of the areas of the plants’ genomes responsible for traits such as nutritional content and stress tolerance. It’s hoped that in the long term this knowledge could be used to improve modern varieties of wheat.


Science: ‘Gold mine’ of century-old wheat varieties could help breeders restore long lost traits


Subscribe to Nature Briefing, an unmissable daily round-up of science news, opinion and analysis free in your inbox every weekday.



Hosted on Acast. See acast.com/privacy for more information.

  continue reading

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