More than 2.2 billion compute hours exceeded the annual NCMAS compute share on NCI's Gadi and Pawsey's Setonix by nearly 3 times.
#NCRISimpact #NCMAS
More than 2.2 billion compute hours exceeded the annual NCMAS compute share on NCI's Gadi and Pawsey's Setonix by nearly 3 times.
#NCRISimpact #NCMAS
More than 2.2 billion compute hours exceeded the annual NCMAS compute share on NCI's Gadi and Pawsey's Setonix by nearly 3 times.
#NCRISimpact #NCMAS
My 2 year old colleague left a message on our creation for future generations. 😊
My 2 year old colleague left a message on our creation for future generations. 😊
Tap => pressure limiter 1 => timer => backflow preventer => Venturi fertiliser injector => disc filter => pressure limiter 2 => drip line.
Fertigation here we come!
Tap => pressure limiter 1 => timer => backflow preventer => Venturi fertiliser injector => disc filter => pressure limiter 2 => drip line.
Fertigation here we come!
Hear from @mcderbyshire.bsky.social in this GRDC podcast as he discusses the path to more resilient cultivars and reducing fungicide reliance. 🌾🛡️
🎙️ Listen: buff.ly/1AqhmBL
#GRDC #CurtinUni
For more details, visit: bewerbungsmanagement.uni-koeln.de/ausschreibun...
For more details, visit: bewerbungsmanagement.uni-koeln.de/ausschreibun...
doi.org/10.1038/d415...
doi.org/10.1038/d415...
📍 #BotryScleroMoni2025 (Greece): Sharing insights on Sclerotinia stem rot and Botrytis cinerea.
📍 #APPS2025 (Sydney): Presenting work on fungicide resistance, cereal tolerance & disease control. 🌾👏
📍 #BotryScleroMoni2025 (Greece): Sharing insights on Sclerotinia stem rot and Botrytis cinerea.
📍 #APPS2025 (Sydney): Presenting work on fungicide resistance, cereal tolerance & disease control. 🌾👏
Catch @mcderbyshire.bsky.social presenting on new breeding lines and field screening methods for developing sclerotinia stem rot resistant canola cultivars 🧬
📅 Mon 24 Feb | 🕑 4:35pm | 📍Session 11
Register here 👉 https://buff.ly/4gr7XZm
Any thoughts from people with neural network expertise? Papers describing these models often show plausibly that unsupervised training has learnt something about the data. Why is this no better than random for downstream tasks?
Any thoughts from people with neural network expertise? Papers describing these models often show plausibly that unsupervised training has learnt something about the data. Why is this no better than random for downstream tasks?
Our latest paper published in @CommsBio led by the
@jameskhane.bsky.social lab @theccdm.bsky.social shown the ⚖️balancing act of RIP vs negative selection in generating genetic diversity in a major🌾wheat fungal pathogen!
Find out more! 👇👇👇
They found it uses DNA mutations like RIP to diversify—while harmful mutations are filtered out🦠
📰 https://buff.ly/4jXm63B
@jameskhane.bsky.social
Our latest paper published in @CommsBio led by the
@jameskhane.bsky.social lab @theccdm.bsky.social shown the ⚖️balancing act of RIP vs negative selection in generating genetic diversity in a major🌾wheat fungal pathogen!
Find out more! 👇👇👇
Full story here, requires Farm Weekly sub: www.farmweekly.com.au/story/887534...
Full story here, requires Farm Weekly sub: www.farmweekly.com.au/story/887534...