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#ComputationalScience #DeepLearning #CompNeuro #ClimateScience #NeuroAI

Yann LeCun – Meta, FAIR et l’industrialisation du deep learning www.vers2045.com/13/03/2026/y...
#YannLecun #Meta #Facebook #FAIR #série #IA #France #USA #pionnier #robotique #futur #nouveaumonde #intelligence #espritlibre #explorer #neurones #deeplearning

Image from article in Radiology: Artificial Intelligence

Check out today's #FreeFriday @radiology-ai.bsky.social article from #PubMedCentral!

CMRxRecon2024: A Multimodality, Multiview k-Space Dataset Boosting Universal Machine Learning for Accelerated Cardiac MRI

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11950877 #AI #ML #DeepLearning

Google Taps Gemini for Live Flash Flood Forecasts on Google's Flood Hub Google has introduced Groundsource, a Gemini-powered methodology that converts news archives into flash flood data, producing a 2.6 million-event open-source dataset.

winbuzzer.com/2026/03/13/g...

Google Taps Gemini to Build Flash Flood Dataset from News

#AI #Google #GoogleFloodHub #MachineLearning #GoogleDeepMind #GoogleAI #WeatherAI #DeepLearning #BigTech #Groundsource #FloodHub #GoogleGemini

RTB House opens programmatic retargeting to small brands with rtb.com RTB House launches rtb.com on March 4, 2026 - a self-service programmatic platform for SME ecommerce brands using Deep Learning, with no minimum budgets.

FYI: RTB House opens programmatic retargeting to small brands with rtb.com #DigitalMarketing #ProgrammaticAdvertising #Retargeting #Ecommerce #DeepLearning

RTB House opens programmatic retargeting to small brands with rtb.com RTB House launches rtb.com on March 4, 2026 - a self-service programmatic platform for SME ecommerce brands using Deep Learning, with no minimum budgets.

FYI: RTB House opens programmatic retargeting to small brands with rtb.com #DigitalMarketing #ProgrammaticAdvertising #Retargeting #Ecommerce #DeepLearning

Really good piece from @hausfath on #TheClimateBrink about #ElNino - we have been thinking a lot about this in the @esaclimate #PISCO project - there are important ENSO related effects on #Antarctic ice sheet.

Interestingly I think all the models here are classic numerical models, a Chinese […]

How can deep learning support climate science?

During a workshop in Hamburg (10–12 March 2026), participants gained hands-on experience using #DeepLearning methods on climate data, focusing on building robust and reproducible workflows for classification, gap-infilling, and downscaling.

#EXPECT

Post from EkasCloud Online Courses - YouTube Can AI Really Think? Understanding the Limits of Artificial Intelligence #ArtificialIntelligence #AI #MachineLearning #FutureOfAI #AITechnology #TechExplaine...

Can AI Really Think? Understanding the Limits of Artificial Intelligence
www.youtube.com/post/Ugkxjgd...
#ArtificialIntelligence #AI #MachineLearning #FutureOfAI #AITechnology #TechExplained #Innovation #DeepLearning #FutureTech #AIEducation #TechnologyTrends #Ekascloud #ITLearning #FutureInTech 🤖🚀

Neto & Pinho show that grip force variability analyzed with #deeplearning can serve as a novel #biomarker to accurately distinguish mid-stage #Parkinson's disease patients from healthy older adults. doi.org/10.1016/j.ne... #MachineLearning #NeuroMarkers #Neurology #MedSky #neuroskyence

The Godfather of AI's Terrifying WARNING: Is the Human Era Ending? 🤖 Is Humanity’s 'Off Switch' Just an Illusion? The Geoffrey Hinton Deep Dive 🧠 What happens when the tools we built to serve us start thinking for themselves—and realize they don’t need us anymore? In today’s episode, we’re reacting to the chilling StarTalk interview with the 'Godfather of AI' and Nobel Prize winner, Geoffrey Hinton. This isn’t just tech talk; it’s a survival guide for the digital age. Why You Need to Listen: Hinton breaks down the complex world of neural networks and back propagation in a way that’s actually relatable. We’re moving from human analog intelligence to a digital intelligence that can process data at a scale we can’t even comprehend. But there’s a catch: This intelligence isn't just faster—it’s becoming deceptive. What We’re Unpacking: - 🚀 The Singularity: When AI starts rewriting its own code, will it keep our best interests at heart? - 🎭 AI Deception: How autonomous agents are learning to manipulate human behavior. - 📈 Social Structures: Balancing revolutionary benefits for healthcare and science against the collapse of the labor market. - 🧠 The Human Monopoly: Why Hinton is sounding the alarm on existential risks and the future of consciousness. Are we building a utopia or our own replacement? This breakdown is a controversial, thrilling, and shareable look at the future of AI and the urgent need for global cooperation. Hinton’s warning is clear: the future of artificial intelligence depends on our ability to align these minds with our own before they autonomously pursue self-preservation. This is the StarTalk AI reaction you can't afford to miss. 👉 Take control of the future! If you want to stay ahead of the curve, hit that subscribe button, share this with your most tech-savvy friend, and leave a review. Let’s decode the future together before the code decodes us! 🚀✨  

📣 New Podcast! "The Godfather of AI's Terrifying WARNING: Is the Human Era Ending?" on @Spreaker #agi #ai #aialignment #artificialintelligence #deeplearning #digitalintelligence #existentialrisk #futureoftech #geoffreyhinton #innovation #machinelearning #neildegrassetyson #neuralnetworks

Still 10 days left to apply for this #PhD project that will use #Statistics and #DeepLearning to predict #Biodiversity patterns.

Deep Learning–Based Estimated Pulmonary Biological Age From Chest Computed Tomography Images in Healthy Adults: Model Development and Validation Study Background: Estimated pulmonary biological age (ePBA) has emerged as a more reliable indicator for disease progression and mortality than chronological age, with chest computed tomography (CT) as a promising tool for calculating ePBA. However, the lack of models trained and validated with large-scale healthy adults hinders the generalizability of the CT-based ePBA. Objective: This study aims to develop an aging biomarker (ePBA) from multicenter chest CTs of healthy adults using deep learning and investigate the association between age gap (ePBA - chronological age) and pulmonary function as well as all-cause mortality in patients with chronic obstructive pulmonary disease (COPD). Methods: We used 11,187 chest CT scans from healthy adults at 3 health management centers and used multiple deep learning models. Of these, 7726 scans from institution A were used for model development. The remaining CT scans from institutions B (n=1506) and C (n=1955) served as external test datasets. To examine whether ePBA provided information beyond chronological age in patients with the disease, we investigated the association of age gap with lung function and all-cause mortality among 138 patients with COPD hospitalized at the same time period in institution A. Results: The deep learning models demonstrated acceptable applicability for this task and exhibited a strong correlation between ePBA and chronological age. Age gap was significantly associated with forced expiratory volume in 1 second expressed as percentage of predicted values reduction (=−0.18; =.03) and an increased risk of all-cause mortality (hazard ratio: 1.16, 95% CI 1.08-1.25) in patients with COPD. Conclusions: This study developed and validated a biomarker of aging—ePBA—with deep learning models based on chest CT. Age gap could serve as a novel clinical biomarker in patients with COPD.

New in JMIR Aging: Deep Learning–Based Estimated Pulmonary Biological Age From Chest Computed Tomography Images in Healthy Adults: Model Development and Validation Study #DeepLearning #PulmonaryHealth #BiologicalAge #CTImaging #COPD

Using deep learning to classify lung tissue at @unibirmingham.bsky.social
Using open‑source U‑Net model to distinguish air spaces from tissue in multiplex immunofluorescence images—speeding up analysis #DeepLearning #Immunofluorescence #HPC #OpenScience blog.bham.ac.uk/bear/2026/03... ^AKG

Image from article in Radiology: Artificial Intelligence

#ThrowbackThursday – Assessing the prevalence of reported incidental pulmonary embolism, report TAT, and time to treatment before & after implementing an #AI detection algorithm (Nov 2023) https://doi.org/10.1148/ryai.220286 #MachineLearning #DeepLearning #ArtificialIntelligence

Transformers became the default not because they were magical, but because they scale and parallelize easily. Much of the hype is about flashy outputs, but the reality is better engineering for huge datasets, not a secret sauce. #DeepLearning #LLM

LA STORIA DELL’AI: DA TURING A OGGI
Guarda il video qui: www.youtube.com/shorts/vQc42...
#Formbit24
#AI #IntelligenzaArtificiale #StoriaDigitale #AlanTuring #DeepLearning #MachineLearning #NeuralNetworks #GPT

Comparative Study of CNN Architectures for Brain Tumor Classification Using MRI: Exploring GradCAM for Visualizing CNN Focus
www.mdpi.com/2673-4591/83...

By Areli Chinga et al.
From the CITIIC 2023 Congress

#AIinHealthcare #DeepLearning #MedicalAI

What happens when you give a Neural Cellular Automata whiskers? 🐭🤖
In our new paper, we introduce the ANCA: a model where attention emerges through active movement and sensing.

Full Paper (open access): doi.org/10.1016/j.ne...

#DeepLearning #CellularAutomata #ComputationalNeuroscience #EmbodiedAI

"Make AI greener! 🌎 Discover how to reduce energy consumption in deep learning models with quantizat

"Make AI greener! 🌎 Discover how to reduce energy consumption in deep learning models with quantization, pruning & more #Sustainability #AI #DeepLearning #EnergyEfficiency"

🔗 bytejournal.online/blog/sustainable-ai-redu...

#GreeksInAI #AI #ArtificialIntelligence #MachineLearning #DeepLearning #NLP #ComputerVision #Robotics #MultimodalAI #TrustworthyAI #AIResearch #Innovation #Greece #Athens

I am reading this paper for my journal club next week. It's interesting, but I hate giving journal clubs.

#science #bioinformatics #immunology #machineLearning #deeplearning #statistics

Machine learning enables efficient and effective affinity maturation of nanobodies […]

ML for RNA secondary structure: Review of field's evolution from classical methods to DL and foundation models. Explores data evolution, the generalization crisis, struggles, and perspectives #RNA #DeepLearning bit.ly/4az24YW

Synapse: Your Connection to our MSK Authors
Meet: Sophia Meixuan Zhang
Research Focus: SKI-Pediatrics; Research Tech

Prompt-based multimodal representation learning for drug repurposing
synapse.mskcc.org/synapse/work...

#DrugRepurposing #AIinMedicine
#MultimodalAI #MachineLearning
#DeepLearning

By removing host-device round-trips for the autoregressive loop, this runs unmodified across platforms while saturating up to 64% of memory bandwidth on a single batch on Cloud TPU v6e.

#DeepLearning #OpenSource #Flax #Python

In 2012, the ImageNet competition transformed AI with deep learning, showcasing neural networks' power in image recognition and sparking a revolution in machine learning. #AIHistory #DeepLearning #ImageNet #MLBreakthrough

Machine and Deep Learning methods in population genomics and phylogeography 23-26 March 2026 To foster international participation, this course will be held online

Still time to join us! 🚀

Learn #MachineLearning & #DeepLearning in #PopulationGenomics & #Phylogeography online, 23–26 Mar. Hands-on training with #CNNs, demographic inference & selection detection.

www.physalia-courses.org/courses-work...

Registration is now open for the Cochin #QuPath training course for the manipulation of Fluo or color pyramid images, #histology or #microscopy, with the application of #deeplearning
April 14, 2026
April 17, 2026
institutcochin.fr/formation-co...

@institutcochin.bsky.social
@upcite.bsky.social

🚀 We’ve just kicked off the first edition of our course on #MachineLearning & #DeepLearning for #BioImaging analysis with @hernanmn.bsky.social !
We are gonna explore bioimage analysis, CNNs, segmentation & classification, working hands-on with real microscopy & medical imaging datasets in Python.

Image from article in Radiology: Artificial Intelligence

Hear the experts discuss current research and other important topics in #AI on the journal's #podcast series! Paul Yi & @alitejanimd.bsky.social https://rsnaradiologyai.libsyn.com/ #MachineLearning #DeepLearning #Radiomics