Why Developers Should Care About Generative AI (Even They Aren’t AI Expert) https://hackread.com/why-developers-care-about-generative-ai-experts/ #ArtificialIntelligence #MachineLearning #GenerativeAI #Technology #ChatGPT #Claude #OpenAI #GenAI #AI
My #Introduction.
A #programmer by day and a programmer by night.
I probably spend more time on my computer than doing anything else.
I have interests in #machinelearning and #quantumcomputing.
I also enjoy #ttrpg, #manga, #electronics and just #reading.
My weekly newsletter is out - Airflow 3.0 review, Think Stats book, and new tutorials 
https://ramikrispin.substack.com/p/review-of-airflow-30-think-stats
Digital Squid’s Behavior Shaped by Neural Network https://hackaday.com/2025/04/26/digital-squids-behavior-shaped-by-neural-network/ #MachineLearning #machinelearning #neuralnetwork #digitalpet #hebbian
Digital Squid’s Behavior Shaped by Neural Network - In the 90s, a video game craze took over the youth of the world — but unlike today... - https://hackaday.com/2025/04/26/digital-squids-behavior-shaped-by-neural-network/ #machinelearning #neuralnetwork #digitalpet #hebbian
Weekly Update from the Open Journal of Astrophysics – 26/04/2025
It’s Satuday morning once again, and time for another update of papers published at the Open Journal of Astrophysics. Since the last update we have published two papers, which brings the number in Volume 8 (2025) up to 44 and the total so far published by OJAp up to 279.
The first paper to report is “Approximating non-Gaussian Bayesian partitions with normalising flows: statistics, inference and application to cosmology” by Tobias Röspel, Adrian Schlosser & Björn Malte Schäfer (Universität Heidelberg, Germany) which was published on April 23rd 2025 in the folder Cosmology and NonGalactic Astrophysics. It is an introduction to normalizing flows – a machine learning technique for transforming distributions – and its application to the extraction of cosmological parameters from supernova data.
The overlay is here:
You can find the officially accepted version on arXiv here.
The other paper this week is “Dwarf Galaxies in the TNG50 Field: connecting their Star-formation Rates with their Environments” by Joy Bhattacharyya & Annika H.G. Peter (Ohio State University, USA) and Alexie Leauthaud (UC Santa Cruz, USA). This one was published on 24th April 2025 in the older Astrophysics of Galaxies and it studies dwarf galaxies with properties similar to the Large and Small Magellanic Clouds that form in different environments in the TNG50 simulation of the IllustrisTNG project.
The overlay is here:
and you can find the final accepted version on arXiv here.
That’s all for this week. I’ll have another update next Saturday.
Why Developers Should Care About Generative AI (Even They Aren’t AI Expert) – Source:hackread.com https://ciso2ciso.com/why-developers-should-care-about-generative-ai-even-they-arent-ai-expert-sourcehackread-com/ #1CyberSecurityNewsPost #artificialintelligence #CyberSecurityNews #MachineLearning #generativeAI #Technology #Hackread #Chatgpt #Claude #OpenAI #GenAI #AI
https://www.europesays.com/uk/50788/ AI Uncovers New Cause of Alzheimer’s #AI #Alzheimer'sDisease #ArtificialIntelligence #BrainResearch #DeepLearning #Genetics #Health #MachineLearning #neurobiology #Neurology #Neuroscience #UCSD #UK #UnitedKingdom
App Store: Apple provides insight into how AI summaries are created
iOS 18.4 introduced AI summaries of user reviews in the App Store. The complex creation process is now explained in a blog post.
App Store: Apple gewährt Einblick, wie KI-Zusammenfassungen entstehen
Mit iOS 18.4 führte KI-Zusammenfassungen von Nutzerrezensionen im App Store ein. In einem Blogpost wird jetzt die komplexe Erstellung erläutert.
A Predictive Model For Household Displacement Duration After Disasters
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https://doi.org/10.1111/risa.17710 <-- shared paper
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https://nicolepaul.eu.pythonanywhere.com/ <-- interactive web interface
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#GIS #spatial #mapping #HouseholdPulseSurvey #risk #hazard #damage #loss #spatialanalysis #model #modeling #disaster #naturaldisaster #storm #hurricane #flood #fire #cost #economics #community #publicsafety #effects #predictivemodel #AI #machinelearning #riskanalysis #classifactiontree #socioeconomics #casestudy #mitigation #preparedness #displacement #population
I was revisiting the slides of a talk I gave a while back about graph neural networks and the material and references still hold up, so I've posted them on my personal web site:
LLMs Coming for a DNA Sequence Near You https://hackaday.com/2025/04/24/llms-coming-for-a-dna-sequence-near-you/ #ArtificialIntelligence #artificialintellegence #syntheticbiology #machinelearning #biohacking #biology #CRISPR #LLM
https://www.europesays.com/uk/47816/ AI Still Falls Short in Understanding Human Social Interactions #AI #ArtificialIntelligence #BrainResearch #DeepLearning #JHU #MachineLearning #neurobiology #Neuroscience #Psychology #SocialInteractions #Technology #UK #UnitedKingdom
Recently I had a very odd experience. I decided to write about it.
I'm more interested in this essay circulating than anything else I've ever written.
"Why I AI-Pilled Myself:"
Petition to stop calling simple old-school machine learning models "AI".
No, a good ol' #perceptron is not suddenly an 'AI application'.
In #machinelearning, ground-truth is a term of #art
Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle https://arxiv.org/abs/2303.14151
... We provide visual intuition using polynomial regression, then mathematically analyze double descent with ordinary linear regression and identify three interpretable factors that, when simultaneously all present, together create double descent.
Double descent will not occur if any of the three factors are absent.
1. Small-but-nonzero singular values do not appear in the training data features.
2. The test datum does not vary in different directions than the training features (same subspace)
3. The best possible model in the model class makes no errors on the training data.
Intuition extends to nonlinear models
Greg Cocks 
