Leon FurzeFeb 10, 2023

A Brief History of Artificial Intelligence

Like any complex technology, Artificial Intelligence has its roots in a number of fields. From philosophy to computer science, mathematics to linguistics, tracing the history of AI and automation is a difficult business. The field was officially named in the 1950s, but ideas about automated machines have existed since long before then. This is a history of the development of Artificial Intelligence from some of its earliest philosophical and theoretical inceptions through to modern day […]

https://leonfurze.com/2023/02/11/a-brief-history-of-artificial-intelligence/

N-gated Hacker NewsMar 12
🚨 Breaking News: A new way to procrastinate and pretend to learn emerges! CNN Explainer promises to teach you convolutional neural networks in your browser—because reading real papers was too mainstream, and who needs depth when you have GIFs? 🤓💻📉
https://poloclub.github.io/cnn-explainer/ #BreakingNews #Procrastination #Learning #ConvolutionalNeuralNetworks #GIFs #HackerNews #ngated
CNN Explainer

An interactive visualization system designed to help non-experts learn about Convolutional Neural Networks (CNNs).

Hacker NewsMar 12

CNN Explainer – Learn Convolutional Neural Network in Your Browser (2020)

https://poloclub.github.io/cnn-explainer/

#HackerNews #CNN #Explainer #ConvolutionalNeuralNetworks #MachineLearning #BrowserBased #Education #2020

CNN Explainer

An interactive visualization system designed to help non-experts learn about Convolutional Neural Networks (CNNs).

Hacker NewsMar 3

Talos: Hardware accelerator for deep convolutional neural networks

https://talos.wtf/

#HackerNews #Talos #Hardware #Accelerator #Deep #Learning #ConvolutionalNeuralNetworks

Talos

Documentation for Talos, a high-performance hardware accelerator for convolutional neural networks

Ars Technica NewsNov 12
Meta’s star AI scientist Yann LeCun plans to leave for own startup https://arstechni.ca/pufk #convolutionalneuralnetworks #FundamentalAIResearch #largelanguagemodels #AIdevelopmenttools #NewYorkUniversity #AIinfrastructure #machinelearning #MarkZuckerberg #AlexandrWang #deeplearning #AIalignment #Turingaward #worldmodels #AIresearch #AIstrategy #Anthropic #YannLeCun #startups #ScaleAI #Biz&IT #google #openai #FAIR #meta #AI
Meta’s star AI scientist Yann LeCun plans to leave for own startup

AI pioneer reportedly frustrated with Meta’s shift from research to rapid product releases.

Ars Technica
ErUM-Data-HubOct 10

🕵‍♂️ Are you curious to dive into the concepts of #DeepLearning ? On the "PhysikDenken" YouTube channel, you’ll find concise and accessible lectures that provide a smooth introduction to the key concepts of Deep Learning (based on the book "Deep Learning for Physics Research" by Martin Erdmann, Jonas Glombitza, Gregor Kasieczka and Uwe Klemradt.

👉 Check out the videos here: youtube.com/@PhysikDenken

#neuralnetworks #neuralnetworkbuildingblocks #convolutionalneuralnetworks #ObjectiveFunctions

HackerNoonSep 9, 2025
Log-quant cuts model memory 4× with minimal accuracy loss; compute fits mobile SoCs, enabling real-time, wearable lung-sound screening. https://hackernoon.com/patient-specific-cnn-rnn-for-lung-sound-detection-with-4-smaller-memory #convolutionalneuralnetworks
Patient-Specific CNN-RNN for Lung-Sound Detection With 4× Smaller Memory | HackerNoon

Log-quant cuts model memory 4× with minimal accuracy loss; compute fits mobile SoCs, enabling real-time, wearable lung-sound screening.

HackerNoonSep 9, 2025
Mel-spectrograms feed a CNN-RNN; last layers retrain on tiny patient sets, then log-quant weights trim memory 4× for wearables. https://hackernoon.com/dataset-features-model-and-quantization-strategy-for-respiratory-sound-classification #convolutionalneuralnetworks
Dataset, Features, Model, and Quantization Strategy for Respiratory Sound Classification | HackerNoon

Mel-spectrograms feed a CNN-RNN; last layers retrain on tiny patient sets, then log-quant weights trim memory 4× for wearables.

HackerNoonSep 9, 2025
Hybrid spectrogram CNN-RNN outperforms VGG/MobileNet and shows that transfer learning solves data scarcity in respiratory AI. https://hackernoon.com/patient-specific-cnn-rnn-for-wheeze-and-crackle-detection-with-4-memory-savings #convolutionalneuralnetworks
Patient-Specific CNN-RNN for Wheeze and Crackle Detection with 4× Memory Savings | HackerNoon

Hybrid spectrogram CNN-RNN outperforms VGG/MobileNet and shows that transfer learning solves data scarcity in respiratory AI.

HackerNoonAug 13, 2025
This article’s results show Faster R-CNN with ResNet backbones beats YOLOv5 for road damage detection, with noted gains and failure case insights. https://hackernoon.com/lessons-from-testing-ai-models-on-global-damage-data #convolutionalneuralnetworks
Lessons from Testing AI Models on Global Damage Data | HackerNoon

This article’s results show Faster R-CNN with ResNet backbones beats YOLOv5 for road damage detection, with noted gains and failure case insights.