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A New Link to an Old Model Could Crack the Mystery of Deep Learning | Quanta Magazine
To help them explain the shocking success of deep neural networks, researchers are turning to older but better-understood models of machine learning.
The Consequences of Violating Linear Regression Assumptions | by Hajime Alabanza | Towards Data Science
Recently, a friend learning linear regression asked me what happens when assumptions like multicollinearity are violated. Despite being a former statistics student, I could only give him general…
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How I Got a Job at Google DeepMind (No ML Degree) | Medium
I recently landed a job at DeepMind as a Research Engineer! It’s a dream come true for me, I still can’t believe it! 😍
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The Turbulent Past and Uncertain Future of Artificial Intelligence
Is there a way out of AI's boom-and-bust cycle?
Hey Siri, what happened?
Ten years ago, Apple launched its digital assistant Siri with the iPhone 4s. As the first major voice interface for consumers, it was a huge hit. But over the years, Siri has fallen behind rivals like Google Assistant and Amazon’s Alexa. After Apple’s head start, what went wrong?
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For Tesla, Facebook and Others, AI’s Flaws Are Getting Harder to Ignore
Investors are pouring money into artificial intelligence, despite clear setbacks in self-driving cars, social media and even healthcare.
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How to Train Really Large Models on Many GPUs?
How to train large and deep neural networks is challenging, as it demands a large amount of GPU memory and a long horizon of training time. This post reviews...
Video Face Recognition Demo of ArcFace
ArcFace: Additive Angular Margin Loss for Deep Face Recognition. Jiankang Deng*, Jia Guo*, Niannan Xue, Stefanos Zafeiriouhttps://arxiv.org/abs/1801.07698(1)...
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The First Rule of Machine Learning: Start without Machine Learning
Why this is the first rule, some baseline heuristics, and when to move on to machine learning.
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The Journey to Define Dimension | Quanta Magazine
The concept of dimension seems simple enough, but mathematicians struggled for centuries to precisely define and understand it.
GPT-4 Will Have 100 Trillion Parameters — 500x the Size of GPT-3 | by Alberto Romero | Sep, 2021 | Towards Data Science
OpenAI will release GPT-4 in the next few years. It will have around 100 trillion parameters.