Paper

Machine Learning

DeepMind tackles Math and More in ML News

Here’s the latest round up of ML News: 0:00 – Intro 0:15 – Sponsor: Weights & Biases 3:10 – DeepMind tackles fundamental math 6:45 – Microsoft focuses on scaling effectively and efficiently 10:15 – NeurIPS Anthology Visualization 13:30 – Timnit Gebru launches research institute independent from big tech 16:50 – SageMaker Canvas for no-code ML […]

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AI Research

Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions

Backpropagation is the workhorse of deep learning, but unfortunately, it only works for continuous functions that are amenable to the chain rule of differentiation. Since discrete algorithms have no continuous derivative, deep networks with such algorithms as part of them cannot be effectively trained using backpropagation. This paper presents a method to incorporate a large […]

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AI Machine Learning

[ML News] Google introduces Pathways | OpenAI solves Math Problems | Meta goes First Person

Yannic provides us with a  dose of Machine Learning News. Time stamps: 0:00 – Intro 0:20 – Sponsor: Weights & Biases 2:10 – Google Introduces Pathways AI Architecture 6:30 – OpenAI trains Language Models to do High School Math 8:25 – Sam Altman says Neural Networks truly learn 9:35 – Google AI researchers frustrated with […]

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AI Natural Language Processing

[ML News] New ImageNet SOTA | Uber’s H3 hexagonal coordinate system | New text-image-pair dataset

Yannic provides the latest news in machine learning in this video. Time Stamps: 0:00 – Intro 0:20 – TruthfulQA benchmark shines new light on GPT-3 2:00 – LAION-400M image-text-pair dataset 4:10 – GoogleAI’s EfficientNetV2 and CoAtNet 6:15 – Uber’s H3: A hexagonal coordinate system 7:40 – AWS NeurIPS 2021 DeepRacer Challenge 8:15 – Helpful Libraries […]

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AI Interesting Research

PonderNet: Learning to Ponder

Humans don’t spend the same amount of mental effort on all problems equally. Instead, we respond quickly to easy tasks, and we take our time to deliberate hard tasks. DeepMind’s PonderNet attempts to achieve the same by dynamically deciding how many computation steps to allocate to any single input sample. This is done via a […]

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Apple Google Privacy

What Your Phone Sends Every 5 Minutes to Apple or Google

Apple’s push into privacy may be mostly talk as a new privacy study analyzed which data smartphones transmit to Apple and Google, even with telemetry options disabled. It turns out, iPhones and Androids not only send a number of identifiers on average every 5 minutes, some network connections even include location and nearby devices. Professor […]

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AI Research

Why AI is Harder Than We Think

Yannic Kilcher  explains how the AI community has gone through regular cycles of AI Springs, where rapid progress gave rise to massive overconfidence, high funding, and overpromise, followed by these promises being unfulfilled, subsequently diving into periods of disenfranchisement and underfunding, called AI Winters. This video he explores a paper which examines the reasons for […]

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AI Deep Learning

Deep Networks Are Kernel Machines

Yannic Kilcher explains the paper “Every Model Learned by Gradient Descent Is Approximately a Kernel Machine.” Deep Neural Networks are often said to discover useful representations of the data. However, this paper challenges this prevailing view and suggest that rather than representing the data, deep neural networks store superpositions of the training data in their […]

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AI Research

SingularityNET – A Decentralized, Open Market and Network for AIs

Yannic Kilcher explains this white paper on SingularityNET. Big Tech is currently dominating the pursuit of ever more capable AI. This happens behind closed doors and results in a monopoly of power. SingularityNET is an open, decentralized network where anyone can offer and consume AI services, and where AI agents can interlink with each other […]

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