Flipboard

FEBRUARY 28, 2023

The majority of companies developing the application-layer AI that’s driving the widespread adoption of the technology still rely on supervised learning, using large swaths of labeled training data. Then, it tries to make predictions on the rest of the unlabeled data based on what it has learned.

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Explosion

MAY 17, 2023

In 2014 I started working on spaCy , and here’s an excerpt of how I explained the motivation for the library: Computers don’t understand text. Supervised learning is very strong for tasks such as text classification, entity recognition and relation extraction. That’s not a path to improvement. You need to be systematic.

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Becoming Human

MARCH 16, 2023

Overhyped or not, investments in AI drug discovery jumped from $450 million in 2014 to a whopping $58 billion in 2021. Since the advent of deep learning in the 2000s, AI applications in healthcare have expanded. ML solutions encompass a diverse array of branches, each with its own unique characteristics and methodologies.

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Google Research AI blog

JANUARY 18, 2023

Language Models Computer Vision Multimodal Models Generative Models Responsible AI* Algorithms ML & Computer Systems Robotics Health General Science & Quantum Community Engagement * Other articles in the series will be linked as they are released. language models, image classification models, or speech recognition models).

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Mlearning.ai

JULY 31, 2023

2014; Bojanowski et al., Data2Vec: A General Framework For Self-Supervised Learning in Speech, Vision and Language. Instead, why not use a set of embeddings that are already trained? Sometimes, this can be easier and much faster. Patch Embeddings What about images and audio files? References Baevski, A., and Auli, M.,

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Deep Learning Deep Learning Supervised Learning Algorithm 52

AssemblyAI

SEPTEMBER 12, 2023

Though once the industry standard, accuracy of these classical models had plateaued in recent years, opening the door for new approaches powered by advanced Deep Learning technology that’s also been behind the progress in other fields such as self-driving cars. hours of audio data.

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