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Generative vs Discriminative AI: Understanding the 5 Key Differences

Data Science Dojo

A visual representation of discriminative AI – Source: Analytics Vidhya Discriminative modeling, often linked with supervised learning, works on categorizing existing data. Generative AI often operates in unsupervised or semi-supervised learning settings, generating new data points based on patterns learned from existing data.

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ChatGPT's Hallucinations Could Keep It from Succeeding

Flipboard

Yes, large language models (LLMs) hallucinate , a concept popularized by Google AI researchers in 2018. Hallucinations May Be Inherent to Large Language Models But Yann LeCun , a pioneer in deep learning and the self-supervised learning used in large language models, believes there is a more fundamental flaw that leads to hallucinations.

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Modern NLP: A Detailed Overview. Part 2: GPTs

Towards AI

Year and work published Generative Pre-trained Transformer (GPT) In 2018, OpenAI introduced GPT, which has shown, with the implementation of pre-training, transfer learning, and proper fine-tuning, transformers can achieve state-of-the-art performance. But, the question is, how did all these concepts come together?

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Are AI technologies ready for the real world?

Dataconomy

AI practitioners choose an appropriate machine learning model or algorithm that aligns with the problem at hand. Common choices include neural networks (used in deep learning), decision trees, support vector machines, and more. The next critical step is model selection.

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RLHF vs RLAIF for language model alignment

AssemblyAI

After processing an audio signal, an ASR system can use a language model to rank the probabilities of phonetically-equivalent phrases Starting in 2018, a new paradigm began to emerge. Using such data to train a model is called “supervised learning” On the other hand, pretraining requires no such human-labeled data.

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Improving ML Datasets with Cleanlab, a Standard Framework for Data-Centric AI

ODSC - Open Data Science

Previously, he was a senior scientist at Amazon Web Services developing AutoML and Deep Learning algorithms that now power ML applications at hundreds of companies. About the author/ODSC East 2023 speaker: Jonas Mueller is Chief Scientist and Co-Founder at Cleanlab, a company providing data-centric AI software to improve ML datasets.

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How foundation models and data stores unlock the business potential of generative AI

IBM Journey to AI blog

It’s the underlying engine that gives generative models the enhanced reasoning and deep learning capabilities that traditional machine learning models lack. They can also perform self-supervised learning to generalize and apply their knowledge to new tasks. An open-source model, Google created BERT in 2018.

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