AI Weekly

JULY 27, 2023

techcrunch.com The Essential Artificial Intelligence Glossary for Marketers (90+ Terms) BERT - Bidirectional Encoder Representations from Transformers (BERT) is Google’s deep learning model designed explicitly for natural language processing tasks like answering questions, analyzing sentiment, and translation.

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Analytics Vidhya

APRIL 16, 2024

Introduction Welcome into the world of Transformers, the deep learning model that has transformed Natural Language Processing (NLP) since its debut in 2017. These linguistic marvels, armed with self-attention mechanisms, revolutionize how machines understand language, from translating texts to analyzing sentiments.

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Towards AI

OCTOBER 19, 2024

Photo by Amr Taha™ on Unsplash In the realm of artificial intelligence, the emergence of transformer models has revolutionized natural language processing (NLP). In this guide, we will explore how to fine-tune BERT, a model with 110 million parameters, specifically for the task of phishing URL detection.

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AWS Machine Learning Blog

APRIL 4, 2025

They use real-time data and machine learning (ML) to offer customized loans that fuel sustainable growth and solve the challenges of accessing capital. This approach combines the efficiency of machine learning with human judgment in the following way: The ML model processes and classifies transactions rapidly.

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Unite.AI

OCTOBER 11, 2023

This is particularly useful for applications like machine learning , where data points (such as images or text) can be represented as vectors in multi-dimensional spaces. Scalable for Large Datasets : As AI and machine learning applications continue to grow, so does the amount of data they process.

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Marek Rei

NOVEMBER 4, 2024

I have written short summaries of 68 different research papers published in the areas of Machine Learning and Natural Language Processing. link] Investigating how much pre-trained language models capture syntactic information and how well are they able to detect syntactic errors out-of-the-box.

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Analytics Vidhya

NOVEMBER 16, 2022

Source: totaljobs.com Introduction Transformers have become a powerful tool for different natural language processing tasks. This article was published as a part of the Data Science Blogathon. The impressive performance of the transformer is mainly attributed to its self-attention mechanism.

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Marktechpost

JANUARY 10, 2024

BERT is a language model which was released by Google in 2018. However, in the past half a decade, many significant advancements have been made with other types of architectures and training configurations that have yet to be incorporated into BERT. BERT-Base reached an average GLUE score of 83.2% hours compared to 23.35

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BERT Large Language Models Natural Language Processing NLP 126

Towards AI

JUNE 12, 2024

Both BERT and GPT are based on the Transformer architecture. Word embedding is a technique in natural language processing (NLP) where words are represented as vectors in a continuous vector space. It was the Attention Mechanism breakthrough that gave birth to Large Pre-Trained Models and Transformers.

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AWS Machine Learning Blog

JANUARY 19, 2024

In this post, we demonstrate how to use neural architecture search (NAS) based structural pruning to compress a fine-tuned BERT model to improve model performance and reduce inference times. First, we use an Amazon SageMaker Studio notebook to fine-tune a pre-trained BERT model on a target task using a domain-specific dataset.

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Marktechpost

FEBRUARY 25, 2024

In our ever-evolving world, the significance of sequential decision-making (SDM) in machine learning cannot be overstated. Much like how foundation models in language, such as BERT and GPT, have transformed natural language processing by leveraging vast textual data, pretrained foundation models hold similar promise for SDM.

Machine Learning 126

Machine Learning Natural Language Processing Robotics BERT 126

Unite.AI

JULY 11, 2023

Introduction To Generative AI Image Source Course difficulty: Beginner-level Completion time: ~ 45 minutes Prerequisites: No What will AI enthusiasts learn? What is Generative Artificial Intelligence, how it works, what its applications are, and how it differs from standard machine learning (ML) techniques.

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AWS Machine Learning Blog

MAY 15, 2024

ONNX is an open source machine learning (ML) framework that provides interoperability across a wide range of frameworks, operating systems, and hardware platforms. You can see that for the BERT, RoBERTa, and GPT2 models, the throughput improvement is up to 65%. for the same fp32 model inference. for the same model inference.

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Flipboard

JUNE 20, 2023

Machine learning (ML) engineers have traditionally focused on striking a balance between model training and deployment cost vs. performance. Training experiment: Training BERT Large from scratch Training, as opposed to inference, is a finite process that is repeated much less frequently.

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Marktechpost

MARCH 27, 2024

However, sifting through thousands of text-based reviews across multiple platforms and languages can be overwhelming and time-consuming, often leaving valuable insights buried beneath the sheer volume of data. Traditional methods for feedback analysis have relied heavily on machine learning models and natural language processing techniques.

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Marktechpost

MAY 30, 2024

Google plays a crucial role in advancing AI by developing cutting-edge technologies and tools like TensorFlow, Vertex AI, and BERT. It helps data scientists, AI developers, and ML engineers enhance their skills through engaging learning experiences and practical exercises.

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Pickl AI

APRIL 6, 2025

Neural Networks are foundational structures, while Deep Learning involves complex, layered networks like CNNs and RNNs, enabling advanced AI capabilities such as image recognition and natural language processing. Introduction Deep Learning and Neural Networks are like a sports team and its star player.

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Marktechpost

APRIL 21, 2024

Introduction to Generative AI: This course provides an introductory overview of Generative AI, explaining what it is and how it differs from traditional machine learning methods. Participants will learn about the applications of Generative AI and explore tools developed by Google to create their own AI-driven applications.

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Marktechpost

MARCH 27, 2024

These adapters allow BERT to be fine-tuned for specific downstream tasks while retaining most of its pre-trained parameters. These adapters allow BERT to be fine-tuned for specific downstream tasks while retaining most of its pre-trained parameters. Join our Telegram Channel , Discord Channel , and LinkedIn Gr oup.

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Unite.AI

AUGUST 2, 2023

Machine learning models have heavily relied on labeled data for training, and traditionally speaking, training models on labeled data yields accurate results. To tackle the annotation issue, developers came up with the concept of SSL or Self Supervised Learning. They require a high amount of computational power.

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Marktechpost

JUNE 4, 2024

Keras is a widely used machine learning tool known for its high-level abstractions and ease of use, enabling rapid experimentation. Table 1 compares the average time per training or inference step for models like SAM, Gemma, BERT, and Mistral across different versions and frameworks of Keras.

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IBM Journey to AI blog

AUGUST 1, 2023

It’s the underlying engine that gives generative models the enhanced reasoning and deep learning capabilities that traditional machine learning models lack. A foundation model is built on a neural network model architecture to process information much like the human brain does.

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Mlearning.ai

JUNE 7, 2023

In 2018 when BERT was introduced by Google, I cannot emphasize how much it changed the game within the NLP community. This ability to understand long-range dependencies helps transformers better understand the context of words and achieve superior performance in natural language processing tasks.

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ODSC - Open Data Science

JUNE 9, 2023

Once a set of word vectors has been learned, they can be used in various natural language processing (NLP) tasks such as text classification, language translation, and question answering. This allows BERT to learn a deeper sense of the context in which words appear.

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IBM Journey to AI blog

MARCH 27, 2024

In recent years, remarkable strides have been achieved in crafting extensive foundation language models for natural language processing (NLP). These innovations have showcased strong performance in comparison to conventional machine learning (ML) models, particularly in scenarios where labelled data is in short supply.

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Probably Approximately a Scientific Blog

JANUARY 12, 2021

Figure 1: adversarial examples in computer vision (left) and natural language processing tasks (right). Machine learning models today perform reasonably well on perception tasks (image and speech recognition). So knowledge in language models is not the most accurate and reliable. Using the AllenNLP demo.

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Unite.AI

APRIL 15, 2024

When it comes to natural language processing (NLP) and information retrieval, the ability to efficiently and accurately retrieve relevant information is paramount. ColBERT: Efficient and Effective Late Interaction One of the standout models in the realm of reranking is ColBERT ( Contextualized Late Interaction over BERT ).

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Marktechpost

MAY 5, 2024

However, the computational complexity associated with these mechanisms scales quadratically with sequence length, which becomes a significant bottleneck when managing long-context tasks such as genomics and natural language processing. Compared to the BERT-base, the Orchid-BERT-base has 30% fewer parameters yet achieves a 1.0-point

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Marktechpost

NOVEMBER 10, 2024

Through the use of these libraries, data scientists can easily create precise sentiment models using pre-trained models and sophisticated machine learning frameworks. spaCy A well-known open-source natural language processing package, spaCy is praised for its robustness and speed while processing massive amounts of text.

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AssemblyAI

MAY 3, 2023

We are going to explore these and other essential questions from the ground up , without assuming prior technical knowledge in AI and machine learning. The core process is a general technique known as self-supervised learning , a learning paradigm that leverages the inherent structure of the data itself to generate labels for training.

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ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. BERT even accounts for the context of words, allowing for more accurate results related to respective queries and tasks.

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NVIDIA Developer

JUNE 2, 2021

Applications for natural language processing (NLP) have exploded in the past decade. With the proliferation of AI assistants and organizations infusing their businesses with more interactive human-machine experiences, understanding how NLP techniques can be used to manipulate, analyze, and generate text-based data is essential.

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Pickl AI

AUGUST 14, 2024

Summary: Neural networks are a key technique in Machine Learning, inspired by the human brain. They consist of interconnected nodes that learn complex patterns in data. Reinforcement Learning: An agent learns to make decisions by receiving rewards or penalties based on its actions within an environment.

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Neural Network Machine Learning Convolutional Neural Networks Natural Language Processing 52

Marktechpost

NOVEMBER 10, 2023

NLP, or Natural Language Processing, is a field of AI focusing on human-computer interaction using language. NLP aims to make computers understand, interpret, and generate human language. Recent NLP research has focused on improving few-shot learning (FSL) methods in response to data insufficiency challenges.

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Marktechpost

JANUARY 26, 2024

Understanding proteins is crucial for human biology and health, requiring advanced machine-learning models for protein representation. Self-supervised pre-training, inspired by natural language processing, has significantly improved protein sequence representation.

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Marktechpost

AUGUST 19, 2024

This study by researchers from Communication Science, Vrije Universiteit Amsterdam and Department of Politics, IR and Philosophy, Royal Holloway University of London addresses the critical issue of measurement validity in supervised machine learning for social science tasks , particularly focusing on how biases in fine-tuning data impact validity.

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Flipboard

JULY 4, 2023

Famous LLMs like GPT, BERT, PaLM, and LLaMa are revolutionizing the AI industry by imitating humans. The well-known chatbot called ChatGPT, based on GPT architecture and developed by OpenAI, imitates humans by generating accurate and creative content, answering questions, summarizing massive textual paragraphs, and language translation.

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