Artificial Corner

JULY 30, 2023

In this world of complex terminologies, someone who wants to explain Large Language Models (LLMs) to some non-tech guy is a difficult task. So that’s why I tried in this article to explain LLM in simple or to say general language. Natural Language Processing (NLP) is a subfield of artificial intelligence.

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Marktechpost

JULY 4, 2023

Natural language processing (NLP) activities, including speech-to-text, sentiment analysis, text summarization, spell-checking, token categorization, etc., rely on Language Models as their foundation. Unigrams, N-grams, exponential, and neural networks are valid forms for the Language Model.

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Topbots

JUNE 22, 2023

SA is a very widespread Natural Language Processing (NLP). So, to make a viable comparison, I had to: Categorize the dataset scores into Positive , Neutral , or Negative labels. Interestingly, ChatGPT tended to categorize most of these neutral sentences as positive. finance, entertainment, psychology).

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Heartbeat

OCTOBER 11, 2023

Supervised, unsupervised, and reinforcement learning : Machine learning can be categorized into different types based on the learning approach. Interpretability and Explainability: Deep neural networks are one machine learning model that can be very complex and difficult to assess.

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Heartbeat

FEBRUARY 2, 2024

Visual Question Answering (VQA) stands at the intersection of computer vision and natural language processing, posing a unique and complex challenge for artificial intelligence. is a significant benchmark dataset in computer vision and natural language processing. or Visual Question Answering version 2.0,

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Heartbeat

AUGUST 23, 2023

But what if there was a technique to quickly and accurately solve this language puzzle? Enter Natural Language Processing (NLP) and its transformational power. But what if there was a way to unravel this language puzzle swiftly and accurately? However, in this sea of complexity, NLP offers a ray of hope.

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Towards AI

FEBRUARY 20, 2024

If you want an overview of the Machine Learning Process, it can be categorized into 3 wide buckets: Collection of Data: Collection of Relevant data is key for building a Machine learning model. Natural language processing: Helps computers understand and generate human language, powering chatbots, and machine translation.

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IBM Journey to AI blog

OCTOBER 16, 2023

Voice-based queries use Natural Language Processing (NLP) and sentiment analysis for speech recognition. For instance, email management automation tools such as Levity use ML to identify and categorize emails as they come in using text classification algorithms. The platform has three powerful components: the watsonx.ai

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Unite.AI

NOVEMBER 8, 2023

Natural Language Processing (NLP) has experienced some of the most impactful breakthroughs in recent years, primarily due to the the transformer architecture. GPT : Is generative in nature and can be prompted to perform tasks with minimal changes to its structure. One-hot encoding is a prime example of this limitation.

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AWS Machine Learning Blog

JANUARY 17, 2023

In this solution, we train and deploy a churn prediction model that uses a state-of-the-art natural language processing (NLP) model to find useful signals in text. In addition to textual inputs, this model uses traditional structured data inputs such as numerical and categorical fields.

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Heartbeat

JULY 11, 2023

Photo by Oleg Laptev on Unsplash By improving many areas of content generation, optimization, and analysis, natural language processing (NLP) plays a crucial role in content marketing. Artificial intelligence (AI) has a subject called natural language processing (NLP) that focuses on how computers and human language interact.

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Heartbeat

AUGUST 21, 2023

AlexNet was created to categorize photos in the ImageNet dataset, which contains approximately 1 million images divided into 1,000 categories. Natural Language Processing : CNNs have been implemented for sentiment analysis and text categorization in natural language processing jobs.

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IBM Journey to AI blog

FEBRUARY 23, 2024

Beyond the simplistic chat bubble of conversational AI lies a complex blend of technologies, with natural language processing (NLP) taking center stage. Also, conversational AI systems can manage and categorize support tickets, prioritizing them based on urgency and relevance.

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Viso.ai

APRIL 17, 2024

Age, No of products, and categorical features (Gender, Country, etc). Better Model Explainability: Simplifying the feature space and focusing on relevant patterns improve the overall explainability (or interpretability) of the model. The type of features and extraction techniques also vary depending on the input data type.

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Snorkel AI

AUGUST 24, 2023

AI is accelerating complaint resolution for banks AI can help banks automate many of the tasks involved in complaint handling, such as: Identifying, categorizing, and prioritizing complaints. Natural language processing to extract key information quickly. Model explainability. Assigning complaints to staff.

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Snorkel AI

AUGUST 24, 2023

AI is accelerating complaint resolution for banks AI can help banks automate many of the tasks involved in complaint handling, such as: Identifying, categorizing, and prioritizing complaints. Natural language processing to extract key information quickly. Model explainability. Assigning complaints to staff.

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Snorkel AI

AUGUST 24, 2023

AI is accelerating complaint resolution for banks AI can help banks automate many of the tasks involved in complaint handling, such as: Identifying, categorizing, and prioritizing complaints. Natural language processing to extract key information quickly. Model explainability. Assigning complaints to staff.

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IBM Journey to AI blog

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Achieving these feats is accomplished through a combination of sophisticated algorithms, natural language processing (NLP) and computer science principles.

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Heartbeat

MAY 16, 2023

Sentiment analysis is a common natural language processing (NLP) task that involves determining the sentiment of a given piece of text, such as a tweet, product review, or customer feedback. We’re committed to supporting and inspiring developers and engineers from all walks of life.

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Becoming Human

MAY 12, 2023

In order to develop training data for AI and machine learning, there are several types of image annotation as explained below: Bounding Box Annotation As a type of image annotation technique, bounding box annotation is used to outline the boundaries of objects. In this process, a box is drawn around the object and a label is applied.

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Towards AI

FEBRUARY 13, 2023

Let me explain. Zero-Shot Classification Imagine you want to categorize unlabeled text. Transformers is a library in Hugging Face that provides APIs and tools. It allows you to easily download and train state-of-the-art pre-trained models. You may ask what pre-trained models are. Let’s have a look at a few of these.

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Marktechpost

JULY 16, 2023

Their RAIC (Rapid Automatic Image Categorization) technology does not require time-consuming human labeling to build the models. From AI training to explainability, bias mitigation, and governance to realistic test data with subsetting, referential integrity, and conditioned test data generation, Mostly AI does it all.

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Heartbeat

FEBRUARY 15, 2023

Source: [link] Text classification is an interesting application of natural language processing. As a machine learning engineer, you start with a labeled data set that has vast amounts of text that have already been categorized. These algorithms can perform sentiment analysis, create spam filters, and other applications.

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Heartbeat

FEBRUARY 21, 2024

Deep learning uses deep (multilayer) neural networks to process large amounts of data and learn highly abstract patterns. This technology has achieved great success in many application areas, especially in image recognition, natural language processing, autonomous vehicles, voice recognition, and many more.

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Heartbeat

JUNE 28, 2023

Types of Knowledge Distillation It is broadly categorized into two main categories:- Soft target distillation: In this type of knowledge distillation, the teacher model generates soft targets in the form of probability distributions for each input example, which are then used to train the student model.

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AWS Machine Learning Blog

FEBRUARY 12, 2024

Essential ML capabilities such as hyperparameter tuning and model explainability were lacking on premises. In both cases, the evaluation and explainability report, if generated, are recorded in the model registry. Explain – SageMaker Clarify generates an explainability report. AWS_ACCOUNT] region = eu-central-1.

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AWS Machine Learning Blog

MARCH 13, 2024

The LLM analysis provides a violation result (Y or N) and explains the rationale behind the model’s decision regarding policy violation. The Anthropic Claude V2 model delivers responses in the instructed format (Y or N), along with an analysis explaining why it thinks the message violates the policy.

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Heartbeat

AUGUST 29, 2023

While integrating deep learning into software development can be difficult, it has made significant progress in several fields, including computer vision, natural language processing, and speech recognition. Speech and Audio Processing : Speaker identification, speech recognition, creation of music, etc.

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Viso.ai

MARCH 26, 2024

This enhances the interpretability of AI systems for applications in computer vision and natural language processing (NLP). Furthermore, attention mechanisms work to enhance the explainability or interpretability of AI models. In a way, you can consider it offering a window into the “thought processes” of AI.

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Heartbeat

JUNE 22, 2023

Yet not all chatbots are made equal, and some are more adept than others in deciphering and answering natural language questions. Natural language processing (NLP) can help with this. Recognition of named entities , such as individuals, locations, and organizations, involves identifying and categorizing them.

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The MLOps Blog

FEBRUARY 22, 2024

Methods for continual learning can be categorized as regularization-based, architectural, and memory-based, each with specific advantages and drawbacks. It is designed for PyTorch and can be used in various domains like Computer Vision and Natural Language Processing. Renate is a library designed by the AWS Labs.

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IBM Journey to AI blog

AUGUST 1, 2023

A foundation model is built on a neural network model architecture to process information much like the human brain does. They can also perform self-supervised learning to generalize and apply their knowledge to new tasks. The platform comprises three powerful products: The watsonx.ai

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Marktechpost

OCTOBER 18, 2023

Surprisingly, recent developments in self-supervised learning, foundation models for computer vision and natural language processing, and deep understanding have significantly increased data efficiency. However, most training datasets in the present literature on treatments have small sample sizes.

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John Snow Labs

APRIL 30, 2024

Named Entity Recognition (NER) is a pivotal tool in understanding documents because it identifies and categorizes specific entities mentioned within the text. It streamlines tasks such as information retrieval, summarization, and knowledge extraction, enhancing the efficiency of various natural language processing applications.

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Pickl AI

JULY 17, 2023

Unsupervised learning helps in finding the features which are useful for categorization It takes place in real-time, which implies that all the input data is essential to be analyzed and labeled in the presence of the users. It employs unsupervised learning to categorize articles on the same news story from different online news outlets.

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Heartbeat

MARCH 8, 2023

Source: Author Introduction Text classification, which involves categorizing text into specified groups based on its content, is an important natural language processing (NLP) task. This article will look at how R can be used to execute text categorization tasks efficiently. Curious to see how Comet works?

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Snorkel AI

MAY 25, 2023

A brief history of large language models Large language models grew out of research and experiments with neural networks to allow computers to process natural language. Text editing Large language models can edit text or suggest improvements or corrections to an existing piece of writing.

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