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. NLP translates the user’s words into machine actions, enabling machines to understand and respond to customer inquiries accurately.

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Conversational AI Chatbots NLP AI 263

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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ESG Categorization Large Language Models NLP 203

Ehud Reiter

APRIL 8, 2024

I have written a lot of papers and blogs about aspects of evaluation. In this blog I want to try to pull out a few high-level messages and “tips” for good evaluation, based on mistakes I have seen people make. This is basically a “summary” blog which refers to many of my more detailed blogs on evaluation.

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NLP BERT Machine Learning 136

Great Learning

SEPTEMBER 6, 2023

Natural Language Processing helps machines understand and analyze natural languages. NLP is an automated process that helps extract the required information from data by applying machine learning algorithms.

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NLP Natural Language Processing Data Scientist Machine Learning 98

IBM Journey to AI blog

OCTOBER 4, 2023

IBM and Intel have a long history of collaboration on data and AI products, including AI acceleration with IBM Watson NLP Library for Embed with OneAPI, the optimization of IBM Db2 on Intel Xeon platforms, and now, watsonx.data. The post Common Grounds: Unleashing innovation and growth through partnership appeared first on IBM Blog.

Business Intelligence 267

Business Intelligence NLP Machine Learning AI 267

Towards AI

MAY 10, 2024

This is known as speech to text and is something I will try and re-create in this post using python and a bit of machine learning. If you want to learn more, see here for the first part of the series that uses Python to make your computer talk. Join thousands of data leaders on the AI newsletter.

Python 82

Python Neural Network Natural Language Processing NLP 82

AI Weekly

APRIL 11, 2024

Read the blog] global.ntt In The News When an antibiotic fails: MIT scientists are using AI to target “sleeper” bacteria mit.edu Microsoft AI opens London hub to access ‘enormous pool’ of talent Microsoft is doubling down on its AI efforts in the UK with the opening of a major new AI hub in London. No legacy process is safe.

Robotics 207

Robotics Large Language Models Artificial Intelligence Artificial Intelligence 207

IBM Journey to AI blog

FEBRUARY 14, 2024

Voice-based queries use natural language processing (NLP) and sentiment analysis for speech recognition so their conversations can begin immediately. Using machine learning (ML), AI can understand what customers are saying as well as their tone—and can direct them to customer service agents when needed.

Computer Vision 221

Computer Vision Automation Robotics AI 221

Towards AI

JULY 15, 2023

Using CountVectorizer, an implementation of bag-of-words Top highlight Image by Flo on OpenSea, UX Natural Language Processing In this article, we build our machine learning model to guess customer reviews tone based on historical data. It is a classification problem solved with Natural Language Processing (NLP).

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Natural Language Processing NLP Machine Learning Algorithm 87

IBM Journey to AI blog

APRIL 18, 2024

Imagine a world where machines aren’t confined to pre-programmed tasks but operate with human-like autonomy and competence. AGI, sometimes referred to as strong AI , is the science-fiction version of artificial intelligence (AI), where artificial machine intelligence achieves human-level learning, perception and cognitive flexibility.

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Neural Network LLM AI AI 239

IBM Journey to AI blog

OCTOBER 16, 2023

Machine learning (ML)—the artificial intelligence (AI) subfield in which machines learn from datasets and past experiences by recognizing patterns and generating predictions—is a $21 billion global industry projected to become a $209 billion industry by 2029.

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Machine Learning ML Algorithm Chatbots 129

IBM Journey to AI blog

JUNE 26, 2023

Imagine the possibilities of providing text-based queries and opening a world of knowledge for improved learning and productivity. It’s like having a conversation with a very smart machine. It uses vast amounts of internet data, large-scale pre-training and reinforced learning to enable surprisingly human like user transactions.

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Generative AI Explainability Explainable AI Natural Language Processing 177

Ehud Reiter

DECEMBER 19, 2023

Papers mentioned in blogs I have talked about some of the 2023 papers which impressed me in previous blogs, including What LLMs cannot do A bad way to measure hallucination LLM hype brings memories of IBM Watson Future of NLG evaluation: LLMs and high quality human eval? Which is great! G Abercrombie et al (2023). Proc of WMT-2023.

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NLP Large Language Models LLM Algorithm 124

Towards AI

JULY 17, 2023

Natural language processing, computer vision, machine learning I recently moved from the computer vision (CV) domain to the natural language processing (NLP) domain and found some interesting observations. NLP is language-specific, but CV is not. NLP in a different language could be very different. Here we go.

Natural Language Processing 82

Natural Language Processing Computer Vision Machine Learning NLP 82

Towards AI

NOVEMBER 19, 2023

Pre-trained models in machine and deep learningPhoto by Arnold Francisca on Unsplash In simple terms, it is a technique to use a trained model on the dataset that is run on a new, different dataset. What is the issue of training deep learning models from scratch? takes… Read the full blog for free on Medium.

Deep Learning 114

Deep Learning Natural Language Processing Computer Vision NLP 114

Great Learning

MARCH 18, 2024

In the continuously evolving artificial intelligence (AI) landscape, the quest for more interactive and intuitive systems has led to note-worthy advancements in natural language processing (NLP) and machine learning (ML).

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Artificial Intelligence Artificial Intelligence Natural Language Processing Machine Learning 52

Towards AI

AUGUST 10, 2023

All created layers will be included in Machine Learning Training Utilities (“mltu” PyPi library), so they can be easily reused in other projects. At the end of these tutorials, I’ll create practical examples of training and using Transformer in NLP tasks. The model is based on the… Read the full blog for free on Medium.

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NLP Machine Learning Explainability AI 90

ODSC - Open Data Science

JANUARY 1, 2024

Over the years, ODSC has developed a close relationship with them, working together to host webinars, write blogs, and even collaborate on sessions at ODSC conferences. Below, you’ll find a rundown of all of our Microsoft and ODSC collaborative efforts, including past webinars & talks, blogs, and more. Where can I stay up to date?

Data Science 52

Data Science Machine Learning Deep Learning Large Language Models 52

Towards AI

JULY 20, 2023

The Lookout — “All’s Well” | Homer NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER The NLP Cypher | 03.07.21 The wild concept uses neural net theory to unify quantum and… www.popularmechanics.com FYI, we added 25 new notebooks to the Super Duper NLP Repo!! ? For NLP focused content, start on page 62.

NLP 92

NLP Neural Network Natural Language Processing Machine Learning 92

Ehud Reiter

MARCH 12, 2024

One of the fundamental principles of machine learning is that systems should not be tested and evaluated on the data they were trained on. LLMs can also learn from prompts and other user inputs. What is data contamination? Hence an LLM could get perfect scores on the evaluation simply by memorising the articles.

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LLM NLP ChatGPT Machine Learning 109

Becoming Human

MAY 15, 2023

When it comes to AI, there are a number of subfields, like Natural Language Processing (NLP). One of the models used for NLP is the Large Language Model (LLMs). As a result, LLMs have become a key tool for a wide range of NLP applications. This data comes everywhere, including articles, blogs, news sites, and journals.

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Large Language Models ChatGPT Neural Network LLM 124

Marktechpost

MARCH 6, 2024

Recent advancements in the field of Artificial Intelligence and Deep Learning have made remarkable strides, especially in generative modelling, which is a subfield of Machine Learning where models are trained to produce new data samples that match the training data. Check out the Paper , Github , and Blog.

Machine Learning 125

Machine Learning Natural Language Processing Deep Learning Artificial Intelligence 125

Becoming Human

MAY 9, 2024

Introduction about NER Named entity recognition (NER) is a fundamental aspect of natural language processing (NLP). NLP is a branch of artificial intelligence (AI) that aims to teach machines how to understand, interpret, and generate human language. It’s crucial in various AI and machine learning (ML) applications.

Natural Language Processing 52

Natural Language Processing NLP Categorization Data Mining 52

Towards AI

JULY 21, 2023

Photo by Kunal Shinde on Unsplash NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER NLP News Cypher | 08.09.20 What is the state of NLP? Deep learning and semantic parsing, do we still care about information extraction? As of right now, the architecture can help with language modeling and machine translation.

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NLP Auto-complete Natural Language Processing BERT 89

Mlearning.ai

MAY 5, 2023

These models, which are based on artificial intelligence and machine learning algorithms, are designed to process vast amounts of natural language data and generate new content based on that data. In the 1980s and 1990s, the field of natural language processing (NLP) began to emerge as a distinct area of research within AI.

Large Language Models 98

Large Language Models Neural Network Natural Language Processing Deep Learning 98

Towards AI

MARCH 5, 2024

It has been demonstrating great capability in various aspects such as text summarisation, machine translation and knowledge-intensive NLP tasks. Despite its powerful performance, one of the shortcomings of LLMs is that their knowledge is limited to the data they have learned in the training.

Large Language Models 89

Large Language Models NLP Generative AI AI 89

IBM Journey to AI blog

DECEMBER 15, 2023

The diversity and accessibility of open-source AI allow for a broad set of beneficial use cases, like real-time fraud protection, medical image analysis, personalized recommendations and customized learning. TensorFlow is a flexible, extensible learning framework that supports programming languages like Python and Javascript.

AI Tools 179

AI Tools Deep Learning Computer Vision AI 179

Unite.AI

JULY 20, 2023

NLP Analysis Scalenut uses NLP (Natural Language Processing) AI to generate human-like content. NLP key terms. Leveraging machine learning , Surfer SEO has become an industry standard for bloggers and content marketers to create search engine-optimized content. When you’re ready, select Export to Editor.

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AI AI NLP Natural Language Processing 245

Towards AI

DECEMBER 28, 2023

Before starting, consider taking a look at my Medium profile where I cover topics on Data Science, Machine Learning, and Python! NLTK stands for Natural Language Toolkit, comprising Python modules, datasets, corpora, and tutorials designed for Natural Language Processing (NLP). stars on GitHub. stars on GitHub.

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Natural Language Processing Python Computational Linguistics NLP 93

Unite.AI

OCTOBER 31, 2023

Jasper AI's strengths lie in its array of pre-written templates, enabling the quick and easy generation of clever, well-crafted copy for various purposes including emails, ads, websites, listings, and blogs. Effective Email Generation : Utilizes NLP and machine learning to produce personalized and effective emails.

AI 189

AI AI Machine Learning Natural Language Processing 189

IBM Journey to AI blog

OCTOBER 9, 2023

Artificial intelligence (AI) can help usher in a new era of human resource management, where data analytics, machine learning and automation can work together to save people time and support higher-quality outcomes. These are some possible use cases: Professional learning and development: Where do workers see themselves in five years?

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Artificial Intelligence Artificial Intelligence Automation Natural Language Processing 185

IBM Journey to AI blog

SEPTEMBER 6, 2023

AI marketing is the process of using AI capabilities like data collection, data-driven analysis, natural language processing (NLP) and machine learning (ML) to deliver customer insights and automate critical marketing decisions. What is AI marketing?

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Automation Data Scientist AI AI 214

IBM Journey to AI blog

SEPTEMBER 19, 2023

Generative AI for coding is possible because of recent breakthroughs in large language model (LLM) technologies and natural language processing (NLP). It uses deep learning algorithms and large neural networks trained on vast datasets of diverse existing source code. How does generative AI code generation work?

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IBM Journey to AI blog

AUGUST 2, 2023

An HR Chatbot that leverages natural language processing (NLP) and machine learning can understand, communicate, and even automate actions to support candidates and employees. Transform your HR support experience with Watson Assistant The post How chatbots improve human resource operations appeared first on IBM Blog.

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Chatbots Conversational AI Natural Language Processing Artificial Intelligence 166

Pickl AI

MARCH 27, 2023

Well, it’s Natural Language Processing which equips the machines to work like a human. But there is much more to NLP, and in this blog, we are going to dig deeper into the key aspects of NLP, the benefits of NLP and Natural Language Processing examples. What is NLP? Thus making it apt for analysis.

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Natural Language Processing NLP Data Analysis Chatbots 52

The MLOps Blog

FEBRUARY 15, 2024

Due to the rise of LLMs and the shift towards pre-trained models and prompt engineering, specialists in traditional NLP approaches are particularly at risk. Data scientists and NLP specialists can move towards analytical roles or into engineering to stay relevant. Are LLMs entirely overtaking AI and natural language processing (NLP)?

NLP 59

NLP Natural Language Processing Data Scientist Software Engineer 59

Towards AI

DECEMBER 28, 2023

The advent of more powerful personal computers paved the way for the gradual acceptance of deep learning-based methods. The introduction of attention mechanisms has notably altered our approach to working with deep learning algorithms, leading to a revolution in the realms of computer vision and natural language processing (NLP).

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Large Language Models Natural Language Processing Prompt Engineer Prompt Engineering 110