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Analytics Vidhya
NOVEMBER 29, 2021
In this article, we will learn about model explainability and the different ways to interpret a machine learning model. What is Model Explainability? Model explainability refers to the concept of being able to understand the machine learning model. For example – If a healthcare […].
396 
Analytics Vidhya
JULY 7, 2023
Introduction I’m going to explain transformers encoders to you in very simple way.
307
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The Intersection of AI and Sales: Personalization Without Compromise
How to Achieve High-Accuracy Results When Using LLMs
Relevance, Reach, Revenue: How to Turn Marketing Trends From Hype to High-Impact
Analytics Vidhya
JANUARY 25, 2022
The post Building Explainer Dashboards in Python appeared first on Analytics Vidhya.
268 
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. The introduction of word embeddings, most notably Word2Vec, was a pivotal moment in NLP. One-hot encoding is a prime example of this limitation.
298 
IBM Journey to AI blog
MAY 21, 2024
And now, it’s also the language spoken and understood by Scout Advisor—an innovative tool using natural language processing (NLP) and built on the IBM® watsonx™ platform especially for Spain’s Sevilla Fútbol Club. In fact, paperwork is a much more significant part of the job than one might imagine.
211 
AssemblyAI
NOVEMBER 9, 2023
In Natural Language Processing (NLP), Text Summarization models automatically shorten documents, papers, podcasts, videos, and more into their most important soundbites. What is Text Summarization for NLP? This video is brought to you by AssemblyAI and is part of our Deep Learning Explained series.
256 
Towards AI
FEBRUARY 11, 2025
This was the limit of our interaction with technology until Natural Language Processing (NLP) emerged, giving computers a voice. Natural Language Processing: Speaking Human NLP is an AI technology that allows computer programs to understand human languages as they are spoken and written. AI: Its 4 PM.
Unite.AI
JULY 5, 2023
ALiBi Support To explain this feature, let’s consider a question: How can MPT-30B understand and make predictions for longer sequences than what it was trained on? The post MPT-30B: MosaicML Outshines GPT-3 With A New LLM To Push The Boundaries of NLP appeared first on Unite.AI. For the latest AI news, visit unite.ai.
264 
JUNE 21, 2023
If you are interested in learning more about ChatGPT and artificial intelligence put together a quick introductory list of 100 ChatGPT terms explained …
123 
Towards AI
FEBRUARY 10, 2025
Natural language processing NLP technology allows these agents to understand and interpret human language so that they can efficiently interact with users and process information from text sources. The working of Agentic AI involves the use of several technologies that make it capable of doing its job.
Ehud Reiter
MARCH 2, 2025
BNs as a reasoning mechanism are attractive in principle because they deal naturally with uncertainty while being configurable and explainable ( blog ), which is very important when an AI system is used to support human professionals in making decisions. Nikolay’s goal is to make BNs easier to build and explain, and hence more useful.
129 
Marek Rei
NOVEMBER 4, 2024
link] Proposes an explainability method for language modelling that explains why one word was predicted instead of a specific other word. Adapts three different explainability methods to this contrastive approach and evaluates on a dataset of minimally different sentences. UC Berkeley, CMU. EMNLP 2022. Imperial, Cambridge, KCL.
Unite.AI
DECEMBER 12, 2024
Or between an AI that can explain code and one that can write and debug it in real-time. This includes developments in natural language processing (NLP) , computer vision , and machine learning that power current services like Bedrock and Q Business. That is the gap Amazon is aiming to bridge.
Ehud Reiter
MARCH 25, 2024
years old), I’m trying to come back to this vision, collaborating with my students and colleagues in Aberdeen’s medical school in a variety of areas, including supporting cancer patients, helping people understand nutritional data, and explaining IVF predictions. We’ll be using vision (to analyse skin images) as well as NLP.
129 
Unite.AI
JANUARY 28, 2025
DeepSeek focuses on modular and explainable AI, making it ideal for healthcare and finance industries where precision and transparency are vital. DeepSeek focuses on multi-modal reasoning and explainable AI , while OpenAI enhances contextual learning and explores quantum computing integration. Both companies are advancing rapidly.
147 
Towards AI
JANUARY 31, 2025
Explaining a black box Deep learning model is an essential but difficult task for engineers in an AI project. Image by author When the first computer, Alan Turings machine, appeared in the 1940s, humans started to struggle in explaining how it encrypts and decrypts messages. Author(s): Chien Vu Originally published on Towards AI.
Unite.AI
MARCH 6, 2025
We also make sure AI systems are explainable and their decisions can be easily understood to provide full transparency. Explainability is a key part of our approach, making sure that AI decisions are understandable for both businesses and consumers.
165 
Unite.AI
DECEMBER 27, 2024
Natural Language Processing (NLP) models like ChatGPT are trained on billions of text samples to understand language nuances, cultural references, and context. Many platforms collect personal information without clearly explaining how it will be used. There are also serious ethical concerns tied to this control over data.
173 
FEBRUARY 16, 2023
Natural language processing ( NLP ), while hardly a new discipline, has catapulted into the public consciousness these past few months thanks in large part to the generative AI hype train that is ChatGPT. ‘Data-centric’ NLP With NLP one of the hot AI trends of the moment, Kern AI today announced that it has raised €2.7
123 
Analytics Vidhya
JANUARY 20, 2022
As a result, in this article, we are going to define and explain Machine Learning boosting. Introduction Boosting is a key topic in machine learning. Numerous analysts are perplexed by the meaning of this phrase. With the help of “boosting,” machine learning models are […].
370 
Towards AI
OCTOBER 31, 2024
A Complete Guide to Embedding For NLP & Generative AI/LLM By Mdabdullahalhasib This article provides a comprehensive guide to understanding and implementing vector embedding in NLP and generative AI.
116 
Unite.AI
JANUARY 1, 2025
Integrating natural language processing (NLP) is particularly valuable, allowing for more intuitive customer interactions. To address these issues, banks are investing in explainable AI frameworks that allow for greater transparency in AI-driven decisions.
140 
Towards AI
JULY 19, 2023
We speak with each other using various languages Ex: English, German, French, Hindi, etc… Photo by Alexandra on Unsplash Natural Language Processing (NLP) is just one part of Artificial Intelligence (AI) that helps Computers understand and process human language. But hey, why do we even care about learning NLP??
98 
Unite.AI
APRIL 9, 2024
These techniques include Machine Learning (ML), deep learning , Natural Language Processing (NLP) , Computer Vision (CV) , descriptive statistics, and knowledge graphs. The Need for Explainability The demand for Explainable AI arises from the opacity of AI systems, which creates a significant trust gap between users and these algorithms.
182 
Marktechpost
JULY 22, 2024
Authorship Verification (AV) is critical in natural language processing (NLP), determining whether two texts share the same authorship. This lack of explainability is a gap in academic interest and a practical concern. This is a critical limitation as the demand for explainable AI grows.
104 
Analytics Vidhya
APRIL 19, 2024
It integrates vision, language, and action to explain and determine driving behavior. Introduction Wayve, a leading artificial intelligence company based in the United Kingdom, introduces Lingo-2, a groundbreaking system that harnesses the power of natural language processing.
Unite.AI
DECEMBER 1, 2023
SHAP's strength lies in its consistency and ability to provide a global perspective – it not only explains individual predictions but also gives insights into the model as a whole. This method requires fewer resources at test time and has been shown to effectively explain model predictions, even in LLMs with billions of parameters.
264 
IBM Journey to AI blog
JUNE 26, 2023
Possibilities are growing that include assisting in writing articles, essays or emails; accessing summarized research; generating and brainstorming ideas; dynamic search with personalized recommendations for retail and travel; and explaining complicated topics for education and training. What is generative AI? What is watsonx.governance?
203 
AI News
NOVEMBER 30, 2023
“Efficiency is key in the future of computing,” explains Jakubiuk. AI workloads today fall into four categories: computer vision, NLP, recommendation engines, and generative AI. Ampere Computing’s software and hardware combination caters seamlessly across all these workloads for sustainable AI deployments at scale.
347 
Analytics Vidhya
JANUARY 20, 2022
Introduction In this article, I am going to explain, how can we use log parsing with Spark and Scala to get meaningful data from unstructured data. This article was published as a part of the Data Science Blogathon. In my experience, after parsing a lot of logs from different sources, I have found no data is […].
320 
AWS Machine Learning Blog
MARCH 7, 2025
The graph, stored in Amazon Neptune Analytics, provides enriched context during the retrieval phase to deliver more comprehensive, relevant, and explainable responses tailored to customer needs. This new capability integrates the power of graph data modeling with advanced natural language processing (NLP).
119 
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). As previously explained, spend data is more readily available in an organization and is a common proxy of quantity of goods/services.
238 
IBM Journey to AI blog
SEPTEMBER 20, 2023
When implemented in a responsible way—where the technology is fully governed, privacy is protected and decision making is transparent and explainable—AI has the power to usher in a new era of government services. AI’s value is not limited to advances in industry and consumer products alone.
307 
Towards AI
AUGUST 10, 2023
I’ll implement them step-by-step in TensorFlow, explaining all the parts. At the end of these tutorials, I’ll create practical examples of training and using Transformer in NLP tasks. All created layers will be included in Machine Learning Training Utilities (“mltu” PyPi library), so they can be easily reused in other projects.
98 
IBM Journey to AI blog
AUGUST 13, 2024
An early hint of today’s natural language processing (NLP), Shoebox could calculate a series of numbers and mathematical commands spoken to it, creating a framework used by the smart speakers and automated customer service agents popular today.
291 
IBM Journey to AI blog
JANUARY 25, 2024
Additionally, the models themselves are created from limited architectures: “Almost all state-of-the-art NLP models are now adapted from one of a few foundation models, such as BERT, RoBERTa, BART, T5, etc. How are you making your model explainable? Typical questions include: What is your model’s use case?
247 
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. What makes a good AI conversationalist?
John Snow Labs
JANUARY 25, 2024
The shift across John Snow Labs’ product suite has resulted in several notable company milestones over the past year including: 82 million downloads of the open-source Spark NLP library. The no-code NLP Lab platform has experienced 5x growth by teams training, tuning, and publishing AI models.
94 
AI Weekly
APRIL 11, 2024
And this is particularly true for accounts payable (AP) programs, where AI, coupled with advancements in deep learning, computer vision and natural language processing (NLP), is helping drive increased efficiency, accuracy and cost savings for businesses. Answering them, he explained, requires an interdisciplinary approach.
264 
Unite.AI
APRIL 17, 2024
In recent years, Natural Language Processing (NLP) has undergone a pivotal shift with the emergence of Large Language Models (LLMs) like OpenAI's GPT-3 and Google’s BERT. These models, characterized by their large number of parameters and training on extensive text corpora, signify an innovative advancement in NLP capabilities.
236 
Towards AI
FEBRUARY 10, 2025
We have used machine learning models and natural language processing (NLP) to train and identify distress signals. Our teams careful selection and annotation of data points has given the dataset a strong foundation for NLP applications to detect distress signals, making further processes more straightforward and accurate.
98 
Unite.AI
SEPTEMBER 30, 2024
This article explains how AI in quality assurance streamlines software testing while improving product performance. Test Management Tools TestRail integrates AI to streamline test management by generating test cases through NLP. As AI takes center stage, AI quality assurance can empower teams to deliver higher-quality software faster.
317 
Towards AI
SEPTEMBER 7, 2023
The encoder will process the sentence word by word (technically token by token as per Natural Language Processing (NLP) terminology). The model contains two parts: the encoder and the decoder. The encoder produces a context that is fed into the decoder. The decoder will then produce the output one word at a time.
126 
Analytics Vidhya
JULY 27, 2023
This article explains how to build a translator using LLMs and […] The post Build Your Own Translator with LLMs & Hugging Face appeared first on Analytics Vidhya. Language Models (LLMs) trained on vast text data have deep language understanding, enabling seamless translation between people of different languages.
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