AWS Machine Learning Blog

MARCH 14, 2025

This post focuses on RAG evaluation with Amazon Bedrock Knowledge Bases, provides a guide to set up the feature, discusses nuances to consider as you evaluate your prompts and responses, and finally discusses best practices. Jesse Manders is a Senior Product Manager on Amazon Bedrock, the AWS Generative AI developer service.

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Marktechpost

MAY 30, 2024

Introduction to AI and Machine Learning on Google Cloud This course introduces Google Cloud’s AI and ML offerings for predictive and generative projects, covering technologies, products, and tools across the data-to-AI lifecycle. It covers how to develop NLP projects using neural networks with Vertex AI and TensorFlow.

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Unite.AI

APRIL 26, 2024

Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP) by demonstrating remarkable capabilities in generating human-like text, answering questions, and assisting with a wide range of language-related tasks. While effective in various NLP tasks, few LLMs, such as Flan-T5, adopt this architecture.

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Unite.AI

MARCH 27, 2024

Milestones such as IBM's Deep Blue defeating chess grandmaster Garry Kasparov in 1997 demonstrated AI’s computational capabilities. Moreover, breakthroughs in natural language processing (NLP) and computer vision have transformed human-computer interaction and empowered AI to discern faces, objects, and scenes with unprecedented accuracy.

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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. Composite AI plays a pivotal role in enhancing interpretability and transparency. Combining diverse AI techniques enables human-like decision-making.

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ODSC - Open Data Science

MARCH 12, 2025

The Boom of Generative AI and Large Language Models(LLMs) 20182020: NLP was gaining traction, with a focus on word embeddings, BERT, and sentiment analysis. 20232024: The emergence of GPT-4, Claude, and open-source LLMs dominated discussions, highlighting real-world applications, fine-tuning techniques, and AI safety concerns.

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Unite.AI

DECEMBER 1, 2023

As we continue to integrate AI more deeply into various sectors, the ability to interpret and understand these models becomes not just a technical necessity but a fundamental requirement for ethical and responsible AI development.

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Marktechpost

MAY 6, 2024

In the quickly changing field of Natural Language Processing (NLP), the possibilities of human-computer interaction are being reshaped by the introduction of advanced conversational Question-Answering (QA) models. The Llama project is expected to spur responsible AI adoption across various areas and boost innovation as it develops.

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Marktechpost

JUNE 8, 2024

Microsoft’s AI courses offer comprehensive coverage of AI and machine learning concepts for all skill levels, providing hands-on experience with tools like Azure Machine Learning and Dynamics 365 Commerce.

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Marktechpost

AUGUST 9, 2024

introduces advanced natural language processing (NLP) capabilities. These enhancements allow the AI to understand and interpret human language better, making interactions with the AI more intuitive and seamless. AI Ethics and Responsible Innovation In developing EXAONE 3.0, Image Source EXAONE 3.0

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Marktechpost

SEPTEMBER 23, 2024

The creation of MMMLU reflects OpenAI’s focus on measuring models’ real-world proficiency, especially in languages that are underrepresented in NLP research. The MMMLU dataset helps bridge this gap by offering a framework for testing models in languages traditionally underrepresented in NLP research.

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Unite.AI

JULY 1, 2024

At the core of Seekr's technology is an independent search engine, powered by proprietary AI and utilizing natural language processing (NLP) to produce a Seekr Score and Political Lean Indicator. It allows enterprises to leverage their data securely, to rapidly develop AI they can rely on optimized for their industry.

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Snorkel AI

FEBRUARY 22, 2023

At Snorkel AI’s 2022 Future of Data-Centric AI virtual conference, Eisenberg gave a short presentation on the way he and his colleagues are working to operationalize the assessment of responsible AI systems using a Credo AI tool called Lens. My name is Ian Eisenberg, and I head the data science team at Credo AI.

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Snorkel AI

FEBRUARY 22, 2023

At Snorkel AI’s 2022 Future of Data-Centric AI virtual conference, Eisenberg gave a short presentation on the way he and his colleagues are working to operationalize the assessment of responsible AI systems using a Credo AI tool called Lens. My name is Ian Eisenberg, and I head the data science team at Credo AI.

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Unite.AI

AUGUST 28, 2024

Overview of Jamba Jamba is a hybrid large language model developed by AI21 Labs, leveraging a combination of Transformer layers and Mamba layers, integrated with a Mixture-of-Experts (MoE) module. This architecture allows Jamba to balance memory usage, throughput, and performance, making it a powerful tool for a wide range of NLP tasks.

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Marktechpost

SEPTEMBER 3, 2024

It excels in natural language processing (NLP) tasks such as text generation, sentiment analysis, translation, and summarization. CausalLM has emphasized the importance of responsible AI development and has taken steps to ensure that miniG is used in a manner that aligns with ethical standards.

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John Snow Labs

AUGUST 28, 2023

John Snow Labs developed LangTest to address biases in language models. We introduce an end-to-end NLP pipeline, which involves training, evaluating, testing for biases, augmenting the dataset, retraining, and comparing models. The library provides comprehensive tests to detect biases in language models.

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IBM Journey to AI blog

OCTOBER 16, 2023

Foundation models: The power of curated datasets Foundation models , also known as “transformers,” are modern, large-scale AI models trained on large amounts of raw, unlabeled data. Open-source projects, academic institutions, startups and legacy tech companies all contributed to the development of foundation models.

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NYU Center for Data Science

DECEMBER 12, 2023

The Center for Responsible AI (NYU R/AI) is leading this charge by embedding ethical considerations into the fabric of artificial intelligence research and development. The Center for Responsible AI is a testament to NYU’s commitment to pioneering research that upholds and advances these ideals.

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NYU Center for Data Science

JANUARY 3, 2024

Moreover, her collaboration with Microsoft researchers resulted in (De)Toxigen , a cutting-edge NLP model that significantly enhances hate speech detection capabilities, offering a robust support system for content moderators. Her goal is to empower everyday users, equipping them with tools to improve online safety.

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John Snow Labs

OCTOBER 19, 2023

Understanding the Impact of Bias on NLP Models Why test NLP models for Bias? Natural Language Processing (NLP) models rely heavily on bias to function effectively. This is due to the fact that bias helps NLP models to identify important features and relationships among data points.

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IBM Journey to AI blog

AUGUST 16, 2023

While ChatGPT has gained significant attention and popularity, it faces competition from other AI-powered chatbots and natural language processing (NLP) systems. Google, for example, has developed Bard , its AI chatbot, which is powered by its own language engine called PaLM 2.

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Unite.AI

SEPTEMBER 7, 2023

From spreading misinformation to facilitating unauthorized access, the fallout from these vulnerabilities underscores the critical need for responsible AI development. Developers, researchers, and policymakers must collaborate to establish robust safeguards against potential harm. Want to enhance your AI IQ?

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Unite.AI

JANUARY 12, 2024

Competitions also continue heating up between companies like Google, Meta, Anthropic and Cohere vying to push boundaries in responsible AI development. The Evolution of AI Research As capabilities have grown, research trends and priorities have also shifted, often corresponding with technological milestones.

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Towards AI

JANUARY 6, 2025

Professional Development Certificate in Applied AI by McGill UNIVERSITY The Professional Development Certificate in Applied AI from McGill is an appropriate advanced and practical program designed to equip professionals with actionable industry-relevant knowledge and skills required to be senior AI developers and the ranks.

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Marktechpost

AUGUST 22, 2024

These models will be integrated into the NVIDIA NeMo framework for generative AI, providing developers with powerful tools for various NLP tasks. As a result, there is a risk that the model could amplify these biases or produce inappropriate responses.

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Unite.AI

OCTOBER 22, 2024

At Appen, we work at the intersection of AI and data, and my experience has allowed me to lead the company and navigate complexities in the rapidly evolving AI space, moving through major developments like voice recognition, NLP, recommendation systems, and now generative AI.

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ODSC - Open Data Science

FEBRUARY 25, 2025

Large Language Models & RAG TrackMaster LLMs & Retrieval-Augmented Generation Large language models (LLMs) and retrieval-augmented generation (RAG) have become foundational to AI development. Whats Next in AI TrackExplore the Cutting-Edge Stay ahead of the curve with insights into the future of AI.

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Allen AI

FEBRUARY 1, 2024

The framework features a suite of completely open AI development tools, including: Full pretraining data : The model is built on AI2’s Dolma set which features three trillion token open corpus for language model pretraining, including code that produces the training data.

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ODSC - Open Data Science

MARCH 5, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI. Secondly, governments are investing in building their own internal AI capabilities.

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How to Learn Machine Learning

JULY 20, 2024

Generative AI solutions gained popularity with the launch of ChatGPT, developed by OpenAI, in 2023. Supported by Natural Language Processing (NLP), Large language modules (LLMs), and Machine Learning (ML), Generative AI can evaluate and create extensive images and texts to assist users.

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ODSC - Open Data Science

MARCH 24, 2023

Creating a Custom Vocabulary for NLP tasks Using exBERT and spaCY There are several approaches to adding custom terms to a vocabulary for NLP, but in this tutorial, we’ll focus on exBERT and spaCY tokenizer. Officially Released PyTorch 2.0 Register by Friday for 50% off.

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John Snow Labs

OCTOBER 19, 2023

Imagine asking your AI assistant about a contentious political issue, and it effortlessly mirrors your beliefs, regardless of the facts. It’s a phenomenon called sycophancy , and it’s a thorn in the side of AI development. Sound familiar? But fret not, for this blog post unveils a powerful antidote to this frustrating issue.

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AWS Machine Learning Blog

MARCH 14, 2024

Amazon Kendra uses natural language processing (NLP) to understand user queries and find the most relevant documents. The relevant information is then provided to the LLM for final response generation. Development: Getting the data ready As with any data-driven project, performance will only ever be as good as the data.

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Topbots

JULY 29, 2024

Prompt Tuning: An overview of prompt tuning and its significance in optimizing AI outputs. Google’s Gen AI Development Tools: Insight into the tools provided by Google for developing generative AI applications. Vertex AI Studio: Learn how to use Vertex AI Studio for developing and deploying generative AI models.

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Chatbots Life

APRIL 19, 2024

They are followed by marketing and sales (42%), and customer service (40%); 64% expect it to confer a competitive advantage; By 2026, companies focusing on responsible AI could enhance business goal achievement and user acceptance by 50% ; Artificial intelligence disruption may increase global labor productivity by 1.5%-3.0%

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Viso.ai

DECEMBER 20, 2023

The integrated approach promotes collaboration, innovation, and responsible AI practices with deep learning algorithms. Today, MindSpore is widely used for research and prototyping projects across ML Vision, NLP, and Audio tasks. Thus, allowing for collaboration between domain experts and AI developers.

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