Unite.AI

MARCH 6, 2025

The platform speeds up workflows and helps agents provide faster, more accurate responses. TaskGPT helps agents retrieve information and make smart suggestions in real-time, which makes customer interactions smoother and more efficient. Agentic AI can tap those stores to inform its ability to act.

Automation 165

Automation AI Modeling Natural Language Processing Explainability 165

Unite.AI

APRIL 8, 2025

Can you explain how your approach to retrieval differs from other AI-powered search and knowledge management systems? With unstructured data growing over 50% annually, our ingestion engine transforms scattered information into structured, actionable knowledge. Pryon focuses on Retrieval-Augmented Generation (RAG).

Chatbots 147

Chatbots LLM Data Quality Generative AI 147

Flipboard

JANUARY 22, 2025

With this new feature, when an agent node requires clarification or additional context from the user before it can continue, it can intelligently pause the flows execution and request user-specific information. This creates a more interactive and context-aware experience, because the node can adapt its behavior based on user responses.

Generative AI 171

Generative AI ML Automation Explainability 171

Towards AI

FEBRUARY 11, 2025

NLP process: Identify keywords: weather, today Understand intent: weather forecast request Generate a response AI response: Expect partly sunny skies with a light breeze today. NLG Generate: AI response: It looks like theres a 30% chance of showers this afternoon. Finally, respond how a person would.

Conversational AI 74

Conversational AI Explainability NLP Natural Language Processing 74

IBM Journey to AI blog

SEPTEMBER 20, 2023

AI’s value is not limited to advances in industry and consumer products alone. 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.

Generative AI 307

Generative AI AI AI Explainability 307

Unite.AI

DECEMBER 13, 2023

However, challenges include the rise of AI-driven attacks and privacy issues. Responsible AI use is crucial. The future involves human-AI collaboration to tackle evolving trends and threats in 2024. About 80% of executives incorporate AI technology in their strategies and business decisions.

Explainability 290

Explainability AI AI Responsible AI 290

AWS Machine Learning Blog

NOVEMBER 29, 2023

These challenges include some that were common before generative AI, such as bias and explainability, and new ones unique to foundation models (FMs), including hallucination and toxicity. Guardrails drive consistency in how FMs on Amazon Bedrock respond to undesirable and harmful content within applications.

Responsible AI 122

Responsible AI Generative AI AI AI 122

Unite.AI

JANUARY 20, 2025

Transparency = Good Business AI systems operate using vast datasets, intricate models, and algorithms that often lack visibility into their inner workings. This opacity can lead to outcomes that are difficult to explain, defend, or challengeraising concerns around bias, fairness, and accountability.

Explainability 113

Explainability Explainable AI AI AI 113

Flipboard

FEBRUARY 19, 2025

As weve seen from Andurils experience with Alfred, building a robust data infrastructure using AWS services such as Amazon Bedrock , Amazon SageMaker AI , Amazon Kendra , and Amazon DynamoDB in AWS GovCloud (US) creates the essential backbone for effective information retrieval and generation.

Responsible AI 81

Responsible AI Natural Language Processing Explainability Large Language Models 81

IBM Journey to AI blog

OCTOBER 12, 2023

But the implementation of AI is only one piece of the puzzle. The tasks behind efficient, responsible AI lifecycle management The continuous application of AI and the ability to benefit from its ongoing use require the persistent management of a dynamic and intricate AI lifecycle—and doing so efficiently and responsibly.

Data Scientist 234

Data Scientist Metadata Responsible AI Explainability 234

Unite.AI

MARCH 20, 2025

Seamlessly integrated with third party digital pathology software solutions, scanning platforms and laboratory information systems, Ibexs AI-enabled workflows deliver automated high-quality insights that enhance patient safety, increase physician confidence and boost productivity.

Convolutional Neural Networks 147

Convolutional Neural Networks Algorithm Explainability Neural Network 147

Towards AI

OCTOBER 19, 2024

Yet, for all their sophistication, they often can’t explain their choices — this lack of transparency isn’t just frustrating — it’s increasingly problematic as AI becomes more integrated into critical areas of our lives. What is Explainability AI (XAI)? It’s particularly useful in natural language processing [3].

Explainability 105

Explainability Explainable AI Natural Language Processing Prompt Engineer 105

Google Research AI blog

MARCH 16, 2023

The Impact Lab team, part of Google’s Responsible AI Team , employs a range of interdisciplinary methodologies to ensure critical and rich analysis of the potential implications of technology development. We examine systemic social issues and generate useful artifacts for responsible AI development.

Responsible AI 111

Responsible AI ML AI AI 111

Unite.AI

JANUARY 1, 2025

For example, an AI model trained on biased or flawed data could disproportionately reject loan applications from certain demographic groups, potentially exposing banks to reputational risks, lawsuits, regulatory action, or a mix of the three. The average cost of a data breach in financial services is $4.45

Explainable AI 140

Explainable AI AI AI Natural Language Processing 140

Unite.AI

APRIL 9, 2024

As organizations strive for responsible and effective AI, Composite AI stands at the forefront, bridging the gap between complexity and clarity. 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.

Composite AI 182

Composite AI Explainability Black Box AI Explainable AI 182

Unite.AI

FEBRUARY 17, 2025

With non-AI agents, users had to define what they had to automate and how to do it in great detail. Model Interpretation and Explainability: Many AI models, especially deep learning models, are often seen as black boxes. At SymphonyAI, our mission is to provide enterprises with AI agents that deliver operational excellence.

Automation 147

Automation Responsible AI Generative AI AI Modeling 147

Unite.AI

JULY 26, 2024

As the adoption of artificial intelligence (AI) accelerates, large language models (LLMs) serve a significant need across different domains. LLMs excel in advanced natural language processing (NLP) tasks, automated content generation, intelligent search, information retrieval, language translation, and personalized customer interactions.

ChatGPT 281

ChatGPT OpenAI Natural Language Processing NLP 281

Flipboard

DECEMBER 3, 2024

This conversational agent offers a new intuitive way to access the extensive quantity of seed product information to enable seed recommendations, providing farmers and sales representatives with an additional tool to quickly retrieve relevant seed information, complementing their expertise and supporting collaborative, informed decision-making.

Generative AI 149

Generative AI Metadata Machine Learning Natural Language Processing 149

AWS Machine Learning Blog

NOVEMBER 26, 2024

In this post, we discuss how to use LLMs from Amazon Bedrock to not only extract text, but also understand information available in images. It also provides a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI. 90B Vision model. The numbers are shown in blue squares.

LLM 95

LLM Convolutional Neural Networks Metadata Explainability 95

Flipboard

APRIL 1, 2025

Today, organizations struggle with AI hallucination when moving generative AI applications from experimental to production environments. Model hallucination, where AI systems generate plausible but incorrect information, remains a primary concern.

Automation 165

Automation Generative AI AI AI 165

Chatbots Life

MAY 23, 2023

Responsible AI — deployment framework I asked ChatGPT and Bard to share their thoughts on what policies governments have to put in place to ensure responsible AI implementations in their countries. They should also work to raise awareness of the importance of responsible AI among businesses and organizations.

Responsible AI 82

Responsible AI Chatbots AI AI 82

AWS Machine Learning Blog

MARCH 21, 2025

Research papers and engineering documents often contain a wealth of information in the form of mathematical formulas, charts, and graphs. Navigating these unstructured documents to find relevant information can be a tedious and time-consuming task, especially when dealing with large volumes of data. samples/2003.10304/page_5.png"

Metadata 110

Metadata Convolutional Neural Networks Generative AI Data Scientist 110

IBM Journey to AI blog

JANUARY 15, 2024

Two critical elements driving this digital transformation are data and artificial intelligence (AI). AI plays a pivotal role in unlocking value from data and gaining deeper insights into the extensive information that governments collect to serve their citizens.

Generative AI 200

Generative AI Responsible AI Neural Network Natural Language Processing 200

IBM Journey to AI blog

FEBRUARY 28, 2024

IBM watsonx™ , an integrated AI, data and governance platform, embodies five fundamental pillars to help ensure trustworthy AI: fairness, privacy, explainability, transparency and robustness. This platform offers a seamless, efficient and responsible approach to AI development across various environments.

Generative AI 293

Generative AI Explainability AI AI 293

Unite.AI

JULY 4, 2024

This technique prevents logits from growing excessively large without hard truncation, maintaining more information while stabilizing the training process. Factual Accuracy : While highly capable, Gemma 2 can sometimes generate incorrect or inconsistent information. Always critically evaluate its outputs.

Large Language Models 312

Large Language Models LLM Natural Language Processing Explainability 312

Unite.AI

MAY 27, 2024

Detecting fraud with AI Traditional fraud detection methods rely on rule-based systems that can only identify pre-programmed patterns. By considering this broad data set, AI can create a more nuanced picture of a borrower's creditworthiness, identifying complex relationships within the data that might be missed by traditional methods.

Machine Learning 223

Machine Learning Explainability Algorithm AI 223

Unite.AI

MARCH 18, 2025

Certain large companies have control over a vast amount of data, which creates an uneven playing field wherein only a select few have access to information necessary to train AI models and drive innovation. That way, AI development is not concentrated in the hands of just a few major players. This is not how things should be.

AI Modeling 147

AI Modeling Automation Explainable AI AI Chatbots 147

Unite.AI

JULY 1, 2024

Its AI technology assesses all types of content, whether human-created or machine-generated. Seekr enhances user choice and control by providing streamlined access to trustworthy information. Seekr’s commitment to reliability and explainability is engrained throughout SeekrFlow.

Explainability 173

Explainability Software Engineer AI Modeling Responsible AI 173

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. Risks with Personal Data LLMs require extensive training data, which may include sensitive personal information.

LLM 264

LLM Machine Learning Explainability Algorithm 264

IBM Journey to AI blog

JULY 26, 2023

Critical considerations for responsible AI adoption While the possibilities are endless, the explosion of use cases that employ generative AI in HR also poses questions around misuse and the potential for bias. As such, HR leaders cannot simply rely on data and AI to make decisions. HR leaders set the tone.

Auto-complete 188

Auto-complete Generative AI AI Strategy Responsible AI 188

AWS Machine Learning Blog

OCTOBER 31, 2024

By implementing this architectural pattern, organizations that use Google Workspace can empower their workforce to access groundbreaking AI solutions powered by Amazon Web Services (AWS) and make informed decisions without leaving their collaboration tool. In the following sections, we explain how to deploy this architecture.

Generative AI 116

Generative AI AI AI Python 116

Marktechpost

JANUARY 17, 2024

The NIST AI Risk Management Framework and AI Trustworthiness taxonomy have indicated that these operational characteristics are necessary for trustworthy AI. The goal is to provide a thorough resource that helps shape future practice guides and standards for evaluating and controlling the security of AI systems.

Machine Learning 103

Machine Learning Responsible AI Artificial Intelligence Artificial Intelligence 103

John Snow Labs

MARCH 20, 2025

They are designed to elaborate on their thought processes, consider multiple hypotheses, evaluate evidence systematically, and explain conclusions transparently. The Medical LLM Reasoner can track multiple variables, hypotheses, and evidence points simultaneously without losing context. To learn more about Medical LLM Reasoner, visit: [link].

LLM 59

LLM Large Language Models Explainability Responsible AI 59

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.

Artificial Intelligence 137

Artificial Intelligence Artificial Intelligence BERT Large Language Models 137

Unite.AI

JULY 3, 2023

He has been quoted in a number of publications and routinely speaks to groups of clients regarding trends in IT, information security, and compliance. Could you share the genesis story behind Cranium AI? What is the Cranium AI Card and what key insights does it reveal ? and “Has this information been validated?”.

Responsible AI 162

Responsible AI AI AI Explainability 162

IBM Journey to AI blog

OCTOBER 16, 2023

Foundation models are widely used for ML tasks like classification and entity extraction, as well as generative AI tasks such as translation, summarization and creating realistic content. The development and use of these models explain the enormous amount of recent AI breakthroughs. Increase trust in AI outcomes.

Metadata 220

Metadata Explainability Automation Explainable AI 220

AWS Machine Learning Blog

MARCH 28, 2025

You can independently configure moderation for either image or text content (or both) with adjustable thresholds from low to high, helping you to build generative AI applications that align with your organizations responsible AI policies. This new capability is generally available in US East (N.

Generative AI 104

Generative AI Automation Explainability Responsible AI 104