Unite.AI

APRIL 9, 2024

The adoption of Artificial Intelligence (AI) has increased rapidly across domains such as healthcare, finance, and legal systems. However, this surge in AI usage has raised concerns about transparency and accountability. Composite AI is a cutting-edge approach to holistically tackling complex business problems.

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Marktechpost

OCTOBER 6, 2024

Don’t Forget to join our 50k+ ML SubReddit Interested in promoting your company, product, service, or event to over 1 Million AI developers and researchers? The post FakeShield: An Explainable AI Framework for Universal Image Forgery Detection and Localization Using Multimodal Large Language Models appeared first on MarkTechPost.

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IBM Journey to AI blog

OCTOBER 16, 2023

Artificial intelligence (AI) adoption is still in its early stages. As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. ” Are foundation models trustworthy?

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Dlabs.ai

AUGUST 16, 2022

Artificial intelligence can transform any organization. That’s why 37% of companies already use AI , with nine in ten big businesses investing in AI technology. Still, not everyone can appreciate the benefits of AI. One of the major hurdles to AI adoption is that people struggle to understand how AI models work.

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Pickl AI

JANUARY 13, 2025

Summary: This curated list of 20 Artificial Intelligence books for beginners highlights foundational concepts, coding practices, and ethical insights. Introduction Artificial Intelligence (AI) continues to shape the future, with its market size skyrocketing from $515.31 billion in 2023 to a projected $2,740.46

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Towards AI

OCTOBER 19, 2024

Originally published on Towards AI. Why We’re Demanding Answers from Our Smartest Machines Image generated by Gemini AI Artificial intelligence is making decisions that impact our lives in profound ways, from loan approvals to medical diagnoses. What is Explainability AI (XAI)?

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Unite.AI

JULY 2, 2024

Artificial intelligence (AI) is revolutionizing industries, streamlining processes, improving decision-making, and unlocking previously unimagined innovations. As we witness AI's rapid evolution, the European Union (EU) has introduced the EU AI Act, which strives to ensure these powerful tools are developed and used responsibly.

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Viso.ai

FEBRUARY 12, 2024

True to its name, Explainable AI refers to the tools and methods that explain AI systems and how they arrive at a certain output. Artificial Intelligence is used in every sphere of today’s digital world. Why do we need Explainable AI (XAI)? SHAP is short for Shapley Additive Explanations.

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NVIDIA

MARCH 1, 2024

Artificial intelligence, like any transformative technology, is a work in progress — continually growing in its capabilities and its societal impact. Trustworthy AI initiatives recognize the real-world effects that AI can have on people and society, and aim to channel that power responsibly for positive change.

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Unite.AI

MARCH 18, 2024

This content often fills the gap when data is scarce or diversifies the training material for AI models, sometimes without full recognition of its implications. While this expansion enriches the AI development landscape with varied datasets, it also introduces the risk of data contamination.

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Pickl AI

APRIL 8, 2024

We delve into real-world examples to illustrate the impact of these mistakes and pave the way for a more ethical and responsible future of AI Failures. 13 Biggest AI Failures: A Look at the Pitfalls of Artificial Intelligence Artificial intelligence (AI) has become a ubiquitous term, woven into the fabric of our daily lives.

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Aiiot Talk

JULY 7, 2023

Black-box AI poses a serious concern in the aviation industry. In fact, explainability is a top priority laid out in the European Union Aviation Safety Administration’s first-ever AI roadmap. Explainable AI, sometimes called white-box AI, is designed to have high transparency so logic processes are accessible.

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Mlearning.ai

DECEMBER 31, 2023

Principles of Explainable AI( Source ) Imagine a world where artificial intelligence (AI) not only makes decisions but also explains them as clearly as a human expert. This isn’t a scene from a sci-fi movie; it’s the emerging reality of Explainable AI (XAI). What is Explainable AI?

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Unite.AI

JANUARY 12, 2024

The field of artificial intelligence (AI) has seen tremendous growth in 2023. Generative AI, which focuses on creating realistic content like images, audio, video and text, has been at the forefront of these advancements. Enhancing user trust via explainable AI also remains vital.

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ODSC - Open Data Science

MARCH 10, 2025

Walk away with practical approaches to designing robust evaluation frameworks that ensure AI systems are measurable, reliable, and deployment-ready. Explainable AI for Decision-Making Applications Patrick Hall, Assistant Professor at GWSB and Principal Scientist at HallResearch.ai

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Towards AI

APRIL 2, 2024

On the other hand, new developments in techniques such as model merging (see story below from Sakana) can provide a new avenue for affordable development and improvement of open-source models. Hence, we are focused on making AI more accessible and releasing AI learning materials and courses! Why should you care?

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AWS Machine Learning Blog

NOVEMBER 15, 2024

The rapid advancement of generative AI promises transformative innovation, yet it also presents significant challenges. Concerns about legal implications, accuracy of AI-generated outputs, data privacy, and broader societal impacts have underscored the importance of responsible AI development.

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Pickl AI

JANUARY 29, 2024

Join me on this journey as we unravel the intricacies of 2024’s tech revolution, exploring the realms of data, intelligence, and the opportunity for growth, including a special mention of a free Machine Learning course. ML catalyses AI advancements, enabling systems to evolve and improve decision-making. billion by 2029.

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ODSC - Open Data Science

FEBRUARY 18, 2025

As AI capabilities grow, many traditional knowledge-based roles may shift from execution to oversight and decision-making. AI Ethicists: As AI systems become more integrated into society, ethical considerations are paramount. Explainable AI (XAI) techniques are crucial for building trust and ensuring accountability.

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Flipboard

JUNE 20, 2023

Understanding AI’s mysterious “opaque box” is paramount to creating explainable AI. This can be simplified by considering that AI, like all other technology, has a supply chain. These are the mathematical formulas written to simulate functions of the brain, which underlie the AI programming.

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Marktechpost

DECEMBER 11, 2024

Image Source : LG AI Research Blog ([link] Responsible AI Development: Ethical and Transparent Practices The development of EXAONE 3.5 models adhered to LG AI Research s Responsible AI Development Framework, prioritizing data governance, ethical considerations, and risk management. model scored 70.2.

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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. AI Engineering TrackBuild Scalable AISystems Learn how to bridge the gap between AI development and software engineering.

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ODSC - Open Data Science

OCTOBER 21, 2024

As AI systems become increasingly embedded in critical decision-making processes and in domains that are governed by a web of complex regulatory requirements, the need for responsible AI practices has never been more urgent. But let’s first take a look at some of the tools for ML evaluation that are popular for responsible AI.

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ODSC - Open Data Science

SEPTEMBER 26, 2024

Using AI to Detect Anomalies in Robotics at the Edge Integrating AI-driven anomaly detection for edge robotics can transform countless industries by enhancing operational efficiency and improving safety. Where do explainable AI models come into play? Here’s everything that you can watch on-demand whenever you like!

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AI News

APRIL 25, 2024

As artificial intelligence continues to rapidly advance, ethical concerns around the development and deployment of these world-changing innovations are coming into sharper focus. Pryon also emphasises explainable AI and verifiable attribution of knowledge sources.

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Unite.AI

JULY 1, 2024

In recent years, the world has witnessed the unprecedented rise of Artificial Intelligence (AI) , which has transformed numerous sectors and reshaped our everyday lives. Transparency and Explainability Enhancing transparency and explainability is essential.

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IBM Journey to AI blog

SEPTEMBER 3, 2024

Artificial intelligence (AI) has enormous value but capturing the full benefits of AI means facing and handling its potential pitfalls. Those learned biases might be perpetuated during the deployment of AI, resulting in skewed outcomes. AI bias can have unintended consequences with potentially harmful outcomes. .

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Viso.ai

JANUARY 21, 2025

Computer vision is a field of artificial intelligence that enables machines to understand and analyze objects in visual data (e.g. Moreover, their ability to handle large datasets with fewer resources makes them a game-changer in AI development. images and videos). It allows data to be processed locally on edge devices.

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The MLOps Blog

FEBRUARY 27, 2025

How to integrate transparency, accountability, and explainability? As LLMs become increasingly integrated into applications and individuals and organizations rely on AI development for their own projects, concerns surrounding the transparency, accountability, and explainability of these systems are growing.

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ODSC - Open Data Science

OCTOBER 3, 2024

AI Development Lifecycle: Learnings of What Changed with LLMs Noé Achache | Engineering Manager & Generative AI Lead | Sicara Using LLMs to build models and pipelines has made it incredibly easy to build proof of concepts, but much more challenging to evaluate the models.

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Pickl AI

DECEMBER 29, 2024

Through ethical guidelines, robust governance, and interdisciplinary collaboration, organisations can harness AI’s transformative power while safeguarding fairness and inclusivity. Responsible AI is essential for creating trustworthy systems that prioritise societal well-being.

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AI Weekly

AUGUST 22, 2024

Here’s why that’s a problem Using generative large language models (LLMs) like those behind ChatGPT and other AI chatbots, the system can brainstorm, select a promising idea, code new algorithms, plot results, and write a paper summarising the experiment and its findings, complete with references. pdf, Word, etc.) into their platform.

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Pickl AI

DECEMBER 10, 2024

It promotes fairness, regulatory compliance, and stakeholder trust across the AI lifecycle. This framework empowers organisations to adopt AI responsibly while safeguarding against risks and ethical concerns. AI TRiSM aligns AI systems with legal standards like GDPR, future-proofing organisations against evolving regulations.

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IBM Journey to AI blog

FEBRUARY 28, 2024

They also found that, while the public is still wary about new technologies like artificial intelligence (AI), most people are in favor of government adoption of generative AI. This platform offers a seamless, efficient and responsible approach to AI development across various environments.

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IBM Journey to AI blog

FEBRUARY 9, 2024

2022 was the year that generative artificial intelligence (AI) exploded into the public consciousness, and 2023 was the year it began to take root in the business world. iii] “AI models haven’t had that kind of data before. Those models will just have a better understanding of everything.”

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