Unite.AI

DECEMBER 19, 2024

Thats why explainability is such a key issue. People want to know how AI systems work, why they make certain decisions, and what data they use. The more we can explain AI, the easier it is to trust and use it. Large Language Models (LLMs) are changing how we interact with AI. Lets dive into how theyre doing this.

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Unite.AI

JULY 7, 2023

To address this conundrum, our team at the Fidelity Center for Applied Technology (FCAT) — in collaboration with the Amazon Quantum Solutions Lab — has proposed and implemented an interpretable machine learning model for Explainable AI (XAI) based on expressive Boolean formulas.

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Analytics Vidhya

MARCH 14, 2023

The quality of AI is what matters most and is one of the vital causes of the failure of any business or organization. According to a survey or study, AI […] The post What are Explainability AI Techniques? Why do We Need it? appeared first on Analytics Vidhya.

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Marktechpost

OCTOBER 31, 2024

It elicits the need to design models that allow researchers to understand how AI predictions are achieved so they can trust them in decisions involving materials discovery. XElemNet, the proposed solution, employs explainable AI techniques, particularly layer-wise relevance propagation (LRP), and integrates them into ElemNet.

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Analytics Vidhya

JUNE 17, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon eXplainable AI(XAI) What does Interpretability/Explainability mean in AI? The post Beginner’s Guide to Machine Learning Explainability appeared first on Analytics Vidhya. The following points.

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Analytics Vidhya

MAY 26, 2022

Introduction The ability to explain decisions is increasingly becoming important across businesses. Explainable AI is no longer just an optional add-on when using ML algorithms for corporate decision making. This article was published as a part of the Data Science Blogathon.

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Marktechpost

APRIL 24, 2024

To ensure practicality, interpretable AI systems must offer insights into model mechanisms, visualize discrimination rules, or identify factors that could perturb the model. Explainable AI (XAI) aims to balance model explainability with high learning performance, fostering human understanding, trust, and effective management of AI partners.

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Unite.AI

MARCH 20, 2025

If AI systems produce biased outcomes, companies may face legal consequences, even if they don't fully understand how the algorithms work. It cant be overstated that the inability to explain AI decisions can also erode customer trust and regulatory confidence. Visualizing AI decision-making helps build trust with stakeholders.

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Unite.AI

JANUARY 28, 2025

This shift has increased competition among major AI companies, including DeepSeek, OpenAI, Google DeepMind , and Anthropic. Each brings unique benefits to the AI domain. DeepSeek focuses on modular and explainable AI, making it ideal for healthcare and finance industries where precision and transparency are vital.

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Towards AI

FEBRUARY 3, 2024

eds) Explainable AI: Interpreting, Explaining and Visualizing Deep Learning. link] Join thousands of data leaders on the AI newsletter. PLoS ONE 10(7), e0130140 (2015) [2] Montavon, G., Lapuschkin, S., Müller, KR. Layer-Wise Relevance Propagation: An Overview. In: Samek, W., Montavon, G., Vedaldi, A., Müller, KR.

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Marktechpost

AUGUST 7, 2024

The Role of Explainable AI in In Vitro Diagnostics Under European Regulations: AI is increasingly critical in healthcare, especially in vitro diagnostics (IVD). The European IVDR recognizes software, including AI and ML algorithms, as part of IVDs.

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Towards AI

MARCH 17, 2024

It is also garnering massive popularity in organizations and enterprises, with every corner of every business implementing LLMs, Stable Diffusion, and the next trendy AI product. Alongside this, there is a second boom in XAI or Explainable AI. Interpretability — Explaining the meaning of a model/model decisions to humans.

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Unite.AI

DECEMBER 17, 2024

Humans can validate automated decisions by, for example, interpreting the reasoning behind a flagged transaction, making it explainable and defensible to regulators. Financial institutions are also under increasing pressure to use Explainable AI (XAI) tools to make AI-driven decisions understandable to regulators and auditors.

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Towards AI

FEBRUARY 13, 2024

Introduction It’s been a while since I created this package ‘easy-explain’ and published it on Pypi. GradCam is a widely used Explainable AI method that has been extensively discussed in both forums and literature. The plotting functionality is also included, so you only need to run a few lines of code.

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NVIDIA

MAY 1, 2024

Their conversation spans a range of topics, including AI bias, the observability of AI systems and the practical implications of AI in business. The AI Podcast · Explainable AI: Insights from Arthur AI’s Adam Wenchel – Ep. 02:31: Real-world use cases of LLMs and generative AI in enterprises.

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ODSC - Open Data Science

NOVEMBER 30, 2023

Healthcare systems are implementing AI, and patients and clinicians want to know how it works in detail. Explainable AI might be the solution everyone needs to develop a healthier, more trusting relationship with technology while expediting essential medical care in a highly demanding world. What Is Explainable AI?

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Unite.AI

JANUARY 1, 2025

This collaborative model promotes the AI ecosystem, reducing reliance on narrow datasets. Using explainable AI systems and implementing regular checks can help identify and correct biases. For example, hugging Face s Datasets Repository allows researchers to access and share diverse data.

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Unite.AI

MARCH 1, 2025

Where AI Gene Editing Can Go From Here The future of AI gene editing hinges on how developers and end users can address the obstacles while leaning into the benefits. Explainable AI models will provide a positive step forward. Reliability issues like these can also be tricky to spot, further complicating the practice.

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AI News

MARCH 5, 2025

Yaniski Ravid featured representatives from leading AI companies, who shared how their organisations implement transparency in AI systems, particularly in retail and legal applications.

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Flipboard

DECEMBER 3, 2024

When you visit a hospital, artificial intelligence (AI) models can assist doctors by analysing medical images or predicting patient outcomes based on …

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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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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.

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Flipboard

FEBRUARY 14, 2025

Hemant Madaan, an expert in AI/ML and CEO of JumpGrowth, explores the ethical implications of advanced language models. Artificial intelligence (AI) has become a cornerstone of modern business operations, driving efficiencies and delivering insights across various sectors. However, as AI systems

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Unite.AI

JUNE 26, 2023

In addition to strict, reasonable and thorough regulations, developers should take steps to prevent AI-gone-wrong scenarios. Explainable AI — also known as white box AI — may solve transparency and data bias concerns. Explainable AI models are emerging algorithms allowing developers and users to access the model’s logic.

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Flipboard

FEBRUARY 1, 2023

AI image generators have been causing a stir in the creative industry for quite some time now, but the main issue is how these tools are undertaking …

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AI News

OCTOBER 8, 2024

So we would like to generalise some of these algorithms and then have a system that can more generally extract information grounded in legal reasoning and normative reasoning,” she explains. Kameswaran suggests developing audit tools for advocacy groups to assess AI hiring platforms for potential discrimination.

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AI Weekly

OCTOBER 3, 2024

At present, we’re in the midst of a furore about the much-abused term ‘AI’, and time will tell whether this particular storm will be seen as a teacup resident. plos.org Sponsor Personalize your newsletter about AI Choose only the topics you care about, get the latest insights vetted from the top experts online!

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AI Weekly

MARCH 20, 2025

theverge.com Google, OpenAI, Meta and Amazon turn to robotics AI companies are developing software and hardware for robots, whether for industrial or domestic use. The ability of these instruments to generate content, proofread, and even offer ideas has attracted broad controversy.

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Unite.AI

MARCH 6, 2025

Renowned for its ability to efficiently tackle complex reasoning tasks, R1 has attracted significant attention from the AI research community, Silicon Valley , Wall Street , and the media. Yet, beneath its impressive capabilities lies a concerning trend that could redefine the future of AI.

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Unite.AI

AUGUST 25, 2023

Can focusing on Explainable AI (XAI) ever address this? To engineers, explainable AI is currently thought of as a group of technological constraints and practices, aimed at making the models more transparent to people working on them. You can't really reengineer the design logic from the source code.

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TransOrg Analytics

FEBRUARY 11, 2025

These are just a few ways Artificial Intelligence (AI) silently influences our daily lives. As AI continues integrating into every aspect of society, the need for Explainable AI (XAI) becomes increasingly important. What is Explainable AI? Why is Explainable AI Important?

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Jay Alammar

MAY 3, 2021

Introducing the Explainable AI Cheat Sheet , your high-level guide to the set of tools and methods that helps humans understand AI/ML models and their predictions. I introduce the cheat sheet in this brief video:

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Unite.AI

DECEMBER 19, 2024

By leveraging multimodal AI, financial institutions can anticipate customer needs, proactively address issues, and deliver tailored financial advice, thereby strengthening customer relationships and gaining a competitive edge in the market.

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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.

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Marktechpost

JULY 6, 2023

On the other hand, explainable AI models are very complicated deep learning models that are too complex for humans to understand without the aid of additional methods. This is why when Explainable AI models can give a clear idea of why a decision was made but not how it arrived at that decision.

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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 (AI) models assist across various domains, from regression-based forecasting models to complex object detection algorithms in deep learning.

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Unite.AI

JUNE 18, 2024

Looking further ahead, one critical area of focus is Explainable AI , which aims to make AI decisions transparent and understandable. This transparency is necessary to build trust in AI systems and ensure they are used responsibly.

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