Unite.AI

NOVEMBER 22, 2024

Artificial Intelligence (AI) is making its way into critical industries like healthcare, law, and employment, where its decisions have significant impacts. However, the complexity of advanced AI models, particularly large language models (LLMs), makes it difficult to understand how they arrive at those decisions.

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Unite.AI

JUNE 26, 2023

At the root of AI mistakes like these is the nature of AI models themselves. Most AI today use “black box” logic, meaning no one can see how the algorithm makes decisions. Black box AI lack transparency, leading to risks like logic bias , discrimination and inaccurate results.

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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.

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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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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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Unite.AI

JANUARY 20, 2025

Ensures Compliance : In industries with strict regulations, transparency is a must for explaining AI decisions and staying compliant. Helps Users Understand : Transparency makes AI easier to work with. These safeguards ensure your data stays secure and under your control while still giving your AI what it needs to perform.

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Marktechpost

JUNE 8, 2024

Despite performing remarkably well on various tasks, these models are often unable to provide a clear understanding of how specific visual changes affect ML decisions. This step confirms that the images contain relevant information for the task. Join our Telegram Channel , Discord Channel , and LinkedIn Gr oup.

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Unite.AI

AUGUST 13, 2024

This allowed Microsoft’s representatives to attend board meetings and access confidential information. The close ties between the two companies and Microsoft's ability to access confidential information attracted scrutiny from regulators regarding fair competition and market practices. However, they would not possess voting rights.

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IBM Journey to AI blog

AUGUST 9, 2024

Generative AI (gen AI) is artificial intelligence that responds to a user’s prompt or request with generated original content, such as audio, images, software code, text or video. Gen AI models are trained on massive volumes of raw data.

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IBM Journey to AI blog

JANUARY 25, 2024

How might this insight affect evaluation of AI models? Model (in)accuracy To quote a common aphorism, all models are wrong. This holds true in the areas of statistics, science and AI. Models created with a lack of domain expertise can lead to erroneous outputs. How are you making your model explainable?

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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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AWS Machine Learning Blog

NOVEMBER 15, 2024

These safeguards can be created for multiple use cases and implemented across multiple FMs, depending on your application and responsible AI requirements. Content filters can be used to detect and filter harmful or toxic user inputs and model-generated outputs.

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Unite.AI

MARCH 18, 2024

As generative AI technology advances, there's been a significant increase in AI-generated content. 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.

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Unite.AI

DECEMBER 13, 2023

The future involves human-AI collaboration to tackle evolving trends and threats in 2024. Importance of Staying Updated on Trends Staying updated on AI trends is crucial because it keeps you informed about the latest advancements, ensuring you remain at the forefront of technological innovation.

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IBM Journey to AI blog

AUGUST 17, 2023

Next, the teams trained a foundation model using watsonx.ai , a powerful studio for training, validating, tuning and deploying generative AI models for business. That’s why the US Open will also use watsonx.governance to direct, manage and monitor its AI activities.

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Dlabs.ai

AUGUST 16, 2022

One of the major hurdles to AI adoption is that people struggle to understand how AI models work. This is the challenge that explainable AI solves. Explainable artificial intelligence shows how a model arrives at a conclusion. What is explainable AI? Let’s begin.

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Unite.AI

SEPTEMBER 13, 2023

Increasingly though, large datasets and the muddled pathways by which AI models generate their outputs are obscuring the explainability that hospitals and healthcare providers require to trace and prevent potential inaccuracies. In this context, explainability refers to the ability to understand any given LLM’s logic pathways.

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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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IBM Journey to AI blog

FEBRUARY 8, 2024

For industries providing essential services to clients such as insurance, banking and retail, the law requires the use of a fundamental rights impact assessment that details how the use of AI will affect the rights of customers. Higher risk tiers have more transparency requirements including model evaluation, documentation and reporting.

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IBM Journey to AI blog

MARCH 7, 2023

The specific approach we took required the use of both AI and edge computing to create a predictive model that could process years of anonymized data to help doctors make informed decisions. We wanted to be able to help them observe and monitor the thousands of data points available to make informed decisions.

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IBM Journey to AI blog

OCTOBER 16, 2023

It encompasses risk management and regulatory compliance and guides how AI is managed within an organization. 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.

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IBM Journey to AI blog

SEPTEMBER 18, 2023

Siloed processes can become integrated by using intelligent workflows, which help enable seamless and automated exchange of financial, informational and physical supply chain data in one distributed network. It can help connect disparate and disconnected manual processes and platforms to a data-driven and connected trade ecosystem.

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IBM Journey to AI blog

AUGUST 12, 2024

LLM usage in generative AI LLMs like Granite from IBM, GPT-4 from OpenAI, are designed to intake and generate human-like text based on large datasets. They are employed in various applications, from generating content to making informed decisions, thanks to their ability to detect context and produce coherent responses.

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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)?

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ODSC - Open Data Science

JANUARY 29, 2025

It is a critical aspect of making AI systems more effective in real-world applications as it helps bridge the gap between humans and machines through contextual understanding. Grounded AI models have improved accuracy and reliability, enabling them to better interpret the nuances of human language and behavior.

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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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NVIDIA

MARCH 1, 2024

Developers of trustworthy AI understand that no model is perfect, and take steps to help customers and the general public understand how the technology was built, its intended use cases and its limitations.

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Unite.AI

JULY 2, 2024

GDPR's stringent data protection standards present several challenges for businesses using personal data in AI. Similarly, the California Consumer Privacy Act (CCPA) significantly impacts AI by requiring companies to disclose data collection practices to ensure that AI models are transparent, accountable, and respectful of user privacy.

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IBM Journey to AI blog

MARCH 4, 2024

Adopting an open technologies-based hybrid cloud platform enables an AI+ enterprise to make informed decisions without limiting its business. Operations Incidents occur, even in an AI-first world. However, an AI+ enterprise uses AI not only to delight customers but also to solve IT problems.

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Marktechpost

AUGUST 24, 2024

EXplainable AI (XAI) has become a critical research domain since AI systems have progressed to being deployed in essential sectors such as health, finance, and criminal justice. The intrinsic complexity—the so-called “black boxes”—given by AI models makes research in the field of XAI difficult.

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Pickl AI

JANUARY 12, 2025

Data forms the backbone of AI systems, feeding into the core input for machine learning algorithms to generate their predictions and insights. For instance, in retail, AI models can be generated using customer data to offer real-time personalised experiences and drive higher customer engagement, consequently resulting in more sales.

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Towards AI

OCTOBER 3, 2024

Yet, despite these advancements, AI still faces significant limitations — particularly in adaptability, energy consumption, and the ability to learn from new situations without forgetting old information. As we stand on the cusp of the next generation of AI, addressing these challenges is paramount.

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Marktechpost

AUGUST 13, 2024

However, the challenge lies in integrating and explaining multimodal data from various sources, such as sensors and images. AI models are often sensitive to small changes, necessitating a focus on trustworthy AI that emphasizes explainability and robustness.

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Unite.AI

JANUARY 12, 2024

Enhancing user trust via explainable AI also remains vital. Addressing these technical obstacles will be key to unlocking multimodal AI's capabilities. Meta-learning Meta-learning, or ‘learning to learn', focuses on equipping AI models with the ability to rapidly adapt to new tasks using limited data samples.

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IBM Journey to AI blog

JULY 17, 2023

Generative AI has the potential to significantly disrupt customer care, leveraging large language models (LLMs) and deep learning techniques designed to understand complex inquiries and offer to generate more human-like conversational responses. Watsonx.data allows scaling of AI workloads using customer data. Watsonx.ai

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Marktechpost

MAY 8, 2024

Among the main advancements in AI, seven areas stand out for their potential to revolutionize different sectors: neuromorphic computing, quantum computing for AI, Explainable AI (XAI), AI-augmented design and Creativity, Autonomous Vehicles and Robotics, AI in Cybersecurity and AI for Environmental Sustainability.

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Unite.AI

SEPTEMBER 20, 2024

Its real-time trend analysis, investment evaluations, risk assessments, and automation features empower financial professionals to make informed choices efficiently. The platform's machine learning models learn from large datasets, identifying patterns and trends that might take time to become apparent.

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