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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Marktechpost

DECEMBER 6, 2023

Google’s latest venture into artificial intelligence, Gemini, represents a significant leap forward in AI technology. Unveiled as an AI model of remarkable capability, Gemini is a testament to Google’s ongoing commitment to AI-first strategies, a journey that has spanned nearly eight years.

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NVIDIA

MARCH 1, 2024

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. What Is Trustworthy AI? Trustworthy AI is an approach to AI development that prioritizes safety and transparency for those who interact with it.

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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.

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Flipboard

JULY 28, 2023

Paige Vickers/Vox; Getty Images The AI debate splitting the tech world, explained. Last week, Meta made a game-changing move in the world of AI. Zuckerberg also made the case for why it’s better for leading AI models to be “open source,” which means making the technology’s underlying code largely available for anyone to use.

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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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Unite.AI

APRIL 30, 2024

AI models, particularly chatbots, learn from interactions through various learning paradigms, for example: In supervised learning , chatbots learn from labeled examples, such as historical conversations, to map inputs to outputs.

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NYU Center for Data Science

JANUARY 3, 2024

We wanted to develop a framework for understanding the toxicity of language that would take into account more than just what’s shown explicitly in the text,” Gabriel explains. This focus on the implicit meanings and the social context of language in AI models is crucial in an era where digital communication is omnipresent.

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Marktechpost

NOVEMBER 23, 2023

This technical prowess positions Leonardo as a crucial asset for advancing AI applications across Europe​​. REAL AI’s unique opportunity- “We aim to provide Europe’s answer to responsible AI development. Together with UNINA and AI supercomputer cluster ‘Leonardo’, we can make this possible”.

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Unite.AI

JANUARY 12, 2024

These innovations signal a shifting priority towards multimodal, versatile generative models. Competitions also continue heating up between companies like Google, Meta, Anthropic and Cohere vying to push boundaries in responsible AI development. Enhancing user trust via explainable AI also remains vital.

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Becoming Human

APRIL 19, 2024

This involves thoroughly examining training data, adjusting algorithms for fairness, and continuously monitoring and updating models to address emerging biases. Transparency and Explainability Transparency in AI systems is crucial for building trust among users and stakeholders.

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Marktechpost

MAY 2, 2024

Human-centricity, respect for democracy and human rights, environmental preservation, sustainable development, equality, non-discrimination, and innovation are the guiding principles of AI development in Brazil. AIDA would create standards for ethical AI development, design, and application with a focus on justice and safety.

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IBM Journey to AI blog

AUGUST 16, 2023

” We’ll come back to this story in a minute and explain how it relates to ChatGPT and trustworthy AI. As the world of artificial intelligence (AI) evolves, new tools like OpenAI’s ChatGPT have gained attention for their conversational capabilities.

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Pickl AI

APRIL 26, 2024

This can lead to discriminatory outcomes, for example, an AI-powered hiring tool trained on historical data might perpetuate existing biases against certain demographics. Ensuring fairness and mitigating bias in AI development is crucial. To reap the benefits and mitigate the risks, we must approach AI development responsibly.

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IBM Journey to AI blog

JANUARY 10, 2024

But even with the myriad benefits of AI, it does have noteworthy disadvantages when compared to traditional programming methods. AI development and deployment can come with data privacy concerns, job displacements and cybersecurity risks, not to mention the massive technical undertaking of ensuring AI systems behave as intended.

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Allen AI

JULY 27, 2023

The AI2 ImpACT License Project: Open, Responsible AI Licenses for the Common Good A new way to think about AI licensing By Jen Dumas, Crystal Nam, Will Smith, David Atkinson, and Nicole DeCario AI Is Everywhere; What Are the Risks? We welcome your feedback on this initiative: please reach us at ai2impact@allenai.org.

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AWS Machine Learning Blog

MAY 9, 2024

Additionally, pay special attention to the changing nature of the risk and cost that is associated with the development as well as the scaling of AI. To provide ethical integrity , an AI/ML CoE helps integrate robust guidelines and safeguards across the AI/ML lifecycle in collaboration with stakeholders.

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Viso.ai

DECEMBER 18, 2023

Organizations can easily source data to promote the development, deployment, and scaling of their computer vision applications. An example is a privacy-preserving solution for developing healthcare AI models. This allows for: Developing Robust and Generalizable AI Models. Rapid AI Development.

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