AI News

APRIL 19, 2024

The tech giant is releasing the models via an “open by default” approach to further an open ecosystem around AI development. Llama 3 will be available across all major cloud providers, model hosts, hardware manufacturers, and AI platforms.

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Unite.AI

JANUARY 2, 2025

By setting a new benchmark for ethical and dependable AI , Tlu 3 ensures accountability and makes AI systems more accessible and relevant globally. The Importance of Transparency in AI Transparency is essential for ethical AI development. This is particularly important in areas like hiring.

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IBM Journey to AI blog

MARCH 27, 2024

In fact, they are central to the innovation and continued development of this field. Women have been challenging the outdated notion that AI development solely belongs to those who code and construct algorithms—a field that, while shifting, remains significantly male-dominated—for years.

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AI News

SEPTEMBER 22, 2023

In a stark address to the UN, UK Deputy PM Oliver Dowden has sounded the alarm on the potentially destabilising impact of AI on the world order. Speaking at the UN General Assembly in New York, Dowden highlighted that the UK will host a global summit in November to discuss the regulation of AI.

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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.

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AI News

OCTOBER 24, 2024

This support aims to enhance the UK’s infrastructure to stay competitive in the AI market. Public sector integration: The UK Government Digital Service (GDS) is working to improve efficiency using predictive algorithms for future pension scheme behaviour.

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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.

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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. Transparency is non-negotiable because it: Builds Trust : When people understand how AI makes decisions, theyre more likely to trust and embrace it.

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IBM Journey to AI blog

JANUARY 15, 2024

The differences between generative AI and traditional AI To understand the unique challenges that are posed by generative AI compared to traditional AI, it helps to understand their fundamental differences. Teams should have the ability to comprehend and manage the AI lifecycle effectively.

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Unite.AI

MARCH 27, 2024

Back then, people dreamed of what it could do, but now, with lots of data and powerful computers, AI has become even more advanced. Along the journey, many important moments have helped shape AI into what it is today. Today, AI benefits from the convergence of advanced algorithms, computational power, and the abundance of data.

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Unite.AI

JULY 24, 2024

In 2017, Apple introduced Core ML , a machine learning framework that allowed developers to integrate AI capabilities into their apps. Core ML brought powerful machine learning algorithms to the iOS platform, enabling apps to perform tasks such as image recognition, NLP, and predictive analytics.

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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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Unite.AI

DECEMBER 1, 2023

Machine learning , a subset of AI, involves three components: algorithms, training data, and the resulting model. An algorithm, essentially a set of procedures, learns to identify patterns from a large set of examples (training data). This obscurity makes it challenging to understand the AI's decision-making process.

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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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ODSC - Open Data Science

NOVEMBER 21, 2024

Alfred Spector: Beyond Models — Applying AI and Data Science Effectively In the rapidly evolving fields of AI and data science, the emphasis often falls on data collection, model building, and machine learning algorithms.

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Marktechpost

DECEMBER 24, 2023

This ethical consciousness adds depth to the paper’s contributions, aligning it with broader discussions on responsible AI development and deployment. In conclusion, the paper significantly addresses the multifaceted safety challenges in LLMs.

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AWS Machine Learning Blog

JANUARY 28, 2025

By investing in robust evaluation practices, companies can maximize the benefits of LLMs while maintaining responsible AI implementation and minimizing potential drawbacks. To support robust generative AI application development, its essential to keep track of models, prompt templates, and datasets used throughout the process.

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Unite.AI

JULY 1, 2024

It doesn’t matter if you are an online consumer or a business using that information to make key decisions – responsible AI systems allow all of us to fully and better understand information, as you need to ensure what is coming out of Generative AI is accurate and reliable.

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Flipboard

DECEMBER 31, 2023

Moral and Ethical Judgment: AI algorithms can make decisions based on their programming, but they cannot truly understand the moral or ethical implications of those choices. This ability to weigh different factors and make decisions that are aligned with human values is essential for responsible AI development.

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NYU Center for Data Science

DECEMBER 12, 2023

In an era where algorithms determine everything from creditworthiness to carceral sentencing, the imperative for responsible innovation has never been more urgent. The Center for Responsible AI (NYU R/AI) is leading this charge by embedding ethical considerations into the fabric of artificial intelligence research and development.

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Flipboard

APRIL 1, 2025

To improve factual accuracy of large language model (LLM) responses, AWS announced Amazon Bedrock Automated Reasoning checks (in gated preview) at AWS re:Invent 2024. Through systematic validation and continuous refinement, organizations can make sure that their AI applications deliver consistent, accurate, and trustworthy results.

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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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ODSC - Open Data Science

MARCH 12, 2025

However, with this growth came concerns around misinformation, ethical AI usage, and data privacy, fueling discussions around responsible AI deployment. Takeaway: The rapid evolution of LLMs suggests a shift from model development to domain-specific applications and ethical considerations.

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Unite.AI

JULY 12, 2024

Between 2024 and 2030, the AI market is expected to grow at a CAGR of 36.6% Needless to say, the pool of AI-driven solutions will only expand— more choices, more decisions. Together with strict regulations underway, responsible AI development has become paramount, with an emphasis on transparency, safety, and sustainability.

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Marktechpost

JANUARY 7, 2024

Bias and Discrimination : If AI algorithms are trained on biased or discriminatory data, they can perpetuate and amplify existing biases, leading to unfair and discriminatory outcomes, especially in areas like hiring, lending, or law enforcement.

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AWS Machine Learning Blog

FEBRUARY 25, 2025

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

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Marktechpost

NOVEMBER 15, 2023

Before TRUST, the stock media industry faced potential problems related to using unlicensed data for training AI systems. This raised questions about copyright infringement and fair compensation for creators whose work contributes to developing these powerful algorithms.

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NYU Center for Data Science

NOVEMBER 26, 2024

CDS Faculty Fellow Umang Bhatt l eading a practical workshop on Responsible AI at Deep Learning Indaba 2023 in Accra In Uganda’s banking sector, AI models used for credit scoring systematically disadvantage citizens by relying on traditional Western financial metrics that don’t reflect local economic realities.

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AWS Machine Learning Blog

JANUARY 29, 2025

Decentralized model In a decentralized approach, generative AI development and deployment are initiated and managed by the individual LOBs themselves. LOBs have autonomy over their AI workflows, models, and data within their respective AWS accounts.

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Towards AI

FEBRUARY 14, 2023

Generative AI is a fascinating field that has gained a lot of attention in recent years. It involves using machine learning algorithms to generate new data based on existing data. In this article, we will explore what generative AI is, how it is being used today, and what the future holds for this exciting field.

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Becoming Human

APRIL 19, 2024

The rise of AI consulting services AI consulting services have emerged as a key player in the digital transformation landscape. Businesses are leveraging the expertise of AI consultants to navigate the complexities of implementing AI solutions, from developing custom algorithms to integrating off-the-shelf AI tools.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

Verifiable evaluation scores are provided across text generation, summarization, classification and question answering tasks, including customer-defined prompt scenarios and algorithms. FMEval allows you to upload your own prompt datasets and algorithms. Depending on the evaluation algorithm you are utilizing these fields may vary.

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Unite.AI

JANUARY 12, 2024

Competitions also continue heating up between companies like Google, Meta, Anthropic and Cohere vying to push boundaries in responsible AI development. The Evolution of AI Research As capabilities have grown, research trends and priorities have also shifted, often corresponding with technological milestones.

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Marktechpost

AUGUST 7, 2024

Artificial Intelligence (AI) has rapidly advanced, revolutionizing various sectors by performing tasks that require human intelligence, such as learning, reasoning, and problem-solving. Improvements in machine learning algorithms, computational capabilities, and the availability of large datasets drive these advancements.

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Marktechpost

APRIL 20, 2024

With expertise spanning technical AI knowledge, policy, and governance, the group aims to increase transparency and foster collective solutions to the challenges of AI safety evaluation. of the AI Safety Benchmark.

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ODSC - Open Data Science

OCTOBER 9, 2023

Microsoft Azure One of the giants of the cloud computing realm, Microsoft Azure offers a comprehensive suite of AI and machine learning services that are easy to use, scalable, and backed by Microsoft’s commitment to responsible AI.

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Towards AI

JANUARY 6, 2025

Professional Development Certificate in Applied AI by McGill UNIVERSITY The Professional Development Certificate in Applied AI from McGill is an appropriate advanced and practical program designed to equip professionals with actionable industry-relevant knowledge and skills required to be senior AI developers and the ranks.

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