IBM Journey to AI blog

JANUARY 15, 2024

Generative AI is emerging as a valuable solution for automating and improving routine administrative and repetitive tasks. This technology excels at applying foundation models, which are large neural networks trained on extensive unlabeled data and fine-tuned for various tasks. It helps to ensure consistent outputs.

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Unite.AI

APRIL 9, 2024

Organizations deploying AI systems must adhere to ethical guidelines and legal requirements. Transparency is fundamental for responsible AI usage. Transparent AI is not optional—it is a necessity now. Fairness and privacy are critical considerations in responsible AI deployment.

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AI Weekly

JUNE 29, 2023

mit.edu Ethics AI ChatGPT Responds to UN’s Proposed Code of Conduct to Monitor AI Achieving a global consensus on the specifics of the code of conduct might be challenging, as different countries and stakeholders may have differing views on AI development, applications, and regulation.

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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

JULY 24, 2024

In the consumer technology sector, AI began to gain prominence with features like voice recognition and automated tasks. Over the past decade, advancements in machine learning, Natural Language Processing (NLP), and neural networks have transformed the field.

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Marktechpost

MAY 30, 2024

Introduction to AI and Machine Learning on Google Cloud This course introduces Google Cloud’s AI and ML offerings for predictive and generative projects, covering technologies, products, and tools across the data-to-AI lifecycle. It covers how to develop NLP projects using neural networks with Vertex AI and TensorFlow.

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Unite.AI

APRIL 26, 2024

All three architecture types can be extended using the mixture-of-experts (MoE) scaling technique, which sparsely activates a subset of neural network weights for each input. LLMs based on prefix decoders include GLM130B and U-PaLM. These layers introduce non-linearities and enable the model to learn more complex representations.

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Marktechpost

JULY 31, 2024

In AI, developing language models that can efficiently and accurately perform diverse tasks while ensuring user privacy and ethical considerations is a significant challenge. Traditional AI models often rely heavily on massive server-based computations, leading to challenges in efficiency and latency. Check out the Paper.

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NVIDIA

MAY 1, 2024

Gemma was developed from the same research and technology used to create the company’s Gemini models and is built for responsible AI development. ChatRTX also now supports ChatGLM3, an open, bilingual (English and Chinese) LLM based on the general language model framework.

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Unite.AI

MARCH 6, 2024

Gemma's architecture leverages advanced neural network techniques, particularly the transformer architecture, a backbone of recent AI developments. It also supports easy deployment options, including Vertex AI and Google Kubernetes Engine.

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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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Unite.AI

DECEMBER 1, 2023

As we continue to integrate AI more deeply into various sectors, the ability to interpret and understand these models becomes not just a technical necessity but a fundamental requirement for ethical and responsible AI development. The Scale and Complexity of LLMs The scale of these models adds to their complexity.

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ODSC - Open Data Science

MARCH 12, 2025

The next wave of advancements, including fine-tuned LLMs and multimodal AI, has enabled creative applications in content creation, coding assistance, and conversational agents. However, with this growth came concerns around misinformation, ethical AI usage, and data privacy, fueling discussions around responsible AI deployment.

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IBM Journey to AI blog

AUGUST 16, 2023

These include security and data leakage, confidentiality and liability concerns, intellectual property complexities, compliance with open-source licenses, limitations on AI development, and uncertain privacy and compliance with international laws. IBM watsonx strikes a balance between innovation and responsible AI usage.

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Unite.AI

SEPTEMBER 26, 2024

It all started in 2012 with AlexNet, a deep learning model that showed the true potential of neural networks. This move was vital in reducing development costs and encouraging innovation. The desire to cut costs could compromise the quality of AI solutions. But things have changed a lot since then.

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Becoming Human

APRIL 19, 2024

Transparency and Explainability Transparency in AI systems is crucial for building trust among users and stakeholders. Consultants must bridge this knowledge gap by providing education and training on ethical considerations in AI. Ethical leadership fosters a commitment to responsible AI consulting at all levels of the organization.

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Towards AI

FEBRUARY 14, 2023

Generative AI involves the use of neural networks to create new content such as images, videos, or text. Another important trend to watch in the future of generative AI is the growing focus on ethical and responsible AI development.

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NVIDIA

JUNE 20, 2023

Huang and Read backstage at Cannes Lions At the event attended by thousands of creators, marketers and brand execs from around the world, Huang outlined the impact of AI on the $700 billion digital advertising industry. He also touched on the ways AI can enhance creators’ abilities, as well as the importance of responsible AI development.

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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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Viso.ai

DECEMBER 20, 2023

At its core, the MindSpore open-source project is a solution that combines ease of development with advanced capabilities. It accelerates AI research and prototype development. The integrated approach promotes collaboration, innovation, and responsible AI practices with deep learning algorithms.

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Flipboard

JULY 28, 2023

The move is being welcomed by many AI developers, researchers, and academics who say this will give them unprecedented access to build new tools or study systems that would otherwise be prohibitively expensive to create. What matters more at this point, they say, is how that misinformation is distributed.

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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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Pickl AI

DECEMBER 16, 2024

With the global AI market exceeding $184 billion in 2024a $50 billion leap from 2023its clear that AI adoption is accelerating. This blog aims to help you navigate this growth by addressing key enablers of AI development. Key Takeaways Reliable, diverse, and preprocessed data is critical for accurate AI model training.

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Allen AI

FEBRUARY 1, 2024

The framework features a suite of completely open AI development tools, including: Full pretraining data : The model is built on AI2’s Dolma set which features three trillion token open corpus for language model pretraining, including code that produces the training data.

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ODSC - Open Data Science

OCTOBER 13, 2023

At ODSC West this October 30th to November 2nd, we’re excited to have some of the best and brightest in AI acting as our keynote speakers this year. Chelsea Finn, PhD Assistant Professor | Stanford University | In-Person | Session: Neural Networks Make Stuff Up. Here’s a bit more on each of them. What Should We do About it?

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ODSC - Open Data Science

MARCH 11, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI. And the best place to do that is at ODSC East this April 23rd to 25th !

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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. Generation With Neural Network Techniques Neural Networks are the most advanced techniques of automated data generation. This allows for: Developing Robust and Generalizable AI Models.

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ODSC - Open Data Science

FEBRUARY 29, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI. So get your pass today and see for yourself how AI will shape our future.

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Mlearning.ai

AUGUST 28, 2023

The idea of parallel processing and multi-path architectures could find applications in other AI domains, driving innovation and breakthroughs in fields such as computer vision, speech recognition, and more. Ethical Considerations and Responsible AI As with any powerful technology, responsible development and deployment are paramount.

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Viso.ai

FEBRUARY 12, 2024

Why do we need Explainable AI (XAI)? The complexity of machine learning models has exponentially increased from linear regression to multi-layered neural networks, CNNs , transformers , etc. While neural networks have revolutionized the prediction power, they are also black-box models.

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Pickl AI

JULY 18, 2023

Model Selection and Optimization Identifying appropriate machine learning models and techniques, fine-tuning parameters, and optimizing the performance of AI systems. Develop Programming Skills Master programming languages such as Python, R, or Java, which are widely used in AI development.

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Dlabs.ai

DECEMBER 6, 2022

launched an initiative called ‘ AI 4 Good ‘ to make the world a better place with the help of responsible AI. They use various state-of-the-art technologies, such as statistical modeling, neural networks, deep learning, and transfer learning to uncover the underlying relationships in data.

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Bugra Akyildiz

FEBRUARY 24, 2024

Increased Democratization: Smaller models like Phi-2 reduce barriers to entry, allowing more developers and researchers to explore the power of large language models. Responsible AI Development: Phi-2 highlights the importance of considering responsible development practices when building large language models.

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Unite.AI

JUNE 7, 2024

GANs consist of two neural networks : the generator and the discriminator. Robust frameworks are urgently required to limit misuse and protect the public from AI-driven scams and fraudulent activities. Moreover, AI creators bear ethical responsibility. Notable incidents involving deepfakes have already occurred.

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