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. politico.com Will AI Take Over Your Job?

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IBM Journey to AI blog

DECEMBER 20, 2023

On retail websites, for instance, machine learning algorithms influence consumer buying decisions by making recommendations based on purchase history. They’re also part of a family of generative learning algorithms that model the input distribution of a given class or/category.

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ODSC - Open Data Science

MARCH 10, 2025

By 2017, deep learning began to make waves, driven by breakthroughs in neural networks and the release of frameworks like TensorFlow. Sessions on convolutional neural networks (CNNs) and recurrent neural networks (RNNs) started gaining popularity, marking the beginning of data sciences shift toward AI-driven methods.

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Unite.AI

APRIL 9, 2024

Composite AI is a cutting-edge approach to holistically tackling complex business problems. These techniques include Machine Learning (ML), deep learning , Natural Language Processing (NLP) , Computer Vision (CV) , descriptive statistics, and knowledge graphs. Transparency is fundamental for responsible AI usage.

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IBM Journey to AI blog

JANUARY 10, 2024

The category of AI algorithms includes ML algorithms, which learn and make predictions and decisions without explicit programming. Computing power: AI algorithms often necessitate significant computing resources to process such large quantities of data and run complex algorithms, especially in the case of deep learning.

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Pickl AI

AUGUST 1, 2024

Summary : Deep Learning engineers specialise in designing, developing, and implementing neural networks to solve complex problems. Introduction Deep Learning engineers are specialised professionals who design, develop, and implement Deep Learning models and algorithms.

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Deep Learning Neural Network Machine Learning Natural Language Processing 52

Unite.AI

DECEMBER 1, 2023

Exploring the Techniques of LIME and SHAP Interpretability in machine learning (ML) and deep learning (DL) models helps us see into opaque inner workings of these advanced models. Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP) are two such mainstream interpretability techniques.

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AWS Machine Learning Blog

MARCH 21, 2025

Amazon Bedrock is a fully managed service that provides a single API to access and use various high-performing foundation models (FMs) from leading AI companies. It offers a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI practices. samples/2003.10304/page_0.png'

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Metadata Convolutional Neural Networks Generative AI Data Scientist 111

Viso.ai

DECEMBER 20, 2023

Huawei’s Mindspore is an open-source deep learning framework for training and inference written in C++. license, MindSpore AI allows users to use, modify, and distribute the software. Our no-code solution enables teams to rapidly build real-world computer vision using the latest deep learning models out of the box.

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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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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

APRIL 3, 2024

However, this progress has significantly increased the energy demands of data centers powering these AI workloads. Extensive AI tasks have transformed data centers from mere storage and processing hubs into facilities for training neural networks , running simulations, and supporting real-time inference.

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ODSC - Open Data Science

MARCH 6, 2024

Be sure to check out her talk, “ Language Modeling, Ethical Considerations of Generative AI, and Responsible AI ,” there! Decades of technological innovation have shaped Artificial Intelligence (AI) as we know it today, but there has never been a moment for AI quite like the present one.

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NYU Center for Data Science

SEPTEMBER 11, 2024

What sets Dr. Ho apart is her pioneering work in applying deep learning techniques to astrophysics. Ho’s innovative approach has led to several groundbreaking achievements: Her team at Carnegie Mellon University was the first to apply 3D convolutional neural networks in astrophysics.

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ODSC - Open Data Science

MARCH 11, 2024

Introducing the Topic Tracks for ODSC East 2024 — Highlighting Gen AI, LLMs, and Responsible AI ODSC East 2024 , coming up this April 23rd to 25th, is fast approaching and this year we will have even more tracks comprising hands-on training sessions, expert-led workshops, and talks from data science innovators and practitioners.

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AssemblyAI

MAY 23, 2023

Neural Networks and Transformers What determines a language model's effectiveness? The performance of LMs in various tasks is significantly influenced by the size of their architectures, which are based on artificial neural networks. A simple artificial neural network with three layers.

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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. Then, in 2015, Google released TensorFlow, a powerful tool that made advanced machine learning libraries available to the public. The necessary hardware, software, and data storage costs were very high.

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Dlabs.ai

MARCH 17, 2021

But she works outside faculty as well, having co-founded AI4ALL , a non-profit organization intent on boosting diversity and inclusion in AI education, research, development, and policy. And her research expertise spans AI, machine learning , deep learning , computer vision , and cognitive neuroscience.

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Marktechpost

OCTOBER 14, 2024

raising widespread concerns about privacy threats of Deep Neural Networks (DNNs). raising widespread concerns about privacy threats of Deep Neural Networks (DNNs). To address this, data users need to apply strong and reliable defense strategies and methods. Check out the Paper.

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Google Research AI blog

FEBRUARY 10, 2023

We also had a number of interesting results on graph neural networks (GNN) in 2022. We provided a model-based taxonomy that unified many graph learning methods. Research in this area spans many products and uses principles from differential privacy (DP) and federated learning.

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Bugra Akyildiz

FEBRUARY 26, 2023

Libraries MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvements in both training algorithms and models. While deep learning models have replaced hand-designed features across many domains, these models are still trained with hand-designed optimizers.

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AWS Machine Learning Blog

JUNE 18, 2024

Traditional neural network models like RNNs and LSTMs and more modern transformer-based models like BERT for NER require costly fine-tuning on labeled data for every custom entity type. Amin Tajgardoon is an Applied Scientist in the Generative AI Innovation Center (GAIIC).

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Large Language Models Natural Language Processing LLM Computer Vision 119

Towards AI

FEBRUARY 14, 2023

Generative AI involves the use of neural networks to create new content such as images, videos, or text. How to Get Started With Generative AI? Getting started with generative AI can be a daunting task, but it is not as difficult as you might think.

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AWS Machine Learning Blog

FEBRUARY 24, 2023

This satisfies the strong MME demand for deep neural network (DNN) models that benefit from accelerated compute with GPUs. These include computer vision (CV), natural language processing (NLP), and generative AI models. The impact is more for models using a convolutional neural network (CNN).

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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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The MLOps Blog

JUNE 27, 2023

With extensive language support and integration with major deep learning frameworks, the Model Hub simplifies the integration of pre-trained models and libraries into existing workflows, making it a valuable resource for researchers, developers, and data scientists. Monitor the performance of machine learning models.

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Flipboard

APRIL 13, 2023

Prime Air (our drones) and the computer vision technology in Amazon Go (our physical retail experience that lets consumers select items off a shelf and leave the store without having to formally check out) use deep learning. To give a sense for the change in scale, the largest pre-trained model in 2019 was 330M parameters.

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AI Impacts

FEBRUARY 1, 2023

For a typical example, here is a diagram from a US Department of Defense report on responsible AI: 3 The system in this diagram is not formally evaluated for safety or performance until after “Acquisition/Development” 4 I do not find it surprising that this model is so common. 3 DoD Responsible AI Working Council (U.S.).

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Pickl AI

JULY 14, 2023

Machine Learning and Neural Networks (1990s-2000s): Machine Learning (ML) became a focal point, enabling systems to learn from data and improve performance without explicit programming. Techniques such as decision trees, support vector machines, and neural networks gained popularity.

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Neural Network Software Engineer Artificial Intelligence Artificial Intelligence 52

Heartbeat

OCTOBER 12, 2023

The Rise of Large Language Models The emergence and proliferation of large language models represent a pivotal chapter in the ongoing AI revolution. These models, powered by massive neural networks, have catalyzed groundbreaking advancements in natural language processing (NLP) and have reshaped the landscape of machine learning.

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ODSC - Open Data Science

FEBRUARY 25, 2025

Topics Include: AI Workflow Orchestration Low-Code/No-Code AI Development Scalability & Infrastructure Cost Management AI for Software Testing & Quality Assurance AI Copilots & Code Assistants Who Should Attend: Software Engineers, Developers, and AI Practitioners building production-ready AIsystems.

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Unite.AI

JANUARY 23, 2024

LLMs are a class of deep learning models that are pretrained on massive text corpora, allowing them to generate human-like text and understand natural language at an unprecedented level. Word2Vec pioneered the use of shallow neural networks to learn embeddings by predicting neighboring words.

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Large Language Models Prompt Engineering Prompt Engineer LLM 100

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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ODSC - Open Data Science

AUGUST 21, 2023

NLP and LLMs The NLP and LLMs track will give you the opportunity to learn firsthand from core practitioners and contributors about the latest trends in data science languages and tools, such as pre-trained models, with use cases focusing on deep learning, speech-to-text, and semantic search.

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Data Science Machine Learning Deep Learning Data Mining 52

Dlabs.ai

AUGUST 31, 2021

And you can expect them to cover topics as far-flung as business intelligence, machine learning, deep learning, AI algorithms, virtual assistants, and chatbots. Day two is for workshops — with twelve intimate sessions covering: “Practical machine learning for Python time series” “Uncertainty?

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Viso.ai

DECEMBER 18, 2023

Generation With Neural Network Techniques Neural Networks are the most advanced techniques of automated data generation. Neural networks can also synthesize unstructured data like images and video. 2: Generative Adversarial Network (GAN). Technique No.1: 1: Variational Auto-Encoder. Technique No.

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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. But that’s not all.

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