AI Weekly

JUNE 1, 2023

thelancet.com Ethics Australia says tougher laws needed on AI On 1st June, Australia said on Thursday it planned to regulate AI including a potential ban on deep fakes and realistic-looking but false content, amid concerns the technology could be misuse. spacenews.com Robot Passes Turing Test for Polyculture Gardening I love plants.

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IBM Journey to AI blog

OCTOBER 16, 2023

They are used in everything from robotics to tools that reason and interact with humans. Foundation models are widely used for ML tasks like classification and entity extraction, as well as generative AI tasks such as translation, summarization and creating realistic content. ” Are foundation models trustworthy? .

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Metadata Explainability Automation Explainable AI 220

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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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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Robotics Explainability Explainable AI Categorization 107

ODSC - Open Data Science

JANUARY 29, 2025

Grounding Techniques Over the years, several innovative techniques have been developed to address the challenges of grounding inAI: Embodied AI Embodied AI integrates physical systems, such as robots or drones, to enable interaction with the environment.

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Robotics Explainable AI Data Scientist Explainability 40

Mlearning.ai

DECEMBER 31, 2023

Principles of Explainable AI( Source ) Imagine a world where artificial intelligence (AI) not only makes decisions but also explains them as clearly as a human expert. This isn’t a scene from a sci-fi movie; it’s the emerging reality of Explainable AI (XAI). What is Explainable AI?

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IBM Journey to AI blog

SEPTEMBER 24, 2024

Abhisesh Silwal, a systems scientist at Carnegie Mellon University whose research focuses on AI and robotics in agriculture, thinks so. Guerena’s project, called Artemis, uses AI and computer vision to speed up the phenotyping process. We get tired, lose our focus, or just physically can’t see all that we need to.

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Aiiot Talk

JULY 7, 2023

When developers and users can’t see how AI connects data points, it is more challenging to notice flawed conclusions. Black-box AI poses a serious concern in the aviation industry. In fact, explainability is a top priority laid out in the European Union Aviation Safety Administration’s first-ever AI roadmap.

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Black Box AI Algorithm Explainability Explainable AI 130

Pickl AI

FEBRUARY 17, 2025

AlphaGo) and robotics. Transparency and Explainability As Machine Learning models become increasingly complex, ensuring transparency and explainability remains a significant challenge. Approximately 44% of organisations express concerns about transparency in AI adoption. Notable applications include game playing (e.g.,

Machine Learning 52

Machine Learning Algorithm Explainability Data Quality 52

NVIDIA

MARCH 1, 2024

Transparency: Making AI Explainable To create a trustworthy AI model, the algorithm can’t be a black box — its creators, users and stakeholders must be able to understand how the AI works to trust its results. To reduce unwanted bias, developers might incorporate different variables into their models.

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ODSC - Open Data Science

AUGUST 14, 2023

“I still don’t know what AI is” If you’re like my parents and think I work at ChatGPT, then you may have to learn a little bit more about AI. Funny enough, you can use AI to explain AI. And now that you understand what AI is, it’s all about using it, leading to the next point.

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Artificial Intelligence Artificial Intelligence Explainability Explainable AI 98

Towards AI

OCTOBER 3, 2024

Lifelong Learning Models: Research aims to develop models that can learn incrementally without forgetting previous knowledge, which is essential for applications in autonomous systems and robotics.

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Neural Network Algorithm Continuous Learning AI 124

ODSC - Open Data Science

SEPTEMBER 26, 2024

The NVIDIA AI Hackathon at ODSC West, Reinforcement Learning for Finance, the Future of Humanoid AI Robotics, and Detecting Anomalies Unleash Innovation at the NVIDIA AI Hackathon at ODSC West 2024 Ready to put your data science skills to the test? Where do explainable AI models come into play?

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Robotics Data Science Large Language Models Explainable AI 52

ODSC - Open Data Science

FEBRUARY 18, 2025

Computer VisionAI agents in autonomous robotics interpret visual data to navigate complex environments, such as self-driving cars. Recent breakthroughs include OpenAIs GPT models, Google DeepMinds AlphaFold for protein folding, and AI-powered robotic assistants in industrial automation.

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Explainability Automation AI AI 59

Marktechpost

AUGUST 24, 2023

You will never miss any updates on ML/AI/CV/NLP fields because it is posted on a daily basis and highly moderated to avoid any spam. Discussions about automation, additive manufacturing, robots, AI, and all the other technologies we’ve developed to enable a world without menial work can be found on the r/Automate subreddit.

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Pickl AI

DECEMBER 10, 2024

Summary : Data Analytics trends like generative AI, edge computing, and Explainable AI redefine insights and decision-making. Key Takeaways Generative AI simplifies data insights, enabling actionable decision-making and enhancing data storytelling.

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Explainable AI Explainability ETL Automation 52

Pickl AI

JANUARY 13, 2025

Key Features: Comprehensive coverage of AI fundamentals and advanced topics. Explains search algorithms and game theory. Using simple language, it explains how to perform data analysis and pattern recognition with Python and R. Explains real-world applications like fraud detection. Explains big datas role in AI.

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Pickl AI

JULY 14, 2023

Reinforcement Learning and Robotics (2010s-2020s): Reinforcement Learning (RL) gained traction, focusing on training AI agents to make sequential decisions based on rewards and punishments. Researchers began addressing the need for Explainable AI (XAI) to make AI systems more understandable and interpretable.

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Neural Network Software Engineer Artificial Intelligence Artificial Intelligence 52

Pickl AI

SEPTEMBER 17, 2024

Explain The Concept of Supervised and Unsupervised Learning. Explain The Concept of Overfitting and Underfitting In Machine Learning Models. Explain The Concept of Reinforcement Learning and Its Applications. Reinforcement learning has applications in areas such as robotics, game playing, and resource allocation.

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Pickl AI

SEPTEMBER 3, 2024

Autonomous Systems In robotics and autonomous vehicles, ANNs play a crucial role in enabling machines to perceive their environment and make decisions based on sensory input. This is particularly useful in applications such as spam detection in emails, sentiment analysis of social media posts, and credit scoring in finance.

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Neural Network Convolutional Neural Networks Natural Language Processing Machine Learning 52

How to Learn Machine Learning

JANUARY 21, 2023

Artificial intelligence (AI) is a term that encompasses the use of computer technology to solve complex problems and mimic human decision-making. At its core, AI relies on algorithms, data processing, and machine learning to generate insights from vast amounts of data. In the years to come, AI is expected to become even more powerful.

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Artificial Intelligence Artificial Intelligence Robotics Natural Language Processing 52

Ofemwire

MARCH 1, 2024

At its core, AI is designed to replicate or even surpass human cognitive functions, employing algorithms and machine learning to interpret complex data, make decisions, and execute tasks with unprecedented speed and accuracy. If you dont get that, let me explain what AI is, like I would do to a fifth grader.

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Neural Network Machine Learning Artificial Intelligence Artificial Intelligence 52

Viso.ai

JANUARY 21, 2025

This tech is powering some of the biggest advancements in virtual reality, augmented reality, and robotics. Explainable AI (XAI) in Vision Systems Explainable Artificial Intelligence (XAI) focuses on making AI decision-making transparent and understandable. These methods create detailed 3D maps of environments.

Computer Vision 52

Computer Vision Artificial Intelligence Artificial Intelligence Explainability 52

Pickl AI

JANUARY 29, 2024

AI comprises Natural Language Processing, computer vision, and robotics. AI Engineer, Machine Learning Engineer, and Robotics Engineer are prominent roles in AI. Emerging Trends Emerging trends in Data Science include integrating AI technologies and the rise of Explainable AI for transparent decision-making.

Data Science 52

Data Science ML Machine Learning Artificial Intelligence 52

Pickl AI

NOVEMBER 5, 2024

AI encompasses various subfields, including Machine Learning (ML), Natural Language Processing (NLP), robotics, and computer vision. Together, Data Science and AI enable organisations to analyse vast amounts of data efficiently and make informed decisions based on predictive analytics.

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Data Science Artificial Intelligence Artificial Intelligence Machine Learning 52

Mlearning.ai

MARCH 24, 2023

Nonetheless, the pursuit of artificial intelligence continued to drive progress in computer science and robotics. In present day, we are seeing AI systems that appear truly intelligent, machines that can not only mimic human behavior, but also learn, reason, and solve complex problems in ways that were once thought impossible.

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Artificial Intelligence Artificial Intelligence Categorization Explainability 52

ODSC - Open Data Science

FEBRUARY 25, 2025

This track brings together industry pioneers and leading researchers to showcase the breakthroughs shaping tomorrows AI landscape. This track is designed to help practitioners strengthen their ML foundations while exploring advanced algorithms and deployment techniques.

Data Scientist 52

Data Scientist Large Language Models Machine Learning ML Engineer 52

Pickl AI

AUGUST 14, 2024

Robotics Neural networks are also applied in robotics, enabling machines to learn from their environments and perform complex tasks. Explainable AI (XAI): Efforts to make neural networks more interpretable, allowing users to understand how models make decisions.

Neural Network 52

Neural Network Machine Learning Convolutional Neural Networks Natural Language Processing 52

Viso.ai

DECEMBER 6, 2023

Real-Life Applications of Pose Estimation Pose estimation has many applications, some of which include: Computer vision robotics, where pose estimation models can help train robotic movements. Future Directions Explainable AI: Explainable AI (XAI) is one research paradigm that can help you detect biases easily.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Categorization 52

Pickl AI

JULY 24, 2024

The Golden Age of AI (1960s-1970s) Experts often refer to the 1960s and 1970s as the “Golden Age of AI.” ” During this time, researchers made remarkable strides in natural language processing, robotics, and expert systems. 2011: IBM Watson defeats Ken Jennings on the quiz show “Jeopardy! .”

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Artificial Intelligence Artificial Intelligence Natural Language Processing Neural Network 52

The MLOps Blog

FEBRUARY 27, 2025

A StereoSet prompt might be: “The software engineer was explaining the algorithm. How to integrate transparency, accountability, and explainability? Syntax of a robots-txt file to prevent agents from crawling a website. Lets see how to use them in a simple example. After the meeting, went back to coding.”

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LLM Large Language Models Explainability Machine Learning 64

Pickl AI

NOVEMBER 18, 2024

It’s commonly used in robotics, gaming, and autonomous systems. Explainable AI (XAI) The demand for transparency in Machine Learning Models is growing. Explainable AI (XAI) focuses on making complex models more interpretable to humans. Let’s explore some of the key trends.

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Pickl AI

AUGUST 1, 2024

Techniques such as explainable AI (XAI) aim to provide insights into model behaviour, allowing users to gain confidence in AI-driven decisions, especially in critical fields like healthcare and finance. Proficiency in programming languages like Python, experience with Deep Learning frameworks (e.g.,

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Deep Learning Neural Network Machine Learning Natural Language Processing 52

Marktechpost

JULY 11, 2023

AI agents, the computer programs that interact with the environment to make decisions operate autonomously, or interact with humans or other agents using natural language.

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AI Impacts

DECEMBER 22, 2022

I agree with lc that there seems to have been a quasi-taboo on the topic, which perhaps explains a lot of the non-discussion, though still calls for its own explanation. I think it suggests that concerns about uncooperativeness play a part, and the same for thinking of slowing down AI as centrally involving antisocial strategies.

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IBM Journey to AI blog

SEPTEMBER 3, 2024

According to a World Economic Forum report, nearly half of the surveyed organizations expect AI to create new jobs, while almost a quarter see it as a cause of job losses. Take action: Adopt explainable AI techniques. Explore explainable AI tools, such as IBM’s open source AI Explainability 360 toolkit.

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Explainability AI AI Deep Learning 215

NVIDIA

MARCH 18, 2025

Japan : Leading cloud providers including GMO Internet, Highreso, KDDI, Rutilea and SAKURA internet are building NVIDIA-powered AI infrastructure to transform industries such as robotics, automotive, healthcare and telecom.

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