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US Intel Warns China Could Dominate Advanced Technologies

#artificialintelligence

U.S. officials issued new warnings Friday about China's ambitions in artificial intelligence and a range of advanced technologies that could eventually give Beijing a decisive military edge and possible dominance over health care and other essential sectors in America. The warnings include a renewed effort to inform business executives, academics and local and state government officials about the risks of accepting Chinese investment or expertise in key industries, officials at the National Counterintelligence and Security Center said. While the center does not intend to tell officials to reject Chinese investment, it will encourage efforts to control intellectual property and implement security measures. National security agencies under President Joe Biden's administration are making an aggressive public push against China, which some officials have called the greatest strategic threat to the United States. The Biden administration has simultaneously tried to ease some tensions with Beijing dating to the Trump administration and seek common ground on trade and climate change.


Nvidia clarifies Megatron-Turing scale claim

ZDNet

You may have noticed that last week, Microsoft and Nvidia announced they had trained "the world's largest and most powerful generative language model," known as "Megatron-Turing NLG 530B," as ZDNet's Chris Duckett reported. The model, in this case, is a neural network program based on the "Transformer" approach that has become widely popular in deep learning. Megatron-Turing is able to produce realistic-seeming text and also perform on various language tests such as sentence completion. The news was somewhat perplexing in that Microsoft had already announced a program a year ago that seemed to be bigger and more powerful. While Megatron-Turing NLG 530B uses 530 billion neural "weights," or parameters, to compose its language model, what's known as "1T" has one trillion parameters.


What does the future of driverless cars look like?

NPR Technology

Amazon's autonomous vehicle unit, Zoox, announced plans to test-drive "robotaxis" in downtown Seattle. NPR's David Folkenflik speaks with historian Peter Norton.


NVIDIA and ROS Teaming Up To Accelerate Robotics Development

Robohub

The collaboration will improve the way ROS and NVIDIA's line of products such as Isaac SIM and the Jetson line of embedded boards operate together. NVIDIA's Isaac SIM lets developers build robust and scalable simulations. Their Jetson line of embedded boards is core to many robotics architectures, leveraging hardware-optimized chips for machine learning, computer vision, video processing, and more. The improvements to ROS will allow robotics companies to better utilize the available computational power, while still developing on the robotics-centric platform familiar to many. Amit Goel Amit Goel is Director of Product Management for Autonomous Machines at NVIDIA, where he leads the product development of NVIDIA Jetson, the most advanced platform for AI computing at the edge.


Why is Python popular?

#artificialintelligence

Python is a high-level, general-purpose programming language. It was created to have a syntax that would be easy to read and simple to understand. Python is also used for data science, machine learning, artificial intelligence, and other tasks where one needs a language that handles computation very efficiently. Python is popular because it's not too hard to learn and read. This makes it ideal for beginners or those looking for a way to make their code more efficient without learning another programming language.


3 Different Approaches for Train/Test Splitting of a Pandas Dataframe

#artificialintelligence

Usually, the Train/Test Splitting process is one of the Machine Learning tasks taken for granted. In fact, data scientists focus more on Data Preprocessing or Feature Engineering, delegating the process of dividing the dataset into a line of code. In this tutorial, I assume that the whole dataset is available as a CSV file, which is loaded as a Pandas Dataframe. As input parameters of the function either lists or Pandas Dataframes can be passed. Pandas provide a Dataframe function, named sample(), which can be used to split a Dataframe into train and test sets.


AI rules: what the European Parliament wants

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Parliament is working on the Commission proposal, presented on 21 April 2021, for turning Europe into the global hub for trustworthy AI. Ahead of the Commission's proposal on AI, the Parliament set up a special committee to analyse the impact of artificial intelligence on the EU economy. "Europe needs to develop AI that is trustworthy, eliminates biases and discrimination, and serves the common good, while ensuring business and industry thrive and generate economic prosperity," said the new committee chair Dragoș Tudorache. On 20 October 2020, Parliament adopted three reports outlining how the EU can best regulate AI while boosting innovation, ethical standards and trust in technology. One of the reports focuses on how to ensure safety, transparency and accountability, prevent bias and discrimination, foster social and environmental responsibility, and ensure respect for fundamental rights.


Scientists used a tiny brain implant to help a blind teacher see letters again

NPR Technology

Former science teacher Berna Gómez played a pivotal role in new research on restoring some sight to blind people. She is named as a co-author of the study that was published this week. Former science teacher Berna Gómez played a pivotal role in new research on restoring some sight to blind people. She is named as a co-author of the study that was published this week. A former science teacher who's been blind for 16 years became able to see letters, discern objects' edges -- and even play a Maggie Simpson video game -- thanks to a visual prosthesis that includes a camera and a brain implant, according to American and Spanish researchers who collaborated on the project.


Azure ML (AML) Alternatives for MLOps - neptune.ai

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Azure Machine Learning (AML) is a cloud-based machine learning service for data scientists and ML engineers. You can use AML to manage the machine learning lifecycle--train, develop, and test models, but also run MLOps processes with speed, efficiency, and quality. For organizations that want to scale ML operations and unlock the potential of AI, tools like AML are important. Creating machine learning solutions that drive business growth becomes much easier. But what if you don't need a comprehensive MLOps solution like AML? Maybe you want to build your own stack, and need specific tools for tasks like tracking, deployment, or for managing other key parts of MLOps? Experiment tracking documents every piece of information that you care about during your ML experiments. Machine learning is an iterative process, so this is really important. Azure ML provides experimental tracking for all metrics in the machine learning environment.


Artificial Intelligence

#artificialintelligence

The course is an introduction to the area of Artificial Intelligence and will introduce the basic ideas and techniques underlying the design of intelligent machines. By the end of this course, you will have learned how to build autonomous (software) agents that efficiently make decisions in fully informed, partially observable and adversarial settings as well as how to optimize actions in uncertain sequential decision making environments to maximize expected reward.