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Daily AI Roundup: Biggest Machine Learning, Robotic And Automation Updates


This is our AI Daily Roundup today. We are covering the top updates from around the world. The updates will feature state-of-the-art capabilities in artificial intelligence (AI), Machine Learning, Robotic Process Automation, Fintech, and human-system interactions. We cover the role of AI Daily Roundup and its application in various industries and daily lives. The Eclipse Software's Software Defined Vehicle (SDV) Working Group Adds Seven New Projects

AI Is Learning Human Biases: Robot's Racist And Sexist Behaviour Shocks Researchers


'Everything a creator builds is in their own image' - a sentiment we've been fed since forever might actually be true. A robot recently shocked scientists after it became racist and sexist. While such deplorable behaviour is commonly observed among humans, we had better hopes from artificial intelligence. If you expected AI to be impartial and intellectually superior, that's clearly not the case. A recent experiment by researchers from John Hopkins University, Georgia Institute of Technology, and the University of Washington showed how a robot controlled by a machine learning tool began to categorise people based on dangerous stereotypes about race and gender.

3D Machine Learning 201 Guide: Point Cloud Semantic Segmentation


Having the skills and the knowledge to attack every aspect of point cloud processing opens up many ideas and development doors. It is like a toolbox for 3D research creativity and development agility. And at the core, there is this incredible Artificial Intelligence space that targets 3D scene understanding. It is particularly relevant due to its importance for many applications, such as self-driving cars, autonomous robots, 3D mapping, virtual reality, and the Metaverse. And if you are an automation geek like me, it is hard to resist the temptation to have new paths to answer these challenges! This tutorial aims to give you what I consider the essential footing to do just that: the knowledge and code skills for developing 3D Point Cloud Semantic Segmentation systems. But actually, how can we apply semantic segmentation? And how challenging is 3D Machine Learning? Let me present a clear, in-depth 201 hands-on course focused on 3D Machine Learning.

Azure Machine Learning vs IBM Watson: Software comparison


With the ability to revolutionize everything from self-driving cars to robotic surgeons, artificial intelligence is on the cutting edge of tech innovation. Two of the most widely recognized AI services are Microsoft's Azure Machine Learning and IBM's Watson. Both boast impressive functionality, but which one should you choose for your business? Azure Machine Learning is a cloud-based service that allows data scientists or developers to train, build and deploy ML models. It has a rich set of tools that makes it easy to create predictive analytics solutions. This service can be used to build predictive models using a variety of ML algorithms, including regression, classification and clustering.

The History of Artificial Intelligence - Science in the News


It began with the "heartless" Tin man from the Wizard of Oz and continued with the humanoid robot that impersonated Maria in Metropolis. By the 1950s, we had a generation of scientists, mathematicians, and philosophers with the concept of artificial intelligence (or AI) culturally assimilated in their minds. One such person was Alan Turing, a young British polymath who explored the mathematical possibility of artificial intelligence. Turing suggested that humans use available information as well as reason in order to solve problems and make decisions, so why can't machines do the same thing? This was the logical framework of his 1950 paper, Computing Machinery and Intelligence in which he discussed how to build intelligent machines and how to test their intelligence.

Humans in the loop help robots find their way: Computer scientists' interactive program aids motion planning for environments with obstacles


Engineers at Rice University have developed a method that allows humans to help robots "see" their environments and carry out tasks. The strategy called Bayesian Learning IN the Dark -- BLIND, for short -- is a novel solution to the long-standing problem of motion planning for robots that work in environments where not everything is clearly visible all the time. The peer-reviewed study led by computer scientists Lydia Kavraki and Vaibhav Unhelkar and co-lead authors Carlos Quintero-Peña and Constantinos Chamzas of Rice's George R. Brown School of Engineering was presented at the Institute of Electrical and Electronics Engineers' International Conference on Robotics and Automation in late May. The algorithm developed primarily by Quintero-Peña and Chamzas, both graduate students working with Kavraki, keeps a human in the loop to "augment robot perception and, importantly, prevent the execution of unsafe motion," according to the study. To do so, they combined Bayesian inverse reinforcement learning (by which a system learns from continually updated information and experience) with established motion planning techniques to assist robots that have "high degrees of freedom" -- that is, a lot of moving parts.

Consciousness And Light


Consciousness And Light Are Explored. The Inter Mind Bridges The Gap Between The Physical Mind And The Conscious Mind.

Global Big Data Conference


Artificial intelligence and machine learning careers have an attractive, futuristic sparkle about them. Artificial intelligence and machine learning applications are integral to the operations of countless industries, and their wide-scale adoption, coupled with projected steady growth, make them some of the hottest careers available. In today's time, high-paying jobs in India include data scientists, machine learning experts, blockchain developers, and many more related to the tech world. Artificial Intelligence has been one of the hottest buzzwords in the tech sphere for quite some time now. As Data Science is advancing, both AI and ML are also advancing by leaps and bounds. Essentially, AI is a broad canvas that encompasses machine learning, deep learning, and natural language processing (NLP), among other things.

The Role of Symbolic AI and Machine Learning in Robotics


Robotics is a multi-disciplinary field in computer science dedicated to the design and manufacture of robots, with applications in industries such as manufacturing, space exploration and defence. While the field has existed for over 50 years, recent advances such as the Spot and Atlas robots from Boston Dynamics are truly capturing the public's imagination as science fiction becomes reality. Traditionally, robotics has relied on machine learning/deep learning techniques such as object recognition. While this has led to huge advancements, the next frontier in robotics is to enable robots to operate in the real world autonomously, with as little human interaction as possible. Such autonomous robots differ to non-autonomous ones as they operate in an open world, with undefined rules, uncertain real-world observations, and an environment -- the real world -- which is constantly changing.

Fears AI may create sexist bigots as test learns 'toxic stereotypes'

Daily Mail - Science & tech

Fears have been raised about the future of artificial intelligence after a robot was found to have learned'toxic stereotypes' from the internet. The machine showed significant gender and racial biases, including gravitating toward men over women and white people over people of colour during tests by scientists. It also jumped to conclusions about peoples' jobs after a glance at their face. 'The robot has learned toxic stereotypes through these flawed neural network models,' said author Andrew Hundt, a postdoctoral fellow at Georgia Tech who co-conducted the work as a PhD student working in Johns Hopkins' Computational Interaction and Robotics Laboratory in Baltimore, Maryland. 'We're at risk of creating a generation of racist and sexist robots but people and organisations have decided it's OK to create these products without addressing the issues.'