robot


Artificial Intelligence: Automation is transforming the workplace

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The concept of artificial intelligence (AI) was first used in 1956. New technologies have made AI more and more efficient, and robots are now able to perform human actions. Intelligent robots can perform increasingly complex tasks, most of the time in the workplace. In order to improve their performance, companies are increasingly using new technologies. The industrial robot is one of the most used tools; they resort to increasing production rates and output.


We Need a Drastic Rethink on Export Controls for AI

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Dave Aitel is the founder and CTO of Immunity. You can follow him @daveaitel. Export control on AI and machine learning algorithms is becoming a more important part of national security strategy as the world moves to a great-power competition landscape and technological changes force accommodation and rapid change to many national interests. However, like security software before it, AI presents unique challenges to how export control has traditionally worked, and these should be considered before being codified into international regulatory frameworks. As an example, on January 6, 2020, The Bureau of Industry and Security (BIS) in the U.S. Department of Commerce released the following rule, which imposed a license requirement on a particular kind of software useful for automatically identifying objects from drone or other imagery: "Geospatial imagery "software" "specially designed" for training a Deep Convolutional Neural Network to automate the analysis of geospatial imagery and point clouds, and having all of the following: Technical Note: A point cloud is a collection of data points defined by a given coordinate system. A point cloud is also known as a digital surface model."


We know ethics should inform AI. But which ethics?

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Artificial intelligence (AI) relies on big data and machine learning for myriad applications, from autonomous vehicles to algorithmic trading and from clinical decision support systems to data mining. The availability of large amounts of data is essential to the development of AI. But the scandal over the use of personal and social data by Facebook and Cambridge Analytica has brought ethical considerations to the fore - and it's just the beginning. As AI applications require ever greater amounts of data to help machines learn and perform tasks hitherto reserved for humans, companies are facing increasing public scrutiny, at least in some parts of the world. Tesla and Uber have scaled down their efforts to develop autonomous vehicles in the wake of widely reported accidents.


How a McKinsey co-designed robot is creating a better future for minimally invasive surgery

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February 12, 2020When German internist and surgeon Georg Kelling performed the first laparoscopic surgery in 1901, he likely hadn't envisioned that machines would one day follow in his footsteps. But today, robotic surgery is a health-care reality that promises certain benefits, like improved surgical precision that can contribute to quicker patient healing times. Still, widespread adoption of the technology has remained elusive. "The traditional approach to robotic surgery brings with it a lot of complexity and high cost," says Marcus Heneen, a design director at McKinsey Design. Today's surgical robots, Marcus explains, tend to situate the surgeon at a console in a non-sterile environment away from the patient.


How Is AI Used In Healthcare - 5 Powerful Real-World Examples That Show The Latest Advances

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When it comes to our health, especially in matters of life and death, the promise of artificial intelligence (AI) to improve outcomes is very intriguing. While there is still much to overcome to achieve AI-dependent health care, most notably data privacy concerns and fears of mismanaged care due to machine error and lack of human oversight, there is sufficient potential that governments, tech companies, and healthcare providers are willing to invest and test out AI-powered tools and solutions. Here are five of the AI advances in healthcare that appear to have the most potential. With an estimated value of $40 billion to healthcare, robots can analyze data from pre-op medical records to guide a surgeon's instrument during surgery, which can lead to a 21% reduction in a patient's hospital stay. Robot-assisted surgery is considered "minimally invasive" so patients won't need to heal from large incisions.


Near-Optimal Edge Evaluation in Explicit Generalized Binomial Graphs

Neural Information Processing Systems

Robotic motion-planning problems, such as a UAV flying fast in a partially-known environment or a robot arm moving around cluttered objects, require finding collision-free paths quickly. Typically, this is solved by constructing a graph, where vertices represent robot configurations and edges represent potentially valid movements of the robot between theses configurations. The main computational bottlenecks are expensive edge evaluations to check for collisions. State of the art planning methods do not reason about the optimal sequence of edges to evaluate in order to find a collision free path quickly. In this paper, we do so by drawing a novel equivalence between motion planning and the Bayesian active learning paradigm of decision region determination (DRD).


TOP 25 Artificial Intelligence Companies 2019

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The Evaluation Committee has completed the evaluations for the AI Time Journal TOP 25 Artificial Intelligence Companies 2019. The objective of the AI Time Journal TOP 25 Artificial Intelligence Companies 2019 Initiative is to give recognition and showcase AI companies for their contribution in 2019 to applying Artificial Intelligence, Machine Learning and Deep Learning to solve significant and complex problems and improve people's lives in a multitude of domains including Healthcare, Education, Finance, Autonomous Vehicles and more. Note: companies that employ evaluation committee members have not been included in the evaluations. Alvin Foo: "The adoption of Artificial Intelligence, Deep Learning and Machine Learning to facilitate human decision-making will continue to accelerate. While it creates opportunities to automate, it will also open up new challenges for IT team to address the potential increase in cyberattack. The advancement of AI provides a scalable cybersecurity solution for companies to automate and protect their IT assets. The future of cybersecurity will be AI-powered!"


Top 10 Artificial Intelligence Trends for 2020

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Artificial intelligence, machine learning, neural networks or whatever other fancy terms industry is coming out with for what is defined as the sophisticated computer technology that is becoming widely utilized to understand and improve business and customer experiences. I assume you have heard of it before, but the way it is defined today is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans. Digital IQ, as the measurement of how well an organization can understand its business processes from a variety of critical perspectives, will play an increasingly important role in every digital transformation strategy as more enterprises come to the realization that they must have visibility into their operations. Digital intelligence solutions will help organizations increase this business-critical ability by optimizing automation initiatives and complementing platforms like RPA and BPM. In 2020, more organizations will adopt digital intelligence technologies into their overarching digital transformation initiatives, as enterprises realize that these solutions illuminate paths to improved customer experience, reduce operating costs and sharpen competitive advantage.


Where Are the Robots?

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Automation fears distract from the real problem: too few blue-collar workers. This article is part of an MIT SMR initiative exploring how technology is reshaping the practice of management. Following the Great Recession, anxiety intensified over the prospect of automation causing permanent, widespread unemployment. Feeding on public alarm, a large number of studies assessed the likely impact of future automation on jobs. Although some touted the potential for job creation, others predicted catastrophic job loss.


Designing Conscious Systems

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This article may come about 30 years too early but I hope it will be fun for you to read it as it was for me to write it. It assumes, at least, the existence of machine cognition - AI agents or systems able to reason, to understand the world model and concepts, to properly interact with environment changes. The Singularity is not required. They do not have to pass Turing tests nor do they need to have some awesome language skills. At present, in 2019, we have a number of chatbots and assistants largely available to the public.