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Six-month-olds see people who imitate them as more friendly

Daily Mail - Science & tech

Babies know when you imitate them - and they perceive it as a sign of friendliness, according to a new study. Swedish research suggest the imitation game is an infant's favourite way of interacting with adults, making them more engaged and likely to approach an adult. In experiments, six-month-old babies looked and smiled longer, and tried to approach the adult more often during the close mirroring of their actions. Babies also responded to being imitated with'testing behaviour' – actions that encouraged the adult imitator to imitate in turn. Imitation on behalf of the adult helps nurture a baby's sensitivity to others and could be a driving force of driving early social cognition, the research team report.

Monash, Swinburne, and RMIT universities use optical chip to achieve 44Tbps data speed


A group of researchers from Monash, Swinburne, and RMIT universities have claimed that they have successfully tested and recorded the world's fastest internet data speed of 44.2Tbps using a single optical chip known as a micro-comb. The findings, published in the Nature Communications journal, revealed how the data speed achieved has the capacity to support high-speed internet connections of 1.8 million households in Melbourne, and users can download 1,000 HD movies in seconds. According to the researchers, the micro-comb, which is touted to be a smaller and lighter device than existing telecommunications hardware, was used to replace 80 infrared lasers and load-tested in infrastructure that mirrored networks used by the National Broadband Network. They did this by placing the micro-comb in 76.6km of installed dark optical fibres between RMIT's Melbourne city campus and Monash University's Clayton campus. The micro-comb was used to mimic a rainbow of infrared lasers so that each'laser' has the capacity to be used as a separate communications channel.

MarineXchange Receives Government Grant for Artificial Intelligence Project – IAM Network


The Austrian Research Promotion Agency (FFG) has officially announced to support the development of an AI (Artificial intelligence) forecasting project with MarineXchange (MXP), which provides enterprise software solutions to the cruise industry. "Accurate supply chain forecasting is a huge challenge for the cruise industry," MXP said, in a press release ."Because Consumption patterns depend on guest profiles, seasonal items, substitutions and menu cycles. Vendor performance, freight and currency exchange rates need to be considered. The overall CO2 impact, waste reduction and fair trade are additional factors. To aid cruise companies in this complex decision-making process, more accurate forecasts are needed."

Top 10 B.Tech Data Science and Artificial Intelligence Colleges In India


Are you a student looking for the top 10 colleges for pursuing bachelor's/Btech in data science and artificial intelligence? In fact, as soon as a child passes high school, he/she starts to inquire about various colleges and universities which match his learning profile so that he gains proficiency in the subject which he decides to study. There are subjects that are not traditional in nature and require extra efforts to look into so that the right decision is taken. One such subject is Artificial Intelligence, which calls for counterfeit of human intelligence procedures by computers and other machines. This course requires expert faculty to teach so that students get adequate knowledge and are able to meet the industries' demands with their skills.

Flying Cloud Technology Announces Strategic Partnership With Wireless Guardian


Today Flying Cloud Technology announces it has entered into an OEM relationship with Wireless Guardian. Wireless Guardian is the world's first forward-facing human threat detection system and the most effective investigative security solution for today's high-tech environment. Providing protection to patrons and facilities, Wireless Guardian tracks both security and pandemic threats up to a mile outside the facility's perimeter. "Flying Cloud is extremely happy to enter into this strategic partnership with Wireless Guardian. We feel that this partnership will showcase the incredible strengths of both companies. Wireless Guardian will be an invaluable data source that is fed into and analyzed by Flying Cloud. This data will allow our joint customers to not only detect someone entering their facility with a temperature, but with our patented AI models, we can clearly show where they went in a facility and show who they were in contact with. Flying cloud is now the only company that can track both the user and the data that they interact with," said Brian Christian, CEO of Flying Cloud Technology.


Communications of the ACM

Moritz Lipp is a Ph.D. candidate at Graz University of Technology, Flanders, Austria. Michael Schwarz is a postdoctoral researcher at Graz University of Technology, Flanders, Austria. Daniel Gruss is an assistant professor at Graz University of Technology, Flanders, Austria. Thomas Prescher is a chief architect at Cyberus Technology GmbH, Dresden, Germany. Werner Haas is the Chief Technology Officer at Cyberus Technology GmbH, Dresden, Germany.

The Machine Learning Course


Online Courses Udemy - Learn and understand Machine Learning from scratch. A complete beginner's guide to learn Machine Learning. Hasanur Rahaman Hasib English [Auto-generated] Students also bought Applied Machine Learning For Healthcare Deploy Serverless Machine Learning Models to AWS Lambda Machine Learning A-Z: Hands-On Python & R In Data Science Python for Data Science and Machine Learning Bootcamp 2020 AWS SageMaker, AI and Machine Learning Specialty Exam Preview this course GET COUPON CODE Description Machine learning relates to many different ideas, programming languages, frameworks. Machine learning is difficult to define in just a sentence or two. But essentially, machine learning is giving a computer the ability to write its own rules or algorithms and learn about new things, on its own.

Stanford CS224N: NLP with Deep Learning Winter 2019 Lecture 1 – Introduction and Word Vectors


Take an adapted version of this course as part of the Stanford Artificial Intelligence Professional Program. Professor Christopher Manning Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science Director, Stanford Artificial Intelligence Laboratory (SAIL) To follow along with the course schedule and syllabus, visit: To get the latest news on Stanford's upcoming professional programs in Artificial Intelligence, visit: To view all online courses and programs offered by Stanford, visit:

Lecture 8: Recurrent Neural Networks and Language Models


Lecture 8 covers traditional language models, RNNs, and RNN language models. Also reviewed are important training problems and tricks, RNNs for other sequence tasks, and bidirectional and deep RNNs. This lecture series provides a thorough introduction to the cutting-edge research in deep learning applied to NLP, an approach that has recently obtained very high performance across many different NLP tasks including question answering and machine translation. It emphasizes how to implement, train, debug, visualize, and design neural network models, covering the main technologies of word vectors, feed-forward models, recurrent neural networks, recursive neural networks, convolutional neural networks, and recent models involving a memory component. For additional learning opportunities please visit:

[L4-BD] Introduction to Big Data with KNIME Analytics Platform - Online


This course focuses on how to use KNIME Analytics Platform for in-database processing and writing/loading data into a database. Get an introduction to the Apache Hadoop ecosystem and learn how to write/load data into your big data cluster running on premise or in the cloud on Amazon EMR, Azure HDInsight, Databricks Runtime or Google Dataproc.. Learn about the KNIME Spark Executor, preprocessing with Spark, machine learning with Spark, and how to export data back into KNIME/your big data cluster. This course lets you put everything you've learnt into practice in a hands-on session based on the use case: Eliminating missing values by predicting their values based on other attributes. This course consists of four, 75-minutes online sessions run by one of our KNIME data scientists. Each session has an exercise for you to complete at home and together, we will go through the solution at the start of the following session.