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inductive learning

Tokyo marks record ninth straight 'extremely hot day' as heat wave continues

The Japan Times

Tokyo marked a record ninth consecutive "extremely hot day" above 35 degrees Celsius on Sunday, the Meteorological Agency announced, after the capital saw the mercury hit 35.3 C just after 12 p.m. The agency said the streak bested the previous record set from July 31 to Aug. 7, 2015. This could be due to a conflict with your ad-blocking or security software. Please add and to your list of allowed sites. If this does not resolve the issue or you are unable to add the domains to your allowlist, please see this support page.

Is Lifelong #machinelearning, a paradigm for continuous learning? - Pinaki Laskar on LinkedIn


AI Researcher, Cognitive Technologist Inventor - AI Thinking, Think Chain Innovator - AIOT, XAI, Autonomous Cars, IIOT Founder Fisheyebox Spatial Computing Savant, Transformative Leader, Industry X.0 Practitioner Is Lifelong #machinelearning, a paradigm for continuous learning? Real ML is Lifelong ML. Real ML is about lifelong and constant learning with the memory (knowledge base). Human beings always retain and accumulate the knowledge learned in the past and use it in future learning. Over time we learn more and become more knowledgeable, and more effective at learning.

Learning with not Enough Data Part 3: Data Generation


Here comes the Part 3 on learning with not enough data (Previous: Part 1 and Part 2). Let's consider two approaches for generating synthetic data for training. The goal of data augmentation is to modify the input format (e.g. There are several ways to modify an image while retaining its semantic information. We can use any one of the following augmentation or a composition of multiple operations. If the downstream task is known, it is possible to learn the optimal augmentation strategies (i.e.

Introduction to Machine Learning: Supervised Learning


In this course, you'll be learning various supervised ML algorithms and prediction tasks applied to different data. You'll learn when to use which model and why, and how to improve the model performances. We will cover models such as linear and logistic regression, KNN, Decision trees and ensembling methods such as Random Forest and Boosting, kernel methods such as SVM. Prior coding or scripting knowledge is required. We will be utilizing Python extensively throughout the course.

Ledecky And Sjostrom Extend Their Reigns In World Championships

International Business Times

Katie Ledecky won a record-breaking fifth straight 800m world title on Friday, just over an hour after Sarah Sjostrom surged to her fourth consecutive victory in the women's 50m butterfly. Local hero Kristof Milak sparked delirium in the Duna Arena in Budapest when he grabbed the gold medal in the 100m butterfly, his second of the week. The Australian mixed 100m freestyle team ended the evening by setting a world record in an event only added to the world championships in 2015. Their time of 3min 19.38sec beat the record set by the United States in last World Championships in 2019 by 0.02sec. Canada were second, the Americans third.

Programmable Object Detection, Fast and Easy


So far, to showcase BigML's upcoming Object Detection release, we have demonstrated how you can annotate images on the platform, we have covered an example use case to detect cats and dogs and shared how to execute the newly available features by using the BigML Dashboard, as well as another example to build a plant disease detector. In contrast, this installment demonstrates how to perform Object Detection by calling the BigML REST API. Briefly, Object Detection is a supervised learning technique for images that not only shows where an object is in the image, but it also can show where instances of objects from multiple classes are located in the image. Let's jump in and see how we can put it to use programmatically. Before using the API, you must set up your environment variables.

SpaceX launches a Falcon 9 booster for a record-setting 13th flight TODAY

Daily Mail - Science & tech

Elon Musk's SpaceX launched a Falcon 9 for its 13th flight on Friday, setting a new record for the most times one of its rockets have ventured off into space and returned safely back on Earth. The two-stage booster, known as B1060, ignited its nine Merlin engines at 12:09pm while on Pad 39A at NASA's Kennedy Space Center in Florida. B1060 previously launched the US Space Force's GPS III-3 satellite, Turksat-5A, the Transporter-2 rideshare mission and completed nine Starlink missions. Not only does today's mission mark a new milestone for SpaceX, but it also delivered 53 new Starlink satellites into low Earth orbit - brining the total of devices in the constellation to more than 2,200. Elon Musk's SpaceX launched a Falcon 9 for its 13th flight on Friday, setting a new record for the most times one of its rockets have ventured off into space and returned safely back on Earth The Falcon 9 rocket took off from Pad 39A and traveled to an orbit between 144 miles and 209 miles above Earth's surface where the 53 Starlinks were released – deployment of the satellites happened about 15 minutes after liftoff, according to SpaceFlightNow.

Research Papers to read based on Robotic Manipulation part2(Artificial Intelligence)


Abstract: Reinforcement learning (RL) enables agents to make a decision based on a reward function. However, in the process of learning, the choice of values for learning algorithm parameters can significantly impact the overall learning process. In this paper, we proposed a Genetic Algorithm-based Deep Deterministic Policy Gradient and Hindsight Experience Replay method (called GA-DRL) to find near-optimal values of learning parameters. We used the proposed GA-DRL method on fetch-reach, slide, push, pick and place, and door opening in robotic manipulation tasks. With some modifications, our proposed GA-DRL method was also applied to the auboreach environment.

Collegiate runner urges female athletes to demand 'fairness' in women's sports: 'Use our voices and fight'

FOX News

Collegiate runner Madisan DeBos speaks out against transgender athletes in women's sports and asks for a return to'fairness.' After nearly two decades of success in cross-country and track, collegiate athlete Madisan DeBos found herself in 2020 competing against a transgender athlete who had already crushed records set by some of the fastest women in the sport. DeBos, a Southern Utah University rising senior, is now fighting to protect women's sports against domination by transgender competitors. "We really just need to get back to focusing on having fairness in women's sports, because I think so many are afraid to see the end of women's sports with having male athletes competing within our sports," DeBos said on "America's Newsroom" Thursday. DeBos said she decided to be a vocal critic against the embrace of transgender athletes so future generations of female athletes wouldn't have to fight to compete.

How long does it take to calculate 100 trillion digits of pi? Ask Google


For thousands of years, mathematicians and scientists have worked on calculating the digits of pi -- a project that could literally go on forever. For now, we at least know the first 100 trillion digits of pi, thanks to a project at Google. You can view the entire sequence of numbers on this demo site. Google Cloud's Developer Advocate Emma Haruka Iwao has set a new world record for calculating the most digits of pi, using Google Cloud infrastructure to determine that the 100-trillionth decimal place of pi is 0. The project took her just under 158 days and some serious computing power. Iwao's record beat the 2021 record set by scientists at the University of Applied Sciences of the Grisons, who calculated the mathematical constant to 62.8 trillion decimal places.