Asia
Workplaces need to be prepared to overcome disruptions from machine learning: Singh
New Delhi, Feb 17 (PTI) Automation, artificial intelligence and micro-innovation are the three megatrends that will sweep the world beyond 2020 and workplaces need to be prepared to overcome "disruptions" from machine learning, Union minister Satya Pal Singh said. Addressing a gathering here at the 11th Higher Education Summit hosted by ASSOCHAM here, he also said it was "high time", institutions put students through entrepreneurship programmes. "Beyond 2020, three megatrends will sweep the world �?? automation, artificial intelligence and micro innovation. These will have a massive impact on workplaces, and how best we educate and equip people, with appropriate skills since medium and high-skilled jobs will remain in demand," Singh was quoted as saying in a statement by the umbrella business body. "Therefore, workplaces need to be best prepared to overcome disruptions from machine learning," the Minister of State for HRD said.
AI will help judges score gymnastics events at the 2020 Olympics
Mentally keeping pace with the twists, flips, and jumps of a top-level gymnast is no easy task. Olympic judges have to be able to watch performance after performance, noting even the subtlest of movements so they can deliver scores that accurately determine which athletes deserve to go home with the gold and which go home empty-handed. However, just like doctors, lawyers, and a seemingly endless list of other professionals, these judges could find themselves replaced by automated systems in the not-so-distant future. The International Gymnastics Federation (FIG) plans to use an artificial intelligence (AI) developed by the Japanese IT company Fujitsu to help judges score the 2020 Olympic Games in Tokyo. According to a video describing Fujitsu's software, the system analyzes data collected via 3D sensors during gymnasts' performances.
5 Emerging Technology Which Will Change The World In 2018
Every day, new technologies emerge which are making our work much easier. Life is so different to how it was two decades ago. Internet became something that we cannot separate ourselves from. Information technology becomes so advanced that Google allows us to search for virtually anything, except where you lost your keys. Everyone has a camera at their disposal, capturing pictures in high-quality mode, and edits it without the need of a computer. What was only meant for texting and calling is today's means of making money, finding entertainment and even allows us to do video calls across the world.
Book review: The Master Algorithm by Pedro Domingos
I first came across this book when I was reading analysts' review of President Xi Jinping's New Years' address during the turn of the year and this book was apparently one of the two books on AI and robotics that was on the Chinese President's bookshelf. Piqued by this revelation, I then subsequently learnt that this book was also on Bill Gates' recommended reading list. The book's full title, "The Master Algorithm – How the Quest for the Ultimate Learning Machine will Remake our World," provided the necessary hyperbole that helped me make my decision to read it. Whilst I had some rudimentary of what algorithms do, how AI will impact the world we live in, and how machine learning is being used across various industries from healthcare, to education to security. At the heart of machine learning is the ability of learners to use algorithms to collate data, create meaningful and actionable insights from the data and determine or execute next steps or tasks.
IBM-HRL-MLHLS/IBM-Causal-Inference-Benchmarking-Framework
Causality-Benchmark is a library developed by IBM Research Haifa for benchmarking algorithms that estimate the causal effect of a treatment on some outcome. The framework includes unlabeled data, labeled data, and code for scoring algorithm predictions. Currently, the framework contains one essential dataset, a feature matrix that is derived from the linked birth and infant death data, and the labeled and unlabeled data are simulated models of the treatment assignment, treatment effect and censoring data based on it. More details regarding the data can be found in the LBIDD README file. However, the evaluation script is not bounded to the provided data, and can be used on other data as long as some basic requirements are kept regarding the formats.
Artificial intelligence in the End-of-Days: Killer Bots for Gog or Dry Bones to Praise God? Laitman.com
The largest portal Breaking Israel News published article based on my interview with Adam Eliyahu Berkowitz: "Artificial intelligence in the End-of-Days: Killer Bots for Gog or Dry Bones to Praise God?" And He said to me, "Prophesy over these bones and say to them: O dry bones, hear the word of Hashem!" Ezekiel 37:4 (The Israel Bible) Artificial intelligence is advancing at a lightning pace and is already being adopted for military use, raising questions as to what role this powerful new technology will play in the end-of-days. Will it be a terrifying rogue combatant in the final Biblical War of Gog and Magog, or will it be an unforeseen savior of mankind and even have a possible role in the resurrection of the dead? In one potential end-of-days scenario, technology plays a destructive role for humanity. A video, titled "Slaughterbots" and produced by the notorious Campaign to Stop Killer Robots illustrates this outcome in which autonomous drones armed with explosive charges wreak havoc on society.
Trailblazing tech Africanews
As 4,000 VIP guests gather at the World Government Summit in Dubai to discuss everything from business, politics and technology, Inspire Middle East brings to you exclusive interviews with two of the most illuminating personalities on the ground. World-famous producer and musician, will.i.am is also a passionate tech entrepreneur. After his company built an Artificial Intelligence operating system, he was invited to the summit by the UAE's Minister of Artificial Intelligence, His Excellency Omar bin Sultan Al Olama. Will.i.am's activities transcends music, business and technology, going all the way to education. "I also have a school – in the ghetto that I'm from – where we teach kids computer science and engineering – starting from nine years of age, up to 18. "I was one of those kids who was bust out from the ghetto to learn computer science at an early age – and now that I've had success in music I want to go back to my neighbourhood, so kids don't have to leave.