Having to stay indoors is probably one of the best excuses you'll ever get to be able to play an unbelievable amount of video games without judgment from others (or yourself). So, it's time to stock up and create a massive backlog to keep you occupied for the months ahead. PlayStation owners have the opportunity to do just that while getting some pretty sweet discounts in the process -- the PlayStation Store has brought back their Games Under $20 sale, which is exactly what it sounds like. There are almost 200 games up for grabs, and if you want to peruse them all, you can do that here. Prey -- $14.99 (was $29.99) Friday the 13th: The Game -- $4.99 (was $19.99) Just Dance 2020 -- $19.99 (was $39.99) Assassin's Creed Origins: Deluxe Edition -- $13.99 (was $69.99)
A curriculum is an efficient tool for humans to progressively learn from simple concepts to hard problems. It breaks down complex knowledge by providing a sequence of learning steps of increasing difficulty. In this post, we will examine how the idea of curriculum can help reinforcement learning models learn to solve complicated tasks. It sounds like an impossible task if we want to teach integral or derivative to a 3-year-old who does not even know basic arithmetics. That's why education is important, as it provides a systematic way to break down complex knowledge and a nice curriculum for teaching concepts from simple to hard. A curriculum makes learning difficult things easier and approachable for us humans.
As scientists and researchers strive harder to make Artificial Intelligence (AI) mainstream, this ingenious technology is already making its way to our day to day lives and continues ushering across several industry verticals. From voice-powered personal assistants like Siri and Alexa to autonomously-powered self-driving vehicles, AI has been rearing itself as a force to be reckoned with. Many tech giants such as Apple, Google, Facebook, and Microsoft have been making huge bets on the long-term growth potential of Artificial Intelligence. According to a report published by the research firm Markets and Markets, the AI market is expected to grow to a $190 billion industry by 2025. More and more businesses are looking to boost their ROI by leveraging the capabilities of AI.
General AI (Artificial Intelligence) is coming closer thanks to combining neural networks, narrow AI and symbolic AI. Yves Mulkers, Data strategist and founder of 7wData talked to Wouter Denayer, Chief Technology Officer at IBM Belgium, to share his enlightening insights on where we are and where we are going with Artificial Intelligence. Join us in our chat with Wouter. Yves Mulkers Hi and welcome, today we're together with Wouter Denayer, Chief Technology Officer at IBM. Wouter, you're kind of authority in Belgium and I think outside the borders of Belgium as well on artificial intelligence. Can you tell me a bit more about what you're doing at IBM and What keeps you busy?
It is a narrative standard in role-playing adventure games: the hero is pitted against a Big Evil, who has a strategic or chaotic hunger to destroy the world we know. From Shinra's greedy harvesting of the planet's resources in Final Fantasy VII Remake to Ganondorf's quest for power and destruction across more than 30 years of Legend of Zelda games, the stakes are always astronomically high. But what really makes these fictional realms worth saving? Role-playing games need to offer more than a sequence of linked events toward a monumental finale. A world is made of people, not just objectives.
At re:Invent 2019, AWS shared the fastest training times on the cloud for two popular machine learning (ML) models: BERT (natural language processing) and Mask-RCNN (object detection). To train BERT in 1 hour, we efficiently scaled out to 2,048 NVIDIA V100 GPUs by improving the underlying infrastructure, network, and ML framework. Today, we're open-sourcing the optimized training code for ALBERT (A Lite BERT), a powerful BERT-based language model that achieves state-of-the-art performance on industry benchmarks while training 1.7 times faster and cheaper. This post demonstrates how to train a faster, smaller, higher-quality model called ALBERT on Amazon SageMaker, a fully managed service that makes it easy to build, train, tune, and deploy ML models. Although this isn't a new model, it's the first efficient distributed GPU implementation for TensorFlow 2. You can use AWS training scripts to train ALBERT in Amazon SageMaker on p3dn and g4dn instances for both single-node and distributed training.
Twitter users stretch words such as'yes', 'dude' and'hey' to modify their meaning, according to researchers who analysed 100 billion tweets. The US linguist experts say stretched words that convey a different meaning than the original are common feature of social media, but are rare in formal writing. For instance, 'suuuuure' can imply sarcasm, 'duuuuude' can be a sign of incredulity, 'yeeessss' may indicate excitement and'heellllp' may be a sign of desperation. Researchers say they've developed new tools that could be used in future research of stretchable words, such as investigations of mistypings and misspellings. These could also be applied to improve natural language processing for software and search engines and Twitter's spam filters, or even have applications in genetics.
Tue 19 May 2020 06.14 EDT Last modified on Tue 19 May 2020 06.16 EDT When legendary chess grandmaster Garry Kasparov found himself beaten by IBM's Deep Blue supercomputer, it was seen as a seminal moment in the evolution of artificial intelligence. A road trodden by war heroes and student researchers alike, whose singular desire to create a program that could beat the very best in the world would shape an entire science. Early origins Chess lends itself well to computer programming. Where other games can depend more on gut instinct or physical skill, chess is a game of strict binary rules – a move is either correct or it isn't. It's a game where multiple permutations, strategies and responses to moves and gambits could all be pre-programmed.
A truly kick-ass videogame combines clever code, gorgeous graphics, and artful animation--plus thousands of hours of hard work. Researchers at Electronic Arts--the company behind FIFA, Madden, and other popular games--are testing recent advances in artificial intelligence as a way to speed the development process and make games more lifelike. And in a neat twist, the researchers are harnessing an AI technique that proved itself by playing some of the earliest console videogames. A team from EA and the University of British Columbia in Vancouver is using a technique called reinforcement learning, which is loosely inspired by the way animals learn in response to positive and negative feedback, to automatically animate humanoid characters. "The results are very, very promising," says Fabio Zinno, a senior software engineer at Electronic Arts.
File-transfer service WeTransfer BV opened its virtual space on May 1, almost seven weeks after closing its physical offices in New York, Los Angeles and Amsterdam as part of the global effort to slow the spread of the new coronavirus. Graphics reminiscent of early "Tomb Raider" videogames depict a version of the company's Dutch headquarters, adapted to include pool tables, techno music and in-jokes such as a "memorial" library named for the very- much-alive chief creative officer. Staff roam around in the form of avatars such as robots and panda bears. Gordon Willoughby, the chief executive of WeTransfer, said the platform helps provide the social experience of office life in the way that Zoom calls and Slack have replaced business meetings and desk-side chats. That is particularly valuable for recent hires, he said.