Source: ibtimes.sg Artificial intelligence (AI) seems to be taking over the world and is even helping us combat the ongoing coronavirus pandemic, but so far it has been a product of human supervision – we teach computers to see patterns, just like we teach children to read. However, researchers believe the future of AI depends on systems Read More
Category: Reinforcement Learning
Reinforcement Learning
Source: analyticsinsight.net Self-supervised learning is one of those recent ML methods that have caused a ripple effect in the data science network, yet have so far been flying under the radar to the extent Entrepreneurs and Fortunes of the world go; the overall population is yet to find out about the idea yet lots of AI society Read More
Source: chess.com Making an appearance in Lex Fridman’s Artificial Intelligence Podcast, DeepMind’s David Silver gave lots of insights into the history of AlphaGo and AlphaZero and deep reinforcement learning in general. Today, the finals of the Chess.com Computer Chess Championship (CCC) start between Stockfish and Lc0 (Leela Chess Zero). It’s a clash between a conventional chess engine that implements an advanced Read More
Source: unite.ai Creating an Artificial General Intelligence (AGI) is the ultimate endpoint for many AI specialists. An AGI agent could be leveraged to tackle a myriad of the world’s problems. For instance, you could introduce a problem to an AGI agent and the AGI could use deep reinforcement learning combined with its newly introduced emergent consciousness to Read More
Source: infoq.com Uber andOpenAI have open-sourced Fiber, a new library which aims to empower users in implementing large-scale machine learning computation on computer clusters. The main objectives of the library are to leverage heterogeneous computing hardware, dynamically scale algorithms, and reduce the burden on engineers implementing complex algorithms on clusters. It’s a challenge for machine learning Read More
Source:inverse.com You might think you’re good at Atari games, but a new artificial intelligence system from Alphabet subsidiary DeepMind called Agent57 is probably better. The company claims its A.I. can beat the average person on all 57 Atari 2600 games. Agent57 uses a type of machine learning called deep reinforcement learning to learn from its Read More
Source: middleeastheadlines.com Often it feels like every internet site, application, or maybe efficiency device is mentioning Artificial Intelligence 101 (AI) as the top-secret component for their financial success. What’s even less frequent is a breakdown of what Artificial Intelligence is, the reason that it’s so great, and even the way service providers are taking advantage Read More
Source: engineering.com A new simulation system allows driverless vehicles to be trained in an environment with infinite steering possibilities. While autonomous vehicles typically rely on datasets from real-world human drivers, simulated testing opens up opportunities for cars to encounter and navigate through a variety of worst-case scenarios before they’re even released out on the streets. Read More
Source: itprotoday.com When it comes to machine learning, supervised learning has long been the superstar. But recent advancements and emerging enterprise applications are putting new attention on reinforcement learning. In an analysis of more than 16,000 artificial intelligence (AI) research papers undertaken by MIT’s Technology Review, reinforcement learning emerged as one of the leading trends in the past Read More
Source: technologynetworks.com A simulation system invented at MIT to train driverless cars creates a photorealistic world with infinite steering possibilities, helping the cars learn to navigate a host of worse-case scenarios before cruising down real streets. Control systems, or “controllers,” for autonomous vehicles largely rely on real-world datasets of driving trajectories from human drivers. From Read More
Source: siliconangle.com Researchers at Google have open-sourced a new framework that can scale up artificial intelligence model training across thousands of machines. It’s a promising development because it should enable AI algorithm training to be performed at millions of frames per second while reducing the costs of doing so by as much as 80%, Google noted in Read More
Source: iotforall.com A paper published by researchers at Carnegie Mellon University, San Francisco research firm OpenAI, Facebook AI Research, the University of California at Berkeley, and Shanghai Jiao Tong University describes a paradigm that scales up multi-agent reinforcement learning, where AI models learn by having agents interact within an environment such that the agent population increases in Read More
Source: news.mit.edu A simulation system invented at MIT to train driverless cars creates a photorealistic world with infinite steering possibilities, helping the cars learn to navigate a host of worse-case scenarios before cruising down real streets. Control systems, or “controllers,” for autonomous vehicles largely rely on real-world datasets of driving trajectories from human drivers. Read More
Source: inc42.com The last decade of tech was to a large part defined by the advent of Deep Supervised Learning (DL). The availability of cheap data at scale, computational power, and researcher interest have made it the de-facto school of algorithms used for most pattern recognition problems. Face recognition on social media, product recommendations on sites, voice Read More
Source: drugtargetreview.com A new collaboration has demonstrated fully-autonomous Scanning Probe Microscopy (SPM) operation, applying artificial intelligence (AI) and deep learning to remove the need for constant human supervision. According to the researchers, the new system, dubbed DeepSPM, bridges the gap between nanoscience, automation and AI, firmly establishing the use of machine learning for experimental scientific research. “Optimising Read More
Source: eurekalert.org An Australian-German collaboration has demonstrated fully-autonomous SPM operation, applying artificial intelligence and deep learning to remove the need for constant human supervision. The new system, dubbed DeepSPM, bridges the gap between nanoscience, automation and artificial intelligence (AI), and firmly establishes the use of machine learning for experimental scientific research. “Optimising SPM data acquisition Read More
Source: middleeastheadlines.com Often it feels like every internet site, application, or maybe efficiency device is mentioning Artificial Intelligence 101 (AI) as the top-secret component for their financial success. What’s even less frequent is a breakdown of what Artificial Intelligence is, the reason that it’s so great, and even the way service providers are taking advantage Read More
Source: venturebeat.com One way to test machine learning models for robustness is with what’s called a trojan attack, which involves modifying a model to respond to input triggers that cause it to infer an incorrect response. In an attempt to make these tests more repeatable and scalable, researchers at Johns Hopkins University developed a framework Read More
Source: techxplore.com Drones, specifically quadcopters, are an adaptable lot. They’ve been used to assess damage after disasters, deliver ropes and life-jackets in areas too dangerous for ground-based rescuers, survey buildings on fire and deliver medical specimens. But to achieve their full potential, they have to be tough. In the real world, drones are forced to navigate Read More
Source: screenshot-magazine.com In the last few years, advancements in technologies have opened up promising new ways for humans to utilise robots. And although many people still fear AI and robotics by only perceiving them as what will replace humans altogether and take our jobs, a few have already realised their potential in helping the sector Read More
Source: venturebeat.com A preprint paper coauthored by scientists at Facebook AI Research describes Rewarding Impact-Driven Exploration (RIDE), an intrinsic reward method that encourages AI-driven agents to take actions in an environment. The researchers say that it outperforms state-of-the-art methods on hard exploration tasks in procedurally generated worlds, a sign it might be a candidate for devices like robot Read More
Source: technologytimes.pk In “Learning to Resolve Alliance Dilemmas in Many-Player Zero-Sum Games,” DeepMind — the research division of Alphabet whose work chiefly involves reinforcement learning, an area of AI concerned with how software agents ought to take actions to maximize some reward — introduces an economic competition model with a peer-to-peer contract mechanism that enables the discovery and enforcement Read More
Source: analyticsinsight.net Artificial Intelligence has progressed immensely in the past few years. From being just a fiction context to penetrating into the regular lives of people, AI has brought transformation in several ways. Such advancements are an output of various factors that include the application of new statistical approaches and enhanced computing powers. However, according Read More
Source: techxplore.com The field of robotics took one step forward—followed by another, then several more—when a robot called Rainbow Dash recently taught itself to walk. The four-legged machine only required a few hours to learn to walk backward and forward, and turn right and left while doing so. Researchers from Google, UC Berkeley and the Read More
Source: econotimes.com Artificial intelligence (AI) – understood as intelligence demonstrated by machines – and machine learning (ML) – a subfield of AI that focuses on machines’ ability to automatically learn from experience without being explicitly programmed – are two of the computer science technologies that will arguably have the biggest impact on our lives in Read More
Source: businessinsider.my A group of Google researchers have built a robot capable of learning to walk by itself with minimal human intervention. The researchers used a kind of AI called deep reinforcement learning to enable the robot to learn how to walk by trial-and-error. The robot learned to walk on a variety of surfaces, including Read More
Source: unite.ai The AI startup Covariant and the industrial robotics company ABB will be partnering to engineer sophisticated robots that can pick up and manipulate a wide variety of objects. These robots will be used in warehouses and other industrial settings. As Fortune reported, the industrial robotics company ABB is primarily involved in the creation of Read More
Source: analyticsindiamag.com AI research startup DeepMind has now open-sourced new libraries for neural networks and reinforcement learning based on JAX. JAX is a numerical computing library launched by Google a couple of years ago, and can automatically differentiate native Python and NumPy functions. JAX uses XLA (Accelerated Linear Algebra) to compile and run your NumPy programs Read More
Google researchers use multiple cameras to reduce error rates for robot insertion and stacking tasks
Source: venturebeat.com Object-manipulating robots rely on cameras to make sense of the world around them, but these cameras often require careful installation and ongoing calibration and maintenance. A new study published by researchers at Google’s Robotics division and Columbia University proposes a solution, which involves a technique that learns to accomplish tasks using multiple color cameras without Read More
Source: venturebeat.com Reinforcement learning, which spurs AI to complete goals using rewards or punishments, is a form of training that’s led to gains in robotics, speech synthesis, and more. Unfortunately, it’s data-intensive, which motivated research teams — one from Google Brain (one of Google’s AI research divisions) and the other from Alphabet’s DeepMind — to prototype more Read More