Tag Archives: Robotics
Amazon Fresh grocery store: Meet Just Walk Out shopping
For the first time, Just Walk Out technology is available in a new full-size Amazon Fresh grocery store.
Now customers can save time shopping for groceries by skipping the checkout line with the launch of our new Amazon Fresh grocery store with Just Walk Out shopping, now open in The Marketplace at Factoria in Bellevue, Washington.
Using a combination of overhead cameras equipped with computer vision to identify items customers put in their cart, weight-detecting sensors to log whenever they move items from or back to store shelves, and back-end systems to track the data and manage inventory, Amazon is proving out the scalability of the Amazon Fresh concept. Read More
First virtual student ‘enrolls’ at Tsinghua University
China’s Tsinghua University developed an “AI robot” virtual student that will start studying in the university’s computer laboratory. Introduced on Weibo, China’s version of Twitter, the robot, Hua Zhibing, is based on the Wudao 2.0 deep learning model and has already attracted a following of over 2,000 followers. Read More
A Clever Robot Spies on Creatures in the Ocean’s ‘Twilight Zone’
Mesobot looks like a giant AirPods case, but it’s in fact a sophisticated machine that tracks animals making the most epic migration on Earth.
The grandest migration on Earth isn’t the journey of some herbivore in Africa or a bird in the sky, but the vertical movement of whole ecosystems in the open ocean. All kinds of animals, from fish to crustaceans, hang out in the depths during the day, where the darkness provides protection from predators. At night, they migrate up to the shallows to forage. Then they swim back down again when the sun rises—a great big conveyor belt of biomass.
But now a spy swims among them: Mesobot. Today in the journal Science Robotics, a team of engineers and oceanographers describes how they got a new autonomous underwater vehicle to lock onto movements of organisms and follow them around the ocean’s “twilight zone,” a chronically understudied band between 650 feet and 3,200 feet deep, which scientists also refer to as mid-water. Thanks to some clever engineering, the researchers did so without flustering these highly sensitive animals, making Mesobot a groundbreaking new tool for oceanographers. Read More
AI system outperforms humans in designing floorplans for microchips
A machine-learning system has been trained to place memory blocks in microchip designs. The system beats human experts at the task, and offers the promise of better, more-rapidly produced chip designs than are currently possible.
Success or failure in designing microchips depends heavily on steps known as floorplanning and placement. These steps determine where memory and logic elements are located on a chip. The locations, in turn, strongly affect whether the completed chip design can satisfy operational requirements such as processing speed and power efficiency. So far, the floorplanning task, in particular, has defied all attempts at automation. It is therefore performed iteratively and painstakingly, over weeks or months, by expert human engineers. But in a paper in Nature, researchers from Google (Mirhoseini et al.1) report a machine-learning approach that achieves superior chip floorplanning in hours. Read More
Cecilia.ai The First Robotic Interactive Bartender
The Role of Surrogate Models in the Development of Digital Twins of Dynamic Systems
Digital twin technology has significant promise, relevance and potential of widespread applicability in various industrial sectors such as aerospace, infrastructure and automotive. However, the adoption of this technology has been slower due to the lack of clarity for specific applications. A discrete damped dynamic system is used in this paper to explore the concept of a digital twin. As digital twins are also expected to exploit data and computational methods, there is a compelling case for the use of surrogate models in this context. Motivated by this synergy, we have explored the possibility of using surrogate models within the digital twin technology. In particular, the use of Gaussian process (GP) emulator within the digital twin technology is explored. GP has the inherent capability of addressing noisy and sparse data and hence, makes a compelling case to be used within the digital twin framework. Cases involving stiffness variation and mass variation are considered, individually and jointly along with different levels of noise and sparsity in data. Our numerical simulation results clearly demonstrate that surrogate models such as GP emulators have the potential to be an effective tool for the development of digital twins. Aspects related to data quality and sampling rate are analysed. Key concepts introduced in this paper are summarised and ideas for urgent future research needs are proposed. Read More
Embodying Pre-Trained Word EmbeddingsThrough Robot Actions
We propose a promising neural network model with which to acquire a grounded representation of robot actions and the linguistic descriptions thereof. Properly responding to various linguistic expressions, including polysemous words, is an important ability for robots that interact with people via linguistic dialogue.Previous studies have shown that robots can use words that are not included in the action-description paired datasets by using pre-trained word embeddings. However, the word embeddings trained under the distributional hypothesis are not grounded, as they are derived purely from a text corpus. In this letter, we trans-form the pre-trained word embeddings to embodied ones by using the robot’s sensory-motor experiences. We extend a bidirectional translation model for actions and descriptions by incorporating non-linear layers that retrofit the word embeddings. By training the retrofit layer and the bidirectional translation model alternately, our proposed model is able to transform the pre-trained word embeddings to adapt to a paired action-description dataset. Our results demonstrate that the embeddings of synonyms form a semantic cluster by reflecting the experiences (actions and environments) of a robot. These embeddings allow the robot to properly generate actions from unseen words that are not paired with actions in a dataset. Read More
Watson Orchestrate
Watson Orchestrate gives you interactive AI–in tools like email and Slack–to increase your productivity. This isn’t a static bot programmed by IT. You initiate work in natural language, and Watson Orchestrate uses a powerful AI engine to combine pre-packaged skills, on-the-fly and in-context, based on organizational knowledge and your prior interactions. Read More
See Demo
Rick's Cafe AI 