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MIT scientists find new way to help robots handle fluids

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Researchers create new simulation tool for robots to manipulate complex fluids in a step towards helping robots more effortlessly assist with daily tasks that deal with liquids

Imagine you’re enjoying a picnic by a riverbank on a windy day. (Why you chose to do this on a windy day was your own poor decision).

A gust of wind accidentally catches your paper napkin and lands on the water’s surface, quickly drifting away from you. You grab a nearby stick and carefully agitate the water to retrieve it, creating a series of small waves.

These waves eventually push the napkin back towards the shore, so you grab it. In this scenario, the water acts as a medium for transmitting forces, enabling you to manipulate the position of the napkin without direct contact. [Read more…] about MIT scientists find new way to help robots handle fluids

Drones navigate unseen environments with liquid neural networks

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MIT researchers exhibit a new advancement in autonomous drone navigation, using brain-inspired liquid neural networks that excel in out-of-distribution scenarios

In the vast, expansive skies where birds once ruled supreme, a new crop of aviators is taking flight. These pioneers of the air are not living creatures, but rather a product of deliberate innovation: drones.

But these aren’t your typical flying bots, humming around like mechanical bees. Rather, they’re avian-inspired marvels that soar through the sky, guided by liquid neural networks to navigate ever-changing and unseen environments with precision and ease.

Inspired by the adaptable nature of organic brains, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory introduced a method for robust flight navigation agents to master vision-based fly-to-target tasks in intricate, unfamiliar environments. [Read more…] about Drones navigate unseen environments with liquid neural networks

5 Ways to Build AR & AI Face Filters App

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Augmented Reality (AR) and Artificial Intelligence (AI) are two futuristic technologies that have taken the world by storm. They are revolutionizing various industries, from gaming and beauty to education and healthcare.

But do you know what’s the coolest thing about them? Face filters apps.

These apps use computer vision and machine learning to apply fun and engaging filters to your face in real time, making you look like anything from a cute puppy to a superhero. [Read more…] about 5 Ways to Build AR & AI Face Filters App

How Machine Learning Helps Improve Fleet Safety

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Artificial intelligence is one of those technical buzzwords that has captivated the press and is being discussed in practically every facet of life.

A subset of artificial intelligence known as machine learning, in particular, may assist building and construction fleet operators in optimizing fleet performance while preserving safety as a primary concern.

As roads become increasingly dangerous, safety directors face a challenging task: sifting through terabytes of information to uncover weaknesses in fleet safety. [Read more…] about How Machine Learning Helps Improve Fleet Safety

6 Things to Know About Computational Intelligence in Robotics Before Learning

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Studying different methods and strategies for building intelligent devices and systems is known as computational intelligence. It covers techniques like swarm intelligence, fuzzy logic, evolutionary computation, and artificial neural networks.

These methods can be used in various applications, such as robots, autonomous systems, natural language processing, image and audio recognition, and many more. Creating systems that can adapt, learn, and make judgments in complex and dynamic contexts is the general aim of computational intelligence.

In this guide, let’s check out the six things you should know about computational intelligence in robotics before learning it! [Read more…] about 6 Things to Know About Computational Intelligence in Robotics Before Learning

Interactive cyber-physical human: Generating contact-rich whole-body motions

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Performing human-like motions that involve multiple contacts is challenging for robots. In this regard, a researcher from the Tokyo University Science has envisioned an interactive cyber-physical human (iCPH) platform with complementary humanoid (physical twin) and simulation (digital twin) elements.

iCPH combines human measurement data, musculoskeletal analysis, and machine learning for data collection and augmentation. As a result, iCPH can understand, predict, and synthesize whole-body contact motions.

Humans naturally perform numerous complex tasks. These include sitting down, picking something up from a table, and pushing a cart. These activities involve various movements and require multiple contacts, which makes it difficult to program robots to perform them. [Read more…] about Interactive cyber-physical human: Generating contact-rich whole-body motions

How to Automate eLearning Process: 5 Features to Save Time and Money

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Here are 5 LMS automation features that help eLearning businesses scale up by saving time and money.  [Read more…] about How to Automate eLearning Process: 5 Features to Save Time and Money

What is Data Labeling, and Why is it Important to Artificial Intelligence?

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Data labeling is the process of identifying and tagging items in data samples. The process can be manual or through designated software. The labels tagged on the different class items must be unique, descriptive, and independent to provide a unique sequence, also called an algorithm.

In machine learning, data labeling adds meaningful labels to the identified raw data so that the machine learning model can learn from the data.

Image annotation tools are software that simplifies the process of data annotation and labeling through structured datasets that are used to train computer vision algorithms. You can use the tools on any form of raw data, such as texts, images, databases, and formats such as PowerPoint presentations or whiteboards. [Read more…] about What is Data Labeling, and Why is it Important to Artificial Intelligence?

Reinforcing the value of simulation: Teaching dexterity to a real robot hand

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Nvidia researchers show how training in simulation enables the transfer of complex manipulation skills to a robot hand with project DeXtreme

The human hand is one of the most remarkable outcomes of millions of years of evolution. The ability to pick up all sorts of objects and use them as tools is a crucial differentiator allowing us to shape the world around us.

For robots to work in the everyday human world, the ability to deftly interact with our tools and the environment around them is critical. Without that capability, they will continue to be useful only in specialized domains such as factories or warehouses.

While it has been possible to teach robots with legs how to walk for some time, robots with hands have generally proven to be much trickier to control. A hand with fingers has more joints, and they must move in specific coordinated ways to accomplish a given task. [Read more…] about Reinforcing the value of simulation: Teaching dexterity to a real robot hand