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A submersible soft robot survived the pressure in the Mariana Trench

New Scientist

This silicone rubber robot can withstand the pressures in the ocean's deepest abyss A silicone robot has survived a journey to 10,900 metres below the ocean's surface in the Mariana trench, where the crushing pressure can implode all but the strongest enclosures. This device could lead to lighter and more nimble submersible designs. A team led by Guorui Li at Zhejiang University in China based the robot's design on snailfish, which have relatively delicate, soft bodies and are among the deepest living fish. They have been observed swimming at depths of more than 8000 metres. The submersible robot looks a bit a manta ray and is 22 centimetres long and 28 centimetres in wingspan.


Brave is developing its own privacy-focused search engine

Engadget

Privacy-focused browser Brave is working on its own search engine. It has bought Tailcat, an open-source engine created by a team who worked on the defunct anti-tracking browser and search engine Cliqz, to power Brave Search. The company will allow others to use Brave Search tech to build their own search engines. Brave says the search engine will provide an alternative to Google Search and Chrome. It's developing Brave Search using the same principles as its browser, which now has more than 25 million monthly active users.


Drones With 'Most Advanced AI Ever' Coming Soon To Your Local Police Department

#artificialintelligence

Three years ago, Customs and Border Protection placed an order for self-flying aircraft that could launch on their own, rendezvous, locate and monitor multiple targets on the ground without any human intervention. In its reasoning for the order, CBP said the level of monitoring required to secure America's long land borders from the sky was too cumbersome for people alone. To research and build the drones, CBP handed $500,000 to Mitre Corp., a trusted nonprofit Skunk Works that was already furnishing border police with prototype rapid DNA testing and smartwatch hacking technology. They were "tested but not fielded operationally" as "the gap from simulation to reality turned out to be much larger than the research team originally envisioned," a CBP spokesperson says. This year, America's border police will test automated drones from Skydio, the Redwood City, Calif.-based startup that on Monday announced it had raised an additional $170 million in venture funding at a valuation of $1 billion.


AI and ML: Key Drivers to Building a Resilient Business

#artificialintelligence

The previous year has shown us that you have to be prepared for both expected and unexpected disruption, emerging risks, and economic uncertainties. Your business models and operations, employees and technology have to be agile and resilient. New business risks are everywhere. What challenges can organizations expect in the emerging and evolving risk landscape, and how can they overcome them? Ronald van Loon is a Protiviti partner, and recently had the opportunity to examine their study, conducted jointly with North Carolina State University Poole College of Management's Enterprise Risk Management (ERM) Initiative, on Executive Perspectives on Top Risks:2021 and 2030 and share his outlook regarding the shifting risk landscape and its impact on modern organizations.


Learn Who Is Potentially Using Cutting Edge Solutions to Create the Next Generation of Robotics and Automation

#artificialintelligence

Clinton Township, Michigan--(Newsfile Corp. - March 1, 2021) - Resgreen Group (OTC PINK: RGGI) ("RGGI"), a leading mobile robot company, today announced the development of Atlas, its new Autonomous Mobile Robot (AMR) for demanding industrial and mission critical 24/7 applications. The vehicle can use either natural feature or magnetic tape guidance to navigate through manufacturing facilities and warehouses. The natural feature or free guidance requires no wires, tape or navigation marks. Instead, the vehicle uses advanced lasers to scan its surroundings, and then determines its position based on the mapped features along its path. "Atlas mobile robot was designed to meet a wide variety of customers' needs, whether it's free navigation requiring no modification to your facility or more cost-effective magnetic tape guidance," said Parsh Patel, CEO of RGGI. "We also understand industrial customers require a rugged vehicle that is built to last and moves heavy loads easily." It features 5G communications and operates using an Android or iOS application in manual mode and WiFi in automatic mode.


Sentiment Analysis (Opinion Mining) with Python -- NLP Tutorial

#artificialintelligence

Check out our editorial recommendations on the best machine learning books. A "sentiment" is a generally binary opposition in opinions and expresses the feelings in the form of emotions, attitudes, opinions, and so on. It can express many opinions. By using machine learning methods and natural language processing, we can extract the personal information of a document and attempt to classify it according to its polarity, such as positive, neutral, or negative, making sentiment analysis instrumental in determining the overall opinion of a defined objective, for instance, a selling item or predicting stock markets for a given company. Sentiment analysis is challenging and far from being solved since most languages are highly complex (objectivity, subjectivity, negation, vocabulary, grammar, and others).


Maximize existing QA vision systems with Deep Learning AI - Mariner

#artificialintelligence

The reputation and bottom line of a company can be adversely affected if defective products are released. If a defect is not detected, and the flawed product is not removed early in the production process, the damage can be costly – and the higher the unit value, the higher those costs will be. And worst of all, dissatisfied customers can demand returns. To mitigate these costs, many manufacturers install cameras to monitor their products as they move along their production lines. However, the data obtained may not always be useful – or more appropriately said, the data is useful, but existing machine vision systems may not be able to accurately assess it at full production speeds.


david o. houwen on LinkedIn: The world is just a great big onion

#artificialintelligence

Iedereen weet toch dat we parasieten zijn op een hele grote ui?';) New research indicates the whole universe could be a giant neural network TNW (...) If we're all nodes in a neural network, what's the network's purpose? Is the universe one giant, closed network or is it a single layer in a grander network? Or perhaps we're just one of trillions of other universes connected to the same network. When we train our neural networks we run thousands or millions of cycles until the AI is properly "trained." Are we just one of an innumerable number of training cycles for some larger-than-universal machine's greater purpose?


Here's how Riot's offline 'League' and 'Valorant' competitions landed in Iceland

Washington Post - Technology News

For "League of Legends," the event is the beginning of a return to normalcy after the cancellation of last year's Mid-Season Invitational and the recalibration of Worlds in Shanghai in light of covid. The stakes are higher for "Valorant," which launched shortly after the beginning of the pandemic in the United States. The Iceland event will mark the first occasion of competition between teams from different regions; the strengths and weaknesses of respective regions has been a source of rampant speculation among professional players, coaches and analysts.


Google Open-Sources Trillion-Parameter AI Language Model Switch Transformer

#artificialintelligence

Researchers at Google Brain have open-sourced the Switch Transformer, a natural-language processing (NLP) AI model. The model scales up to 1.6T parameters and improves training time up to 7x compared to the T5 NLP model, with comparable accuracy. The team described the model in a paper published on arXiv. The Switch Transformer uses a mixture-of-experts (MoE) paradigm to combine several Transformer attention blocks. Because only a subset of the model is used to process a given input, the number of model parameters can be increased while holding computational cost steady.