Lifeboat Foundation

There are few environments as unforgiving as the ocean. Its unpredictable weather patterns and limitations in terms of communications have left large swaths of the ocean unexplored and shrouded in mystery.

“The ocean is a fascinating environment with a number of current challenges like microplastics, algae blooms, coral bleaching, and rising temperatures,” says Wim van Rees, the ABS Career Development Professor at MIT. “At the same time, the ocean holds countless opportunities — from aquaculture to energy harvesting and exploring the many ocean creatures we haven’t discovered yet.”

Ocean engineers and mechanical engineers, like van Rees, are using advances in scientific computing to address the ocean’s many challenges, and seize its opportunities. These researchers are developing technologies to better understand our oceans, and how both organisms and human-made vehicles can move within them, from the micro scale to the macro scale.

After receiving a lot of love here at Bored Panda and all over the internet with the first post, I decided to continue this project of bringing historical figures to modernity through artificial intelligence.

The Korea Advanced Institute of Science and Technology (KAIST) announced on Jan. 5 that professor Lee Sang-wan and his research team at its Department of Bio and Brain Engineering found a way to solve overfitting and underfitting in machine learning.

Artificial intelligence models present optimal solutions to various problems. However, their situational flexibility is still at a very low level. On the other hand, people focus on given problems while responding flexibly to changing conditions and situations.

The more a technology or concept permeates and gets normalized in our day-to-day lives, the more we grow to expect from it. About two decades ago, a sub-56kpbs dial-up internet connection seemed miraculous. Today, with internet speeds as high as 2000Mbps becoming normal, the 56Kbps connection would be considered a failure of sorts—in the developed world, at least. This shift in expectation also applies to AI. Having seen numerous practical AI applications aid human convenience and progress, both the general population and the AI research community now expects every new breakthrough in the field to be more earth-shattering than the previous one. Similarly, what qualifies as AI failure has also seen a massive shift in recent years, especially from a problem owner’s perspective. failure, in most cases, is attributed to technology-centric factors like the quality of data or the capabilities of algorithms and hardware used, ignoring the most crucial aspect of AI success—the end user.

Coffman said he could not elaborate on many of the specifics related to advanced degrees of autonomy, but he did point out a few distinct and significant advantages newer applications of robotic autonomy will bring to the force. For example, perhaps an autonomous vehicle could benefit from force-wide, cross-domain networking and learn of upcoming barriers, obstacles or even enemy force locations? Perhaps artificial-intelligence-enabled forward robots can gather large volumes of sensor data, process and organize the critical information during operations and make adjustments and determinations as needed according to certain variables.

“What we learned is based on their mobility, their excellent mobility and their autonomous behaviors, we can actually have them move on a separate axis of advance and link up with the humans on the objective. So they can autonomously move without humans, link up with the humans, transfer back control, and then execute the mission. This gives the enemy multiple dilemmas,” Coffman said.

Replika users say that it’s all too easy to form a meaningful – even romantic – attachment to your AI friend.

What’s the missing ingredient in the secret sauce behind human-level intelligence? Is it something we can teach the machines? property= description.

In computer simulations of possible universes, researchers have discovered that a neural network can infer the amount of matter in a whole universe by studying just one of its galaxies.

The latest artificial intelligence systems start from zero knowledge of a game and grow to world-beating in a matter of hours. But researchers are struggling to apply these systems beyond the arcade.