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Category: robotics/AI – Page 2078

Wizebit is proud to welcome Machine Learning guru Peter Morgan to its elite team of blockchain specialists and developers.

Peter is the author of the popular report, “Machine Learning is Changing the Rules: Ways Businesses Can Utilize AI to Innovate”, and brings years of real world experience designing, building, and implementing AI and IP networks for Cisco, IBM, and BT Labs.

As the first company to create a confidential smart assistant on the blockchain, Wizebit officially launched in 2018 with the mission of allowing personal data to be connected while remaining protected.

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How close are we really to space travel? Our featured contributor Lola Akinmade Åkerström talks to Space Nation, a company that’s researching both space tourism and how space technology can help us on Earth.

Thanks to Google, it can often feel like there are no mysterious places left on earth to explore—and finding new places to call the ‘final’ frontier seems increasingly difficult. Even the Pacific Ocean’s Marianna Trench, at over 36,000 feet deep and arguably the most legit final frontier on earth, has been explored by Hollywood director James Cameron in a submersible. As a result, the past few decades have seen us looking upwards to the most mysterious of places: Our own galaxy.

Blockbuster movies set in space and fictional alien encounters continue to intrigue us. Space discovery programs on TV science channels continually pique our curiosity. Even kids’ cartoons such as the 1960s American series The Jetsons brought the concept of commercial space travel closer to us, thanks to its flying space cars, pod-like apartments, and a robot maid called Rosie.

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NASA wants to go to Mars. SpaceX wants to go to Mars. Michio Kaku wants humanity to go to Mars so we can avoid extinction. The rest of us just want to see our species actually set foot on Mars. But first, the moon.

Think of the moon as a launchpad for the Red Planet. As LiveScience found out, Boeing’s Crew Space Transportation (CST)-100 Starliner is going to take advantage of our satellite as a blast-off point for the next frontier. Starliner (the name is about as sci-fi as you can get) is what happens when Boeing, which probably makes everyone think airplanes not spaceships, joins forces with NASA to develop a reusable space capsule that will be able to fly up to seven astronauts to the ISS. It will also be the world’s first commercial space vehicle.

Starliner is even autonomous. Meaning crews will spend less time on training and take off sooner. It only needs one astronaut to fly it, or more like assist it in flight, using tablets and touch screens.

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Machines don’t actually have bias. AI doesn’t ‘want’ something to be true or false for reasons that can’t be explained through logic. Unfortunately human bias exists in machine learning from the creation of an algorithm to the interpretation of data – and until now hardly anyone has tried to solve this huge problem.

A team of scientists from Czech Republic and Germany recently conducted research to determine the effect human cognitive bias has on interpreting the output used to create machine learning rules.

The team’s white paper explains how 20 different cognitive biases could potentially alter the development of machine learning rules and proposes methods for “debiasing” them.

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We created the first working AI using the theory of practopoiesis. We are still far away from biological intelligence, but still we have something much better than classical machine learning. You can play with a live demo here:

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next is an advanced smart transportation system based on swarms of modular self-driving vehicles, refined by italian designers and engineers. the modules can drive autonomously on regular roads, joining themselves and detach even when in motion. when joined, the doors between modules fold, creating a walkable open space among modules. founded by tommaso gecchelin, the concept would greatly outperform conventional transportation when used in conjunction with other modules. the collection of next modules would improve traffic fluidity, commute time, running costs and pollution prevention by optimizing each module occupancy rate.

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once linked, passengers would be able to walk between modules next-future-transportation-concept-designboom-03
the modules would be individualized next-future-transportation-concept-designboom-04
shipping and goods transportation could be adapted next-future-transportation-concept-designboom-05
companies would offer specific modules to the system piotr boruslawski I designboom.

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“If you went to bed last night as an industrial company, you’re going to wake up this morning as a software and analytics company.” Jeff Immelt, former CEO of General Electric

The second wave of digitization is set to disrupt all spheres of economic life. As venture capital investor Marc Andreesen pointed out, “software is eating the world.” Yet, despite the unprecedented scope and momentum of digitization, many decision makers remain unsure how to cope, and turn to scholars for guidance on how to approach disruption.

The first thing they should know is that not all technological change is “disruptive.” It’s important to distinguish between different types of innovation, and the responses they require by firms. In a recent publication in the Journal of Product Innovation, we undertook a systematic review of 40 years (1975 to 2016) of innovation research. Using a natural language processing approach, we analyzed and organized 1,078 articles published on the topics of disruptive, architectural, breakthrough, competence-destroying, discontinuous, and radical innovation. We used a topic-modeling algorithm that attempts to determine the topics in a set of text documents. We quantitatively compared different models, which led us to select the model that best described the underlying text data. This model clustered text into 84 distinct topics. It performs best at explaining the variability of the data in assigning words to topics and topics to documents, minimizing noise in the data.

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