Weird-looking robots are the best robots.
Category: robotics/AI – Page 2,258
Ethicist Warns: Future AI Could Take Revenge for How We Treat It Now
If machines become truly intelligent or sentient, an ethicist at Victoria University Wellington named Nicholas Agar is sharing a dire warning: future machines may want payback for how we treat their insentient ancestors today.
Should robots ever become sentient, they may be pissed at how much we insult Alexa today.
Why modern enterprises need to adopt cognitive computing for faster business growth in a digital economy
Cognitive computing (CC) technology revolves around making computers adept at mimicking the processes of the human brain, which is basically making them more intelligent. Even though the phrase cognitive computing is used synonymously with AI, the term is closely associated with IBM’s cognitive computer system, Watson. IBM Watson is a supercomputer that leverages AI-based disruptive technologies like machine learning (ML), real-time analysis, natural language processing, etc. to augment decision making and deliver superior outcomes.
To Compete With Google, OpenAI Seeks Investors–and Profits
On Monday, OpenAI’s leaders said that a paltry $1 billion wouldn’t be enough to compete with the well-resourced AI labs at companies such as Google and Facebook after all. They announced the new investment vehicle, a company called OpenAI LP, as a way to raise extra money for the computing power and people needed to steer the destiny of AI. Musk left the board of OpenAI last February and is not formally involved in OpenAI LP.
OpenAI, the independent research lab cofounded by Elon Musk, created a for-profit arm to attract more funding to hire researchers and run computers.
Magnetic nano-probe explores individual cells from the inside
There’s a good chance that in the future, microscopic robots could be swimming and crawling their way through our bodies to deliver drugs or fight infections. While some of these have been capable of manipulating individual cells, researchers at the University of Toronto have developed a new way to get nano-scale probes inside cells, and precisely control them once they’re in there.
Made In Space Archinaut Program Reaches Major Milestone as Development Continues
The Made In Space Archinaut program has accomplished another exciting milestone. During recent testing at Northrop Grumman’s Space Park facilities in Redondo Beach, California, we successfully operated Archinaut’s core additive manufacturing and robotic assembly technology suite in a space-like environment. These operations took place in a thermal vacuum (TVAC) chamber, simulating the extreme temperature and vacuum pressure of what a satellite in Low Earth Orbit (LEO) would be exposed to. The completion of this ground-based testing raises the technology readiness level (TRL) of the Archinaut platform and demonstrates that core Archinaut technologies are now prepared to operate in space.
The Archinaut platform looks to provide mission critical, space-optimized structures on orbit that would otherwise be too large to launch, using on-demand, adaptable manufacturing. With the marriage of additive manufacturing and robotic assembly, Archinaut enabled structures can range from:
Volvo’s first electric driverless bus swings into action in Singapore
Singapore is intent on positioning itself at the vanguard of self-driving technologies. Now it is looking to ramp things up even further, rolling what it claims to be the world’s first full size, autonomous electric bus onto a university campus in partnership with Volvo.
Unmasking Clever Hans predictors and assessing what machines really learn
Is your AI intelligent or just looking like it’s intelligent? In many ways, this depends on your idea of AI and what it is supposed to do. Scientists at Singapore University of Technology and Design have worked out a way to check for the issue. Open Access Journal: https://www.nature.com/articles/s41467-019-08987-4
Current learning machines have successfully solved hard application problems, reaching high accuracy and displaying seemingly intelligent behavior. Here we apply recent techniques for explaining decisions of state-of-the-art learning machines and analyze various tasks from computer vision and arcade games. This showcases a spectrum of problem-solving behaviors ranging from naive and short-sighted, to well-informed and strategic. We observe that standard performance evaluation metrics can be oblivious to distinguishing these diverse problem solving behaviors. Furthermore, we propose our semi-automated Spectral Relevance Analysis that provides a practically effective way of characterizing and validating the behavior of nonlinear learning machines. This helps to assess whether a learned model indeed delivers reliably for the problem that it was conceived for. Furthermore, our work intends to add a voice of caution to the ongoing excitement about machine intelligence and pledges to evaluate and judge some of these recent successes in a more nuanced manner.
Sir Martin Rees on the Future: Prospects for Humanity
Astronomer Royal Sir Martin Rees on the #Future: Prospects for #Humanity https://www.singularityweblog.com/martin-rees/ #AI #Singularity #Futurism
Martin Rees has been concerned with our ever-heavier ‘footprint’ on the global environment and with the runaway consequences of our powerful technologies.