face_with_colon_three Big change to cellular satellites directly to cell phones now where wherever there is sky you link up with no receiver other than a smartphone.
T-Mobile’s push to allow AT&T and Verizon customers to tap into its cellular Starlink service underscores a growing competition in the satellite-to-phone market.
“Kara”, Quantic Dream’s newest tech demo featuring the early 2011 version of our new PS3 engine.
Valorie Curry’s acting was performance captured (body, face, voice) on December 14. 2010 in our then newly renovated motion capture studio, using a 64 high-precision Vicon camera system. This is a compressed (QT.H264 720 p) video capture of the realtime running demo on PS3. A making-of will follow soon. KARA is NOT Quantic Dream’s upcoming PS3 title. The later shall be revealed soon.
A new mathematical model sheds light on how the brain processes different cues, such as sights and sounds, during decision making. The findings from Princeton neuroscientists may one day improve how brain circuits go awry in neurological disorders, such as Alzheimer’s, and could help artificial brains, like Alexa or self-driving car technology, more helpful.
The simulation hypothesis suggests that our entire universe and reality could just be hyper-enhanced reality illusions.
He believes recent developments in the field of information physics ‘appear to support this possibility’ in that the physical world is made up of bits of information.
Vopson goes even further by claiming that information might have physical weight and could be a key part of the universe.
The report highlights breakthroughs in AI, connectivity, and sustainability, such as deep learning, reconfigurable intelligent surfaces, and engineered organisms to combat climate change.
A team of researchers at Google’s DeepMind project, reports that its AlphaGeometry2 AI performed at a gold-medal level when tasked with solving problems that were given to high school students participating in the International Mathematical Olympiad (IMO) over the past 25 years. In their paper posted on the arXiv preprint server, the team gives an overview of AlphaGeometry2 and its scores when solving IMO problems.
Prior research has suggested that AI that can solve geometry problems could lead to more sophisticated apps because they require both a high level of reasoning ability and an ability to choose from possible steps in working toward a solution to a problem.
To that end, the team at DeepMind has been working on developing increasingly sophisticated geometry-solving apps. Its first iteration was released last January and was called AlphaGeometry; its second iteration is called AlphaGeometry2.
Evolution is traditionally associated with a process of increasing complexity and gaining new genes. However, the explosion of the genomic era shows that gene loss and simplification is a much more frequent process in the evolution of species than previously thought, and may favor new biological adaptations that facilitate the survival of living organisms.
This evolutionary driver, which seems counter-intuitive—” less is more” in genetic terms—now reveals a surprising dimension that responds to the new evolutionary concept of “less, but more,” i.e., the phenomenon of massive gene losses followed by large expansions through gene duplications.
This is one of the main conclusions of an article published in the journal Molecular Biology and Evolution, led by a team from the Genetics Section of the Faculty of Biology and the Institute for Research on Biodiversity (IRBio) of the University of Barcelona, in which teams from the Okinawa Institute of Science and Technology (OIST) have also participated.
Before joining MPFI, Wang was a research scientist at the Janelia Research Campus of Howard Hughes Medical Institute, working with Dr. Jeffery Magee and previously with Dr. Eva Pastalkova. At Janelia, she studied the hippocampal neuronal activities that represent memory traces. In particular, she employed memory tasks that can reversibly toggle the influence of sensory inputs on and off and isolated neuronal activities associated with internally stored memory.
Wang was trained as an electrical engineer. She completed her graduate study under the mentorship of Drs. Shih-Chii Liu, Tobi Delbruck and Rodney Douglas at the Swiss Federal Institute of Technology Zurich (ETHZ). During her Ph.D. training, she designed brain-inspired computational systems on silicon chips. These fully reconfigurable systems incorporated electronic circuits of a network of neurons with dendrites and synapses. Using these systems as simulation tools, she also investigated the computational principles native to a neuron with active dendrites.