detroix.exe

V1-Effect is Fab..! , Text , Textures Ps : Both are good.

When @Mr.Love know's about @G-Dark™'s multi account His reaction

V1 : Size, effect , text , text colour

I hope this can't be fixeded #HERE in Adobe community the team gave no rply so try to reset photoshop

@Mr.Daniel ♔♔♔

V2 : Text , Effect , Clear

@#Superme

V2 : Effect , Brush , Texture

@#Garrix which font!!

On a slow news day, an NVIDIA high-end GPU being out of stock might be something worth covering, but it takes an especially slow-news-day to take an out of stock card, speculate it has been delisted and then contrive a story about mass recalls. Contrary to reports you might see floating around, the NVIDIA RTX 2080 Ti has not in fact been delisted and is just out of stock. You can tell by simply heading over to Geforce.com and seeing that the product page is still there and it appears to be undergoing its usual stock refresh cycles. Scandalous scoop: NVIDIA’s RTX 2080 Ti graphics card goes out of stock Some media houses have published the out-of-stock status of the RTX 2080 Ti as proof of an impending mass recall (to be clear, there is none) and even quoted a forum post which conceded that some initial batches had problematic dies – which of course has nothing to do with the OOS status at all and is simply the result of the complex nature of the Turing die and how the fabrication process works. While I love a good scoop as much as any other tech-head (probably more considering I am the senior editor over here¯\_(ツ)_/¯ ), the only sensational scoop I could find in this story is the RTX 2080 Ti being out of stock. Ironically, this is actually a good indicator for the card because it means the stock is evaporating faster than the company can restock it seamlessly. You can also go out and buy the RTX 2080 Ti on any retailer right now – including but not limited to Amazon, Newegg and the like – so there clearly isn’t any recall happening. Still don’t believe me? I reached out to NVIDIA directly and they practically laughed at this one. They confirmed that the card is just out of stock and is undergoing a scheduled restock and will be available for purchase before long: The eTeknix story is incorrect. 2080 Ti Founders Edition is available on GeForce.com as usual. There seems to be confusion regarding the store link on nvidia.com which defaults to listing products that are currently in stock only. If a product does not show up there, that merely means the item is out of stock at the time you conducted a search. It does not mean a product has been delisted. Geforce.com is always your best choice for all things gaming related. https://www.nvidia.com/en-us/geforce/ – NVIDIA spokesperson to Wccftech If I didn’t know any better, I would think this was a hit-story concocted by shorts of NVIDIA stock wanting to make a quick buck and to take advantage of the prevailing sentiment since the quarterly earnings. Shorts have already rejoiced and this is the ideal time to take advantage of the presence of bears to bring the stock down a further few notches. The RTX 2080 Ti is a very complex die – I would even go as far as to call it one of the most complex dies ever made for gaming simply because it houses a triumvirate of processor classes inside. It’s hard and expensive to fab, and yield bugs are expected when dealing with something like this. But none of that actually translates even remotely to anything resembling a mass recall. That is just another example of baseless hysteria for the masses and should be avoided for the sake of a healthy rumor mill that we all know and love.

A computer built to mimic the brain's neural networks produces similar results to that of the best brain-simulation supercomputer software currently used for neural-signaling research, finds a new study published in the open-access journal Frontiers in Neuroscience. Tested for accuracy, speed and energy efficiency, this custom-built computer named SpiNNaker, has the potential to overcome the speed and power consumption problems of conventional supercomputers. The aim is to advance our knowledge of neural processing in the brain, to include learning and disorders such as epilepsy and Alzheimer's disease. "SpiNNaker can support detailed biological models of the cortex -- the outer layer of the brain that receives and processes information from the senses -- delivering results very similar to those from an equivalent supercomputer software simulation," says Dr. Sacha van Albada, lead author of this study and leader of the Theoretical Neuroanatomy group at the Jülich Research Centre, Germany. "The ability to run large-scale detailed neural networks quickly and at low power consumption will advance robotics research and facilitate studies on learning and brain disorders." The human brain is extremely complex, comprising 100 billion interconnected brain cells. We understand how individual neurons and their components behave and communicate with each other and on the larger scale, which areas of the brain are used for sensory perception, action and cognition. However, we know less about the translation of neural activity into behavior, such as turning thought into muscle movement. Supercomputer software has helped by simulating the exchange of signals between neurons, but even the best software run on the fastest supercomputers to date can only simulate 1% of the human brain. "It is presently unclear which computer architecture is best suited to study whole-brain networks efficiently. The European Human Brain Project and Jülich Research Centre have performed extensive research to identify the best strategy for this highly complex problem. Today's supercomputers require several minutes to simulate one second of real time, so studies on processes like learning, which take hours and days in real time are currently out of reach." explains Professor Markus Diesmann, co-author, head of the Computational and Systems Neuroscience department at the Jülich Research Centre. He continues, "There is a huge gap between the energy consumption of the brain and today's supercomputers. Neuromorphic (brain-inspired) computing allows us to investigate how close we can get to the energy efficiency of the brain using electronics." Developed over the past 15 years and based on the structure and function of the human brain, SpiNNaker -- part of the Neuromorphic Computing Platform of the Human Brain Project -- is a custom-built computer composed of half a million of simple computing elements controlled by its own software. The researchers compared the accuracy, speed and energy efficiency of SpiNNaker with that of NEST -- a specialist supercomputer software currently in use for brain neuron-signaling research. "The simulations run on NEST and SpiNNaker showed very similar results," reports Steve Furber, co-author and Professor of Computer Engineering at the University of Manchester, UK. "This is the first time such a detailed simulation of the cortex has been run on SpiNNaker, or on any neuromorphic platform. SpiNNaker comprises 600 circuit boards incorporating over 500,000 small processors in total. The simulation described in this study used just six boards -- 1% of the total capability of the machine. The findings from our research will improve the software to reduce this to a single board." Van Albada shares her future aspirations for SpiNNaker, "We hope for increasingly large real-time simulations with these neuromorphic computing systems. In the Human Brain Project, we already work with neuroroboticists who hope to use them for robotic control."

V1 text