to Sell 10 Million Unit
Final Fantasy XV has a launch date of September 30, and the team in charge at publisher Square Enix has been offering a range of new details about the coming Japanese role-playing game, but there are still questions that the company is unwilling to address directly.
It is clear that, initially, the title will only debut on the Xbox One from Microsoft and the PlayStation 4 from Sony, but it seems that there’s still hope that, at some point in the future, a port for the PC will be offered.
Hajime Tabata, the director working on Final Fantasy XV, tells Engadget that his team knows that PC gamers are interested in the title and that it will evaluate the possibility of creating a special version that uses the unique advantages of the platform.
He adds, “We had to focus on the console version and our goal was to maximize, optimize everything for the HD consoles. Once that’s done, then we will definitely take a good, hard look at PC and what we need to do, and consider all our options. But right now we aren’t decided, we’re still considering a lot of things.”
The new title in the long-running franchise is introducing a number of unique mechanics, designed to appeal to both long-term fans and to those who might only now try it out.
Final Fantasy XV might need to sell more than 10 million units
A PC version for the JRPG might be needed if Square Enix wants to reach its impressive sales goals for the video game, with the company saying that it is expecting to move more than 10 million units before the end of the current fiscal year, which is in March 2017.
The goal is hard to reach because the franchise is not as popular as it once was, especially after the relatively bad impression that Final Fantasy XIV made on launch and after the issues that XIII had during its lifetime.
To boost the attractiveness of the title, Square Enix has announced some very solid special editions for its video game, including a Noctis figure and specially designed cases.
Final Fantasy XV has been in development under different names for about 10 years and is designed to introduce an interesting story as well as a range of new battle mechanics.
Before the video game is launched, gamers can find out more about characters in the Brotherhood anime, and a full CGI movie called Kingsglaive will be launched alongside the video game.
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Healthcare is one of the biggest adopters of virtual reality which encompasses surgery simulation, phobia treatment, robotic surgery and skills training.
One of the advantages of this technology is that it allows healthcare professionals to learn new skills as well as refreshing existing ones in a safe environment. Plus it allows this without causing any danger to the patients.
Human simulation software
One example of this is the HumanSim system which enables doctors, nurses and other medical personnel to interact with others in an interactive environment. They engage in training scenarios in which they have to interact with a patient but within a 3D environment only. This is an immersive experience which measures the participant’s emotions via a series of sensors.
Virtual reality diagnostics
Virtual reality is often used as a diagnostic tool in that it enables doctors to arrive at a diagnosis in conjunction with other methods such as MRI scans. This removes the need for invasive procedures or surgery.
Virtual robotic surgery
A popular use of this technology is in robotic surgery. This is where surgery is performed by means of a robotic device – controlled by a human surgeon, which reduces time and risk of complications. Virtual reality has been also been used for training purposes and, in the field of remote telesurgery in which surgery is performed by the surgeon at a separate location to the patient.
The main feature of this system is force feedback as the surgeon needs to be able to gauge the amount of pressure to use when performing a delicate procedure.
But there is an issue of time delay or latency which is a serious concern as any delay – even a fraction of a second – can feel abnormal to the surgeon and interrupt the procedure. So there needs to be precise force feedback in place to prevent this.
Robotic surgery and other issues relating to virtual reality and medicine can be found in the virtual reality and healthcare section. This section contains a list of individual articles which discuss virtual reality in surgery etc.
More Examples of Virtual Reality and Healthcare
This section looks at the various uses of VR in healthcare and is arranged as a series of the following articles:
- Advantages of virtual reality in medicine
- Virtual reality in dentistry
- Virtual reality in medicine
- Virtual reality in nursing
- Virtual reality in surgery
- Surgery simulation
- Virtual reality therapies
- Virtual reality in phobia treatment
- Virtual reality treatment for PTSD
- Virtual reality treatment for autism
- Virtual reality health issues
- Virtual reality for the disabled
Some of these articles contain further sub-articles. For example, the virtual reality in phobia treatment article links to a set of articles about individual phobias, e.g. arachnophobia, and how they are treated with this technology.
Most of us think of virtual reality in connection with surgery but this technology is used in non-surgical ways, for example as a diagnostic tool. It is used alongside other medical tests such as X-rays, scans and blood tests to help determine the cause of a particular medical condition. This often removes the need for further investigation, such as surgery, which is both time consuming and risky.
Augmented reality is another technology used in healthcare. If we return to the surgery example; with this technology, computer generated images are projected onto the part of the body to be treated or are combined with scanned real time images.
What is augmented reality? This is where computer generated images are superimposed onto a real world object with the aim of enhancing its qualities. Augmented reality is discussed in more detail as a separate section.
Virtual reality has been adopted by the military – this includes all three services (army, navy and air force) – where it is used for training purposes. This is particularly useful for training soldiers for combat situations or other dangerous settings where they have to learn how to react in an appropriate manner.
A virtual reality simulation enables them to do so but without the risk of death or a serious injury. They can re-enact a particular scenario, for example engagement with an enemy in an environment in which they experience this but without the real world risks. This has proven to be safer and less costly than traditional training methods.
Military uses of virtual reality
- Flight simulation
- Battlefield simulation
- Medic training (battlefield)
- Vehicle simulation
- Virtual boot camp
Virtual reality is also used to treat post-traumatic stress disorder. Soldiers suffering from battlefield trauma and other psychological conditions can learn how to deal with their symptoms in a ‘safe’ environment. The idea is for them to be exposed to the triggers for their condition which they gradually adjust to. This has the effect of decreasing their symptoms and enabling them to cope to new or unexpected situations.
This is discussed further in the virtual reality treatment for PTSD (post traumatic stress disorder) article.
VR equipment and the military
Virtual reality training is conducted using head mounted displays (HMD) with an inbuilt tracking system and data gloves to enable interaction within the virtual environment.
Another use is combat visualisation in which soldiers and other related personnel are given virtual reality glasses to wear which create a 3D depth of illusion. The results of this can be shared amongst large numbers of personnel.
Find out more about individual uses of virtual reality by the different services, e.g. virtual reality navy training in the separate virtual reality and the military section.
This section discusses the various military applications of virtual reality and the ramifications from using this form of technology. The military may not be an obvious candidate for virtual reality but it has been adopted by all branches – army, navy and air force.
What the military stress is that virtual reality is designed to be used as an additional aid and will not replace real life training.
This section discusses all aspects of how virtual reality is used by military, from training through to combat situations. It is arranged as follows:
- Virtual reality war
- Virtual reality and the Army
- Virtual reality and the Navy
- Virtual reality and the Air force
- Virtual reality army training
- Virtual reality army exercises
- Virtual reality air force training
- Virtual reality navy training
- Virtual reality combat training
- Virtual reality combat simulation
- Virtual reality military weapons
- Virtual reality military history
Each of these subjects is discussed as a separate article.
What is apparent is that virtual environments are ideal set ups for military training in that they enable the participants, i.e. soldiers, to experience a particular situation within a controlled area. For example, a battlefield scenario in which they can interact with events but without any personal danger to themselves.
The main advantages of this are time and cost: military training is prohibitively expensive especially airborne training so it is more cost-effective to use flight simulators than actual aircraft. Plus it is possible to introduce an element of danger into these scenarios but without causing actual physical harm to the trainees.
Flight simulators are a popular theme in military VR training but there are others which include: medical training (battlefield), combat training, vehicle training and ‘boot camp’.
But another use and one which is not immediately thought of is virtual reality and post traumatic stress disorder (PTSD). PTSD or ‘combat stress’ has only recently been acknowledged as a medical condition but it causes very real damage to the person concerned and their family. Virtual reality is used to help the sufferer adjust to their symptoms and develop coping strategies whenever they are placed in a new situation.
This is discussed at greater length in our virtual reality treatment for PTSD article.
Generally, virtual reality training involves the use of head mounted displays (HMD) and data gloves to enable military personnel to interact with objects within a virtual environment. Alternately, they may be given virtual reality glasses to wear which display a 3D image.
Last night Google’s AI AlphaGo won the first in a five-game series against the world’s best Go player, in Seoul, South Korea. The success comes just five months after a slightly less experienced version of the same program became the first machine to defeat any Go professional by winning five games against the European champion.
This victory was far more impressive though because it came at the expense of Lee Sedol, 33, who has dominated the ancient Chinese game for a decade. The European champion, Fan Hui, is ranked only 663rd in the world.
And the machine, by all accounts, played a noticeably stronger game than it did back in October, evidence that it has learned much since then. Describing their research in the journal Nature, AlphaGo’s programmers insist that it now studies mostly on its own, tuning its deep neural networks by playing millions of games against itself.
The object of Go is to surround and capture territory on a 19-by-19 board; each player alternates to place a lozenge-shaped white or black piece, called a stone, on the intersections of the lines. Unlike in chess, the player of the black stones moves first.
The neural networks judge the position, and do so well enough to play a good game. But AlphaGo rises one level further by yoking its networks to a system that generates a “tree” of analysis that represents the many branching possibilities that the game might follow. Because so many moves are possible the branches quickly become an impenetrable thicket, one reason why Go programmers haven’t had the same success as chess programmers when using this “brute force” method alone. Chess has a far lower branching factor than Go.
It seems that AlphaGo’s self-improving capability largely explains its quick rise to world mastery. By contrast, chess programs’ brute-force methods required endless fine-tuning by engineers working together with chess masters. That partly explains why programs took nine years to progress from the first defeat of a grandmaster in a single game, back in 1988, to defeating then World Champion Garry Kasparov, in a six-game match, in 1997.
Even that crowning achievement—garnered with worldwide acclaim by IBM’s Deep Blue machine—came only on the second attempt. The previous year Deep Blue had managed to win only one game in the match—the first. Kasparov then exploited weaknesses he’d spotted in the computer’s game to win three and draw four subsequent games.
Sedol appears to face longer odds of staging a comeback. Unlike Deep Blue, AlphaGo can play numerous games against itself during the 24 hours until Game Two (to be streamed live tonight at 11 pm EST, 4 am GMT). The machine can study ceaselessly, unclouded by worry, ambition, fear, or hope.
Sedol, the king of the Go world, must spend much of his time sleeping—if he can. Uneasy lies the head that wears a crown.
A business strategy learning game can be just as effective at teaching as a professor, according to a recent experiment conducted by Hult International Business School professor John Beck.
Beck and his team designed a new game, One Day, to challenge his students to develop a business strategy for an airport based on data reports and interactions with non-game playing characters -variables that change every time a student plays. Beck’s class was then divided into two groups: those who only played One Day and those who only received traditional instruction, such as reading, lecture, case study and in-class presentations, from a top-rated professor. At the end of the semester, students who played One Day achieved similar results as their peers.
According to Beck, One Day uses a unique learning method that complements traditional instruction. Instead of replicating what happens in the classroom, the game presents students with a business scenario that evolves as they plan, strategize and interact with given materials. This allows students to experience basic concepts in a more immersive way.
Professors benefit, too. The game also offers them more time to help students refine their skills in harder to learn areas, and to conduct research and teach more granular material.
Beck’s experiment comes at a time when many business schools are experimenting with making their curriculum more virtual after largely resisting increased use of technology due to the difficulty of programming high-level concepts.
Elite colleges around the country, such as Stanford and Harvard, are already exploring new ways to present difficult concepts to online users. A single course for HarvardX, the university’s online learning platform which launched last year, already has more than 10,000 registered students. Schools typically do not charge students for these courses, affording many people who normally would not have access to graduate degrees an opportunity to obtain one.
The inclusion of video game-based learning in business schools is a significant extension of this model. These games provide the opportunity to learn to more people without sacrificing educational payoff, as Beck’s experiment shows. Successes of programs such as One Day also show an unprecedented leap in capabilities and complexity for learning games otherwise reserved for simple concepts like basic math and typing.
The video game industry continues to pave the way for advancements outside of entertainment. Now, a creative new partnership between technology and pharmaceutical giants is reimagining medical imaging, and with it, tackling an incurable and unpredictable central nervous system disease that affects 2.3 million people globally.
Microsoft recently teamed up with Novartis AG to develop AssessMS to treat those suffering from multiple sclerosis (MS). The new program, which uses the Microsoft Kinect’s motion-tracking and camera technology, allows researchers to analyze important data regarding the patient’s physical symptoms, such as gait and dexterity, by recording their movements.
Imprecise measurements and inconsistent assessments of patients’ movements currently complicate patients and doctors’ ability to evaluate the severity of MS symptoms and make informed choices about care and treatment options. These medical difficulties carry over into the pharmaceutical industry, making new drug trials challenging and costly.
Microsoft and Novartis believe their new program can change this calculus by offering more refined data. As patients perform simple body movements and gestures in front of the Kinect motion-sensing camera, doctors are able to evaluate precise information to evaluate the degree of impairment.
So far, prototypes have run hundreds of tests with patients in three of the top MS clinics in Europe. If the system shows promise, Novartis hopes to pursue the clinical validation process and seek regulatory approval.
This new system marks a break with previous games-based treatment options. Previously, doctors and patients primarily used games such as the Nintendo Wii Balance Board to help people with MS improve their balance. However, as several recent studies have found, games can help patients improve motor skills and visual acuity, sharpen short-term memory, reduce depressive symptoms, and relieve chronic pain, all difficulties common among people with MS.
“This is really super-interesting work,” Tim Coetzee, chief advocacy, services, and research officer at the National MS Society in the U.S. told Bloomberg. “The problem we are trying to solve in MS cries out for tools like this one where it is about being able to give the physician some consistent approach to measure the evolution of the disease.”
With these new advancements, the video game industry has the potential to revolutionize healthcare. As studies and tests continue to improve and evolve, researchers and game companies alike are working together to discover new treatments – even cures – to some of today’s biggest medical challenges.
Last month, the 2016 D.I.C.E. Summit brought together video game executives, designers, developers, and publishers from around the world to explore the creative process and discuss the industry’s current state and exciting future.
Industry icons like Randy Pitchford and Todd Howard examined the promises innovations such as virtual reality represent for the future of video games; debated the challenges facing the industry such as gender diversity; and offered unique insights into how video games have become the leading entertainment industry in the United States.
Michael D. Gallagher, president and CEO of the Entertainment Software Association (ESA), gave an in-depth look at the evolution of the industry as well as its significant impact on the economy, education, and technology. The speech illustrated how far video games have come, drawing on ESA’s pivotal role in the landmark Supreme Court decision, growing relationships with federal and state policymakers, and initiatives like the Higher Education Video Game Alliance (HEVGA) and the ESA Foundation.
Gallagher concluded by calling on the industry to join ESA in ensuring that the industry keeps growing, and for players to get involved through the Video Game Voters Network. “This work must continue. The mission isn’t over. And our strength and success depend upon the continued support of all of you.” Watch the full speech online here.
Afterward, Gallagher fielded questions about the role ESA plays in other important issues, such as increasing gender diversity in tech-related fields. As Gallagher noted, the video game industry employs more women than other tech sectors and nearly a third of students enrolled in video game programs are women. Women are increasingly represented in games too: every major game released in the fourth quarter of 2015 had playable female characters. “I see the pipeline looks much brighter when it comes to the diversity issues of today,” Gallagher remarked.
For a full recap of this year’s summit, visit the D.I.C.E. website.
System learns to play text-based computer game using only linguistic information.
MIT researchers have designed a computer system that learns how to play a text-based computer game with no prior assumptions about how language works. Although the system can’t complete the game as a whole, its ability to complete sections of it suggests that, in some sense, it discovers the meanings of words during its training.
In 2011, professor of computer science and engineering Regina Barzilay and her students reported a system that learned to play a computer game called “Civilization” by analyzing the game manual. But in the new work, on which Barzilay is again a co-author, the machine-learning system has no direct access to the underlying “state” of the game program — the data the program is tracking and how it’s being modified.
“When you play these games, every interaction is through text,” says Karthik Narasimhan, an MIT graduate student in computer science and engineering and one of the new paper’s two first authors. “For instance, you get the state of the game through text, and whatever you enter is also a command. It’s not like a console with buttons. So you really need to understand the text to play these games, and you also have more variability in the types of actions you can take.”
Narasimhan is joined on the paper by Barzilay, who’s his thesis advisor, and by fellow first author Tejas Kulkarni, a graduate student in the group of Josh Tenenbaum, a professor in the Department of Brain and Cognitive Sciences. They presented the paper last week at the Empirical Methods in Natural Language Processing conference.
The researchers were particularly concerned with designing a system that could make inferences about syntax, which has been a perennial problem in the field of natural-language processing. Take negation, for example: In a text-based fantasy game, there’s a world of difference between being told “you’re hurt” and “you’re not hurt.” But a system that just relied on collections of keywords as a guide to action would miss that distinction.
So the researchers designed their own text-based computer game that, though very simple, tended to describe states of affairs using troublesome syntactical constructions such as negation and conjunction. They also tested their system against a demonstration game built by the developers of Evennia, a game-creation toolkit. “A human could probably complete it in about 15 minutes,” Kulkarni says.
To evaluate their system, the researchers compared its performance to that of two others, which use variants of a technique standard in the field of natural-language processing. The basic technique is called the “bag of words,” in which a machine-learning algorithm bases its outputs on the co-occurrence of words. The variation, called the “bag of bigrams,” which looks for the co-occurrence of two-word units.
On the Evennia game, the MIT researchers’ system outperformed systems based on both bags of words and bags of bigrams. But on the homebrewed game, with its syntactical ambiguities, the difference in performance was even more dramatic. “What we created is adversarial, to actually test language understanding,” Narasimhan says.
The MIT researchers used an approach to machine learning called deep learning, a revival of the concept of neural networks, which was a staple of early artificial-intelligence research. Typically, a machine-learning system will begin with some assumptions about the data it’s examining, to prevent wasted time on fruitless hypotheses. A natural-language-processing system could, for example, assume that some of the words it encounters will be negation words — though it has no idea which words those are.
Neural networks make no such assumptions. Instead, they derive a sense of direction from their organization into layers. Data are fed into an array of processing nodes in the bottom layer of the network, each of which modifies the data in a different way before passing it to the next layer, which modifies it before passing it to the next layer, and so on. The output of the final layer is measured against some performance criterion, and then the process repeats, to see whether different modifications improve performance.
In their experiments, the researchers used two performance criteria. One was completion of a task — in the Evennia game, crossing a bridge without falling off, for instance. The other was maximization of a score that factored in several player attributes tracked by the game, such as “health points” and “magic points.”
On both measures, the deep-learning system outperformed bags of words and bags of bigrams. Successfully completing the Evennia game, however, requires the player to remember a verbal description of an engraving encountered in one room and then, after navigating several intervening challenges, match it up with a different description of the same engraving in a different room. “We don’t know how to do that at all,” Kulkarni says.
“I think this paper is quite nice and that the general area of mapping natural language to actions is an interesting and important area,” says Percy Liang, an assistant professor of computer science and statistics at Stanford University who was not involved in the work. “It would be interesting to see how far you can scale up these approaches to more complex domains.”
DirectX 12 introduces the next version of Direct3D, the 3D graphics API at the heart of DirectX. This version of Direct3D is faster and more efficient than any previous version. Direct3D 12 enables richer scenes, more objects, more complex effects, and full utilization of modern GPU hardware.
What makes Direct3D 12 better?
Direct3D 12 provides a lower level of hardware abstraction than ever before, which allows developers to significantly improve the multi-thread scaling and CPU utilization of their titles. With Direct3D 12, titles are responsible for their memory management. In addition, by using Direct3D 12, games and titles benefit from reduced GPU overhead via features such as command queues and lists, descriptor tables, and concise pipeline state objects.
Direct3D 12, and Direct3D 11.3, introduce a set of new features for the rendering pipeline: conservative rasterization to enable reliable hit detection, volume-tiled resources to enable streamed three dimension resources to be treated as if they were all in video memory, rasterizer ordered views to enable reliable transparency rendering, setting the stencil reference within a shader to enable special shadowing and other effects, and also improved texture mapping and typed Unordered Access View (UAV) loads.
Who is Direct3D 12 for?
Direct3D 12 provides four main benefits to graphics developers (compared with Direct3D 11): vastly reduced CPU overhead, significantly improved power consumption, up to around twenty percent improvement in GPU efficiency, and cross-platform development for a Windows 10 device (PC, tablet, console or phone).
Direct3D 12 is certainly for advanced graphics programmers, it requires a fine level of tuning and significant graphics expertise. Direct3D 12 is designed to make full use of multi-threading, careful CPU/GPU synchronization, and the transition and re-use of resources from one purpose to another. All techniques that require a considerable amount of memory level programming skill.
Another advantage that Direct3D 12 has is its small API footprint. There are around 200 methods, and about one third of these do all the heavy lifting. This means that a graphics developer should be able to educate themselves on – and master – the full API set without the weight of having to memorize a great volume of API calls.
Direct3D 12 does not replace Direct3D 11. The new rendering features of Direct3D 12 are available in Direct3D 11.3. Direct3D 11.3 is a low level graphics engine API, and Direct3D 12 goes even deeper.
There are at least two ways a development team can approach a Direct3D 12 title.
For a project that takes full advantage of the benefits of Direct3D 12, a highly customized Direct3D 12 game engine should be developed from the ground up.
One approach is that if graphics developers understand the use and re-use of resources within their titles, and can take advantage of this by minimizing uploading and copying, then a highly efficient engine can be developed and customized for these titles. The performance improvements could be very considerable, freeing up CPU time to increase the number of draw calls, and so adding more luster to graphics rendering.
The programming investment is significant, and debugging and instrumentation of the project should be considered from the very start: threading, synchronization and other timing bugs can be challenging.
A shorter term approach would be to address known bottlenecks in a Direct3D 11 title; these can be addressed by using the 11on12 or interop techniques enabling the two APIs to work together. This approach minimizes the changes necessary to an existing Direct3D 11 graphics engine, however the performance gains will be limited to the relief of the bottleneck that the Direct3D 12 code addresses.
Direct3D 12 is all about dramatic graphics engine performance: ease of development, high level constructs, and compiler support have been scaled back to enable this. Driver support and ease of debugging remain on a par with Direct3D 11.
Direct3D 12 is new territory, for the inquisitive expert to explore.
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