The number of customers who are now deeply deployed on AWS, deployed in the cloud, in a way that's fundamental to their business and fundamental to their success surprised me.

There was a time years ago where there were not that many enterprise CEOs who were well-versed in the cloud. It's not just about deploying technology. The conversation that I most end up having with CEOs is about organizational transformation. It is about how they can put data at the center of their decision-making in a way that most organizations have never actually done in their history.

And it's about using the cloud to innovate more quickly and to drive speed into their organizations. Those are cultural characteristics, not technology characteristics, and those have organizational implications about how they organize and what teams they need to have. It turns out that while the technology is sophisticated, deploying the technology is arguably the lesser challenge compared with how do you mold and shape the organization to best take advantage of all the benefits that the cloud is providing.

How has your experience at Tableau affected AWS and how you think about putting your stamp on AWS? I, personally, have just spent almost five years deeply immersed in the world of data and analytics and business intelligence, and hopefully I learned something during that time about those topics.

I'm able to bring back a real insider's view, if you will, about where that world is heading — data, analytics, databases, machine learning, and how all those things come together, and how you really need to view what's happening with data as an end-to-end story. It's not about having a point solution for a database or an analytic service, it's really about understanding the flow of data from when it comes into your organization all the way through the other end, where people are collaborating and sharing and making decisions based on that data.

AWS has tremendous resources devoted in all these areas. Can you talk about the intersection of data and machine learning and how you see that playing out in the next couple of years? What we're seeing is three areas really coming together: You've got databases, analytics capabilities, and machine learning, and it's sort of like a Venn diagram with a partial overlap of those three circles. There are areas of each which are arguably still independent from each other, but there's a very large and a very powerful intersection of the three — to the point where we've actually organized inside of AWS around that and have a single leader for all of those areas to really help bring those together.

There's so much data in the world, and the amount of it continues to explode. We were saying that five years ago, and it's even more true today. The rate of growth is only accelerating. It's a huge opportunity and a huge problem. A lot of people are drowning in their data and don't know how to use it to make decisions.

Other organizations have figured out how to use these very powerful technologies to really gain insights rapidly from their data. What we're really trying to do is to look at that end-to-end journey of data and to build really compelling, powerful capabilities and services at each stop in that data journey and then…knit all that together with strong concepts like governance. By putting good governance in place about who has access to what data and where you want to be careful within those guardrails that you set up, you can then set people free to be creative and to explore all the data that's available to them.

AWS has more than services now. Have you hit the peak for that or can you sustain that growth? We're not done building yet, and I don't know when we ever will be. We continue to both release new services because customers need them and they ask us for them and, at the same time, we've put tremendous effort into adding new capabilities inside of the existing services that we've already built.

We don't just build a service and move on. Inside of each of our services — you can pick any example — we're just adding new capabilities all the time. One of our focuses now is to make sure that we're really helping customers to connect and integrate between our different services. So those kinds of capabilities — both building new services, deepening our feature set within existing services, and integrating across our services — are all really important areas that we'll continue to invest in.

Do customers still want those fundamental building blocks and to piece them together themselves, or do they just want AWS to take care of all that? There's no one-size-fits-all solution to what customers want.

It is interesting, and I will say somewhat surprising to me, how much basic capabilities, such as price performance of compute, are still absolutely vital to our customers. But it's absolutely vital. Part of that is because of the size of datasets and because of the machine learning capabilities which are now being created. They require vast amounts of compute, but nobody will be able to do that compute unless we keep dramatically improving the price performance.

We also absolutely have more and more customers who want to interact with AWS at a higher level of abstraction…more at the application layer or broader solutions, and we're putting a lot of energy, a lot of resources, into a number of higher-level solutions. One of the biggest of those … is Amazon Connect, which is our contact center solution. In minutes or hours or days, you can be up and running with a contact center in the cloud.

At the beginning of the pandemic, Barclays … sent all their agents home. In something like 10 days, they got 6, agents up and running on Amazon Connect so they could continue servicing their end customers with customer service. We've built a lot of sophisticated capabilities that are machine learning-based inside of Connect. We can do call transcription, so that supervisors can help with training agents and services that extract meaning and themes out of those calls.

We don't talk about the primitive capabilities that power that, we just talk about the capabilities to transcribe calls and to extract meaning from the calls. It's really important that we provide solutions for customers at all levels of the stack.

Given the economic challenges that customers are facing, how is AWS ensuring that enterprises are getting better returns on their cloud investments? Now's the time to lean into the cloud more than ever, precisely because of the uncertainty. We saw it during the pandemic in early , and we're seeing it again now, which is, the benefits of the cloud only magnify in times of uncertainty.

For example, the one thing which many companies do in challenging economic times is to cut capital expense. For most companies, the cloud represents operating expense, not capital expense. You're not buying servers, you're basically paying per unit of time or unit of storage.

That provides tremendous flexibility for many companies who just don't have the CapEx in their budgets to still be able to get important, innovation-driving projects done. Another huge benefit of the cloud is the flexibility that it provides — the elasticity, the ability to dramatically raise or dramatically shrink the amount of resources that are consumed.

You can only imagine if a company was in their own data centers, how hard that would have been to grow that quickly. The ability to dramatically grow or dramatically shrink your IT spend essentially is a unique feature of the cloud. These kinds of challenging times are exactly when you want to prepare yourself to be the innovators … to reinvigorate and reinvest and drive growth forward again.

We've seen so many customers who have prepared themselves, are using AWS, and then when a challenge hits, are actually able to accelerate because they've got competitors who are not as prepared, or there's a new opportunity that they spot. We see a lot of customers actually leaning into their cloud journeys during these uncertain economic times. Do you still push multi-year contracts, and when there's times like this, do customers have the ability to renegotiate?

Many are rapidly accelerating their journey to the cloud. Some customers are doing some belt-tightening. What we see a lot of is folks just being really focused on optimizing their resources, making sure that they're shutting down resources which they're not consuming. You do see some discretionary projects which are being not canceled, but pushed out. Every customer is free to make that choice.

But of course, many of our larger customers want to make longer-term commitments, want to have a deeper relationship with us, want the economics that come with that commitment.

We're signing more long-term commitments than ever these days. We provide incredible value for our customers, which is what they care about. That kind of analysis would not be feasible, you wouldn't even be able to do that for most companies, on their own premises.

So some of these workloads just become better, become very powerful cost-savings mechanisms, really only possible with advanced analytics that you can run in the cloud. In other cases, just the fact that we have things like our Graviton processors and … run such large capabilities across multiple customers, our use of resources is so much more efficient than others.

We are of significant enough scale that we, of course, have good purchasing economics of things like bandwidth and energy and so forth. So, in general, there's significant cost savings by running on AWS, and that's what our customers are focused on.

The margins of our business are going to … fluctuate up and down quarter to quarter. It will depend on what capital projects we've spent on that quarter. Obviously, energy prices are high at the moment, and so there are some quarters that are puts, other quarters there are takes. The important thing for our customers is the value we provide them compared to what they're used to. And those benefits have been dramatic for years, as evidenced by the customers' adoption of AWS and the fact that we're still growing at the rate we are given the size business that we are.

That adoption speaks louder than any other voice. Do you anticipate a higher percentage of customer workloads moving back on premises than you maybe would have three years ago? Absolutely not. We're a big enough business, if you asked me have you ever seen X, I could probably find one of anything, but the absolute dominant trend is customers dramatically accelerating their move to the cloud. Moving internal enterprise IT workloads like SAP to the cloud, that's a big trend. Creating new analytics capabilities that many times didn't even exist before and running those in the cloud.

More startups than ever are building innovative new businesses in AWS. Our public-sector business continues to grow, serving both federal as well as state and local and educational institutions around the world. It really is still day one. The opportunity is still very much in front of us, very much in front of our customers, and they continue to see that opportunity and to move rapidly to the cloud. In general, when we look across our worldwide customer base, we see time after time that the most innovation and the most efficient cost structure happens when customers choose one provider, when they're running predominantly on AWS.

A lot of benefits of scale for our customers, including the expertise that they develop on learning one stack and really getting expert, rather than dividing up their expertise and having to go back to basics on the next parallel stack.

That being said, many customers are in a hybrid state, where they run IT in different environments. In some cases, that's by choice; in other cases, it's due to acquisitions, like buying companies and inherited technology.

We understand and embrace the fact that it's a messy world in IT, and that many of our customers for years are going to have some of their resources on premises, some on AWS. Some may have resources that run in other clouds.

We want to make that entire hybrid environment as easy and as powerful for customers as possible, so we've actually invested and continue to invest very heavily in these hybrid capabilities. A lot of customers are using containerized workloads now, and one of the big container technologies is Kubernetes. We have a managed Kubernetes service, Elastic Kubernetes Service, and we have a … distribution of Kubernetes Amazon EKS Distro that customers can take and run on their own premises and even use to boot up resources in another public cloud and have all that be done in a consistent fashion and be able to observe and manage across all those environments.

So we're very committed to providing hybrid capabilities, including running on premises, including running in other clouds, and making the world as easy and as cost-efficient as possible for customers. Can you talk about why you brought Dilip Kumar, who was Amazon's vice president of physical retail and tech, into AWS as vice president applications and how that will play out? He's a longtime, tenured Amazonian with many, many different roles — important roles — in the company over a many-year period.

Dilip has come over to AWS to report directly to me, running an applications group. We do have more and more customers who want to interact with the cloud at a higher level — higher up the stack or more on the application layer. We talked about Connect, our contact center solution, and we've also built services specifically for the healthcare industry like a data lake for healthcare records called Amazon HealthLake.

We've built a lot of industrial services like IoT services for industrial settings, for example, to monitor industrial equipment to understand when it needs preventive maintenance. We have a lot of capabilities we're building that are either for … horizontal use cases like Amazon Connect or industry verticals like automotive, healthcare, financial services. We see more and more demand for those, and Dilip has come in to really coalesce a lot of teams' capabilities, who will be focusing on those areas.

You can expect to see us invest significantly in those areas and to come out with some really exciting innovations. Would that include going into CRM or ERP or other higher-level, run-your-business applications? I don't think we have immediate plans in those particular areas, but as we've always said, we're going to be completely guided by our customers, and we'll go where our customers tell us it's most important to go next. It's always been our north star. Correction: This story was updated Nov.

Bennett Richardson bennettrich is the president of Protocol. Prior to joining Protocol in , Bennett was executive director of global strategic partnerships at POLITICO, where he led strategic growth efforts including POLITICO's European expansion in Brussels and POLITICO's creative agency POLITICO Focus during his six years with the company.

Prior to POLITICO, Bennett was co-founder and CMO of Hinge, the mobile dating company recently acquired by Match Group. Bennett began his career in digital and social brand marketing working with major brands across tech, energy, and health care at leading marketing and communications agencies including Edelman and GMMB.

Bennett is originally from Portland, Maine, and received his bachelor's degree from Colgate University. Prior to joining Protocol in , he worked on the business desk at The New York Times, where he edited the DealBook newsletter and wrote Bits, the weekly tech newsletter. He has previously worked at MIT Technology Review, Gizmodo, and New Scientist, and has held lectureships at the University of Oxford and Imperial College London. He also holds a doctorate in engineering from the University of Oxford.

We launched Protocol in February to cover the evolving power center of tech. It is with deep sadness that just under three years later, we are winding down the publication. As of today, we will not publish any more stories. Here are a few tips for you to follow if you aspire to become one of the binary options millionaires;.

Simple and effective. Follow these simple steps and stay in the game. Success and failures are part of the journey. Even the most successful traders suffered losses. Be persistent and be ready to become the next big thing in trading binary options.

Trading binary options can be amazing for most traders, especially for those who do not have the necessary skills or time to manually analyze prevailing market conditions on a daily basis. A binary trade is also very helpful for beginner traders who may have low skills at the start of their trading career. An interesting aspect of binary trade is that it is not limited to one or a few markets only , as binary trades can be made in virtually every financial market. However, it is also true that trading binary is most popular in the foreign exchange market, and recently it has gained immense popularity in the cryptocurrency market.

But you may use trading binary options strategy for other markets, such as stock exchange trading, commodities trading, synthetic indices, and even CFDs, among many other financial markets. When trading binary options, the options are limited to yes or no, and binary options broker firms usually provide these yes or no signals with a fair amount of accuracy. With binary trades, it may be easier to exploit various opportunities in the market, especially those opportunities that are time sensitive.

As trading binary options is more about making predictions of future price movements in the market, the right availability of trading binary signals ensures better control of trades.

There is a common misconception in the market that binary trades are far riskier than other trading strategies, as, if the prediction goes wrong, one may end up losing all the money. However, this may not be the case in reality. This is due to the fact that most traders are able to limit their losses by simply limiting their stakes. Hence, binary trading acts similarly to other trade strategies when it comes to managing risks and losses. In order to ensure long term success, it is always useful to keep your long term strategy in mind.

Binary trading is not about arbitrary trade decisions inspired by random events in the market. Instead, it is extremely important to have a bigger picture in mind when making binary trades. Even with trading binary option, it may be possible to come up with a range of different trading strategies. So, make sure to know which strategy suits you and serves your long term needs.

Following a reliable trading strategy is extremely important for ensuring long term profitability in the binary option trading industry. It is not uncommon for those who trade binary options to have question in relation to their personal trade volume. Some traders go as far as to set specific goals for the number of trades to enter into each day.

This approach is fine, so long as the number is reasonable. However, it is important to remember that the markets may yield a larger or smaller number of optimal entry points each day , based upon the events of the day. Consider the following information when making decisions related to volume. First and foremost, no trader should ever feel compelled to trade just for the sake of maintaining a larger trade volume.

There will be times when market conditions are simply not favorable for doing so. There can be periods of several hours, or even an entire day when conditions are not favorable. As discouraging as this may be, it is important to remember that there will also be similar periods during which conditions remain favorable.

These better periods can produce considerable profits which will certainly make up for any downtime. Another important consideration needs to be total account funds. The primary focus when account funds are low should shift to trade quality rather than quantity. Even a small number of profitable binary options trades can help to restore lost funds , while a smaller number of poor trades could deplete an account which is already low on funds.

The best advice is to focus only on low-risk opportunities which offer a higher chance of finishing in the money when account funds are low. A larger number of trades can be taken once account funds have been restored to a respectable level. The provision of short-term expiry times makes it possible to execute a large number of trades each day. However, profit only comes on winning trades, so traders must take care to not get caught up in rapid trading under less than optimal market conditions.

The type of instrument which is being used can also make a difference. With some instruments, more detailed analysis will be required , and this can take time. The total amount of trade setups provided by a broker can also have an impact. Most platforms only include a set number of setups each day.

Having said that, the overall number should greatly exceed the number of trades that any individual could even hope to complete in a days time. There really is no need for concern in this area unless one is focusing on only specific underlying assets, which will present a limited amount of opportunities each day. With just a bit of time and experience, traders will naturally know which trades to take and which to avoid. Daily volume with indeed fluctuate up and down, as market conditions dictate.

While everyone wishes to earn as much money as possibly , and must be actively trading binary options in order to do so, patience is often the most important key to success when trading binary options.

One of the newest features of the binary options market allows for the ability to close trades before their expiration times. But recent trends have shown that brokers are becoming increasingly open to this feature and the increased account signups that have been seen indicate that traders are equally interested in the increased flexibility that is made available through these features.

But when exactly is the right time to close a trade prior to its contract expiry time? And what are the advantages of ending your trade early? In recent years, we have seen events such as the Credit Crisis which led to extreme volatility in the financial markets. These rapid changes in price can make the outcomes for trades less predictable and this can lead to trades that are profitable one day and unprofitable the next. There are many reasons why situations like this might occur.

Some of the most drastic events could come with events like a natural disaster, a surprise central bank decision to change interest rates, a disappointing corporate earnings report or an unexpectedly strong macroeconomic data release can all lead to unpredictable changes in asset prices.

To be sure, this can be a positive when the change falls in line with your trading direction. But it is nearly impossible to know when this favorable outcome will occur and when the news comes out on the opposing side, losses can be seen. This can be a highly frustrating and costly experience, as gains that were seen previously are suddenly wiped away.

Unlike spot markets like Forex there were no defensive moves that binary options traders could take to preserve their gains. Now, however, traders are able to close a profitable position using the early closure function whenever one of these unexpected events occurs. In other cases, trades will move in the wrong direction and create losses to a trading account. Here, the early closure function is also useful. When it becomes clear that a trade is unlikely to turn positive before expiry, traders can close a trade early and reduce the amount of losses that would be seen later.

These percentages will vary depending on which broker you use, and the market conditions seen when the option is bought back. It should be remembered that the early closure function is not something that should be used to arbitrarily close trades. When trading binary options using market makers, the broker is on the other side of your position.

If every trader used this function, losses would occur much less often and the market maker would eventually go out of business because of all the losses they would absorb. Because of this, there are some rules in place when using this feature:. The relatively new early closure feature at the popular IQ option platform allows trader to protect their profits and prevent against potential losses when unforeseen events shift the market. While there are some restrictions to trade binary options for this tool, the added level of trade structuring should be utilized in cases where a trade is unlikely to increase in profitability before the contract expires.

Given the dual nature of the binary options trading market, it makes sense to have a broader understanding of the general trends that are in place so that we can make the most informed trading binary options decisions and increase our chances of creating profitable trades. When looking at the dominant trends that are in places in the markets, it tends to be a good idea to trade along with the momentum: When most asset prices are rising, CALL options tend to be a better choice.

When most asset prices are falling, PUT options tend to be a better choice. To describe which dominant trend is in place, the trading binary options community will usually use term like Bull Market or Bear Market but it is much less common to see a discussion which characteristics actually make up these economic environments. Here, we will look at the differences between Bull and Bear Markets so that traders can more easily identify the dominant trend in a market and to place binary options trades accordingly.

Bull Markets are typically characterized by a financial environment that is composed of a large number of assets that are increasing in value, or are expected to increase in value. In many cases, the term refers to the stock markets but for those in the trading community, the term is applicable for all asset types.

Bull Markets are created by generally optimistic sentiment, rising consumer confidence and the wider expectation that companies will successfully generate profits. One clear indication of the existence of a Bull Market can be seen in the price of commodities, in the changes in valuation of a national currency, and in the overall performance of the major stock indices.

When looking at price activity in all of these various asset classes, it becomes clear that price swings show higher highs and higher lows the definition of an uptrend. When all of these factors are seen in combination with one another, a Bull Market is in place and CALL options will generally be viewed as favorable when entering into trades.

Psychology and news headlines in the financial media are also instrumental in these cases, as positive momentum tends to be contagious. On the flip side of this is the Bear Market, which is typically characterized by a financial environment what a majority of trading assets are decreasing in value, or are expected to decrease in value. Again, this term can be applied to all asset classes and Bear Markets are typically created by pessimistic sentiment, declining consumer confidence and the general expectation that companies will perform weakly in terms of profit generation.

Indications of a Bear Market can be seen all major asset classes commodities, currencies and stock indices when it becomes clear that price swings show lower highs and lower lows in a broad sense which is the definition of a downtrend. The combination of these occurrences create Bear Markets and in these cases, traders tend to prefer PUT options when entering into trades. Before we answer this crucial question, there is a need to understand that the binary option is a trading strategy, similar to various other trading strategies.

It is not an out-of-the-world scheme to help traders make millions or to scam them. Trading binary options is as safe or as unsafe as you make it. Yes, it is true that it entirely depends on whether you make binary trading safe for you. Crate was designed for low-latency and high-performance lazy queries, and we believe it to be the best file format choice for storing scene description consumed by USD. Some of its features include:. Access to files either by mmap or pread , trading VM pressure for file descriptor consumption and system call overhead.

By default crate uses mmap , but the choice is configurable at runtime. Editing crate files does not copy all data to a new file. Instead, it appends. Disused values consume disk space, so repeated editing may produce files larger than ideal. Use usdcat to rewrite files in their most compact form.

You can convert between file formats using usdcat. Def is one of the three possible specifiers a prim and also a primSpec can possess. A def defines a prim, which, for most consumers of USD, equates to the prim being present on the stage and available for processing.

Prims whose specifier resolves to class or over are actually present and composed on a stage, but will not be visited by UsdPrim::GetChildren or UsdStage::Traverse. A def may, but need not declare a schema type for the prim. USD addresses this problem by providing a completely separate field for each attribute, called its default. In text USD layers, the default value is the single value that can be assigned directly to an attribute in the attribute declaration line:. Two examples of where we find it useful to talk about direct vs.

indirect opinions are:. A direct reference is one authored on a prim itself, as opposed to an ancestral reference , authored on some ancestor of the prim. Ancestral references are weaker than direct references, so if the targets of both the direct and ancestral references contain opinions about the same property on the prim, the opinions of the direct reference will win. See specializes for examples. When authoring composed scene description, it is often desirable to edit the targets of various composition arcs in context of the scene you are constructing, rather than needing to edit individual layers in isolation.

Many IsA Schemas and applied API Schemas define attributes that have an identifiable value that makes sense in most situations. The USD schema generation process allows a schema creator to specify such values as a fallback that will be implicitly present on an attribute even when no values have been authored for it. The presence of fallback values allows us to keep our scene description sparse and compact, and allows for self-documenting behavior. A flattened stage is highly portable since its single layer is self-contained, and in some cases, it may be more efficient to compose and resolve, although this is definitely not a given.

For example, flattening a stage to an text USD layer will generally produce extremely large files since assets that were referenced multiple times on a stage will be uniquely baked out into their own namespaces, with all data duplicated; the crate file format will perform better in this metric, at least, since it performs data deduplication.

Regardless of file format, the action of flattening a stage will generally be memory and compute-intensive, and will not, at this time, benefit from multithreading. To flatten a stage, use UsdStage::Flatten or usdcat with the --flatten option. To flatten individual layer stacks , use UsdUtilsFlattenLayerStack or usdcat with the --flattenLayerStack option. Gprim is a first-class concept in USD, embodied in the class UsdGeomGprim.

All Gprims possess the following qualities:. Gprims are boundable , and should always submit to computing an extent even if it be an empty extent , and valid UsdGeom scene description should always provide an authored extent on a gprim that captures its changing shape if its shape is animated.

Transformable gprims necessitate fewer prims overall in most 3D compositions, which aids scalability, since prim-count is one of the primary scaling factors for USD. Do not nest gprims in namespace.

We consider it invalid to nest gprims under other gprims, and usdchecker will issue warnings on scenes that contain this construct. When an ancestor gprim is deactivated or made invisible, there is no possible way to make any descendant gprim active or visible.

Do not directly instance gprims. Because the root-prims of instance prototypes possess no properties, it is pointless to instance a gprim directly. Renderers must not infer instanceability from an instance of a gprim prototype, because each instance is allowed to override any property defined originally on the referenced prototype root prim. In USD a group is a kind of Model. Groups are models that aggregate other models into meaningful collections.

responding to authored or time-varying changes to the scene inputs. It has three major components: the scene delegates which provide scene data , the render index responsible for change tracking and other scene management , and the render delegates which consume the scene data to produce an image. This flexible architecture allows for easy integration within pipelines that have their own scene data, as well as their own renderers.

Pixar uses Hydra for asset preview in many of its tools, including usdview and the Presto Animation System. An index , also referred to as a PrimIndex , is the result of composition , and the primary piece of information we compute and cache for a composed prim on a stage.

what composition arc was traversed to discover it. All of the queries on USD classes except for stage-level metadata rely on prim indices to perform value resolution. USD also uses prim indices to compute primStacks for debugging, and to construct Edit Targets. Inherits is a composition arc that addresses the problem of adding a single, non-destructive edit override that can affect a whole class of distinct objects on a stage.

Consider the following example:. If you paste the example into a. This allows us to always create exceptions to the broadcast behavior of inherits, in the same layerStack in which we are broadcasting inherited overrides. This is not a requirement. A good way to understand inherits is to start by understanding references. Within a layerStack and ignoring any interaction with variantSets since VariantSets come between Inherits and References in LIVRPS inherits are indistinguishable in effect from local references.

In other words, when a prim inherits from another prim, it subscribes itself and all referencing contexts to changes made to the inherited prim. You can see this difference with the following example that uses the previous example as Trees. usd :. Viewing the flattened Forest. Were you to change the inherits to references in Trees.

usd would be to destructively edit the Trees. usd file. Deploy inherits where they are likely to be useful; for example, at asset root-prims. Instanceable is a metadatum that declares whether a given prim should be considered as a candidate for instancing, and is authored via UsdPrim::SetInstanceable. It does not matter whether instanceable is authored in a referenced layer on the prim being referenced or in the layer or a super-layer in which the reference is authored: only the composed value on the prim matters.

See Instancing for more information. When you add a reference , inherits , specializes , or payload to a prim, the targeted scene description will be composed onto the referencing stage, causing new prims to compose beneath the anchoring prim, and allowing the referencing stage to override any of the targeted prims or properties. See, for example, the Trees. usd snippet in the Inherits entry. Although the asset files are shared by a UsdStage each time we add a new reference to any given asset, we compose a unique copy of all of the prims that asset contains.

This is a requirement to be able to non-destructively edit the prims, and conversely for clients to see the unique overrides that may be applied to each copy of the asset. However, since number of prims on a stage is one of the primary factors that governs how USD scales, this cost can become prohibitive as environment size grows, regardless of how many improvements we make over time to the per-prim cost in USD. Often, however, an environment will need to express very few overrides on the assets it references, and the majority of the overrides it tends to need to override bind naturally on the root prim of the asset.

This observation provides us with a means to apply a philosophy to which we try to adhere broadly in USD: pay runtime cost only for the features you need to use. By making a reference instanceable , we declare to USD that we will not need to express any overrides on the prims beneath the reference anchor and any overrides already present in the referencing context will be ignored.

The stage will create a prototype for each unique instancing key, composing fully - just once - all of the prims that would otherwise appear redundantly under each of the instances, and note the relationship between each instance and its prototype. Default stage traversals terminate at instances because instances are not allowed to have prim children , and from any prim for which UsdPrim::IsInstance is true, a client can identify and process its prototype using UsdPrim::GetPrototype.

This behavior can be described as explicit instances, with implicit prototypes: clients are required to be explicit about what prims should be instanced, so that it is not possible to inadvertently defeat instancing by sublayering a new layer that unintentionally contains overrides beneath an instanced prim in namespace, and so that we can very efficiently determine where to apply instancing.

Extending the Trees. Like most features in USD, instanceability can be overridden in stronger layers, so if a Forest. For more information on usage and examples, see Scenegraph Instancing in the USD Manual. By default, when UsdAttribute::Get resolves a value from timeSamples , if the value-type supports linear interpolation, the returned value will be linearly interpolated between the timeSamples that bracket the requested sample time.

This behavior can be inhibited for all attributes on a stage by calling UsdStage::SetInterpolationType UsdInterpolationTypeHeld , which will force all timeSamples to resolve with held interpolation. Spatial Interpolation of Primvar values across a gprim. Interpolation is also the name we give to the metadatum that describes how the value s in a primvar will interpolate over a geometric primitive when that primitive is subdivided for rendering.

For more information, see Interpolation of Primitive Variables. The IsA schema to which a prim subscribes is determined by the authored value of its typeName metadata, from which it follows that a prim can subscribe to at most one IsA schema - unlike API schemas , to which a prim can subscribe many.

UsdGeomMesh , however, is a concrete IsA schema, since it has a Define method and prims can possess the typeName Mesh. IsA schemas can provide fallback values for the properties they define, which will be reflected at runtime in the prim definition. IsA schemas can be generated using the USD schema generation tools , but they can also be created manually.

Kind is a reserved, prim-level metadatum whose authored value is a simple string token, but whose interpretation is backed by an extensible hierarchical typing-system managed by the KindRegistry singleton. model - base class for all model kinds. group - models that simply group other models. assembly - an important group model, often a published asset or reference to a published asset. A Layer is the atomic persistent container of scene description for USD.

A layer contains zero or more PrimSpecs , that in turn describe Property and Metadata values. Each layer possesses an identifier that can be used to construct references to the layer from other layers. This is not only how USD supports direct consumption of Alembic.

Data authored to layers by applications or scripts will remain in memory until SdfLayer::Save is called on the layer. usd file extension. Calling layer. Save periodically: doing so will flush all of the heavy property-value data from memory into the file, while leaving the file open and available for continued writing of data. Composition arcs such as References and SubLayers can include an offset and scaling of time to be applied during attribute value resolution for all data composed from the target layer.

We call this a Layer Offset , embodied in SdfLayerOffset. Layer offsets compose, so that if A references B with a time-scale of 2. When an arc has both an offset and scale applied, the referenced animation is first scaled, then offset as it is brought into the referencing layer.

So, in the following example, a timeSample at timeCode 12 in the file someAnimation. Layer offsets cannot themselves vary over time. If a consuming context requires variable retiming of referenced data, it can use the more powerful and somewhat more costly Value Clips feature. LayerStacks are the keystone to understanding composition in USD.

The definition of a LayerStack is simply:. LayerStack: The ordered set of layers resulting from the recursive gathering of all SubLayers of a Layer , plus the layer itself as first and strongest. When a layer references or payloads or sub-layers another layer, it is targeting and therefore composing not just the data in the single layer, but all the data in strength-order in the LayerStack rooted at the targeted layer. Many of the composition arcs as well as relationships describe not just a single target, but an orderable list of targets , that will be processed in order according to the type of the arc.

References can be list edited among the layers of a LayerStack. This can be a powerful method of non-destructively changing the large-scale structure of a scene as it flows down the pipeline. For example, we might have a generic version of a special effect added into a scene at the sequence level:.

Now, at the shot-level, we have a shotFX. usd layer that participates in the same LayerStack as sequenceFX. usd because one of the shot layers SubLayers in the sequence. usd layer, which in turn SubLayers the above sequenceFX. usd layer. In this particular shot, we need to replace the generic turbulence effect with a different one, which may have completely different prims in it. usd, but not turbulence. In this second example we have also shown that the operand of list-editing operations can be a list that can contain multiple targets.

List editing is a feature to which some array-valued data elements in USD can subscribe, that allows the array-type element to be non-destructively, sparsely modified across composition arcs. It would be very expensive and difficult to reason about list editable elements that are also time-varying, so Attributes can never be list editable. When an element is list editable, instead of only being able to assign an explicit value to it, you can also, in any stronger layer:.

append another value or values to the back of the resolved list; if the values already appear in the resolved list, they will be reshuffled to the back. delete a value or values from the resolved list.

prepend another value or values on the front of the resolved list; if the values already appear in the resolved list, they will be shuffled to the front. A prepended composition arc in a weaker layer of a LayerStack will still be stronger than any arcs of the same type that are appended from stronger layers. This causes the resolved list to be reset to the provided value or values, ignoring all list ops from weaker layers. Also, in the usda text syntax, any operation can assign either a single value without the square-bracket list delimiters, or a sequence of values inside square brackets.

See LayerStack for an example of list editing, as applied to references. See also the FAQ on deleting items with list ops: When can you delete a reference or other deletable thing? LIVRPS is an acronym for Local, Inherits, VariantSets, References, Payload, Specializes , and is the fundamental rubric for understanding how opinions and namespace compose in USD.

LIVRPS describes the strength ordering in which the various composition arcs combine, within each LayerStack. Iterate through all the layers in the local LayerStack looking for opinions on the PrimSpec at path in each layer - recall that according to the definition of LayerStack, this is where the effect of direct opinions in all SubLayers of the root layer of the LayerStack will be consulted. If no opinion is found, then…. Resolve the Inherits affecting the prim at path , and iterate through the resulting targets.

Apply the resolved variant selections to all VariantSets that affect the PrimSpec at path in the LayerStack, and iterate through the selected Variants on each VariantSet. Resolve the References affecting the prim at path , and iterate through the resulting targets. Resolve the Payload arcs affecting the prim at path ; if path has been loaded on the stage, iterate through the resulting targets just as we would references from step 4.

It may sound like a great deal of work to need to perform for every value lookup, and it absolutely would be if we followed all the steps as described above, during value resolution. The algorithm for computing the namespace of the stage i. what prims are present and where are slightly more involved, but still follows the LIVRPS recipe. Wherever a Stage contains at least one Payload payloads can be list-edited and chained , the client has the ability to Load compose all the scene description targeted by the Payload, or to Unload the Payloads and all their scene description, recomposing all prims beneath the payloaded-prim, recursively unloading their payloads, should they possess any.

For more information, see Working Set Management in the USD Manual. USD allows the construction of highly referenced and layered scenes that assemble files from many different sources, which may resolve differently in different contexts for example, your asset resolver may apply external state to select between multiple versions of an asset. UsdUtilsCreateNewUsdzPackage does this for you, although we have not yet exposed the ability to just localize yet, but we hope to eventually.

Metadata are extensible, however adding a new, named piece of metadata requires a change to a configuration file to do so, because the software wants to know, definitively, what the datatype of the metadatum should be.

USD provides a special, dictionary-valued metadatum called customData that provides a place to put user metadata without needing to touch any configuration files. For more information on the allowed types for metadata and how to add new metadata to the system, please see the discussion of metadata in the API manual.

Model is a scenegraph annotation ascribable to prims by setting their kind metadata. See also Model Hierarchy. The model hierarchy defines a contiguous set of prims descending from a root prim on a stage, all of which are models.

Model hierarchy is an index of the scene that is, strictly, a prefix , of the entire scene. The member prims must adhere to the following three rules:.

Only group model prims can have other model children assembly is a kind of group. A prim can only be a model if its parent prim is also a group model - except for the root model prim. This implies that component models cannot have model children. Reasoning about referencing structure can get complicated very quickly and necessitate introducing fragile conventions. Namespace is simply the term USD uses to describe the set of prim paths that provide the identities for prims on a Stage , or PrimSpecs in a Layer.

Opinions are the atomic elements that participate in Value Resolution in USD. Each time you author a value for a Metadatum, Attribute, or Relationship, you are expressing an opinion for that object in a PrimSpec in a particular Layer. On a composed Stage, any object may be affected by multiple opinions from different layers; the ordering of these opinions is determined by the LIVRPS strength ordering. Over is one of the three possible specifiers a prim and also a PrimSpec can possess.

When an application exports sparse overrides into a layer that sits on top of an existing composition, it is common to see deep nesting of overs. A path is a location in namespace. In USD text syntax and documentation , paths are enclosed in angle-brackets, as found in the authored targets for references , payloads , inherits , specializes , and relationships. USD assigns paths to all elements of scene description other than metadata, and the concrete embodiment of a path, SdfPath , serves in the API as a compact, thread-safe, key by which to fetch and store scene description, both within a Layer, and composed on a Stage.

The SdfPath syntax allows for recording paths to different kinds of scene description. For example:. visibility names the property visibility on the prim Grandchild. Path translation is applied during such queries as finding a prim and fetching the targets of a relationship or connection , and inverse path translation is performed by the active Edit Target whenever you author to a stage. usd into a shot.

For UK investors, trading with binary options is a tax free form of investment with very quick results — minutes rather than months or years. During however, European regulators have prohibited the sale or promotion of binary and digital options to retail investors in the EEA. This includes the UK. Only professional clients or professional accounts are now permitted to trade binaries with regulated firms.

A professional trader must meet 2 of these 3 criteria:. Unregulated firms may not adhere to the new ESMA rules, and will continue to accept UK traders. This does increase risk for the trader, and makes finding a trustworthy broker even more important. It is however, possible to find brokers regulated outside of the EU that will accept EU traders, and are still regulated by respected bodies.

Most brokers are regulated, offering consumers the sort of protection they would expect while using financial instruments of this type. Returns from binary trading are also currently viewed as tax free by HMRC. Binary option meaning — Binary options are a derivative, traded on any asset or market. Even cryptocurrencies such as Bitcoin or Ethereum can be traded. The main difference between more traditional stockbroker trades, and binaries, is the clear identification of risk and reward before the trade is made.

An investor knows exactly how much is at risk, and crucially, also knows the exact value of any potential returns. No calculator, formula, or maths degree is needed to work out profit and loss on a binary option. The only decision for a trader is if the value of the underlying asset will rise or fall. The degree of the price change is not important. The trader is purely speculating on whether the price will be higher or lower than the current price, at a specific time in the future.

Short term price movement can be triggered by news stories or headlines, quarterly statistics, buyout rumours or even global security fears. Where trades can be closed, redeemed or sold mid-trade, payouts have absolute figures of 0 and and prices move between as the market dictates — until closure.

Every binary option is offered with an expiry time. This is the point at which the trade will end. Generally however, a binary option is used for short term trading — usually under 30 minutes 5 minutes are the most popular. Longer term expiries — and the element of fixed risk — does make them useful tools for hedging or diversifying other holdings. Payouts change dependant on the asset and the expiry time.

Differences can be significant so traders looking to use binary options long term, need to shop around to find the best payout for the asset class or classes they intend to trade. When watching video tutorials, ensure you know the source or creator of the video. Brokers may produce promo videos that appear to show profits being made easily. Although binary trading is in a period of growth, it remains a relatively unknown product. Over time, this is likely to change. As digital options as they are also known offer a very simple fiscal arrangement.

They are a legitimate way to play the financial markets. There is however, no leveraged exposure with a binary trade, so the risk and reward ratio is also simple to manage. Binary options suffer from a poor reputation. This is basically a result of dishonest and irresponsible marketing and cyber crime, more than an issue with the product itself.

With tighter regulation, and a better understanding by the wider public, these options can — and will — move into the financial mainstream. Which was where they originally developed. While FCA regulated agents and businesses may still have their flaws and faults, they are not fraudsters. Read our section on avoiding scam brokers below.

Many of the advantages of using binaries are related or linked. Here we list some of the benefits to using this form of investment — not just for the retail investor, but also to the market makers or brokers:. Managing risk when trading binary options is clear cut.

The amount of the trade is the full amount that is at risk. This clarifies the risk not only for the trader, but for the broker too. Their pricing model reflects the accurate knowledge of their liability. The certainty of risk provides a solid foundation for brokers to work within and manage. This leads to low trading feed, tighter spreads and higher payouts. To protect themselves further, they may use a liquidity provider or hedge their own positions.

The expensive broker costs of clearing houses becomes unnecessary. Leverage, or gearing, is not generally available with binary trading. This benefits the broker again, as it means all trades must be funded in full. In other words, no trader can default on a trade. With leverage, if things go wrong, there is a real risk of the broker not being paid.

This is a big difference vs spot forex or spread betting. Layers of complexity can be added to the standard fixed payout option. A binary trade offers the greatest level of flexibility. They even provide a mechanism to speculate on a market remaining flat, arbitrage, or to take a view on the trade volume of the underlying asset.

Again, these robots attract many of the undesirable operators, and the automatic nature of the trades increasing risk further. New traders should be especially careful. An alternative approach is for traders to build their own robots using their own entry points. A growing number of brokers now offer traders the ability to put their own trading robot or program together, using simple tools. Binary trading itself is legitimate, and not a scam.

There are however, brokers and signal providers that are untrustworthy and operate scams or frauds. It is important not to write off the concept of binary trading, purely based on dishonest brokers. These fraudsters continue to drag down the image of this form of trading. Regulators, and rule makers are slowly starting to get to grips with these operations and the industry is being cleaned up. If you want to complain about an operator to our watchdog, please let us know via our Contact Us page.

Being aware of the above methods should help those new to binary trading to avoid the less responsible brands. Improved regulation and more awareness should hopefully reduce these types of complaints. This in turn can allow binaries to move forward. Already fallen victim? The services of MyChargeBack. com might be of help. The recent ban of binaries in the EU is ill-thought out, and could well end up pushing more traders towards scams.

Our strategy pages covers over 20 known systems, drawn from a range of forum and club chats, plus expert tips and advice. From high risk Martingale, to intricate systems like the Rainbow.

We also cover more specialist subjects, like forex , technical analysis , the best price action indicators, trading signals and winning strategy. All this is aimed to help you gain an edge, and win. Signals are an alert, sent to traders. They are designed as a trading tool, helping traders to spot opportunities.

They can be communicated via a range of methods — email, SMS or from a live signal website or group. Much of the irresponsible marketing associated with binary scams is linked to signals — or auto trading robots utilising them. There are some very good providers out there too. However, in general, learning how to trade binaries is a safer route than using signals to compensate for a lack of trading knowledge.

Sometimes, but rarely in isolation. Some providers deliver a combination of education alongside signals and that represents a good mix. Traders must be able to fully assess a signal before they can judge the quality of them. We also highlight some of the best providers on the signals page. A binary option can be used in a number of ways, and across a huge array of commodities and markets.

This means finding the best dealer, best account, or best trading platform, really depends on the needs of the individual investor. For example, some brokers may focus on forex foreign exchange and trading the Japanese Yen, Euro or sterling. Others may be strong on commodities and only offer a handful of FX markets. White label platform providers such as SpotOption, Tradologic or TechFinancials also dictate what products the host site can offer, so a proprietary broker with a bespoke design might be preferable.

Payment methods merit some thought — if traders want to use Skrill, Paypal, Neteller or Wire transfer, they need to check the broker delivers that. Mobile trading apps delivered by brokers or binary agents can vary in quality too.

Some specifically program for the features of specific models, like iPad or iPhone. Others ensure cross platform compatibility, catering for android, blackberry and windows tablets and devices. Some traders may have tailored demands for any hand held app, others less so. Trade size limits may point some investors either to, or away from, certain trading accounts.

Collections build on the ability of relationships to identify objects in a USD scene. Would you say things are [rotate 1 and 2] [1] better , [2] worse , or about the same than they were a year ago? Fewer than half of likely voters say the outcome of each of these state propositions is very important to them. How to present a product for a sell-through. Proxy is a highly overloaded term in computer graphics… but so were all the alternatives we considered for the same concept in USD.

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