Artificial Intelligence or AI is expected to be in major demand by retail consumers due to its ability to make interactions in retail as flawless and seamless as possible. Many of us do realize the potential of AI and all that it is capable of, along with the support of Machine Learning or ML, but don’t realize that the implementation of AI in certain segments has already begun.
AI in Retail
The future for AI and the complicated computer processes involved behind it is really bright in the field of retail. AI currently has numerous data sets working along with computer visualization methods to ensure that the users get the most seamless experience when it comes to AI in the workplace. There are some interesting facts that pertain to the use of AI in retail. Here we have some of them to build the insight into what you can expect during the feature;
With such promising figures on the card, one cannot help but notice the wave of change that has already started in the field of retail. With work already in progress, major retailers such as Amazon and Walmart have made advances that are expected to dictate this transition to AI in retail. We will be looking at these advancements, and will see how they can work out in the future.
Walmart’s Shelf Scanning Robots
You might have heard of shelf-scanning robots being tested by retailers, but we’re just about to witness one of the most interesting advances in the deployment of these robots. Walmart, which is one of the biggest physical retail chains across the world, is planning to extend the tests for its shelf-scanning robots across 50 additional stores, including some from its native land of Arkansas.
The machines, which have been deemed to be the future of shelf scanning, will roam around the aisles to check all factors including pricing, misplaced items, and stock levels, to assess the level of stocks within the store. This would not only save human staff all the hassle of checking these trivial details by themselves, but would also mean that they can focus on other more important details. The machines will require technicians to be present on site to handle the situation in case of a technological impairment, but the robots are currently fully autonomous to handle their tasks themselves. These robots will be using the concepts of 3D imaging to roam around aisles, dodge obstacles, and to make notes about the blockages in their pathway.
Amazon Go
Amazon Go is the latest wave of technology in retail that is expected to lead the way to the future of AI in retail. The basic concept behind Amazon Go is that it is a new kind of store that flourishes on the concept of no checkout requirements. Consumers who walk into a store can take whatever they want without having to go through the hassle of lines and waiting for checkout.
The checkout free shopping experience in Amazon Go is only made possible through the use of the same technology that is currently in place behind computer vision, sensor fusion, and self-driving cars. The technology automatically detects all that is being taken and keeps track of them in a virtual cart. Shortly after the consumer leaves, they will be sent a receipt and charged through their Amazon account.
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After the second Bitcoin fork creating a new cryptocurrency, Bitcoin Gold (BTG), it became the victim of aDistributed Denial of Service (DDoS) attack. The DDoS attack of Bitcoin Gold caused it to go offline at a very critical moment in the new cryptocurrencies infancy.
Since that first attack,Bitcoin Gold has been the subject of further cyber attacks. This has had an impact on the digital currency’s value. It has caused less confidence in user investment after previous BTG holders lost millions of dollars.
Some think those who believe the hard fork was disruptive to the crypto-community masterminded the cyber attacks. No one will really ever know, but Bitcoin Gold was hit hard, and repetitively.
The focus should now be shifted to how cryptocurrency attacks can be prevented in the future, or at the least, not become a regular occurrence.
About Bitcoin Gold
Bitcoin Gold was created after the second Bitcoin hard fork. Like Bitcoin Cash, Bitcoin Gold was touted as the new and improved Bitcoin. The hard fork allowed Bitcoin holders to get a one-for-one coin of Bitcoin Gold. This allowed Bitcoin holders to furtherdiversify cryptocurrency portfolios.
The big difference between Bitcoin Gold and its counterparts is that it has mining allowances the others don’t. For instance, companies have monopolized Bitcoin mining, usingapplication-specific integrated circuits (ASICs). This goes against the decentralized nature of cryptocurrency.
Bitcoin Gold aims to decentralize mining once again with an algorithm ASICs can’t penetrate. It is a return to the early Bitcoin days when mining could net cryptocurrency holders extra money.
Unfortunately, the decentralization mission Bitcoin Gold was created for became the subject of much scrutiny. People in the crypto-community were unraveled over the Bitcoin Gold creators’ private mining period that reduced the digital currency’s volume. Thus the speculation that the opposition to Bitcoin Gold facilitated the cyber attacks.
Relentless Cyber Attacks on Bitcoin Gold
There was no shortage of cyber attacks after the Bitcoin hard fork that created Bitcoin Gold. Bitcoin Gold was created in October of 2017 and immediately suffered a DDoS cyber attack. The attack overloaded the server that caused the network to go offline.
Then in November, nearly a month later, Bitcoin Gold’s wallet,mybtgwallet, was found fraudulent. As soon as the scam was identified the wallet was removed, but an estimated $3.3 million was lost.
Yet again, a week after the fraudulent wallet scam, Bitcoin Gold needed to issue a warning that detailedsuspicious files in the network’s Windows wallet installer. Due to a potential for more user money to be lost, those who had downloaded the files were instructed to delete them immediately and remove cryptocurrency access from users’ computers.
Bitcoin Gold is not the only victim of cyber attacks and malicious attempts to steal funds. From Initial Coin Offering ICO scams to hacked exchanges, cryptocurrency has definite pitfalls in the security sector.
Is Poor Security to Blame?
The cyber attacks have led to some serious security concerns for Bitcoin Gold and the entire crypto-community. The poor security of Bitcoin Gold made many question the digital currency’s ability to rise as a cryptocurrency contender.
Even popular exchanges like Coinbase decided to steer clear of the latest Bitcoin offering. The largest exchange in the crypto-community announced that theywouldn’t support Bitcoin Gold on their platform due to developers not making the network’s code available publicly, stating, “This is a major security risk.”
The Bitcoin Gold cyber attacks are no rarity. Various cryptocurrencies and cryptocurrency exchanges have fallen prey to hacks resulting in millions of dollars lost. For instance,CoinDash lost an estimated $7 million after web applications were found vulnerable.
ICOs are a new way to net funding via cryptocurrency. However, these have been vulnerable to scams. Just recentlyscammers posing as Seele ICO admins stole over $1.8 million. This has caused even more security ripples over the cryptocurrency network.
Improving Cryptocurrency Security
The Bitcoin Gold cyber attacks and the scams and hacks of other cryptocurrency platforms is definitely a call to action for improving cryptocurrency security. A few security-minded measures include:
Learning from Crypto-Mistakes . . .
There was a lot to learn from the Bitcoin hard fork to Bitcoin Gold. It highlighted how easy cyber attacks can happen repetitively to the largest cryptocurrency on the digital marketplace. The cyber attacks also put a bright shining light on the lack of security. By improving cryptocurrency security, the crypto-community will secure a digital market for the future. Are you concerned with current cryptocurrency security?
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The AI technology has been picking up steam in the past couple of years. It’s no longer a gimmick or a faraway fiction. Scientists from all around the world are slowly but surely cracking this riddle. Sure, they are still a long journey away from creating a true Artificial Intelligence, but each year we see significant breakthroughs in this field.
Today, you can find some form of AI in many everyday places. For example, Alexa and Siri are world famous AI assistants. They will create appointments, answer your questions, set alarms, shop, and a million other things. Another great example is the Tesla car. Thanks to Tesla’s AI, self-driving cars are no longer a work of fiction.
But what about the poker industry? Surely there must be an AI capable of playing poker at high levels. The answer is yes, there is. This infographic will show you how the poker’s AI developed throughout the history, as well as where it is now.
This infographic originally appeared in pokersites.me.uk. Published with permission.
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I recently interviewed Nitin Chugh, Country Head – Digital Banking at HDFC Bank Limited, and we discussed some hot topics in banking industry today: digital transformation, personalization, AI & machine learning, blockchain etc. HDFC Bank is an acknowledged Innovation leader in the BFSI space. Nitin heads the Digital Innovation Unit which works on new ideas, technologies and solutions, to build and deliver a comprehensive suite of digital solutions and products. He is an engineer and an MBA by qualification with nearly 23 years of experience in retail banking and office automation industry.
Read the complete interview below:
For decades, banks have only competed with one another, on the same terms. As an industry not very used to change, the banking sector is currently undergoing a radical transformation — in terms of digitization, personalization, going mobile etc. “Go digital and be digital”. This is the slogan that drives most banks today. What are the key promising areas where digital advances could revolutionize the banking industry?
First of all, we need to clear a bit of the air around banking industry not having changed in the time. Most of the time, it is perceived to be true probably because you will always have some participants in an industry who will be slower to change or will not change. But at the same time, if you look at banks in the private sector, I think everybody has been changing at the same pace as the technology has been changing. Because most of the new generation banks, like HDFC Bank, are heavy tech users and tech-enabled. But I think we (banks in private sector, like HDFC Bank) have been keeping pace with the technology.
The second aspect is that digital banking has made rapid progress. For example, in our case, we started our sole work about 4-5 years ago with ‘Bank Aaapki Muththi Mein’ campaign. And that is when we actually came up with this slogan – “Go digital and be digital” – that we use even today. Only recently that we stopped using it that extensively. Before, it was intended to encourage customers to start using digital. That is obviously entailed to a lot of other things — how to enable your customer-facing properties, how to enable the backend and processes and how to enable your employees and bring about changes on a systematic basis.
Today, we have come to a point where the same users are driving the next ‘going digital’. To put it simplistically, the first way would be ‘physical driving digital’, and now the second phase is ‘digital driving the next going digital’. With this, we have so many users to be taken to the next level, where there are the 3-4 big things happening. Clearly, we are moving from being an impersonal interface to a very high level of personalization and hyper-personalization and from convenience to experience.
We notice that today’s customers are expecting more contextual stuff; they are expecting more personalized communication, personalized offers, more personalized treatment. Everybody wants to have their own identity around what to do. So, the whole concept of segmentation or personas (whatever you would like to call it) has become a reality now. That is obviously driven by the second big thing which is a whole lot of ability to do cognitive computing, because information is available. There is more data available, and more and more data is being made available on a daily basis. It is so-called new oil and it has to be refined. Like crude oil. For that to happen, those skills are to be brought, which is the third thing. Ok? If you wish to run an enterprise which delivers hyper-personalization – a very high degree of customer experience based on cognitive computing and a whole lot of other big data related concepts, then you need the technology you need, the skills and also need to run at least some processes and some functions in a very different manner.
I think that’s really how logically it should also happen, because you need to go through phases. If somebody wanted to jump into something like this three years ago, people would have struggled with making sense of data itself, maybe not even have more than a few use cases to apply that. I think if I must talk about the big three, obviously there are many more, but these seem like more thematic right now and quite clearly pointing towards a very specified direction.
Your answer almost covered all the questions I was about to ask… Anyways, let me ask rest of the questions. For a traditional bank, digitization is like redesigning an aircraft while flying. It requires us to have a high degree of determination and belief in the digital future. How do you make sure the whole organization is involved and aligned in spirit? What are the key challenges you face at this point of digital transformation at your bank?
Let me start with a disclaimer that you are asking about a traditional bank, but we (HDFC Bank) are a just 23-24-year-old bank. I think in the context of banking, if it is 200 or 250-year old industry – formally 200-250-year-old industry, I think we (HDFC Bank) are still the newbies to the whole industry. We have to look at this in a time frame. If you are looking at the last 5 years, everyone was using the same technology, the same way of enterprising with the customers as much as we are using today. So, the whole thing of a new generation or a traditional bank actually, probably again applies to banks which are really old and have been here for 200 to 250 years. That is the first thing.
The next point is we have been a tech-enabled bank and have been inviting systematic, very forward-looking tech investments much ahead of time, like our analytics practices for example; it is 15 years old. We started working on concepts like our own statistical analytics model for marketing and risk management way back in 2002 and 2003. So, our factors have evolved. They have evolved to be something among the best in the world. Now it is easier for us to create those layers on top of it. Now you have data available, better quality of big data is available, better tech is available to make sense of data, better interfaces in the form of mobile apps, responsive mobile pages, multiple other things: conversational techniques, chatbots etc.
There is a good way of using the domain expertise that you acquired over a period of 15 years, build new skills on top of it and it to a level of personalization, which is real-time, big data led and all contextual. So, for us, if you are asking me, we are only adjusting the altitude. We were flying and it was a continuous journey of scaling altitude. For us, we don’t have to really re-engineer the aircraft while we are flying. It is not applicable in the example of an aircraft, but a similar analogy would be that we are shifting our altitude. And that is helping us deliver in a much better manner. It is helping us deliver better experiences to our customers.
So, I think that is where these kinds of things are looking more visible in the market, but there are people who suddenly get up and say, “now I want to beat the rest”. But it does not happen that way. I think we (HDFC Bank) are fortunate because we were forward-looking from the beginning; we had a clear view on things to deliver customer value, with best of our ability and making using all contemporary technology. Since we have done that, it is very visible for us to change gears and therefore shift altitude. I don’t know whether we are an exception there, but I do believe that it hasn’t been challenging for us.
I’ll give you another example. Like service-oriented architecture which is now moving into concepts of middleware and opensource, API led and banking and all of that. Now if someone wants to get into API open source banking today, he must first fix the middleware, must first get into making sure that they have a service-oriented architecture and then figure out whether their core systems are even conceived to deliver those services and those services can be reused with APIs. So, for him, it is always a depression of what do I do with the legacy system. But in our case, we made our whole investments 8 years ago. We made a middleware investment many years ago.
So, for us, it’s reconfiguration and recalibration only. It is not about bringing in something which we never had and then figuring out what do we do now. So, our challenges are of different kinds. We are not being hooked back because of tech. Our challenges are that we want to scale and we want to go at a certain pace. We want to be the head of the market. How do we do that better? Whom do we benchmark against? Who is best globally? Those kinds of things.
Cool. What are the key digital initiatives HDFC Bank is looking for to scale in the next 2-3 years?
It is not about initiatives, because I have around 250-300 initiatives right now. But they are all part of the master plan.
What is the master plan?
The master plan is obviously not something we can talk about now. But it is almost like I said in the first question itself. In the first phase, we encouraged customers to ‘go physical’ to ‘go digital’; now the second phase is going to take us from digital to hyper-personalization.
The whole concept of personalization, contextual and relevant engagement with the customer is backed by cognitive computing capabilities and big data, delivered through a mix of skills which are acquired, reskilling and capabilities either process wise or functionally or structure wise. This is what will shape the master plan and the master plan therefore will have many initiatives – small and big ones. There will obviously be some which are experimental in nature, which we will keep testing out. We are now saying that we want to move away from proof of concept now. We want to move to a proof of value. Can you demonstrate the value? If the value can be demonstrated, then we will have the necessary tech capability to do a very good deployment.
If you compare banks to companies like Google, PayPal, and Amazon, it’s evident that banks are still at the nascent stage of the digital and data revolution. And they are stealing away a decent chunk of revenue from banks. What’s your take on this? How do you think banks should respond?
There are 3-4 ways to look at the same thing. The first one is it is not happening for the first time. These things happened in every industry, every now and then. You can take any industry for that matter. If the industry will go through phases, other people will go to that industry and will probably start doing some bit of other work that you are trying to do with your customers and they might grab some share. That is number one. The second point is when you are talking about these tech companies, they manufacture tech. We are the ones who consume tech. When we consume tech, we obviously partner with these people; we also partner with other people who partner with them.
The third aspect is India is a market that’s expanding. So, we are anyway going organically otherwise fairly at a health rate much more than any other country in the world. If somebody comes in and even if they chip away a little bit of business, that itself is not that tactical because you are in a partnership ecosystem. So, everybody is partnering with each other. Because the whole headroom is so much available to everybody, I don’t think it’s ever going to be a problem for anyone. The market will only get expanded and be better covered. To the specific point whether we feel we are threatened or any of that, we are obviously looking at these new things we are working on and we are very, totally engaged with all of them. We are in a very close partnership with all of them. And we are working together on a lot of things.
So, if you take the example of Google Play, it was launched with four banks. Google did not go and apply for banking license or said that I want to be a payment bank myself. They are also partnering with banks. So, the whole ecosystem is now about partnerships. It’s lesser being I want to get into this, let me start doing this and hunt away somebody’s business. That chipping away anyway happens in any case. Like you are in a business which I am sure competing with 50 other fellows and you are chipping away at each of other at all points in time. Or you feed in a niche market for yourself; all of you going together in a market because there is so much headroom available.
My next question is about blockchain technology. It is currently the hottest innovation in banking. The technology, which underpins cryptocurrencies such as bitcoin, was initially treated with skepticism by banks. However, this is changing dramatically. What’s your take on this?
I would like to start by admitting that I am not an expert of the blockchain. Rather I am a student who’s still learning and absorbing this new technology. I believe in 2018 we should see far, higher traction and momentum on the deployment of the blockchain. In the last two years, people were just about tested, done POCs and experiments and try to form a view as to what you can do. But I really think, as in when we see more domain experts emerging, it will become something universally available as a knowledge bank. Amongst all the conferences that happen today, people have started adding conferences on Artificial Intelligence, but you don’t see too many blockchain specific conferences even today. It’s very difficult to find somebody who has content on the blockchain. Obviously, there is limited knowledge and experience. So, all of us are learning. But I think the way it looks; my own personal view is that it is promising.
There is a good, strong reason for it to be used for internal workflows like an internal blockchain and more importantly it is going to be logically apt for network level technologies where multiple participants would be able to do many such things. Again, in a concept level, since I said I am not an expert in blockchain and you don’t have to ask me how it actually works as I have a very limited understanding of tech. So, we do believe that 2018 should be some kind of a per daylighting sort of a year for blockchain where you will see a lot more deployment happening.
Recently I read a news saying that Amazon launched its first Amazon Go store in the US which a customer walks in, picks whatever he needs and walks out. Everything happens automatically with the help of AI. So, things are going handsfree. What are the key trends happening in this banking space? Where are we heading?
From what I understand, the module is based on deep learning, which is obviously the next phase of evolved advanced machine learning itself, which is any way powering most of the cognitive computing. We are at the first level which is the artificial intelligence. It is difficult to bring in deep learning immediately right now. It is the same way as what you would do with big data 3-4 years ago. Almost the same journey. When things like these happen, they are obviously changing the customer experience a lot, they are creating an expectation in the market. So, we must prepare. Maybe the choice people are going to be left with is that you don’t have 4 years to move from 8 to 12th standard. Do it in 3 years or 2 years. That might be the only thing that you must do, but still you must move up. And there are many such things. This is much showcased and published experiment that Amazon did, but there are several such things, know? The autonomous vehicle is exactly that. Health care is going through the same thing. Retail is going through the same thing.
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Amazon Web Services (AWS) is currently the most widely used enterprise cloud data storage system, successfully competing against similar services from the likes of Microsoft and Google.
In this article, we look at what AWS offers and outlines how enterprises can cost-effectively match their enterprise data and applications to the right AWS service.
Not so long ago, the only option enterprises had for data storage was to purchase, set-up and manage ever increasing private storage server farms, but there were clear drawbacks to this scenario. First of all, the physical hardware cost too much money, and secondly, it hit company profits with high expenses generated in staff, man-hours, maintenance costs and power.
Cloud storage though is typically not only cheaper, but more reliable, scalable and secure than traditional on-premises storage systems. And instead of companies having to keep up with constant upgrades and the introduction of the next series of important or unimportant storage widgets, they can off-load that responsibility to their cloud storage provider. Analyst house IDC has set out how moving on-premise data to an on-demand cloud service provider can work out much cheaper (see this report by IDC).
The Benefits of Cloud Data Storage
What’s Available from AWS
Amazon Elastic Block Storage (AWS EBS) is designed for persistent local storage via the Amazon EC2 cloud service. It is ideal for relational and NoSQL databases, data warehousing, enterprise applications, big data processing and backup and recovery. See this article by NetApp for a very good illustration as to how users can cost effectively manage their AWS EBS data volumes.
A different service is Amazon Elastic File System (Amazon EFS), which is a file system interface to make data available to one or more EC2 instances. It also supports content serving, enterprise applications, media processing workflows, big data storage and backup and recovery.
There is also Amazon Simple Storage Service (Amazon S3), a scalable platform to make data accessible from any internet location, for user-generated content, active archiving, big data storage and again backup and recovery. In addition, Amazon Glacier is a long-term storage solution that can replace tape for archiving and regulatory compliance.
Making a Choice
So with this in mind, what AWS service is good for me? Well, it depends on which data processes you want supporting, and for a number of organizations, particularly large enterprises, it may be a combination of the lot.
Amazon Elastic File System provides scalable file storage for use with multiple Amazon EC2 instances in the AWS Cloud. Amazon EFS offers a simple interface that allows you to create and configure file systems quickly and easily.
With Amazon EFS, storage capacity is elastic, growing and shrinking automatically as you add and remove files, so your applications have the storage they need, when they need it.
When mounted on Amazon EC2 instances, an Amazon EFS file system provides a standard file system interface and file system access semantics, allowing you to easily integrate Amazon EFS with your existing applications and tools.
Multiple Amazon EC2 instances can be used with an Amazon EFS file system, allowing Amazon EFS to provide a common data source for processing different workloads and applications at the same time.
Amazon EBS
Alternatively, Amazon Elastic Block Storage provides persistent block storage volumes for use with single Amazon EC2 instances in the AWS Cloud. Each EBS volume is automatically replicated within its Availability Zone to protect users from component failure, while offering high availability and durability.
EBS volumes offer the consistent and low-latency performance needed to run your workloads. With AWS EBS, you can scale your usage up or down within minutes – all while paying a low price for only what you provision.
Amazon EBS is designed for application workloads that benefit from fine tuning for performance, cost and capacity.
Typical use cases for AWS EBS include big data analytics engines like Hadoop and Amazon EMR clusters; relational and NoSQL databases such as Microsoft SQL Server, MySQL, Cassandra or MongoDB; stream and log processing applications like Kafka and Splunk; and data warehousing applications such as Vertica and Teradata.
Amazon S3
Another major AWS cloud service is Amazon S3, an object storage service that makes data available through an internet API that can be accessed anywhere.
Enterprises need the ability to simply and securely collect, store, and analyse their data at a massive scale. Amazon S3 is built to store and retrieve any amount of data from anywhere – websites and mobile apps, corporate applications, and data from IoT sensors or devices.
S3 provides comprehensive security and compliance capabilities that meet the most stringent regulatory requirements. It gives customers flexibility in the way they manage data to meet cost and access control considerations.
S3 also provides query-in-place functionality, allowing you to run powerful analytics directly on your data at rest in S3. AWS claims its Amazon S3 is the most supported storage platform available, with the largest ecosystem of ISV solutions and systems integrator partners.
Conclusion
It is clear that users have a good selection of AWS solutions to choose from to benefit from cloud efficiencies in managing their enterprise data. But, as IDC states: “Organizations must actively evaluate and consider the breadth of features and the services available in a service provider’s cloud ecosystem when evaluating and adopting a public cloud service provider. This will allow organizations to maximize the benefits of using public cloud for their infrastructure needs.”
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The role of Artificial Intelligence (AI) devices in augmenting humans and in achieving tasks that were previously considered unachievable is just amazing. With the world progressing towards an age of unlimited innovations and unhindered progress, we can expect that AI will have a greater role in actually serving us for the better.
Since I have been associated with this wave of change towards AI-driven technologies and modules, I have literally been amazed at the ground we have covered during the last couple of years or so. As the technology behind AI gets revamped and updated on a regular basis, we can expect the wave of change to serve us in an even better way in the future.
A few cases of AI at work currently really do make us excited about the future of this technology. Some of the examples of this technology include:
The Future
What we see in AI mechanisms and technology today is that they respond to what we say and do. However, it wouldn’t be unjustified to expect more innovations in this regard during the future. The future could see us witnessing smart devices that actually serve us, rather than responding to what we tell them to do.
Applications in the future could serve us by following open mobile and AI ecosystems. By serving us independently and by knowing us better, these devices would definitely be more intuitive and will provide a more convenient service.
Companies Driving the Future of AI
While we have been discussing possibilities in the future of AI, there are companies across the globe working tirelessly to achieve it. One such example can be of Baidu and Huawei. Both these organizations recently entered into an agreement that could lead the way into the future of Artificial Intelligence. The two companies aim to incorporate their offerings in a way that could benefit services ranging from AI Platforms, to Internet services and content. Both the organizations currently aim to build an open ecosystem through Baidu’s Brain and Huawei’s HiAI platform. The open ecosystem will eventually empower AI developers to explore bolder options by incorporating the services of both the companies. This will eventually open the door towards better AI offerings for consumers looking for a better smart experience.
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