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or a server with a with professional-grade or cards. are also available. Rent GPU servers with instant deployment custom configuration NVIDIA Tesla H100 / H100 80Gb RTX A5000 / A4000 GPU servers with game RTX4090 cards Sporting events today are rife with advertising, from commercials on screens to static company logos on stadium billboards. The airwaves span multiple countries with different brands and advertising laws. Thanks to breakthroughs in AI and AR technology, it is possible to customize the information on display for each audience directly during the live broadcast of a match. Advertising in sports arenas was initially static and intended for the people attending a particular event in a particular city. Later, LED screens appeared, which showed alternating adverts. The next evolution was to insert a green screen into the spots on the billboards for a fraction of a second, allowing the AI to define the space and insert a unique text. Nowadays, you can replace anything with anything. The challenge is to make sure that the replacement is done discreetly and realistically. The major players in this market use special cameras. From the photos, we can conclude that there are specialized sensors that discern positioning and alignment information. That is, popular solutions still have hardwired crutches. All this requires enormous computing power, as the inputs and the original broadcast are processed by specialized software online. That is, servers for computing are connected to the cameras and sensors. This equipment is expensive, the market is closed, and the technology is closed, too. This is where AI and cloud GPU servers come to the rescue. Expensive, static, and not for everyone HOSTKEY has a client, a startup called , which has developed its own technology for implementing virtual advertising and integrating digital content (like augmented reality) in a multi-regional mode. And their solution promises seamless (and boneless) integration of adverts directly into the video stream. PTF Lab Some time ago, they saw information about HOSTKEY in the Open Data Science (ODS) community and reached out to us when they needed cloud capacity, appreciating our service, pricing, and a flexible lineup of available options. The startup's goals are noble, understandable, and quite achievable: To get away from expensive proprietary equipment and complex setup, shifting the task of advertising placement and frame construction to artificial intelligence, which takes into account overlapping people and objects in the frame. By doing so, they can cover relatively small events (such as arena fights, etc.) and bring the technology to the masses. Ultimately, sports advertising should be made accessible and relatively inexpensive. Moreover, the startup has set an ambitious goal of surpassing the solutions offered by monopoly giants in terms of flexibility. For example, it can display "virtual adverts" during replays and use angles from any camera, not just from certain angles. How does it work? The video signal from a sporting event venue can be processed using computing power not only at the venue itself but also in the cloud. This allows for flexible load distribution and the choice of when to apply adverts: before or during broadcasting, taking into account different markets. Also, working with cloud services allows you to use advertising in locations where it is impossible to bring a server (and in principle, it is more convenient). Object segmentation is based on the neural network architecture from U-Net. Neural networks are responsible for the location of objects and for detecting and comparing key points. However, the task is non-trivial, so all the solutions and neural networks had to be reworked and trained for use. It is especially difficult in martial arts broadcasts, where literally everything is unpredictable from the point of view of the picture: light sources, shadows, camera angles, the grid overlapping sponsor logos, and the bodies of the fighters and referees. Neural networks are not used everywhere. Sometimes, to solve a problem, it is enough to show ingenuity and use simple algorithms. For example, tracking algorithms combine neural network methods and systems of linear and nonlinear equations. A significant part of the GPU is taken up by segmentation. The better the detection of people and objects in the frame and their separation by plans and type is implemented, the more natural and attractive the frame will look after the advertising overlay. A separate task is related to lighting and shadows, which must be taken into account in augmented reality when rendering a scene. The realism of shadows is a key element in assessing the "believability" of the picture. Traditionally, sports neural networks are trained on real broadcasts using human markings and synthetic models. Here, Blender comes to the rescue. The company builds 3D models of the ring, fighters, and referees and gets both rendered real footage from the right angles and the segmentation mask, or the position of objects and cameras needed for training. Markup of real data is time-consuming and expensive but of high quality for specific venues or types of competitions. Synthetic data with less realism provides more data for training. The main difficulty is that the venues can vary. In one case, it will be a boxing ring with ropes, and in another case, it will be an arena with mesh walls, each of which creates difficulties for segmentation. Camera tracking and advert position are determined by comparing the point cloud from the venue's 3D model with its actual position in the frame. This allows them to determine the position, even for manual cameras with chaotic movement. After reconstruction of the 3D frame from 2D (the determination of the required angle), the direct rendering of the advertisement in the 3D engine is performed and combined with the video broadcast frame. A 3D scene has to be built before we start work, and, in fact, we have a virtual copy of the venue in the frame, into which we fit real people and objects through render masks. It sounds complicated, but with the right power and optimized neural networks, it is possible to perform these somersaults instantly and seamlessly. Why does the project need GPU computing and server rentals? PTF Lab has its own servers (and the possibility of using them on-site at the competition venue was mentioned earlier), but it is more convenient to use remote resources, as the service provider's engineers are responsible for equipment availability, and the company allocates fewer resources to this. And the client votes with his wallet and cost-effective options are always preferable. Also, the capacity required by the company is constantly growing. If necessary, it can be easily scaled up just by renting more (up to and including changing the server configuration to suit the company's needs). In the future, a startup may need a lot of cloud capacity. It is easier to rent them than to buy and sell the physical servers when the demand for their services rises and falls. The leased servers and GPU capacity are now being used in the following areas: Training of neural networks on GPUs (segmentation of people and other objects in sports broadcasts; 3D virtual camera tracking). Data backup (video from events, datasets, etc.). The direct process of working with video-testing cloud production, when the company's software is deployed on remote servers and video signals flow through it: input - without graphics, output - one or more signals with graphics. In addition to our own computing power at HOSTKEY, the startup is currently leveraging the following GPU configurations: AMD Ryzen 9 5950X 3.4GHz (16 cores)/128Gb/1Tb NVMe SSD+12Tb HDD/2xRTX 3090+PSU] Xeon E3-1230 3.2GHz (4 cores)/16Gb/2x12Tb HDD/PSU] AMD Ryzen 9 5950X 3.4GHz (16 cores)/128Gb/1Tb NVMe SSD+12Tb HDD/2xRTX 3090+PSU+HDMI emulator] AMD Ryzen 9 5950X 3.4GHz (16 cores)/128Gb/1Tb NVMe SSD+12Tb HDD/2xRTX 3090+PSU] AMD EPYC 7402P 2.8GHz (24 cores)/384Gb/2x1.92Tb U3 NVMe SSD/4xRTX 4090+2xPSU] As you can see, most GPU solutions are rented based on the RTX4090/3090, but as the computing power requirements increase, the startup wishes to have the option for servers with more powerful, professional cards that offer better stability when running in continuous 24/7 operation. In the case of the 3090, renting the same A5000 might even be cheaper. PTF Lab is at the beginning of its journey, but its results are already promising, and we at HOSTKEY wish them success and growth, especially in terms of overcoming the monopoly of sports augmented reality. The witty David always defeats the clumsy proprietary Goliath. If you have any questions for our colleagues from PTF Lab, please feel free to ask them in the comments. or a server with a with professional-grade or cards. are also available. Rent GPU servers with instant deployment custom configuration NVIDIA Tesla H100 / H100 80Gb RTX A5000 / A4000 GPU servers with game RTX4090 cards

How AI Is Fighting Monopolies in Sports Advertising With GPUs and Servers

কিভাবে AI GPU এবং সার্ভারের সাথে ক্রীড়া বিজ্ঞাপনে একচেটিয়া লড়াই করছে

Wie KI Monopole in der Sportwerbung mit GPUs und Servern bekämpft

Cómo la IA lucha contra los monopolios en la publicidad deportiva con GPU y servidores

Comment l'IA combat les monopoles dans la publicité sportive avec des GPU et des serveurs

एआई कैसे जीपीयू और सर्वर के साथ खेल विज्ञापन में एकाधिकार से लड़ रहा है

AI が GPU とサーバーを使用してスポーツ広告の独占とどのように戦うか

AI가 GPU와 서버를 사용해 스포츠 광고 독점에 맞서 싸우는 방법

Como a IA está combatendo os monopólios na publicidade esportiva com GPUs e servidores

Как ИИ борется с монополиями в спортивной рекламе с помощью графических процессоров и серверов

Yapay Zeka, GPU'lar ve Sunucularla Spor Reklamcılığında Tekellerle Nasıl Mücadele Ediyor?

AI đang chống lại sự độc quyền trong quảng cáo thể thao bằng GPU và máy chủ như thế nào

人工智能如何利用 GPU 和服务器对抗体育广告领域的垄断

Proxy servers will evolve into dynamic systems that continuously adjust in response to real-time user behavior, network conditions, and emerging security threats. Proxies have evolved significantly over the years, becoming indispensable tools for various applications. Now, the convergence of artificial intelligence and machine learning has the potential to redefine their role in the digital world. Pavlo Zinkovskyi, CTO of Infatica, explores the current landscape of proxy servers and how AI is set to revolutionize them. A proxy is an intermediary that acts as a gateway between a client (such as a user's smartphone) and a target server (like a website or application). In the early days of the internet, proxies were primarily used for caching web content. However, as the internet expanded, so did their roles. Businesses and individuals began to utilize them for content filtering, access control, enhanced security, and bypassing internet censorship. Given that two-thirds of adults worldwide express over identity theft and four out of five are worried about the privacy of their data, it comes as no surprise that VPNs and proxies have popularity to maintain anonymity online. concerns gained Advancements in technology, including improved encryption protocols and better user interfaces, have benefited proxy servers significantly. Now, AI and ML integration is revolutionizing their capabilities. The Current Landscape Proxies are now at the heart of many digital operations. Their applications include, but are not limited to: Bypassing geo-restrictions. Proxies are indispensable for individuals and organizations seeking to access geo-restricted content by routing their connections through servers in different locations. Ensuring privacy. They provide a layer of anonymity by masking users' IP addresses. This is particularly important for people in regions with strict online surveillance or for those who want to safeguard their identity. Content filtering. Proxy servers help organizations enforce content policies, ensuring that users access only approved content. For example, businesses can prevent employees from visiting inappropriate or non-work-related websites. Proxies are helpful in a variety of other use cases, such as content delivery, managing multiple social media accounts, anonymous and continuous web scraping, and many others. Despite their widespread use, they are not without challenges. When too many users connect through a single proxy server, it can become overloaded, leading to delays and poor user experiences. In addition, proxies can be vulnerable to attacks, and their misuse can lead to breaches of security protocols. Finally, setting up and configuring a proxy often requires a significant degree of expertise, and any misconfiguration can cause disruptions in network services. We often have to lean heavily on human expertise to mitigate these issues. This is where AI and machine learning come into play, bringing new possibilities to the table. AI and ML Promise AI and machine learning technologies have the potential to address proxy servers limitations and take this technology to the next level. Enhanced Security Proxies powered by AI and ML can identify suspicious patterns in network traffic and take proactive measures to enhance security. For example, they can detect and block traffic associated with malware or phishing attempts. The ability to continuously learn from new threats makes them more resilient against evolving cyber risks. **AI Traffic Management AI can predict user traffic patterns and dynamically manage servers to ensure optimal performance. By analyzing historical data, algorithms can anticipate surges in demand and allocate resources (bandwidth and server capacity) efficiently. This translates to a smoother and faster user experience, particularly in cases of high load. Adaptive Proxy Configurations AI-driven proxy servers have the potential to adapt to changing conditions in real time. They can self-optimize based on user behavior, network indicators, and other dynamic factors. If a particular content delivery server becomes slow, AI can redirect traffic to a faster alternative automatically. Transforming Industries The combination of AI and proxies could be valuable for diverse sectors. For instance, in the realm of e-commerce, AI-driven proxy servers can optimize web traffic distribution. They can ensure a consistent online shopping experience, even during peak seasons. They can also enhance data-gathering capabilities for online companies. Our data shows that a substantial 24% of all web scraping activities are directed towards e-commerce platforms. These businesses collect data from competitor websites for strategic pricing adjustments, product listing optimization, and maintaining competitiveness. AI-powered proxies could offer intelligent scraping capabilities, enable real-time monitoring and adjustments to avoid detection by anti-scraping measures and ensure uninterrupted data extraction. This robust approach empowers businesses to make informed, data-driven decisions. Another compelling example lies within the cybersecurity sector. AI-powered web scrapers and proxy solutions could identify inactive URLs, generate dynamic fingerprints based on various parameters like IP address, browser, and location, and effectively evade flagging or bans. Over half of business owners have already AI for cybersecurity and fraud management. Proxies could further bolster their capabilities. adopted Challenges and Ethical Implications While the integration of AI and ML into proxies offers tremendous benefits, there are potential risks. Over-reliance on AI with a lack of human oversight can potentially result in misidentifications. AI algorithms can be influenced by biases present in their training data, which can lead to unfair or inaccurate decisions. For instance, if a proxy server relies on an AI algorithm for content filtering, it may inadvertently block websites that shouldn't be restricted or allow access to harmful ones. AI might also block legitimate traffic, causing frustration for users. Moreover, the use of AI raises common ethical concerns related to privacy. OpenAI, along with Microsoft, has recently a class action lawsuit in the federal court of San Francisco, which alleges that they violated multiple privacy laws while developing ChatGPT and other generative AI systems. The complaint contends that AI models were trained by using unlawfully obtained personal data from hundreds of millions of internet users. encountered The Ongoing Evolution of Proxy Servers Despite all the challenges, I strongly believe the development of technology is undeniably linked to AI and ML. PwC has already over 300 AI use cases in various industries, and this trend will not bypass proxies either. identified Proxy servers will no longer be static tools but dynamic systems that continuously learn and adapt. They will evolve based on real-time user behavior, network conditions, and emerging security threats. They will also automatically adjust their configurations, allocate resources more efficiently, and preemptively address performance issues. This means users, both individuals and businesses, will be able to enjoy a seamless online experience with minimal disruptions and maximal security.

Proxy Servers Evolve under the Rising Influence of AI and ML

Microsoft v. United States (2016) Court Filing, retrieved on July 14, 2016, is part of . You can jump to any part in this filing . This part is 2 of 22. HackerNoon’s Legal PDF Series here BACKGROUND - I. Microsoft’s Web‐Based E‐mail Service The factual setting in which this dispute arose is largely undisputed and is established primarily by affidavits submitted by or on behalf of the parties. Microsoft Corporation is a United States business incorporated and headquartered in Washington State.  Since 1997, Microsoft has operated a “web‐based e‐mail” service available for public use without charge. Joint Appendix (“J.A.”) at 35.  It calls the most recent iteration of this service Outlook.com.[1]  The service allows Microsoft customers to send and receive correspondence using e‐mail accounts hosted by the company.  In a protocol now broadly familiar to the ordinary citizen, a customer uses a computer to navigate to the Outlook.com web address, and there, after logging in with username and password, conducts correspondence electronically. Microsoft explains that, when it provides customers with web‐based access to e‐mail accounts, it stores the contents of each user’s e‐mails, along with a variety of non‐content information related to the account and to the account’s e‐mail traffic, on a network of servers.[2]  The company’s servers are housed in datacenters operated by it and its subsidiaries.[3] Microsoft currently makes “enterprise cloud service offerings” available to customers in over 100 countries through Microsoft’s “public cloud.”[4]  The service offerings are “segmented into regions, and most customer data (e.g. email, calendar entries, and documents) is generally contained entirely within one or more data centers in the region in which the customer is located.” J.A. at 109.  Microsoft generally stores a customer’s e‐mail information and content at datacenters located near the physical location identified by the user as its own when subscribing to the service.  Microsoft does so, it explains, “in part to reduce ‘network latency’” [5]—i.e., delay—inherent in web‐based computing services and thereby to improve the user’s experience of its service.  J.A. at 36–37.  As of 2014, Microsoft “manage[d] over one million server computers in [its] datacenters worldwide, in over 100 discrete leased and owned datacenter facilities, spread over 40 countries.” Id. at 109. These facilities, it avers, “host more than 200 online services, used by over 1 billion customers and over 20 million businesses worldwide.”  Id. at 109. One of Microsoft’s datacenters is located in Dublin, Ireland, where it is operated by a wholly owned Microsoft subsidiary. According to Microsoft, when its system automatically determines, “based on [the user’s] country code,” that storage for an e‐mail account “should be migrated to the Dublin datacenter,” it transfers the data associated with the account to that location.  Id. at 37.  Before making the transfer, it does not verify user identity or location; it simply takes the user‐provided information at face value, and its systems migrate the data according to company protocol. Under practices in place at the time of these proceedings, once the transfer is complete, Microsoft deletes from its U.S.‐based servers “all content and non‐content information associated with the account in the United States,” retaining only three data sets in its U.S. facilities.  Id. at 37.  First, Microsoft stores some non‐content e‐mail information in a U.S.‐located “data warehouse” that it operates “for testing and quality control purposes.”  Id.  Second, it may store some information about the user’s online address book in a central “address book clearing house” that it maintains in the United States.  Third, it may store some basic account information, including the user’s name and country, in a U.S.‐sited database.  Id. at 37–38. Microsoft asserts that, after the migration is complete, the “only way to access” user data stored in Dublin and associated with one of its customer’s web‐based e‐mail accounts is “from the Dublin datacenter.” Id. at 37.  Although the assertion might be read to imply that a Microsoft employee must be physically present in Ireland to access the user data stored there, this is not so.  Microsoft acknowledges that, by using a database management program that can be accessed at some of its offices in the United States, it can “collect” account data that is stored on any of its servers globally and bring that data into the United States.  Id. at 39–40. [1] The company inaugurated Outlook.com in 2013 as a successor to Microsoft’s earlier Hotmail.com and MSN.com services. [2] A “server” is “a shared computer on a network that provides services to clients.  . . .  An Internet‐connected web server is [a] common example of a server. ”  Harry Newton & Steve Schoen, Newton’s Telecom Dictionary 1084 (28th ed. 2014) (“Newton’s Telecom Dictionary”). [3] A “datacenter” is “[a] centralized location where computing resources (e.g. host computers, servers, peripherals, applications, databases, and network access) critical to an organization are maintained in a highly controlled physical environment (temperature, humidity, etc.).” at 373. Newton’s Telecom Dictionary [4] The Supreme Court has recently described “[c]loud computing” as “the capacity of Internet‐ connected devices to display data stored on remote servers rather than on the device itself.” Riley v. California, 134 S. Ct. 2473, 2491 (2014). [5] Microsoft explains network latency as “the principle of network architecture that the greater the geographical distance between a user and the datacenter where the user’s data is stored, the slower the service.” J.A. at 36. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case No. 15–777 retrieved on September 27, 2023, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. cases.justia.com

Microsoft Can Collect and Bring Data Stored on Any of Its Servers Globally Into the US

Zeeve, a leading provider of managed blockchain infrastructure, has unveiled a strategic integration with Cherry Servers, a comprehensive private cloud infrastructure provider. This collaborative effort not only enriches the Zeeve platform, benefitting its 27,000+ users with expanded cloud options, but also empowers Cherry Servers to offer services to its global clientele. Web3 Empowering Developers with Cherry Servers Cherry Servers, boasting over two decades of experience, has established itself as a preferred choice among developers by offering top-tier performance, unwavering machine quality, and dedicated support, all at competitive price points. The partnership with Zeeve augments Cherry Servers’ existing offerings, providing businesses with a comprehensive solution for their growth. It also addresses NodeOps concerns related to uptime, request volume, and security. A Synergistic Collaboration Dr. Ravi Chamria, co-founder and CEO of Zeeve, described this collaboration as a fusion of infrastructural and Web3 expertise with the goal of elevating to new heights. This integration enables Cherry Servers to seamlessly transition to a Web3-ready status, harnessing the robust capabilities that Zeeve brings to the table. The partnership empowers Cherry Servers to offer its customers access to the boundless possibilities of Web3, backed by Zeeve’s unwavering support and advanced Web3 engine. Together, they aim to redefine Web3 infrastructure by embedding enterprise-grade capabilities within Cherry Servers for blockchain nodes, networks, and infrastructure. Web3 infrastructure Accelerating Blockchain Development The integration between Zeeve and Cherry Servers will expedite blockchain development and the deployment of enterprise-grade solutions. It achieves this by combining Cherry Servers’ cloud technology with Zeeve’s no-code infrastructure and extensive Web3 experience. Zeeve’s one-click deployment platform simplifies the process for to deploy and manage blockchain nodes and networks. This ensures a seamless transition from MVP to Production with minimal turnaround time. By alleviating deployment challenges and costs, this collaboration empowers developers and system integrators to swiftly enter the market and enhance ROI on production use cases. enterprise IT professionals Optimal Web3 Capabilities According to Ghan Vashishtha, Co-Founder and CTO of Zeeve, unlocking the full potential of Web3 necessitates alignment with the right cloud infrastructure. Cherry Servers’ systems are meticulously configured to meet the unique requirements of Web3, featuring best-in-class microprocessors, bare-metal cloud servers, and globally distributed data centers that significantly boost IOPS operations. This results in optimal performance, superior bandwidth, and minimal global latency. Coupled with Zeeve’s distinctive value-add, this collaboration paves the way for a streamlined and efficient Web3 ecosystem. It enhances reliability and fosters the development of innovative solutions. A Strategic Alliance As numerous cloud providers explore or launch Web3 services, a process that demands substantial investment and dedicated teams, the partnership between Cherry Servers and Zeeve holds immense significance. It provides Cherry Servers with a seamless pathway to blockchain readiness, enabling enhancements to its existing cloud offerings. Zeeve contributes trust, compliance, and expert support to ensure the resilience and robustness of and networks. This strategic move elevates both partners, delivering superior infrastructure quality, advanced network automation, enterprise-level security, and unmatched support for blockchain initiatives. Web3 nodes This story was distributed as a press release under HackerNoon’s Brand As An Author Program. Learn more about the program . here

Revolutionizing Web3 Infrastructure: The Zeeve and Cherry Servers Collaboration

বিপ্লবী ওয়েব 3 পরিকাঠামো: জিভ এবং চেরি সার্ভার সহযোগিতা

Revolutionierung der Web3-Infrastruktur: Die Zusammenarbeit von Zeeve und Cherry Servers

Revolucionando la infraestructura Web3: la colaboración de Zeeve y Cherry Servers

Révolutionner l'infrastructure Web3 : la collaboration entre les serveurs Zeeve et Cherry

वेब3 इन्फ्रास्ट्रक्चर में क्रांतिकारी बदलाव: ज़ीव और चेरी सर्वर सहयोग

Web3 インフラストラクチャの革命: Zeeve と Cherry Server のコラボレーション

Web3 인프라 혁신: Zeeve와 Cherry 서버 협업

Revolucionando a infraestrutura Web3: a colaboração dos servidores Zeeve e Cherry

Революция в инфраструктуре Web3: сотрудничество Zeeve и Cherry Servers

Web3 Altyapısında Devrim Yaratıyor: Zeeve ve Cherry Sunucuları İşbirliği

Cách mạng hóa cơ sở hạ tầng Web3: Sự hợp tác giữa máy chủ Zeeve và Cherry

彻底改变 Web3 基础设施：Zeeve 和 Cherry Servers 的合作

USA v. Google LLC Court Filing, retrieved on January 24, 2023 is part of . You can jump to any part in this filing . This is part 20 of 44. HackerNoon’s Legal PDF Series here IV. GOOGLE’S SCHEME TO DOMINATE THE AD TECH STACK C. Google Buys and Kills a Burgeoning Competitor and Then Tightens the Screws 2. Google Doubles Down on Preventing Rival Publisher Ad Servers from Accessing AdX and Google Ads’ Demand 154. After acquiring and killing AdMeld’s innovative technology in order to prevent publishers from having the opportunity to experience real-time competition between Google and rival ad exchanges and publisher ad servers, Google clamped down on similar attempts by publishers to allow Google’s ad exchange to integrate with rival publisher ad servers. 155. By 2015, Google’s publisher ad server, DFP, had reached a 90% market share and had snuffed out most meaningful competition. In part because of the scale that Google’s publisher ad server had achieved by excluding competitors, Google’s ad exchange was large and growing quickly; Google Ads likewise remained the dominant advertiser ad network and an especially valuable source of advertising demand for many publishers. Emboldened by its success, in 2014 Google changed the AdX terms of service to further entrench its market power. Those changes prohibited publishers from using non-Google ad servers, or the remaining yield management solutions, to compare bids from Google’s ad exchange with bids from other ad exchanges in real time, notwithstanding the increased access to inventory such an integration could provide to advertisers buying on AdX. In effect, Google decreed that any publisher that wanted real-time competition involving AdX would have to use Google’s publisher ad server, DFP, formally cementing in policy what Google had intended from the outset of its relaunch of AdX in 2009. 156. Google’s decision was bad for publishers, locking them into a less innovative publisher ad server with artificial limitations on real-time price competition for advertising inventory. It was also bad for any would-be publisher ad server rivals—effectively sounding the death knell for future publisher ad server competition. Google’s exclusionary policy effectively prohibited a competing publisher ad server from offering any form of real-time competition that included Google’s ad exchange and the unique advertiser demand that came with it. Forgoing such competition was a non-starter for nearly all publishers. This restriction is still in place today, an insurmountable obstacle for any nascent publisher ad server competitor. 157. Google built a wall around its exclusive link between its publisher ad server and ad exchange because it feared competition. In particular, Google feared a rival could offer a more attractive publisher ad server by simply allowing all advertiser demand to compete in real time on a level playing field for publisher inventory. More demand competing in real time for publisher inventory generally increases the likelihood that the advertiser that is willing to pay the most for an impression will have a chance to buy it. Rivals that offered technology upending this policy would be seen as offering a better publisher ad server. As one Google employee wrote, if another publisher ad server could place Google’s ad exchange in real-time competition with other ad exchanges, that ad server could offer publishers a “super set of demand” and “[n]o one would sign up for AdX directly” through Google’s publisher ad server. 158. Even though both publishers and advertisers benefit from real-time competition between AdX and other ad exchanges, by policy, Google limited real-time competition from rival ad exchanges to maintain its dominant positions at both ends of the ad tech stack and to further insulate its growing position in the ad exchange market. Google’s decision was based on business, not technology. As the lead architect of AdX explained in an internal email about the policy, “Our goal should be all or nothing – use AdX as your SSP [ad exchange] or don’t get access to our demand.” Indeed, Google had already worked quietly to develop the technology that might allow AdX to integrate in real time with non-Google publisher ad servers. But Google made a “strategic decision” to prohibit such integrations via contract; it terminated its internal projects and blocked efforts by rivals and publisher customers to implement such integrations. That prohibition endures today, and both publishers and advertisers are paying the price for Google’s anticompetitive refusal to innovate or integrate. 159. Now, the only way a publisher can access Google’s ad exchange outside Google’s publisher ad server is by placing an “AdX Direct” tag on the publisher’s website. Even though these tags could benefit buyers on Google’s ad exchange by providing access to additional publisher inventory, Google designed the tags to discourage publishers from using them. They offer only the most rudimentary functionality: publishers can send a request to Google’s ad exchange with a price floor, and if there is an advertiser on AdX willing to pay that price or higher, Google’s ad exchange wins the inventory. No other competing bids are considered, and Google’s bid cannot be compared to other ad exchanges’ bids. 160. Recognizing that AdX Direct is an antiquated relic in comparison to real-time bidding, Google even planned to eliminate the tag entirely in 2019. Google later paused that project as antitrust enforcers focused their gaze on the company’s digital advertising business. But Google has not retained AdX Direct because it is a competitive product offering valued by publishers. Rather, in the words of a Google employee, it merely serves as “a concept for antitrust”—something Google’s antitrust lawyers could claim offers rival ad servers some remote chance of competing on the merits with Google’s ad server. Google’s internal analyses of AdX Direct, however, reflect publishers’ reality: Google’s restrictions make impossible any reasonable substitute for the real-time integration with Google’s ad exchange available exclusively through Google’s ad server. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case 1:23-cv-00108 retrieved on September 8, 2023, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. justice.gov

Google Prevents Rival Publisher Ad Servers from Accessing AdX and Google Ads' Demand

Google impide que los servidores de anuncios de editores rivales accedan a AdX y a la demanda de Google Ads

Google empêche les serveurs publicitaires des éditeurs rivaux d'accéder à la demande d'AdX et de Google Ads

Google प्रतिद्वंद्वी प्रकाशक विज्ञापन सर्वरों को AdX और Google विज्ञापनों की मांग तक पहुंचने से रोकता है

Google、ライバルのパブリッシャー広告サーバーによる AdX と Google 広告の需要へのアクセスを阻止

Google impede que servidores de anúncios de editores rivais acessem AdX e a demanda do Google Ads

Google ngăn máy chủ quảng cáo của nhà xuất bản đối thủ truy cập nhu cầu của AdX và Google Ads

Google 阻止竞争对手发布商广告服务器访问 AdX 和 Google Ads 的需求

Let's learn about via these 29 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Servers /Learn Repo 1. Using a REST API with Python Requesting fitness data (backlog) from Terra requires HTTP requests, so I’m writing an essential guide here on using a REST API with Python. 2. You’ll Need to Use a Proxy Server, Sooner or Later Why in large web scraping projects there's the need of proxy servers? Here a brief explanation of what they are and how they work and their differences. 3. Containers vs. Serverless: Which is Better for DevOps? Managing your own containers versus letting serverless do it for you - when to choose what? Let's go over the pros and cons. 4. A Look at the Cost of Downtime Over half of businesses need more than one hour to recover a crashed application, costing over $10,000 for every hour of downtime. With how much we rely on technology, system monitoring is more important than ever. The world depends on IT, so when systems fail it makes an impact on people and businesses followed by monetary consequences. Many large companies may be able to pay for protection, but what about the small to medium sized companies that remain vulnerable to uncertain infrastructure? 5. How Nutanix VM Works In the era of enterprise cloud, modern enterprise datacenter must support
virtualization with high availability and live VM migration. The traditional storage area networks (SAN) or network attached storage (NAS) doesn’t suit. Instead, they are ideal to manage a logical unit number (LUN). A LUN can be a single disk, an entire redundant array of independent disks (RAID), or disk partitions. 6. Edge Computing is So Fun Part 5. CDN Is The Magic Inside Disney’s Streaming Services Without the CDN infrastructure, Disney+'s 100 million subscribers will not be able to enjoy the movies at home during the pandemic. 7. Difference Between ECC and Non-ECC RAM Error-Correcting Code (ecc), protects your system from potential crashes and inadvertent changes. So how about it be a ram server? Worth or not? 8. The Data Revolution: Green, Accessible, and Fully-Decentralized it's time to make data sexy again. Let's revive the dream of a truly neutral Internet, from the people for the people with wide accessibility and no censorship 9. Best Physical Security Practices for Your Server Room Your server room hosts your most important assets, so it deserves proper protection. Here are four physical security strategies to keep your server room secure. 10. Businesses Have Countless Web Hosting Options: Here's What They Are In the earliest days of the Internet, pioneering businesses didn't have too many options to get their companies online. At the time (the mid to late 1990s), web hosting options were minimal. 11. Understanding APIs and How to Test Them API (an abbreviation of Application Programming Interface) is a special interface (a set of commands/controls) that is designed for the interaction of different 12. Node.js Vs Flask: Which One Has A Better Performance Curious about how Flask stacks up against Node.js? These are my thoughts on the matter. 13. Tutorial: How to Quickly Set up NodeJS Server NodeJS is a popular framework of JavaScript used for back-end web development. And for this, a server is as important as the backbone to a human body. So in this tutorial, we'll learn how to quickly set up a nodeJS server. 14. How Properly Configure Nginx Server for TLS This is a follow up on a story that I've published a few years ago. It still receives a huge amount of traffic so I decided to update it with the latest information. 15. Developers and Cloud IaaS: Why Devs Should Set Up Their Own Cloud Infrastructure Why Infrastructure as a Service (IaaS) still rules, even for developers. 16. Apache Web Server Hardening: How To Protect Your Server From Attacks he web server has a crucial role in web-based applications. Since most of us leave it to the default configuration, it can leak sensitive data regarding the web server. 17. Which GPU is Better for Business, the RTX 4090 or a Server RTX A5000? We shall compare Nvidia's new gaming graphics card, the GeForce RTX 4090, and the powerful RTX A5000 server card. 18. VMware vCenter Converter Alternatives for V2V? VMware is commonly used to set up data centers for organisations. If the most commonly used solution doesn't work, some alternatives may work better for you. 19. How to Connect With External MySQL Servers (Part 1: Select Operations) This tutorial shows how to perform basic select queries to interact with MySQL Server using mysql2 gem. 20. The Bare Facts: What Businesses Have to Gain with Dedicated Servers By Andreea Jakab, Bigstep 21. Functional Testing With Your Backend in Go For Terrastruct, which has a little over 50K lines of code as of now, I've only written functional end-to-end tests. This blog post describes a successful setup that took some iterating to get to, and it's one I wish existed when I started with a Go API backend. 22. How to Automate the Creation of a Development Server In part one, I have shown how to create a remote development using DigitalOcean and rsync. In part two, I will show how to automate the entire process using Bash script. 23. 🐲 Dragon Router Introduction: HTTP Router and URL Matcher For Building Deno Web Servers ⚡A powerful HTTP router and URL matcher for building Deno web servers with dragon 🐲. 24. Alternative Overview of the SSMSBoost Add-in for SQL Server Management Studio (SSMS) Today we will do a short review and features comparison of dbForge SQL Complete and SSMSBoost. 25. Insight Into TCP/UDP, Network Vulnerabilities and Defense Approaches This article provides the network vulnerabilities and defense approaches, with a focus on all the TCP and UDP ports, Port vulnerability, and learn more about Windows, Linux server operation guide. 26. HTTP Made Easy: Understanding the Web Client-Server Communication If you are anywhere related to web development, understanding the concepts of HTTP plays a vital role. So let us understand more about HTTP and its concepts in brief. 27. How to Connect With External MySQL Servers (Part 2: Insert & Update Operations) This is the second part of the series where we perform insert and update operations to interact with the MySQL server in Rails using MySQL2 gem. 28. How to Create a Remote Development Server Introduction 29. Graceful shutdown in NodeJS In this article, I am going to show you how to do a graceful shutdown in NodeJS application, but first, let's describe what does “graceful shutdown” means and why we need to do that in our application and what are the benefits. Thank you for checking out the 29 most read stories about Servers on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

29 Stories To Learn About Servers

One excellent way to build is by scraping the web. It becomes especially relevant when sources like Common Crawl or official APIs fail to meet your project’s requirements (for example, the data isn’t recent enough or Twitter prices you out). However, web scraping comes with its own challenges like and geo-restrictions. This is where our hero — proxies — enter the scene. datasets CAPTCHAs A proxy server is another computer (a server, phone, or even IoT device) that lets you access the web through itself. This way, you get a new IP address from an optionally different location. Proxies are much like VPNs — the difference is that you can use many of them at once instead of just one or two connections. Proxy servers are becoming more and more necessary as websites implement rate limiting and more sophisticated restrictions to prevent automated access. Sometimes, for good reasons, though often it’s to protect their commercial interests or monopolize data. Proxies won’t solve all your problems; but aside from basic hygiene, such as using realistic user-agents, they’re the most effective way to keep your web scraper running. This guide will give you a strong understanding of proxy servers in the context of web scraping. It comes with theoretical knowledge together with some practical data we collected for our annual . proxy market research First things first: you most likely don’t want to use free proxies When web scrapers (the people) encounter a need for proxies, their first impulse is to try out a free proxy list. These lists are publicly available online; most of the proxies in them come from vulnerable or mismanaged servers. One big problem with free proxy lists is that you never know who runs them. The operator may have malicious intentions, which can manifest in ad injection, traffic logging, and other nasty things. This sounds scary, but it’s unlikely to affect you much as a data scientist: you probably won’t configure proxies on the operating system level or use them to access your bank account. A more boring — though realistic — issue is that free proxies are simply unreliable. They rarely stay online for long; the ones that do run are unbearably slow because they have hundreds of tenants; and because they have hundreds of tenants, such proxies very quickly strike themselves out with any relevant website. Not a great tool to work with. For this reason, I strongly recommend paying for a commercial proxy service. Types of proxy servers out there Proxy servers are most often categorized by the IP source. For web scraping purposes, you’ll most likely choose between three types: datacenter, residential, or ISP (also called static residential) proxies. Datacenter proxies These proxies are hosted on servers in data centers. They can be instances of Amazon Cloud Services (AWS) or come from any other cloud hosting provider. IP databases see datacenter proxies as belonging to or ranges. hosting datacenter Datacenter proxies typically run on powerful hardware and internet connection, so you can scrape a lot of data fast. They can be a very efficient choice for targets that don’t monitor IP reputation but struggle with websites that do. Residential proxies These proxies come from the residential devices of real people (hence the name). For example, they can run on a Windows laptop, Android phone, or a smart fridge on Wi-Fi. IP databases classify residential proxies as or connections. landline mobile Residential proxies always come in large pools of addresses from around the world. They’re less predictable than datacenter IPs because they rely on the connection quality and availability of the host device. However, this very feature makes residential proxies very effective with all kinds of websites, as they look like regular visitors. ISP proxies These proxies are hosted on servers in data centers registered under consumer internet service providers like Verizon. This is achieved by signing a contract with an ISP and getting it to announce IPs on its network. Ideally, IP databases should identify such proxies as or connections. Sometimes, though, smaller regional ISPs are still classified as data centers. but landline mobile ISP proxies retain the qualities of datacenter proxies but are able to scrape more effectively due to a better IP reputation. How proxies are sourced and whether they’re legal At this point, you may be thinking, “Woah, wait a minute! Android phones? Sounds awfully like a botnet! Is that even legal?” This is a good question to ask, and it shows that you care. Many don’t. The fact is that there’s a fine line between a commercial proxy server and a botnet. It applies less to datacenter proxies where the supply chain is pretty much clear: a cloud host buys IPs, puts them on a server, and rents the addresses to a proxy provider. But the question of ethics becomes very relevant with residential proxy networks. Without delving too deep into the topic, residential proxies can be sourced in several ways. The most popular method is via SDKs in desktop and mobile applications. gives concrete examples of what that looks like. This video https://www.youtube.com/watch?v=1-Lbgd4BYHI&embedable=true Another way is to exchange traffic directly for a service (such as a free VPN, see BrightVPN) or money (using bandwidth-sharing apps like Honeygain). In any case, the onus falls on the proxy provider to ensure that the IP source is aware of the arrangement and consents to it. You should be able to find information about proxy sourcing and usage approaches on the provider’s website. This significantly reduces the chance that you’ll be using a botnet. Proxy server configurations Proxy servers may have different configurations based on and . tenancy rotation The first criterion describes how many people can use the same proxy server at once. All free proxy lists have potentially hundreds of tenants, while commercial proxy providers impose limits. In the market lingo, or means you’ll use the same proxy server with several other people (often one to four). or means that you alone will use the proxies for all or particular domains. shared semi-shared Private dedicated The ability to choose tenancy is a feature of datacenter and ISP proxies, as providers have full ownership over them. It’s unavailable with residential proxies but also less relevant — residential users have more natural browsing patterns and are less likely to overload websites with requests. The second criterion, rotation, shows whether proxy servers switch automatically. The ones that don’t often come in proxy lists formatted as IP:Port (1). The ones that do take the format of endpoint:port (2): 192.168.0.1:10000 en.proxyprovider.net:10000 The endpoint functions as a gateway to the provider’s proxy pool. It automatically routes your requests through different addresses in the backend. Even when an IP address changes, the endpoint remains the same. Rotating proxies are very convenient for web scraping, as you get access to an effectively infinite number of IPs (thousands to millions). However, such services often charge for traffic expenditure, while static proxy lists tend to offer unlimited traffic. Comparing the different proxy types Let’s compare the discussed proxy types based on their various characteristics. Affordability In the case of rotating proxy networks, residential proxies cost around eight to 10 times more than datacenter addresses and a little less than rotating ISP proxy networks. Static proxy networks usually charge per IP address. Compared to ISP proxies, datacenter proxy servers cost two to three times less, depending on how much you buy. Infrastructure performance Despite routing traffic through unpredictable end-user devices, major residential proxy networks work very well. For web scraping purposes (when the IP rotates with each connection request), they transfer data almost as well as datacenter proxies: We also failed to see a big difference in latency. Below are response times for requests made to the nearest server of a global CDN (the response size is several kilobytes) and Amazon (around 1 MB response size): One area where datacenter and ISP proxies dominate is throughput. They have wider pipes for transferring data. Some residential proxies can be very fast, but you can just as well encounter servers that fail to reach 1 Mbps. There’s much less predictability. IP Uptime Datacenter and ISP proxies can stay up nearly 24/7, going offline only when an outage or maintenance occurs. The uptime of a residential proxy depends on various factors, such as whether it comes from a Windows or Android device. In any case, it’s much shorter and less dependable compared to server-based proxies. We wrote a script that pinged an IP database every 20 seconds to see how often a residential IP address would change. Here are some results: 43 seconds IP #1: Over an hour IP #2: 3 minutes, 33 seconds IP #3: 8 minutes, 31 seconds IP #4: Over an hour IP #5: Scraping effectiveness Datacenter proxies struggle against protected or highly popular websites like Google or social media. This can be somewhat mitigated by choosing dedicated IPs with a cleaner usage history. Sometimes, connecting from a datacenter IP range is enough for websites not to let you in. In such cases, the only recourse is to use a different proxy type. ISP proxies have a better IP reputation by default, so they face less initial scrutiny. However, they still have less realistic browsing patterns compared to a true residential address. Residential proxy servers form large pools, are very diverse, and share browsing history with real people. These qualities make them very hard to distinguish from the website’s broader audience. Location variety Datacenter and ISP proxies are hosted in data centers, and the number of available datacenters is limited. The most frequent location is probably Ashburn, though major providers can get you datacenter IPs from dozens of countries. However, if you need addresses in smaller locales, and especially their non-capital cities, you’ll be out of luck. Residential proxies have no such restrictions — as long as there’s a device and a willing participant, anyone from anywhere can join. Consequently, major providers can offer IPs in all countries with city, ASN, and sometimes even ZIP code targeting. Popularity Based on our survey of major proxy providers, most chose residential proxies as their most popular product. Only two providers specified datacenter proxy servers, and none ISP proxies. Datacenter proxies have been falling off in recent years, as major targets like Amazon, Google, LinkedIn, and others tightened their security systems. ISP proxies have the capacity to take their place, but their uptake is hindered by sourcing difficulties — it’s hard to get reputable ISPs onboard. Recommendations for your projects But enough theory. How can you apply this knowledge to your project? I’ve modeled multiple scenarios with proxy server suggestions. To keep this article free from commercial interests, I won’t mention particular providers. If you’d like some recommendations, we compare major providers (Disclaimer: we’re in an affiliate relationship with most of those companies. However, this has no impact on our market reports.) on our website Scraping websites without advanced protection Scraping a minor news portal, e-commerce website, or even non-Google search engine. Example: Rotating datacenter proxies. You can get access to a pool of 2,000–100,000 rotating IPs for $0.7/GB or less. You won’t have to worry about replacing blocked IPs, and the cost of traffic is low enough for some serious data extraction. Recommendation: Downloading multimedia content Downloading videos off a streaming service or pictures from an image aggregator for archiving purposes. Example: Static datacenter or ISP proxies. They are fast and don’t count traffic expenditure. Go for datacenter proxies when the website allows it and ISP proxies otherwise. Recommendation: Crawling many different websites Searching for brand mentions throughout the web. Example: Static datacenter or ISP proxies. Crawling requires a lot of data, so it’s best to choose a proxy type that doesn’t use traffic as the main metric. Also, even a finite number of IPs will take you far when you switch targets. Recommendation: Scraping large popular targets Extracting job ads from LinkedIn, company information from G2, or hashtagged posts from a social media network. Example: Residential proxies. With an effectively infinite number of IPs, you won’t risk banning out your proxies. In addition, you’ll experience a higher success rate compared to other proxy types. Recommendation: Collecting real-time data Tracking stock price movements. Example: Datacenter proxies if the website allows them; else, ISP proxies**.** Their fast connection speed ensures that you’ll extract data as it appears. Recommendations: Accessing hyper-localized pages Monitoring search engine page positions for localized Google queries. Example: Residential proxies, as they support city-level IP filtering. Recommendation: Conclusion This article gave you a brief introduction to proxy servers for web scraping purposes. After reading it, you should be able to distinguish between the main proxy types, configurations, and which setup would benefit your data science project the most.

Proxy Servers for Your Data Science Project: A Comprehensive Guide

আপনার ডেটা বিজ্ঞান প্রকল্পের জন্য প্রক্সি সার্ভার: একটি ব্যাপক নির্দেশিকা

Proxyserver für Ihr Data-Science-Projekt: Ein umfassender Leitfaden

Servidores proxy para su proyecto de ciencia de datos: una guía

Serveurs proxy pour votre projet de science des données : un guide

आपके डेटा साइंस प्रोजेक्ट के लिए प्रॉक्सी सर्वर: एक गाइड

データ サイエンス プロジェクトのプロキシ サーバー: ガイド

데이터 과학 프로젝트를 위한 프록시 서버: 종합 가이드

Servidores proxy para seu projeto de ciência de dados: um guia

Veri Bilimi Projeniz için Proxy Sunucuları: Kapsamlı Bir Kılavuz

Máy chủ proxy cho Dự án khoa học dữ liệu của bạn: Hướng dẫn

数据科学项目的代理服务器：指南

Reading through my weekly security news and stumbled on a about using Google Workspace's Drive and Sheets (formerly G-Suite) to communicate and exfiltrate information natively Drive and Sheets. Bleepingcomputer article Please note this article and its contents are for educational purposes only. By explaining tactics used by hackers, I hope only to further enable security professionals to better protect themselves and their companies. Disclaimer: I thought this was a clever project because: You do not have to set up any particular domains, servers as most C2 frameworks do. (And many defense tools maintain a dynamic list of  malicious domains, IPs, etc). This doesn't use common C2 and red team frameworks, such as Cobalt Strike, SilverC2, or Brute Ratel. This program and traffic only interact with Google's domains (*.google.com) to make detection more difficult for tools. A smart tool would be able to identify the malicious commands being executed. A caveat: EDR In this small video, I will be setting up this project and testing the viability of this project, which basically means me pulling this repository and typing commands. You are welcome to follow along with the video tutorial if you would like. I will be using a rudimentary Ubuntu 20.04 host on Digital Ocean as a simulation of my victim machine. that this would be an executable the attacker would deploy on a machine post compromise. NOTE And even though there are caveats, as there often are, the recent use of GC2 by APT41 which is a suspected Chinese state-sponsored hacking group means this tool is being used out in the wild. Take a look at the video for more information on my experience. https://youtu.be/pLfuZnLcR1o?embedable=true&transcript=true What did you think of this guide? Let me know your questions in the comments below. This article was part of where we share the best tech content that YouTube has to offer. HackerNoon’s YouTuber series If you want to see more from this series, check it out here.

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