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Facial Recognition Software Free Download Mac

Face Logon Software Listing (Downloads/Page2). Face Detection in Color Images is designed as a handy and easy-to-use instrument that is able to cover an algorithm for face detection in color images. With this software you can search for faces in your photos, Face Capturix will look for faces in your pictures, detect and compare with the face. Exploring FamilySearch’s Facial Recognition Tool. Facial recognition software has penetrated everyday life for many people. No longer just the domain of law enforcement, facial recognition is now being used as biometric authentication for various computing platforms and devices including smartphones. FamilySearch has even gotten into the act. Download Face Recognition for free. Face Recognition - FastAccess learns about your face as you use your computer.

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Windows

Note: all files are signed with GnuPG and can be verified with this public key

Package By Distribution

Install a package that is made available through your distribution.

Keep in mind that distro-provided versions of digiKam could be out of date.macOS and Windows users should refer to the official bundles listed above.

Note: to integrate the AppImage bundle in Linux desktop, you can use the AppImageLauncher application.

Pre-Releases

These are betas and release-candidates provided by the team for testing.

These should be more stable than weekly snapshots and testing will help to ready them for release.This includes a universal Linux AppImage, macOS package, and Windows installer.

Download the latest pre-release.

Weekly Snapshots

These are compiled weekly versions provided by the team for testing purposes only.

This is the easiest way to try the current implementation that hasn’t been released yet.This includes a universal Linux AppImage, macOS package, and Windows installer.

Download the latest weekly snapshots.

Compile the Official Release

This is an option for those that are comfortable with compiling the project themselves.

Get the source for the latest official release and build.

Compile Latest Development Version

This is more complicated, but is as recent as possible.This is for when you want to help with finding bugs or to hack on the project as a contributor.

Get the latest code from our git repository.

You can choose the one which fits you best. We provide detailed instructions for each of them.

Older-Releases

All previous stable versions are archived.This includes a universal Linux AppImage, macOS package, and Windows installer.

Download the older stable release.

IntroductionTechnical PaperDownloadsMedia/PressLimitationsFAQ

NEWS

4-23-21: v1.0 release for Windows/MacOS apps and Win/Mac/Linux binaries!

4-2-21: Fawkes hits 500,000 downloads!

1-28-21: Adversarial training against Fawkes detected in Microsoft Azure (see below)

1-12-21: Fawkes hits 335,000 downloads!

8-23-20: Email us to join the Fawkes-announce mailing list for updates/news on Fawkes

8-13-20: Fawkes paper presented at USENIX Security 2020

News: Jan 28, 2021. It has recently come to our attention that there was a significant change made to the Microsoft Azure facial recognition platform in their backend model. Along with general improvements, our experiments seem to indicate that Azure has been trained to lower the efficacy of the specific version of Fawkes that has been released in the wild. We are unclear as to why this was done (since Microsoft, to the best of our knowledge, does not build unauthorized models from public facial images), nor have we received any communication from Microsoft on this. However, we feel it is important for our users to know of this development. We have made a major update (v1.0) to the tool to circumvent this change (and others like it). Please download the newest version of Fawkes below.

2020 is a watershed year for machine learning. It has seen the true arrival of commodized machine learning, where deep learning models and algorithms are readily available to Internet users. GPUs are cheaper and more readily available than ever, and new training methods like transfer learning have made it possible to train powerful deep learning models using smaller sets of data.

But accessible machine learning also has its downsides. A recent New York Times article by Kashmir Hill profiled clearview.ai, an unregulated facial recognition service that has downloaded over 3 billion photos of people from the Internet and social media and used them to build facial recognition models for millions of citizens without their knowledge or permission. Clearview.ai demonstrates just how easy it is to build invasive tools for monitoring and tracking using deep learning.

So how do we protect ourselves against unauthorized third parties building facial recognition models that recognize us wherever we may go? Regulations can and will help restrict the use of machine learning by public companies but will have negligible impact on private organizations, individuals, or even other nation states with similar goals.

The SAND Lab at University of Chicago has developed Fawkes1, an algorithm and software tool (running locally on your computer) that gives individuals the ability to limit how unknown third parties can track them by building facial recognition models out of their publicly available photos. At a high level, Fawkes 'poisons' models that try to learn what you look like, by putting hidden changes into your photos, and using them as Trojan horses to deliver that poison to any facial recognition models of you. Fawkes takes your personal images and makes tiny, pixel-level changes that are invisible to the human eye, in a process we call image cloaking. You can then use these 'cloaked' photos as you normally would, sharing them on social media, sending them to friends, printing them or displaying them on digital devices, the same way you would any other photo. The difference, however, is that if and when someone tries to use these photos to build a facial recognition model, 'cloaked' images will teach the model an highly distorted version of what makes you look like you. The cloak effect is not easily detectable by humans or machines and will not cause errors in model training. However, when someone tries to identify you by presenting an unaltered, 'uncloaked' image of you (e.g. a photo taken in public) to the model, the model will fail to recognize you.

Fawkes has been tested extensively and proven effective in a variety of environments and is 100% effective against state-of-the-art facial recognition models (Microsoft Azure Face API, Amazon Rekognition, and Face++). We are in the process of adding more material here to explain how and why Fawkes works. For now, please see the link below to our technical paper, which was presented at USENIX Security Symposium, held on August 12-14, 2000.

The Fawkes project is led by two PhD students at SAND Lab, Emily Wenger and Shawn Shan, with important contributions from Jiayun Zhang (SAND Lab visitor and current PhD student at UC San Diego) and Huiying Li, also a SAND Lab PhD student. The faculty advisors are SAND Lab co-directors and Neubauer Professors Ben Zhao and Heather Zheng.

1The Guy Fawkes mask, a la V for Vendetta.

In addition to the photos of the team cloaked above, here are a couple more examples of cloaked images and their originals. Can you tell which is the original? (Cloaked image of the Queen courtesy of TheVerge).

Publication & Presentation

Fawkes: Protecting Personal Privacy against Unauthorized Deep Learning Models. Shawn Shan, Emily Wenger, Jiayun Zhang, Huiying Li, Haitao Zheng, and Ben Y. Zhao. In Proceedings of USENIX Security Symposium 2020. ( Download PDF here )

Downloads and Source Code - v1.0 Release!

NEW! Fawkes v1.0 is a major update. We made the following updates to significantly improve the protection and software reliability.

We updated the backend feature extractor to the-state-of-art ArcFace models.

We injected additional randomness to the cloak generation process through randomized model selection.

We migrated the code base from TF 1 to TF 2, which resulted in a significant speedup and better compatibility.

Other minor tweaks to improve protection and minimize image perturbations.

Download the Fawkes Software: (new) Fawkes.dmg for Mac (v1.0) DMG file with installer app Compatibility: MacOS 10.13, 10.14, 10.15, 11.0 (new) Fawkes.exe for Windows (v1.0) EXE file Compatibility: Windows 10 Setup Instructions: For MacOS, download the .dmg file and double click to install. If your Mac refuses to open because the APP is from an unidentified developer, please go to System Preference>Security & Privacy>General and click Open Anyway.

Download the Fawkes Executable Binary: Fawkes binary offers additional options on selecting different parameters. Check here for more information on how to select the best parameters for your use case. Download Mac Binary (v1.0) Download Windows Binary (v1.0) Download Linux Binary (v1.0) For binary, simply run './protection -d imgs/'

Fawkes Source Code on Github, for development.

If you have any issues running Fawkes, please feel free to ask us by email or raising an issue in our Github repo. Check back often for new releases, or subscribe to our (very) low-volume mailing list

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for Fawkes announcements and news.

Media and Press Coverage

We stopped trying to keep this up to date. If you see an interesting article talking about Fawkes that's not listed here (especially if in non-English format), email us to let us know. Thanks.

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The Verge, James Vincent: Cloak your photos with this AI privacy tool to fool facial recognition

New York Times, Kashmir Hill: This Tool Could Protect Your Photos From Facial Recognition

UChicago CS, UChicago CS Researchers Create New Protection Against Facial Recognition With more commentary and responses to Clearview.ai CEO's comments in NY Times article.

Tech by Vice, Researchers Want to Protect Your Selfies From Facial Recognition

Die Zeit (Germany), Christoph Drosser: Die unsichtbare Maske (The Invisible Mask)

TechSpot, Adrian Potoroaca: University of Chicago researchers are building a tool to protect your pictures from facial recognition systems

The Register (UK), Sick of AI engines scraping your pics for facial recognition? Here's a way to Fawkes them right up

Gizmodo, Shoshana Wodinsky: This Algorithm Might Make Facial Recognition Obsolete

South China Morning Post (HongKong), Xinmei Shen: Anti-facial recognition tool Fawkes changes your photos just enough to stump Microsoft and Amazon

ZDNet, Fawkes protects your identity from facial recognition systems, pixel by pixel

Schneier on Security, Fawkes: Digital Image Cloaking

SlashGear, Brittany A. Roston: Fawkes photo tool lets anyone secretly 'poison' facial recognition systems

Digital Photography Preview, Brittany Hillen: Researchers release free AI-powered Fawkes image privacy tool for 'cloaking' faces

MIT Technology Review China, article

OneZero on Medium, This Filter Makes Your Photos Invisible to Facial Recognition

Built in Chicago, Nona Tepper: UChicago Researchers Made a Photo-Editing Tool That Hides Your Identity From Facial Recognition Algorithms

Digital Village, Episode 22: Cloaking Your Photos with Fawkes - Language Models

The American Genius, Desmond Meagley: The newest booming business: Hiding from facial recognition

Futurity, 'Fawkes' tool protects you from facial recognition online

Communications of the ACM, Paul Marks: Blocking Facial Recognition

Daily Mail (UK), Stacy Liberatore: AI program named after V For Vendetta masks could help protect your photos...

Today Online (Singapore), This tool could protect your photos from facial recognition

El universal (Mexico), Esta herramienta protege tus fotos del reconocimiento facial

Radio Canada, This tool can keep your photos safe from facial recognition algorithms

DigiArena.CZ (Czech), Adam Kos: Do you care about your privacy? So try this software. It also bypasses face recognition.

Sina Tech (China), Put this 'cloak' on your photos to foil state of the art facial recognition systems

Instalki.pl (Poland), Ten algorytm pozwoli Ci uchronic sie przed systemami rozpoznawania twarzy

Link Estadao (Brazil), Esta ferramenta tenta proteger suas fotos do reconhecimento facial

Manual do Usuario (Brazil), Rodrigo Ghedin: O algoritmo anti-reconhecimento facial

Analytics India, Sejuti Das: Can This AI Filter Protect Human Identities From Facial Recognition System?

News18 (India), Shouvik Das: Privacy vs Facial Recognition: Fawkes Aims to Help Protect Your Public Photos From Misuse

WION News (India), Engineers develop tool called 'Fawkes' to protect online photos from facial recognition

Pttl.gr (Greece), Fawkes: Special free software that 'secures' your photos against face recognition models!

IGuru (Greece), Fawkes: protect your photos from face recognition

Golem.de (Germany), Fawkes soll vor Gesichtserkennung schutzen

Heise Online (Germany), Verzerrungs-Algorithmus Fawkes will Gesichtserkennung verhindern

We Demain, Morgane Russeil-Salvan: Reconnaissance faciale : voici comment y echapper sur les reseaux sociaux

Developpez.com (France), Des chercheurs mettent au point Fawkes, un <> numerique

Asia News Day, Computer engineers develop tool that hopes to protect one's online photos from facial recognition

BundleHaber (Turkey), The Application That Prevents Face Recognition Systems from Recognizing Photos: Fawkes

TechPadi (Africa), Jide Taiwo: Fawkes Digital Image Cloaking Software Could Help Beat Facial Recognition Algorithms

En Segundos (Panama), Esta herramienta podria proteger tus fotografias del reconocimiento facial

TechNews Taiwan, article

KnowTechnie, Ste Knight: You can now prevent your online photos from being used by facial recognition systems

TechXplore, Peter Grad: Image cloaking tool thwarts facial recognition programs

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Limitations

To our users, please note that Fawkes is not a 'silver bullet' for protecting yourself against intrusive facial recognition systems, as our paper clearly states. To be more clear:

Fawkes cannot:

Protect you already-existent facial recognition models. Instead, Fawkes is designed to poison future facial recognition training datasets.

Be future-proof. We do not claim that Fawkes provides you with protection against facial recognition for all time. In fact, the changes we observed in Azure after the release of Fawkes0.3 demonstrate that it cannot.

However, Fawkes can:

Empower individuals to make their personal data less accessible/usable by big tech companies. While Fawkes is not perfect, it provides individuals with recourse they didn’t have before and can provide some protection against unwanted facial recognition.

Catalyze future research which understands and improves upon Fawkes’ strengths and weaknesses. The fight against unwanted facial recognition is far from over. Fawkes is one battlefield in a much-larger war.

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All in all, Fawkes is meant to shift the power dynamic in favor of internet users over intrusive tech companies. We thank you for supporting our tool.

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Frequently Asked Questions

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How effective is Fawkes against 3rd party facial recognition models like ClearView.ai? We have extensive experiments and results in the technical paper (linked above). The short version is that we provide strong protection against unauthorized models. Our tests against state of the art facial recognition models from Microsoft Azure, Amazon Rekognition, and Face++ are at or near 100%. Protection level will vary depending on your willingness to tolerate small tweaks to your photos. Please do remember that this is a research effort first and foremost, and while we are trying hard to produce something useful for privacy-aware Internet users at large, there are likely issues in configuration, usability in the tool itself, and it may not work against all models for all images.

How could this possibly work against DNNs? Aren't they supposed to be smart? This is a popular reaction to Fawkes, and quite reasonable. We hear often in popular press how amazingly powerful DNNs are and the impressive things they can do with large datasets, often detecting patterns where human cannot. Yet the achilles heel for DNNs has been this phenomenon called adversarial examples, small tweaks in inputs that can produce massive differences in how DNNs classify the input. These adversarial examples have been recognized since 2014 (here's one of the first papers on the topic), and numerous defenses have been proposed over the years since (and some of them are from our lab). Turns out they are extremely difficult to remove, and in a way are a fundamental consequence of the imperfect training of DNNs. There have been multiple PhD dissertations written already on the subject, but suffice it to say, this is a fundamentally difficult thing to remove, and many in the research area accept it now as a necessary evil for DNNs. The underlying techniques used by Fawkes draw directly from the same properties that give rise to adversarial examples. Is it possible that DNNs evolve significantly to eliminate this property? It's certainly possible, but we expect that will require a significant change in how DNNs are architected and built. Until then, Fawkes works precisely because of fundamental weaknesses in how DNNs are designed today.

Can't you just apply some filter, or compression, or blurring algorithm, or add some noise to the image to destroy image cloaks? As counterintuitive as this may be, the high level answer is no simple tools work to destroy the perturbation that form image cloaks. To make sense of this, it helps to first understand that Fawkes does not use high-intensity pixels, or rely on bright patterns to distort the classification value of the image in the feature space. It is a precisely computed combination of a number of pixels that do not easily stand out, that produce the distortion in the feature space. If you're interested in seeing some details, we encourage you to take a look at the technical paper (also linked above). In it we present detailed experimental results showing how robust Fawkes is to things like image compression and distortion/noise injection. The quick takeaway is that as you increase the magnitude of these noisy disruptions to the image, protection of image cloaking does fall, but slower than normal image classification accuracy. Translated: Yes, it is possible to add noise and distortions at a high enough level to distort image cloaks. But such distortions will hurt normal classification far more and faster. By the time a distortion is large enough to break cloaking, it has already broken normal image classification and made the image useless for facial recognition.

How is Fawkes different from things like the invisibility cloak projects at UMaryland, led by Tom Goldstein, and other similar efforts? Fawkes works quite differently from these prior efforts, and we believe it is the first practical tool that the average Internet user can make use of. Prior projects like the invisibility cloak project involve users wearing a specially printed patterned sweater, which then prevents the wearer from being recognized by person-detection models. In other cases, the user is asked to wear a printed placard, or a special patterned hat. One fundamental difference is that these approaches can only protect a user when the user is wearing the sweater/hat/placard. Even if users were comfortable wearing these unusual objects in their daily lives, these mechanisms are model-specific, that is, they are specially encoded to prevent detection against a single specific model (in most cases, it is the YOLO model). Someone trying to track you can either use a different model (there are many), or just target users in settings where they can't wear these conspicuous accessories. In contrast, Fawkes is different because it protects users by targeting the model itself. Once you disrupt the model that's trying to track you, the protection is always on no matter where you go or what you wear, and even extends to attempts to identify you from static photos of you taken, shared or sent digitally.

How can Fawkes be useful when there are so many uncloaked, original images of me on social media that I can't take down? Fawkes works by training the unauthorized model to learn about a cluster of your cloaked images in its 'feature space.' If you, like many of us, already have a significant set of public images online, then a model like Clearview.AI has likely already downloaded those images, and used them to learn 'what you look like' as a cluster in its feature space. However, these models are always adding more training data in order to improve their accuracy and keep up with changes in your looks over time. The more cloaked images you 'release,' the larger the cluster of 'cloaked features' will be learned by the model. At some point, when your cloaked cluster of images grows bigger than the cluster of uncloaked images, the tracker's model will switch its definition of you to the new cloaked cluster and abandon the original images as outliers.

Is Fawkes specifically designed as a response to Clearview.ai? It might surprise some to learn that we started the Fawkes project a while before the New York Times article that profiled Clearview.ai in February 2020. Our original goal was to serve as a preventative measure for Internet users to inoculate themselves against the possibility of some third-party, unauthorized model. Imagine our surprise when we learned 3 months into our project that such companies already existed, and had already built up a powerful model trained from massive troves of online photos. It is our belief that Clearview.ai is likely only the (rather large) tip of the iceberg. Fawkes is designed to significantly raise the costs of building and maintaining accurate models for large-scale facial recognition. If we can reduce the accuracy of these models to make them untrustable, or force the model's owners to pay significant per-person costs to maintain accuracy, then we would have largely succeeded. For example, someone carefully examining a large set of photos of a single user might be able to detect that some of them are cloaked. However, that same person is quite possibly capable of identifying the target person in equal or less time using traditional means (without the facial recognition model).

Can Fawkes be used to impersonate someone else? The goal of Fawkes is to avoid identification by someone with access to an unauthorized facial recognition model. While it is possible for Fawkes to make you 'look' like someone else (e.g. 'person X') in the eyes of a recognition model, we would not consider it an impersonation attack, since 'person X' is highly likely to want to avoid identification by the model themselves. If you cloaked an image of yourself before giving it as training data to a legitimate model, the model trainer can simply detect the cloak by asking you for a real-time image, and testing it against your cloaked images in the feature space. The key to detecting cloaking is the 'ground truth' image of you that a legitmate model can obtain, and unauthorized models cannot.

How can I distinguish photos that have been cloaked from those that have not? A big part of the goal of Fawkes is to make cloaking as subtle and undetectable as possible and minimize impact on your photos. Thus it is intentionally difficult to tell cloaked images from the originals. We are looking into adding small markers into the cloak as a way to help users identify cloaked photos. More information to come.

How do I get Fawkes and use it to protect my photos? We are working hard to produce user-friendly versions of Fawkes for use on Mac and Windows platforms. We have some initial binaries for the major platforms (see above). Fawkes is also available as source code, and you can compile it on your own computer. Feel free to report bugs and issues on github, but please bear with us if you have issues with the usability of these binaries. Note that we do not have any plans to release any Fawkes mobile apps, because it requires significant computational power that would be challenging for the most powerful mobile devices.

We are adding more Q&A soon. If you don't see your question here, please email us and we will add it to the page soon.

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Dell Inspiron 13 7000 i7347-7550sLV 13.3" 2 in 1 Notebook-Open Box

Item specifics

Condition: New other (see details) :

A new, unused item with absolutely no signs of wear. The item may be missing the original packaging, or in the original packaging but not sealed. The item may be a factory second or a new, unused item with defects. See the seller’s listing for full details and description of any imperfections. See all condition definitions– opens in a new window or tab

Seller Notes: “Open Box item which includes accessories. Might show minor blemishes and has manufacturer warranty. Where applicable, manuals/software might not be included. This item might be repackaged.”

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MPN:

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Dell Inspiron 13 7000 i7347-7550sLV 13.3″ 2 in 1 Notebook-Open Box

Product Details

Product Information As part of Dell’s 7000 series, this notebook has a 13.3-inch LED-backlit touchscreen display with TrueLife technology that provides you with a brighter wide-angle viewing for easy file and folder navigation. Pan, pinch, and zoom effortlessly around the screen with 10-finger capacitive touch. Precise pointing and gesture recognition provide a fast and responsive performance. The built-in stylus can sketch, take notes, or edit your pictures with incredible precision. Working on the notebook is easy on the eyes as it features the clarity and crispness of full HD 1920 x 1080 resolution.This notebook offers you ultimate versatility as you can switch between different forms whenever you like as the screen can bend to about 360 degrees. Choose between laptop, tent, tablet, or stand modes to get the most out of your computing experience. Whether you need to use the touchscreen or the backlit keyboard, the notebook’s flexible design will easily conform to your needs. Experience excellent wireless connections for high-performance and efficient connectivity as the laptop houses Wi-Fi, Bluetooth 4.0 support, a 2-in-1 SD media card reader, two USB 3.0 ports, and a USB 2.0 port. In addition, the HDMI port easily lets you watch videos and movies on your High-Definition TV set. The notebook gives you multiple ways to transfer your files between devices. It also features FastAccess Facial Recognition for better security protection and an HD webcam for streaming and video conferences.The Dell Inspiron 13 notebook contains a surprising amount of power for its small and compact size. With its 4th generation Intel Core i5-4210U processor and 8GB of DDR3 RAM memory, you can count on having plenty of computing muscle to load apps and high-end software. Moreover, the capable Intel HD Graphics 4400 card will meet the needs of a typical user. Store your content and media with 500GB of storage space on the hybrid hard drive. The Dell Inspiron 13 notebook runs on a 64-bit Windows 8.1 operating system for a pleasant and accessible experience. Thanks to its energy-efficient processors and graphics, you can be assured that your Dell notebook will have a long battery life of up to six hours between charges. This makes it ideal for long commutes or use around the house.Dell computer devices undergo at least 10,000 hours of testing to ensure that they can withstand the wear-and-tear of harsh real-world conditions and the normal duress of everyday life. The hinges on the lid will continue to function properly even after opening and closing the device 20,000 times. Product Identifiers Brand Dell MPN I7347-7550SLV UPC 0884116148449 Model Inspiron 13 eBay Product ID (ePID) 206994037 Product Key Features Color Silver Type Notebook/Laptop Processor Type Intel Core i5 4th Gen. Operating System Windows 8.1 Graphics Processing Type Integrated/On-Board Graphics Additional Product Features Memory 8GB Laptop Type Notebook/Laptop Screen Size 13.3in. Installed Memory 8GB Display Size 13.3in. Hard Drive Capacity 500GB Processor Speed 1.7GHz Hard Drive 500GB

Price : 514.78 Ends on : 1 week

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[nauthfinancialservices-blog]

Worldpay expands real-time payouts to more than 50 countries Worldpay’s dynamic payout solutions combine the enhanced Worldpay Bankout solution, which now delivers 154 direct bank disbursement destinations (up from 65), and Worldpay FastAccess – enabled by Visa The post Worldpay expands real-time payouts to more than 50 countries appeared first on Compelo Banking.

[dineroonline-blog]

Worldpay Incorporated está aumentando su alcance.

Worldpay Incorporated está aumentando su alcance.

Worldpay Incorporated está aumentando su alcance.

Proveedor de pagos electronicos Worldpay Incorporated ha anunciado que sus soluciones de pago en tiempo real de FastAccess y Bankout ahora están a disposición de los usuarios en una selección adicional de países.

Transferir fondos internacionalmente:

El innovador utilizado un comunicado de prensa oficial del miércolespara detallar que los…

[payment-providers]

New Post has been published on Payment-Providers.com

New Post has been published on https://payment-providers.com/visa-vantiv-pair-on-fastaccess-smb-funding/

Visa, Vantiv Pair On FastAccess SMB Funding

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Credit and debit card payments processing company Vantiv and Visa announced news on Thursday that they have jointly debuted FastAccess Funding, which allows merchants to more quickly receive settlement payouts.

FastAccess Funding is the first merchant payment solution available across Vantiv’s push-to-card platform.

In a joint release, Vantiv and Visa said that the settlement time — received by merchants upon funding of debit cards — now takes minutes rather than one to three days, as is typical with ACH processes.

The firms explained that more than one-third of small businesses (SMBs) in the United States say that cash flow management and consistency present a major challenge in day-to-day operations, as noted in research provided by Wasp Barcode Technologies. Vantiv is the first merchant acquirer to speed up the SMB payment process and accelerate B2B disbursements.

Visa’s card-based payment solutions platform is being used to deliver funds in real time to debit cards. The upshot is that cash flow management can be optimized across even weekends and holidays, the companies said.

In a statement, Bill Sheley, head of Global Push Payments at Visa, said that “Visa Direct is a simple, fast and secure real-time payments platform that allows companies to create better payment experiences for their customers. Through this collaboration with Vantiv, small businesses can sign up to receive their earned money when they need it: quickly, and efficiently, with Visa Direct.”

New features will be announced across the next six months, according to the statement.

ACH, B2B, B2B Payments, cash flow management, FastAccess Funding, News, payment solutions, SMB, Vantiv, Visa, visa news

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[precisionload375]

Att Dsl Speed Test

At&t Dsl Speed Test Online

What Speed Is At&t Dsl

Wired Internet

AT&T Internet Speed Test. Using a speed test is a vital tool to determine not only what you’re working with in terms of a connection, but also to determine if you are getting the connection you were promised from your ISP (in this case, AT&T). Use this to compare to other plans, other providers, and average speeds, which we will talk about later. AT&T DSL speed test with 3667 recent results. Compare and test your maximum and average connection speed using our new test.

AT&T Speed TierTypeExpected Speeds††DownloadUploadInternet Basic 768IPBB0.80.4Internet Basic 1.5IPBB1.51Internet Basic 3IPBB31Internet Basic 5IPBB51Internet Basic 6IPBB61Internet 10IPBB101Internet 12IPBB121.5Internet 18IPBB181.5Internet 24IPBB243Internet 25IPBB252Internet 25IPBB255Internet 45IPBB456Internet 50IPBB5010Internet 75IPBB758Internet 75IPBB7520Internet 100IPBB10020Internet 500IPBB500100

AT&T Speed TierTypeExpected Speeds††DownloadUploadInternet 5Fiber55Internet 10Fiber1010Internet 25Fiber2525Internet 50Fiber5050Internet 100Fiber100100Internet 300Fiber300300Internet 500Fiber500500Internet 1000Fiber940940

AT&T Speed TierTypeExpected Speeds††DownloadUploadFastAccess DSL Lite*, Fast Access DSL Direct Lite, High Speed Internet Basic, High Speed Internet Business Edition Basic**, High Speed Internet Business Edition Direct Basic**, FastAccess Business DSL Lite*, FastAccess Business DSL Direct LiteDSL0.7680.256FastAccess DSL Ultra*, Fast Access DSL Direct Ultra, High Speed Internet Express, High Speed Internet Business Edition Express**, High Speed Internet Business Edition Direct Express**, FastAccess Business DSL*, FastAccess Business DSL Direct DSL1.50.256FastAccess DSL Xtreme*, Fast Access DSL Direct Xtreme, High Speed Internet Pro, High Speed Internet Business Edition Pro**, High Speed Internet Business Edition Direct Pro**, FastAccess Business DSL Plus*, FastAccess Business DSL Direct Plus DSL30.384FastAccess DSL XtremePro*, Fast Access DSL Direct XtremePro, High Speed Internet Elite, High Speed Internet Business Edition Elite**, High Speed Internet Business Edition Direct Elite**, FastAccess Business DSL 6.0, FastAccess Business DSL Direct 6.0 DSL60.512

†† Internet speed claims represent maximum network service capabilities. Actual customer speeds may vary based on a number of factors and are not guaranteed. Download and Upload speeds for Internet 1000 typically do not exceed 940 Mbps due to overhead capacity reserved for network management purposes. For more information, go to www.att.com/speed101.

Notes:

IPBB includes ADSL2+, VDSL2, G.Fast and Ethernet technologies delivered over a hybrid of fiber optic and copper facilities which provides subscribers with significantly faster download speeds compared to traditional DSL connections. All speed tiers are asymmetrical or the download/upload speeds are different.

AT&T Fiber is an ultra-fast broadband technology delivered over a fiber optic connection to the premises or to units within certain Multi-Dwelling Units (MDU). All speed tiers are symmetrical or the download/upload speeds are similar

FastAccess DSL' packages are available in: AL, FL, GA, KY, LA, MS, NC, SC and TN

Fixed Wireless Internet

Fixed Wireless services provide qualified households and small businesses with high-speed Internet service via LTE technology, an outdoor antenna and indoor Wi-Fi Gateway

DownloadUploadFixed Wireless Internet(10/1)At least 10MbpsAt least 1Mbps

Notes:

Service performance may be affected by your proximity to a cell site, the capacity of the cell site, the number of other users connected to the same cell site, the surrounding terrain, radio frequency interference, applicable network management practices, and the applications you use.

Is your internet fast enough? Test internet speeds at your location with a single click.

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At&t Dsl Speed Test Online

AT&T Internet

AT&T offers gigabit internet, which means it has download speeds reaching 1,000 Mbps. That speed is fantastic, but it’s available only in select fiber areas. In non-fiber areas, AT&T internet packages come with download speeds varying from 5 Mbps to 100 Mbps.

Don’t worry if your speed test results are slower than the top advertised speed. Internet speeds vary a lot by location, even if you’re paying for top speeds. Just because you don’t have the top advertised speed offered in your area doesn’t mean there’s something wrong with your connection.

Top advertised download speed:

Up to 1000 Mbps

AT&T Avg. Internet Speed Test Results:

Average download speed: 66.44 Mbps

Average latency: 43.67 ms

Total speed tests: 625,662

Fastest Cities for AT&T Internet Service

CityTop advertised download speedAverage download speed*1. Temple, TX1000 Mbps178 Mbps2. Celina, TX1000 Mbps178 Mbps3. Richardson, TX1000 Mbps151 Mbps4. Suwanee, GA1000 Mbps149 Mbps5. Arcadia, CA1000 Mbps149 Mbps

*Average of HighSpeedInternet.com speed test results for AT&T users in each city

AT&T Wireless (Mobile Broadband)

Just like its home internet service, the AT&T mobile broadband network is among the fastest available. At 12 Mbps, AT&T mobile customers get a lot of speed out of their 4G network. And with the AT&T 5G rollout, it will only get faster.

Interference from the weather, tall buildings, or even other wireless signals can cause your mobile broadband speed to fluctuate. If you’re trying to compare your average speed to the speed you’re expecting, test your speed multiple times to get a consistent result.

Top advertised download speed:

Up to 12 Mbps

AT&T Avg. Wireless Speed Test Results:

Average download speed: 26.63 Mbps

Average latency: 6.34 ms

Total speed tests: 214,311

Enter your zip to get speeds and providers available for your area.

Internet Speed Recommendations

The speed you need depends on what you like to do online and how many people use your connection. The more folks in your household, the more bandwidth you’ll need.

These recommendations give you a quick reference on what to shoot for. For a more personalized speed recommendation, use our How Much Speed Do I Need? tool.

1-3 People: 5 Mbps

4 - 6 People: 10 Mbps

1-3 People: 5 Mbps

4 - 6 People: 25 Mbps

1-3 People: 25 Mbps

4 - 6 People: 100 Mbps

1-3 People: SD Video: 10 Mbps HD Video: 50 Mbps

4 - 6 People: SD Video: 50 Mbps HD Video: 100+ Mbps

About our AT&T Internet Speed Test

This AT&T speed test uses nearby servers to deliver the most accurate results possible. Some internet speed tests use servers that are farther away, which can make your latency seem higher than it actually is.

This speed test also includes all the insights you need as an AT&T customer to make meaningful comparisons with your speed test results.

How does the AT&T internet speed test work?

When you start the speed test, it will prompt your computer to download a dummy file. The speed test measures how long your computer takes to download the file through your AT&T internet connection. The size of the file divided by the download time gives you your megabits per second (Mbps). To test upload speed, it does the same thing but in reverse.

The dummy files used during speed tests are small and harmless. Occasionally, security software will flag a dummy file if it’s an unrecognized file type. This will interfere with your test results. If your security software is interfering with your speed test, turn it off for the duration of the test. It’ll be fine. Just remember to turn it back on after the test.

Your connection’s latency is tested by sending a signal, called a ping, to the network server and back. The time required for the ping to make a round-trip is called latency. High latency, sometimes called lag, can interfere with online activities that require real-time reaction, like gaming.

AT&T Internet Speed FAQ

AT&T Fiber vs. AT&T DSL: What’s the difference?

AT&T delivers reliable internet service on both its fiber and DSL packages. While these two internet technologies work very differently, the biggest impact for the end user is speed. Fiber is much faster than DSL, and we recommend getting it if it’s offered in your area. DSL still delivers enough speed for most internet users, but fiber is the superior technology.

What is a good internet download speed?

Generally, you want about 5–10 Mbps per internet user. Bigger households with more people need more bandwidth. However, the things you do on the internet also play a role. For instance, streaming HD video takes a lot more bandwidth than just browsing social media.

The average internet package offered in the US is about 50 Mbps. Most individual internet users won’t need more than that, but whether that’s a good speed for you or not depends on your personal and financial needs.

Use our How Much Speed Do I Need? tool to see what internet speed is right for you.

How many Mbps is 4G LTE?

The average download speed for the 4G LTE networks used by the major wireless providers vary from about 13 Mbps to about 18 Mbps according to our speed test data. That’s plenty of speed for most mobile users, but if you try to use it as your home internet via a hotspot, it’ll probably be too slow for your household.

Expect your mobile internet speeds to fluctuate a lot as you move around. The average download speeds for AT&T, Sprint, T-Mobile, and Verizon are pretty similar, but the actual speed test results will vary across providers. Signal strength depends a lot on where you’re located, which is always changing with a cellphone connection.

How fast is AT&T LTE?

According to our AT&T wireless speed test data, the average AT&T 4G LTE download speed is about 13 Mbps. That’s slightly above the 12 Mbps it advertises.

What Speed Is At&t Dsl

While this looks good, keep in mind that internet speeds fluctuate, especially mobile internet. The 13 Mbps average comes from nearly 13,000 speed tests that ranged from 0 Mbps to 241 Mbps. In short, your AT&T mobile broadband speed will vary widely as you go from place to place but should average out to about 13 Mbps.