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

Other organizations have figured out how to use these very powerful technologies to really gain insights rapidly from their data. What we're really trying to do is to look at that end-to-end journey of data and to build really compelling, powerful capabilities and services at each stop in that data journey and then…knit all that together with strong concepts like governance.

By putting good governance in place about who has access to what data and where you want to be careful within those guardrails that you set up, you can then set people free to be creative and to explore all the data that's available to them. AWS has more than services now. Have you hit the peak for that or can you sustain that growth? We're not done building yet, and I don't know when we ever will be. We continue to both release new services because customers need them and they ask us for them and, at the same time, we've put tremendous effort into adding new capabilities inside of the existing services that we've already built.

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

Do customers still want those fundamental building blocks and to piece them together themselves, or do they just want AWS to take care of all that? There's no one-size-fits-all solution to what customers want. It is interesting, and I will say somewhat surprising to me, how much basic capabilities, such as price performance of compute, are still absolutely vital to our customers.

But it's absolutely vital. Part of that is because of the size of datasets and because of the machine learning capabilities which are now being created. They require vast amounts of compute, but nobody will be able to do that compute unless we keep dramatically improving the price performance. We also absolutely have more and more customers who want to interact with AWS at a higher level of abstraction…more at the application layer or broader solutions, and we're putting a lot of energy, a lot of resources, into a number of higher-level solutions.

One of the biggest of those … is Amazon Connect, which is our contact center solution. In minutes or hours or days, you can be up and running with a contact center in the cloud. At the beginning of the pandemic, Barclays … sent all their agents home.

In something like 10 days, they got 6, agents up and running on Amazon Connect so they could continue servicing their end customers with customer service.

We've built a lot of sophisticated capabilities that are machine learning-based inside of Connect. We can do call transcription, so that supervisors can help with training agents and services that extract meaning and themes out of those calls. We don't talk about the primitive capabilities that power that, we just talk about the capabilities to transcribe calls and to extract meaning from the calls.

It's really important that we provide solutions for customers at all levels of the stack. Given the economic challenges that customers are facing, how is AWS ensuring that enterprises are getting better returns on their cloud investments?

Now's the time to lean into the cloud more than ever, precisely because of the uncertainty. We saw it during the pandemic in early , and we're seeing it again now, which is, the benefits of the cloud only magnify in times of uncertainty.

For example, the one thing which many companies do in challenging economic times is to cut capital expense. For most companies, the cloud represents operating expense, not capital expense. You're not buying servers, you're basically paying per unit of time or unit of storage. That provides tremendous flexibility for many companies who just don't have the CapEx in their budgets to still be able to get important, innovation-driving projects done.

Another huge benefit of the cloud is the flexibility that it provides — the elasticity, the ability to dramatically raise or dramatically shrink the amount of resources that are consumed. You can only imagine if a company was in their own data centers, how hard that would have been to grow that quickly. The ability to dramatically grow or dramatically shrink your IT spend essentially is a unique feature of the cloud.

These kinds of challenging times are exactly when you want to prepare yourself to be the innovators … to reinvigorate and reinvest and drive growth forward again.

We've seen so many customers who have prepared themselves, are using AWS, and then when a challenge hits, are actually able to accelerate because they've got competitors who are not as prepared, or there's a new opportunity that they spot.

We see a lot of customers actually leaning into their cloud journeys during these uncertain economic times. Do you still push multi-year contracts, and when there's times like this, do customers have the ability to renegotiate? Many are rapidly accelerating their journey to the cloud. Some customers are doing some belt-tightening. What we see a lot of is folks just being really focused on optimizing their resources, making sure that they're shutting down resources which they're not consuming.

You do see some discretionary projects which are being not canceled, but pushed out. Every customer is free to make that choice. But of course, many of our larger customers want to make longer-term commitments, want to have a deeper relationship with us, want the economics that come with that commitment.

We're signing more long-term commitments than ever these days. We provide incredible value for our customers, which is what they care about. That kind of analysis would not be feasible, you wouldn't even be able to do that for most companies, on their own premises. So some of these workloads just become better, become very powerful cost-savings mechanisms, really only possible with advanced analytics that you can run in the cloud.

In other cases, just the fact that we have things like our Graviton processors and … run such large capabilities across multiple customers, our use of resources is so much more efficient than others. We are of significant enough scale that we, of course, have good purchasing economics of things like bandwidth and energy and so forth. So, in general, there's significant cost savings by running on AWS, and that's what our customers are focused on.

The margins of our business are going to … fluctuate up and down quarter to quarter. It will depend on what capital projects we've spent on that quarter. Obviously, energy prices are high at the moment, and so there are some quarters that are puts, other quarters there are takes.

The important thing for our customers is the value we provide them compared to what they're used to. And those benefits have been dramatic for years, as evidenced by the customers' adoption of AWS and the fact that we're still growing at the rate we are given the size business that we are. That adoption speaks louder than any other voice. Do you anticipate a higher percentage of customer workloads moving back on premises than you maybe would have three years ago? Absolutely not. We're a big enough business, if you asked me have you ever seen X, I could probably find one of anything, but the absolute dominant trend is customers dramatically accelerating their move to the cloud.

Moving internal enterprise IT workloads like SAP to the cloud, that's a big trend. Creating new analytics capabilities that many times didn't even exist before and running those in the cloud. More startups than ever are building innovative new businesses in AWS. Our public-sector business continues to grow, serving both federal as well as state and local and educational institutions around the world.

It really is still day one. The opportunity is still very much in front of us, very much in front of our customers, and they continue to see that opportunity and to move rapidly to the cloud. In general, when we look across our worldwide customer base, we see time after time that the most innovation and the most efficient cost structure happens when customers choose one provider, when they're running predominantly on AWS. A lot of benefits of scale for our customers, including the expertise that they develop on learning one stack and really getting expert, rather than dividing up their expertise and having to go back to basics on the next parallel stack.

That being said, many customers are in a hybrid state, where they run IT in different environments. In some cases, that's by choice; in other cases, it's due to acquisitions, like buying companies and inherited technology. We understand and embrace the fact that it's a messy world in IT, and that many of our customers for years are going to have some of their resources on premises, some on AWS.

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

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

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

We've built a lot of industrial services like IoT services for industrial settings, for example, to monitor industrial equipment to understand when it needs preventive maintenance.

We have a lot of capabilities we're building that are either for … horizontal use cases like Amazon Connect or industry verticals like automotive, healthcare, financial services. We see more and more demand for those, and Dilip has come in to really coalesce a lot of teams' capabilities, who will be focusing on those areas.

You can expect to see us invest significantly in those areas and to come out with some really exciting innovations. Would that include going into CRM or ERP or other higher-level, run-your-business applications?

I don't think we have immediate plans in those particular areas, but as we've always said, we're going to be completely guided by our customers, and we'll go where our customers tell us it's most important to go next. It's always been our north star. Correction: This story was updated Nov. Bennett Richardson bennettrich is the president of Protocol.

Prior to joining Protocol in , Bennett was executive director of global strategic partnerships at POLITICO, where he led strategic growth efforts including POLITICO's European expansion in Brussels and POLITICO's creative agency POLITICO Focus during his six years with the company. Prior to POLITICO, Bennett was co-founder and CMO of Hinge, the mobile dating company recently acquired by Match Group.

Bennett began his career in digital and social brand marketing working with major brands across tech, energy, and health care at leading marketing and communications agencies including Edelman and GMMB. Bennett is originally from Portland, Maine, and received his bachelor's degree from Colgate University.

Prior to joining Protocol in , he worked on the business desk at The New York Times, where he edited the DealBook newsletter and wrote Bits, the weekly tech newsletter. He has previously worked at MIT Technology Review, Gizmodo, and New Scientist, and has held lectureships at the University of Oxford and Imperial College London.

He also holds a doctorate in engineering from the University of Oxford. We launched Protocol in February to cover the evolving power center of tech. It is with deep sadness that just under three years later, we are winding down the publication.

As of today, we will not publish any more stories. All of our newsletters, apart from our flagship, Source Code, will no longer be sent. Source Code will be published and sent for the next few weeks, but it will also close down in December. Building this publication has not been easy; as with any small startup organization, it has often been chaotic.

But it has also been hugely fulfilling for those involved. We could not be prouder of, or more grateful to, the team we have assembled here over the last three years to build the publication. They are an inspirational group of people who have gone above and beyond, week after week.

Today, we thank them deeply for all the work they have done. We also thank you, our readers, for subscribing to our newsletters and reading our stories. We hope you have enjoyed our work. As companies expand their use of AI beyond running just a few machine learning models, and as larger enterprises go from deploying hundreds of models to thousands and even millions of models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

As companies expand their use of AI beyond running just a few machine learning models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems. Kate Kaye is an award-winning multimedia reporter digging deep and telling print, digital and audio stories. She covers AI and data for Protocol. Her reporting on AI and tech ethics issues has been published in OneZero, Fast Company, MIT Technology Review, CityLab, Ad Age and Digiday and heard on NPR.

Kate is the creator of RedTailMedia. org and is the author of "Campaign ' A Turning Point for Digital Media," a book about how the presidential campaigns used digital media and data.

On any given day, Lily AI runs hundreds of machine learning models using computer vision and natural language processing that are customized for its retail and ecommerce clients to make website product recommendations, forecast demand, and plan merchandising.

And he said that while some MLops systems can manage a larger number of models, they might not have desired features such as robust data visualization capabilities or the ability to work on premises rather than in cloud environments. As companies expand their use of AI beyond running just a few ML models, and as larger enterprises go from deploying hundreds of models to thousands and even millions of models, many machine learning practitioners Protocol interviewed for this story say that they have yet to find what they need from prepackaged MLops systems.

Companies hawking MLops platforms for building and managing machine learning models include tech giants like Amazon, Google, Microsoft, and IBM and lesser-known vendors such as Comet, Cloudera, DataRobot, and Domino Data Lab. It's actually a complex problem. Intuit also has constructed its own systems for building and monitoring the immense number of ML models it has in production, including models that are customized for each of its QuickBooks software customers.

The model must recognize those distinctions. For instance, Hollman said the company built an ML feature management platform from the ground up. For companies that have been forced to go DIY, building these platforms themselves does not always require forging parts from raw materials. DBS has incorporated open-source tools for coding and application security purposes such as Nexus, Jenkins, Bitbucket, and Confluence to ensure the smooth integration and delivery of ML models, Gupta said.

Intuit has also used open-source tools or components sold by vendors to improve existing in-house systems or solve a particular problem, Hollman said. However, he emphasized the need to be selective about which route to take. I think that the best AI will be a build plus buy. However, creating consistency through the ML lifecycle from model training to deployment to monitoring becomes increasingly difficult as companies cobble together open-source or vendor-built machine learning components, said John Thomas, vice president and distinguished engineer at IBM.

The reality is most people are not there, so you have a whole bunch of different tools. Companies struggling to find suitable off-the-shelf MLops platforms are up against another major challenge, too: finding engineering talent.

Many companies do not have software engineers on staff with the level of expertise necessary to architect systems that can handle large numbers of models or accommodate millions of split-second decision requests, said Abhishek Gupta, founder and principal researcher at Montreal AI Ethics Institute and senior responsible AI leader and expert at Boston Consulting Group.

For one thing, smaller companies are competing for talent against big tech firms that offer higher salaries and better resources. For companies with less-advanced AI operations, shopping at the existing MLops platform marketplace may be good enough, Hollman said. To give you the best possible experience, this site uses cookies.

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White House. Electric Vehicles. Power Index. Special Reports. Tech Calendar. Sign Up. About Protocol. The CFPB may be facing its most significant legal threat yet. The 5th Circuit ruling can have a major impact on the Consumer Financial Protection Bureau. Ryan Deffenbaugh is a reporter at Protocol focused on fintech. Before joining Protocol, he reported on New York's technology industry for Crain's New York Business. He is based in New York and can be reached at rdeffenbaugh protocol.

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November 14, The Financial Technology Association FTA represents industry leaders shaping the future of finance. We champion the power of technology-centered financial services and advocate for the modernization of financial regulation to support inclusion and responsible innovation. Penny Lee, Chief Executive Officer, Financial Technology Association. sponsored sponsored content. amazon web services. aws amazon web services cloud computing analytics data analytics adam selipsky. Toggles debug output in Ansible.

This is very verbose and can hinder multiprocessing. Users may need to change this in rare instances when shell usage is constrained, but in most cases it may be left as is. If not set, it will fallback to the default from the ansible. This does not affect user defined tasks that use the ansible. setup module. The real action being created by the implicit task is currently ansible.

setup for POSIX systems but other platforms might have different defaults. setup actions. This option controls if notified handlers run on a host even if a failure occurs on that host. When false, the handlers will not run if a failure has occurred on a host. This can also be set per play or on the command line. See Handlers and Failure for more details. See the module documentation for specifics. It does not apply to user defined ansible. setup tasks. Set the timeout in seconds for the implicit fact gathering, see the module documentation for specifics.

This setting controls the default policy of fact gathering facts discovered about remote systems. This option can be useful for those wishing to save fact gathering time. each new host that has no facts discovered will be scanned, but if the same host is addressed in multiple plays it will not be contacted again in the run.

This setting controls how duplicate definitions of dictionary variables aka hash, map, associative array are handled in Ansible. This does not affect variables whose values are scalars integers, strings or arrays. WARNING , changing this setting is not recommended as this is fragile and makes your content plays, roles, collections non portable, leading to continual confusion and misuse.

We recommend avoiding reusing variable names and relying on the combine filter and vars and varnames lookups to create merged versions of the individual variables. In our experience this is rarely really needed and a sign that too much complexity has been introduced into the data structures and plays.

Most users of this setting are only interested in inventory scope, but the setting itself affects all sources and makes debugging even harder. All playbooks and roles in the official examples repos assume the default for this setting. Changing the setting to merge applies across variable sources, but many sources will internally still overwrite the variables. It is the intention of the Ansible developers to eventually deprecate and remove this setting, but it is being kept as some users do heavily rely on it.

Any variable that is defined more than once is overwritten using the order from variable precedence rules highest wins. Any dictionary variable will be recursively merged with new definitions across the different variable definition sources. This sets the interval in seconds of Ansible internal processes polling each other. Lower values improve performance with large playbooks at the expense of extra CPU load.

Higher values are more suitable for Ansible usage in automation scenarios, when UI responsiveness is not required but CPU usage might be a concern.

This is a developer-specific feature that allows enabling additional Jinja2 extensions. See the Jinja2 documentation for details. This setting causes libvirt to connect to lxc containers by passing —noseclabel to virsh.

This is necessary when running on systems which do not have SELinux. This may be used to log activity from the command line, send notifications, and so on. Callback plugins are always loaded for ansible-playbook. This is only relevant for those two modules. Ansible managed. This sets the default arguments to pass to the ansible adhoc binary if no -a is specified.

Module to use with the ansible AdHoc command, if none is specified via -m. Colon separated paths in which Ansible will search for Module utils files, which are shared by modules. Toggle Ansible logging to syslog on the target when it executes tasks. On Windows hosts this will disable a newer style PowerShell modules from writing to the event log.

For asynchronous tasks in Ansible covered in Asynchronous Actions and Polling , this is how often to check back on the status of those tasks when an explicit poll interval is not supplied. The default is a reasonably moderate 15 seconds which is a tradeoff between checking in frequently and providing a quick turnaround when something may have completed. Option for connections using a certificate or key file to authenticate, rather than an agent or passwords, you can set the default value here to avoid re-specifying —private-key with every invocation.

Makes role variables inaccessible from other roles. This was introduced as a way to reset role variables to default values if a role is used more than once in a playbook. Data corruption may occur and writes are not always verified when a filesystem is in the list. fuse, nfs, vboxsf, ramfs, 9p, vfat. Set the main callback used to display Ansible output. You can only have one at a time.

You can have many other callbacks, but just one can be in charge of stdout. See Callback plugins for a list of available options. When True, this causes ansible templating to fail steps that reference variable names that are likely typoed.

The —encrypt-vault-id cli option overrides the configured value. A list of vault-ids to use by default. Equivalent to multiple —vault-id args. Vault-ids are tried in order. The vault password file to use.

Equivalent to —vault-password-file or —vault-id If executable, it will be run and the resulting stdout will be used as the password. Sets the default verbosity, equivalent to the number of -v passed in the command line. Normally ansible-playbook will print a header for each task that is run. These headers will contain the name: field from the task if you specified one. Sometimes you run many of the same action and so you want more information about the task to differentiate it from others of the same action.

This setting defaults to False because there is a chance that you have sensitive values in your parameters and you do not want those to be printed. for more information. By default Ansible will issue a warning when a duplicate dict key is encountered in YAML. These warnings can be silenced by adjusting this setting to False. Whether or not to enable the task debugger, this previously was done as a strategy plugin. Now all strategy plugins can inherit this behavior.

The debugger defaults to activating when a task is failed on unreachable. Use the debugger keyword for more flexibility. The directory that stores cached responses from a Galaxy server. This is only used by the ansible-galaxy collection install and download commands.

Cache files inside this dir will be ignored if they are world writable. Collection skeleton directory to use as a template for the init action in ansible-galaxy collection , same as --collection-skeleton. Some steps in ansible-galaxy display a progress wheel which can cause issues on certain displays or when outputing the stdout to a file. This config option controls whether the display wheel is shown or not.

The default is to show the display wheel if stdout has a tty. Configure the keyring used for GPG signature verification during collection installation and verification.

If set to yes, ansible-galaxy will not validate TLS certificates. This can be useful for testing against a server with a self-signed certificate. A list of GPG status codes to ignore during GPG signature verification. The number of signatures that must be successful during GPG signature verification while installing or verifying collections. This should be a positive integer or all to indicate all signatures must successfully validate the collection.

A list of Galaxy servers to use when installing a collection. See Configuring the ansible-galaxy client for more details on how to define a Galaxy server. The order of servers in this list is used to as the order in which a collection is resolved. This setting changes the behaviour of mismatched host patterns, it allows you to force a fatal error, a warning or just ignore it. Path to the Python interpreter to be used for module execution on remote targets, or an automatic discovery mode. All discovery modes employ a lookup table to use the included system Python on distributions known to include one , falling back to a fixed ordered list of well-known Python interpreter locations if a platform-specific default is not available.

The fallback behavior will issue a warning that the interpreter should be set explicitly since interpreters installed later may change which one is used. Toggle to turn on inventory caching. This setting has been moved to the individual inventory plugins as a plugin option Inventory plugins.

The existing configuration settings are still accepted with the inventory plugin adding additional options from inventory configuration. This message will be removed in 2. The plugin for caching inventory. The existing configuration settings are still accepted with the inventory plugin adding additional options from inventory and fact cache configuration. The inventory cache connection. The table prefix for the cache plugin. Expiration timeout for the inventory cache plugin data.

orig', '. ini', '. cfg', '. retry' }}.

Just after a. on Sept. An aquarium in Berlin that was home to around 1, exotic fish burst early on Friday, prompting aro.. A quick look at using our MEME generator here on Itemfix You can find the meme generator here: www.

Taking a look at the text to speech engine on ItemFix. Let's see what you can do with it! You can find the text to speech tool here: www. Learn how to use the "It was at this moment Perfect for accidents, stupidity, marriage proposals and more! For this tutorial we use two different templates to create a short tutorial using two video clips and some assets.

Here we take a look at using the Video to GIF template allowing you to create animated GIFs from video clips to use everywhere. video item. Truck loses control Brakes failure Girls safe Vehicles Accident. By: SkyBlueJack Man with fire motorcycle. Driver over speeding car Highway car over speeding Suspect taken over dose Suspect arrested. By: ThisIsButter1 By: brrrtmn What is ItemFix?

Let's look at what you can do with ItemFix. Tutorial: ItemFix Meme Generator A quick look at using our MEME generator here on Itemfix You can find the meme generator here: www. Tutorial: Text to Speech Taking a look at the text to speech engine on ItemFix. It was at this moment a meme tutorial Learn how to use the "It was at this moment ItemFix Tutorial - Short compilation For this tutorial we use two different templates to create a short tutorial using two video clips and some assets. Video to GIF tutorial Here we take a look at using the Video to GIF template allowing you to create animated GIFs from video clips to use everywhere.

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Elizabeth Warren, who oversaw the CFPB's creation , responded to the ruling on Twitter, writing that "extreme right-wing judges are throwing into question every rule the CFPB enforces to protect consumers and businesses alike. For instance: some basic default values Slices indices have useful defaults. This is a copy of the options available from our release, your local install might have extra options due to additional plugins, you can use the command line utility mentioned above ansible-config to browse through those. These are among the key findings of a statewide survey on state and national issues conducted from October 14 to 23 by the Public Policy Institute of California:. This lets you use transpilers other than Babel, and it gives you greater control over the process.

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