Whether it’s pocket-sized mobile communicators, cars that can drive themselves or a global information-sharing network, scientists and researchers have a history of turning the marvels of technology dreamed up by science fiction writers into reality – and the composer of that endeavour is the creation of artificial intelligence.

Although we’re still some way from being served by self-aware robot butlers that can reliably pass the Turing test, AI technology has progressed immeasurably in the last decade alone. AI has moved from being the sole province of research projects working with giant supercomputers to something that all of us carry around in our pockets, and cloud computing has been a huge part of that move from research to reality.

The most foundational change came when public cloud offerings like Amazon Web Services and Google Cloud Platform became widely available. The development of AI using methods such as, deep-learning and neural networks requires a considerable amount of compute power. Once it became possible to rent as many servers as you needed from a cloud provider, tasks that were once only possible by universities and science labs suddenly became accessible to everyone.

Moreover, these servers take advantage of best-in-class hardware from Intel, featuring technical developments specifically designed to enable AI. For example, high-performance Xeon Scalable chips and low-latency Optane Memory. On top of this, many cloud platform providers have, in recent years, started to specifically cater to machine learning and AI development, offering servers and services tailored to make training deep-learning models quicker and easier than ever.

As these barriers to entry come down, companies and hobbyists around the world have started experimenting with machine learning and AI, exploring the possibilities and pushing the boundaries of what it can do. Much of this research has been shared with the wider community under open source licenses. A key example of is TensorFlow™, a machine learning library developed internally by Google and shared freely with the rest of the world.

Alongside the compute power to train deep-learning models, the cloud has also provided the datasets on which to train them. The development of AI has gone hand in hand with the big data boom, as companies start gathering and storing exponentially more data for analytical purposes. A side effect of this is that there are now huge corpuses of data that can be fed into machine learning models in order to train them in tasks like pattern recognition, clustering and regression.

All of this makes it much easier to improve and develop AI technology, but there’s one key reason that it’s now a legitimate business tool rather than simply a technical endeavour, and that’s the ease of consumption that cloud models offer. It’s so much easier for customers and end-users to consume AI tools running in the cloud as part of a SaaS application compared to traditional on-premise software.

None of the processing is done locally, so there’s no hardware requirements, and because the vendor is responsible for maintaining the AI on a day-to-day basis, there’s no need to hire machine learning or AI specialists. With no extra effort or investment required, companies are becoming more and more comfortable with the idea of integrating AI processes into their day-to-day workflows.

The general public has also grown increasingly familiar with AI technology thanks to the growing prevalence of AI-powered digital assistants like Siri, Alexa and Cortana. These services have helped acclimatise people to working with AI, as well as opening their eyes to the benefits offered by the technology.

These factors have made developing commercial AI more viable, resulting in an explosion of AI-enabled tools and services, many of which have been snapped up by cloud giants like Google and Salesforce and integrated into their product portfolios. Most cloud storage companies, for instance, augment their search capabilities by using machine vision algorithms to accurately identify objects in photographs or text in documents.

AI is also increasingly being used by companies as an initial point of contact for customer service, with chatbots handling Tier One support queries and sales inquiries. A far cry from the long-established automated telephone menus, these programs are intelligent and responsive, and are becoming increasingly common.

It’s not just public clouds that have spurred AI advancements; private and hybrid cloud deployments have also seen a great deal of change. Banking is one area where AI can have a huge impact in terms of analysing huge quantities of data very quickly, but for regulatory reasons, financial firms often can’t – or won’t – use public cloud providers. Instead, these institutions use private clouds to run custom-built or specially-adapted machine learning algorithms to sort through their data.

Intel’s advancements in processor technology have brought cloud-scale computing power within the reach of companies operating their own private cloud, meaning that you no longer need a sizeable data centre to run machine learning applications. Instead, you can run AI tasks on as little as one rack, depending on the size of the deployment. This enables you to keep total control of your data and infrastructure, whilst still taking advantage of cloud-style consumption and delivery models.

In the comparatively short timeframe that cloud computing has been a mainstream phenomenon, AI has gone from being the preserve of academics to a day-to-day reality for businesses around the world; used to perform all kinds of diverse tasks from data analysis to customer service. Machine learning applications are now being developed, deployed and delivered via cloud platforms, empowered and enabled by Intel’s next generation data centre technologies. Whether you’re looking to run your AI applications on a public, private, virtual private or hybrid cloud, Intel is making your AI smarter, stronger and faster than ever before.

Discover more about cloud innovations at Intel.co.uk

Whether it’s making a credit card purchase, messaging your friends or even simply ordering a pizza, virtually all of the things we do on a daily basis are powered and supported by data centres.

But the data centres we rely on today are a far cry from the technology of the past; they’ve changed almost immeasurably since digital computing took its first early steps in the 1950s and ‘60s. Processing power and capacity have increased exponentially over the years and the infrastructure needed to support modern applications has grown ever more complex.

These advances have been driven by the growing demands of both businesses and consumers. First, the birth of the internet led to an explosion in the amount of people consuming online services, which necessitated vast increases in the amount of processing power and capacity that data centres had to offer.

Before long, the need for server capacity spawned the creation of third-party providers, who would host companies’ servers in their own facility, thus removing the initial expense and ongoing overheads of setting up an on-premise data centre for companies. Eventually, as network technology and connectivity improved, this gave way to the cloud computing model where companies rent space not in a data centre, but on the server itself.

Cloud computing has been a major catalyst for change in the data centre; not only have many operating models fundamentally shifted as a result as a result of its rise, but it’s also driven technological advancements like multi-tenant systems, lightning-fast storage and AI applications.

Processing

One of the most foundational changes in data centre technology was the advent of multi-core processors around the turn of the millennium. By fitting two or more processing cores onto a single die, chip manufacturers could radically boost the total performance of data centre hardware, allowing the same workloads to be run with fewer machines.

Multi-core processing also brought huge advantages to virtualisation, which has been a linchpin of the data centre’s growth. Because each processing core runs in parallel with the others, multi-core systems can run huge amounts of virtual machines simultaneously with minimal drops in performance, vastly increasing the amount of applications that can be run at once.

Containerisation has had a similar impact; each VM can host multiple containers within it, each of which can host its own application. This allows data centres to exponentially multiply their capacity for applications. As well as spearheading the continued advancement of multi-core processing, Intel has also been a leader in developing virtualisation and container technology, working with engineering partners to make containers and VMs lighter, faster and more resilient.

Cooling

Data centre equipment is highly powerful, but all that power generates large amounts of heat. Unfortunately, server processors are highly sensitive, and need to be kept below a certain temperature in order to ensure optimal performance. In order to maintain this, data centres have to be very carefully climate-controlled, relying on complex and expensive cooling systems that are often the second-largest consumers of power.

While these cooling systems are still very necessary, Intel’s continued advancement in processor technology has made server processors more thermally efficient, generating less heat and therefore requiring less cooling. On top of that, the company also introduced sensors to its server chips in 2011 which allow data centre administrators to measure the temperature and airflow within a data centre. This enables them to better identify hot and cold spots, modelling the placement of new racks and equipment according to temperature conditions.

Along with preventing costly outages, increasing thermal efficiency throughout the data centre also prolongs the lifespan of the servers themselves and reduces the amount of overall cooling necessary, thereby saving administrators money in terms of the substantial operational costs incurred by cooling efforts.

Power

Intel has also steadily improved the power efficiency of its data centre products. Newer chips like its Xeon Scalable range offer greater performance than previous generations, while consuming less electricity. As with improved cooling performance, this saves data centre operators money in operational costs, but it also allows more chips to be packed into the same physical space.

This means that companies can eke more computational power out of the same resources, without needing to invest in more cabinets, increased power consumption or more cooling. Space efficiency is a key concern, too; floor space within a data centre is often in high demand, so the more physical components that can be packed into a single rack, the better.

Storage

The move from traditional spinning-platter HDDs to SSDs was a huge leap forward in this regard, as it meant that storage drives could take up much less space inside a server, albeit at a higher cost. SSDs were also much faster than HDDs at accessing the data stored on them, greatly speeding up overall server operations and enabling much faster performance for tasks like data analytics.

Intel has been instrumental in advancing storage technology through its partnership with Micron, which involved introducing data striping for increased performance and pioneering high-reliability enterprise drives. It also led the workgroup that developed NVMe technology and, more recently, co-developed 3D Xpoint memory technology, which offers unparalleled speeds for low-latency workloads. You may be familiar with Intel’s Optane range of memory and storage products, all of which are powered by 3D Xpoint.

The end result of all of these numerous changes, developments and advancements has been modern data centres, which are capable of supporting complex, cloud-native workloads. Gone are the days of monolithic mainframes supporting single applications; now, data centres play host to hundreds upon hundreds of sophisticated, multi-core, multi-processor servers, each making use of advanced software-defined networking and low-latency solid state storage drives to power millions of simultaneous applications and processes.

Intel has been at the heart of this change for decades, drawing on its engineering heritage and world-class research expertise to push the boundaries of what data centres are capable of. Whether it’s Optane storage technology, high-performance Xeon Platinum processors or the intelligent software supporting virtualised and containerised applications, Intel remains at the bleeding edge of enterprise processing technology.

Discover more about data storage innovations at Intel.co.uk

Salesforce has unveiled a suite of new Einstein features that will enable developers to custom build AI integrations and machine learning into their apps without labouring over code.

The Einstein Platform Services platform has been enhanced to offer developers more advanced tools, including the drag and drop Einstein Translation feature that can translate any object or field seamlessly.

For example, if a business is dealing with a customer whose native language doesn’t match the operator’s language set, they can be re-routed automatically to a staff member that can communicate in the caller’s native tongue.

Einstein Optical Character Recognition reads documents and autonomously updates the records in Salesforce, saving vital resources that are sometimes wasted on such time-consuming tasks, while Einstein Prediction Builder makes use of Einstein’s powerful prediction capabilities, helping admins build AI models on Salesforce fields or objects.

With Einstein Predictions Service, admins are also able to embed these predictions into third-party systems, whether ERP apps, HR apps or other platforms that need a predictive analytics boost. For example, if Einstein predicts that employees are feeling dissatisfied in the workplace, these predictions can be absorbed into a business’s talent management platform to help advise a future retention strategy.

“The promise of AI is no longer reserved for data scientists. With Einstein, we are empowering developers and admins — the lifeblood of every Salesforce deployment — to make customizable AI a reality for their business,” said John Ball, EVP and general manager at Salesforce Einstein.

“But our mission goes beyond just making the technology more accessible, we are committed to democratizing AI that people can trust and use appropriately.”

Epicor has built on its partnership with Microsoft Azure to roll out major artificial intelligence (AI) and Internet of Things (IoT) enhancements to its suite of enterprise resource planning (ERP) tools.

Manufacturers and distributors will benefit from upgrades to the company’s Epicor ERP and Prophet 21 platforms respectively, powered by closer integration with Microsoft’s Azure cloud platform almost a year after this partnership was first announced.

Details of both releases were outlined by Epicor’s chief product and technology officer Himanshu Palsule at the company’s annual Insights customer conference, hosted this year at Mandalay Bay, Las Vegas.

In particular, this Azure base layer will power the company’s digital assistant Epicor Virtual Agent (EVA), as well as render better connectivity between people and smart machines in the firm’s Epicor ERP platform for manufacturers.

«We’ve made great progress in moving many of you onto the Azure platform,» Palsule said during his keynote address. «And as you saw with EVA and the connected enterprise, we have now started using the platform elements of Azure.

«We’ve started using the service levels, service fabric and the IoT Hub and other parts of that. And that’s always been our strategy.»

Improvements to the manufacturer-centric Epicor ERP platform sees a host of tools such as AI and analytics integrate with the system to enhance the company’s vision for a ‘connected enterprise’.

The Epicor IoT module, in particular, will connect smart machines across the manufacturing floor to Microsoft’s Azure IoT Hub, with data pulled directly from sensors and visualised on the ERP home page.

Meanwhile, the Prophet 21 web-based app, targeted at distributors, is encouraging its customers to embrace the public cloud to transform their business processes.

This app was recently ported onto the public cloud in its entirety, with software engineers telling Cloud Pro the most exciting part of the shift is customers’ newfound ability to use the product on any device, from tablets to iMacs.

The latest releases of Epicor’s ERP tools for manufacturers and distributors make steps towards realising ambitions set out last year, when the strategic partnership was first outlined last year.

As to where the company aims to take this in the future, Palsule told the press at a Q&A following the keynote that customers whose own platforms are tied to Azure will in future be able to draw additional benefits.

He also outlined how the partnership would work in practice, and address concerns around security, saying the firm resisted any temptation of trying to solve it themselves.

«The way it works is you get the machines communicate with the IoT Hub, the IoT Hub has a certain restriction on security protocols. Then that data then goes into ERP and communicates back,» said Palsule.

«Everything that we’re doing follows the standard Microsoft protocols so we are relying heavily on this partnership to give us security.»

Meanwhile, for Microsoft, the company sees this partnership as the perfect marriage between the underlying cloud infrastructure and the niche expertise that a partner in the mould of Epicor can offer.

«We got our engineering teams together we sat down, and ultimately worked out all the architectural designs,» Microsoft’s partner director for global ISV alliances and business development Don Woods told Cloud Pro.

«We put the ERP into Azure, and then started going to customers and said ‘look, you want to get into the cloud? Epicor’s moving into the cloud. It’s going to SaaS. You want to benefit from all this? Join us in that movement’.

«And Epicor wanted to make sure that the customers had that capability, because that’s where it’s going.»

Microsoft has vowed to “do more” to cut down the company’s carbon footprint and its latest initiative is to double its internal carbon fee to $15 per metric ton on all carbon emissions, making its departments accountable for cutting emissions.

It means that each departments’ emissions will be continuously scrutinised and budget must be set aside for the tax. The money raised from this penalty will be re-injected into the company’s carbon neutrality efforts and fund new tech initiatives to boost sustainability.

Some of these funded projects include the development of sustainable campuses and data centres, including its HQs in Washington and Redmond.

“In practice, this means we’ll continue to keep our house in order and improve it, while increasingly addressing sustainability challenges around the globe by engaging our strongest assets as a company – our employees and our technologies,” said Microsoft president Brad Smith.

Microsoft will invest in sustainability data research, analysing information to advise scientists about the state of the planet via schemes such as the AI For Earth Programme.

The Redmond company said it’s going to help its customers build more sustainable futures too, helping them identify how they can be more conscious of the environment and helping them build and reach their own carbon footprint targets.

Finally, the company will push for change. Microsoft announced it’s joined the Climate Leadership Council to help identify and drive forward worldwide initiatives to save our planet.

“Addressing these global environmental challenges is a big task,” Smith added. “Meeting this raised ambition will take the work of everyone across Microsoft, as well as partnerships with our customers, policymakers and organizations around the world. This road map is far from complete, but it’s a first step in our renewed commitment to sustainability.”

There may be a wealth of backup solutions aimed at securing virtualized environments but many offer this as an additional feature, so SMEs may find themselves paying through the nose for excess baggage. Not so with Altaro VM Backup: this software product is designed from the ground up to protect VMware and Hyper-V VMs (virtual machines).

Another bonus is its pricing structure, because unlike many products that use the number of sockets or CPUs, Altaro bases costs purely on the number of hosts. The Standard edition starts at a mere £445 per host and this allows you to schedule backups for up to five VMs per host.

The Unlimited edition begins at £545 and, unsurprisingly, supports unlimited VMs per host but also enables high-efficiency inline deduplication, cluster support, GFS (grandfather, father, son) archiving and Exchange item-level restore. Moving up to a still very affordable £685 per host, the Unlimited Plus edition brings Altaro’s cloud management console into play and adds WAN-optimised replication, CDP (continuous data protection) and support for offsite backups to Microsoft Azure.

Altaro VM Backup 8.3 review: Deployment

Altaro claims it’ll take you 15 minutes to install the software and get your first backup running and it’s not wrong. It took us 5 minutes to install it on a Windows Server 2016 host after which we declared our first Hyper-V host, added a Qnap NAS appliance network share as our primary backup location, picked a VM from the list presented and manually ran the job.

The console is very easy to use and we also declared the lab’s VMware ESXi host and another Hyper-V host running our Exchange 2013 and SQL Server 2014 services. Along with NAS appliance shares, Altaro supports a good choice of destinations including local storage, iSCSI targets, USB and eSATA external devices, UNC share paths and RDX cartridges.

For secondary off-site locations, you can copy data to Altaro’s free Offsite Server (AOS) app which supports Windows Server 2012 upwards. The OS and AOS app can also be hosted in the cloud using a range of providers including Microsoft Azure.

Altaro VM Backup 8.3 review: User interface

Creating VM backup strategies doesn’t get any easier as most operations are drag and drop. We viewed all VMs presented by our Hyper-V and VMware hosts and simply dragged them across and dropped them on our primary backup location.

At this stage, you can run them manually with a single click, but applying a schedule is just another drag and drop procedure. Altaro provides two predefined schedules and we could create our own with custom start times plus weekly and monthly recurrences.

A set of default data retention policies are provided and you can easily create new ones for on-site and off-site backup locations. Choose how many versions you want to keep, decide whether older ones are deleted or archived and then just drop VMs onto them to apply the policy.

You can add off-site copies to a schedule at any time by – you’ve guessed it – dragging and dropping VMs onto the secondary backup location icon. CDP can be enabled on selected VMs and scheduled to run as often as every 5 minutes, while application consistent backups can be applied to VMs running VSS-aware apps such as Exchange and SQL Server.

Altaro VM Backup 8.3 review: Replication and restoration

Selected VMs can be replicated to the remote AOS host where CDP defaults to updating them every 5 minutes, or less frequently if you want. Depending on which type of VMs are being replicated, AOS requires access to local Hyper-V and VMware hosts, where it manages VM creation and handles all power up and shutdown commands.

Both the Altaro primary and AOS hosts must be running identical OSes and for the latter, we defined iSCSI storage for off-site copies and declared local Hyper-V and VMware hosts to provide VM replication. Initial off-site copies can be sped up as Altaro provides an option to copy the data to a removable device for seeding the remote vault.

General recovery features are excellent: you can restore a virtual hard disk, clone a VM or boot one straight from a backup to its original host or to another one. We tested the Boot from Backup feature and Altaro provisioned a SQL Server 2014 VM from its latest backup on a new Hyper-V host and had it running and waiting at the Windows login screen in one minute.

Altaro’s Sandbox feature takes the worry out of recovery by verifying the integrity of selected backups. Along with checking the data stored in backups, it clones VM backups to the same host to make sure they will boot when needed – and it does this all in the background.

GRT (granular recovery technology) restores are provided for recovering files, folders and Exchange items. Exchange GRT is undemanding; we selected this for our Exchange 2013 VM, chose a backup and its virtual hard disk, browsed for the EDB file and viewed our users and mailboxes plus items such as individual emails, contacts and calendars. The console creates a PST file containing the recovered items and we used the Exchange Admin Center web app to grab the file and import its contents into the relevant user’s mailbox.

Altaro VM Backup 8.3 review: Verdict

During testing, we were very impressed with Altaro VM Backup’s fast deployment and extreme ease of use. The clever console design makes it easy to create backup strategies for VMs plus it offers a wealth of valuable recovery and replication features. Protecting your Hyper-V and VMware virtualized environments really doesn’t get any easier or more affordable, making Altaro VM Backup a top choice for SMEs.

Jamf has brought its Jamf Premium Cloud service for Apple management to UK servers, meaning customers using the service in the region will be able to continue using it without a hitch following the UK’s split from the EU.

Bringing the Jamf Premium Cloud product to a UK server means businesses in highly regulated industries such as finance and education will be able to ensure their data is stored securely and firmly within the region.

It allows businesses to manage and grant access to IP and network addresses and allow certain users to log into the server without interruption.

Jamf’s premium cloud product allows businesses to white label their own server address too, not only making sure it fits online with company branding but also offering peace of mind to users that it’s the right server.

Previously, the firm’s closest data centre to the UK was in Germany (its only European facility), with additional servers in the US, Japan and Australia. This latest move means Jamf can better tailor its products and services to a UK-focused audience.

“We are excited to bring Jamf Premium Cloud to the U.K. as it will bring flexibility to our customers here,” said Mark Ollila, director, cloud operations at Jamf.

“Jamf users will be able to reap the benefits of the cloud securely, as well as experience additional layers of security and customised branding. As the U.K. prepares to part ways with the EU, the cloud will be an essential tool for British businesses to compete globally, which is why we have launched Jamf Premium Cloud tailored for those in the U.K.”