Amazon has unveiled record high profits, obtaining more than double the levels investors were predicting, with much of its gains coming from the AWS division.

It will come as no surprise to regular readers of Cloud Pro that the cloud arm of Amazon is reeling in the most cash of all its parts, achieving $7.7 billion in revenue ($2.2 billion profit), which represents a 41% year-on-year growth.

However, its cloud revenues of $7.7 billion only represented 13% of the company’s total revenues over the first quarter of the year, but taking almost half of its total profits – demonstrating just how profitable the division is for the company’s bottom line.

There were some big cloud achievements for the firm over the quarter, including the launch of the AWS Asia Pacific (Hong Kong) Region, and announcing plans for the AWS Asia Pacific (Jakarta) Region, the launch of Amazon S3 Glacier Deep Archive, Concurrency Scaling for Amazon Redshift and general availability of Amazon EFS Infrequent Access.

Plus new business from some of the world’s biggest companies including Volkswagen, Ford, Lyft and Gogo had a positive impact on its cloud business.

Revenues for the entire company hit a Wall Street-beating $59.7 billion, although spending on technology such as AI and smart homes has also increased, meaning profits weren’t as high as they could have been and growth is likely to slow in the future.

It’s also spending a lot on developing its own cloud infrastructure, again making a dent in profits in the short term, and its planned one-day Prime shipping rollout is also likely to cost a fair whack in terms of logistics.

Despite being a leader in the server chip market, Intel’s revenue from its data-centric business has dropped by 5%, according to the company’s 2019 first quarter financial results.

While the chip maker reported a 5% hike in cloud revenues in its Data Centre Group, revenues for the arm dropped by 6%. What’s more, overall revenue from its data-related businesses raked in $4.9 billion, which is down from $5.2 billion in the same quarter for 2018.

One of the areas contributing to this decline was the 4% drop in average selling prices and the 8% drop in the volume of units Intel shifted for its data centre platform, which is a continuation of the rather sharp slowdown Intel’s server equipment sales encountered last year. Historically, this has been a booming business for the chip maker.

Yet, while Intel’s data-centric business isn’t as healthy as it would like, revenue from selling desktop and laptop processors rose by 4% to generate $8.6 billion for the company. This rise came in spite of static PC shipments and problems Intel encountered around chip shortages.

Intel’s chief executive Robert Swan also noted that next-generation laptop processors built on the 10nm process node – thereby increasing the number of transistors in a processor to improve power and efficiency – will arrive this year.

“Our confidence in 10nm is also improving,” Swan said in an earnings call transcribed by Seeking Alpha. “In addition to the manufacturing velocity improvement I described earlier, we expect to qualify our first volume 10nm product, Ice Lake, this quarter and are increasing our 10nm volume goals for the year.”

This next-generation of processor could help keep Intel’s PC-centric business ticking along. Swan noted 10-nanometre chips will be rapidly brought from the PC business and into Intel’s data centre chips.

«Historically there has been a 12-18 month gap between client chips and servers. On 10nm that will be much shorter, all we’ll say is it will be a fast follow, some time in 2020, and earlier rather than later,” Swan added.

With a decline in demand from data centre customers and the investment Intel is making into getting its 10nm fabrication ready for the production of chips at volume, the company has reduced its earnings forecast for the full 2019 fiscal year to $69.0 billion from a previously estimated $71.05 billion.

Nevertheless, the determined push to 10nm chips in both the PC and data centre space world could see Intel continue to do well in the PC market while also giving its data-centric business a shot in the arm come some point in the future, most likely 2020.

Whenever artificial intelligence, aka AI, comes up in conversation, the usual image that springs to most people’s minds is a threatening killer robot along the lines of Terminator that has nothing but murderous intentions towards humanity.

But these days the AI acronym is being liberally sprinkled far and wide, often referring to things that stretch well beyond its primary meaning. In this feature, we look at some of the common myths and misconceptions, compared to the real scientific situation in each case.

1. AI will create a malevolent Skynet-style system that will destroy humanity

Let’s look at the most popular myth first – the scary robot elephant in the room. Terminator is the most well-known example, but it is a recurring sci-fi theme from 2001: A Space Odyssey to the latest season of Star Trek: Discovery. On the one hand, technology has been automating the delivery of ordnance for decades, with in-missile video footage from the 1991 Gulf War just one watershed moment in a process towards greater autonomy that dates back to the German V1 and V2 rockets of World War II. The US army has been deploying Unmanned Air Vehicles (UAVs) for decades, and now has around 10,000 of them in regular use. But all of these still have human operators for key functions. The Defence Advanced Research Projects Agency (DARPA) has been awarding grants for the development of UAVs that can navigate themselves indoors. But as the RAND corporation points out, very few countries use armed drones just yet, and there is much controversy about their central value in warfare compared to conventional weapons systems. So even if fully autonomous fighting machines are developed, there are still many hurdles before they are deployed without human oversight, let alone take over the world.

2. AI systems and robots will eventually replace all jobs, making most people redundant

According to a report published by the UK’s Department of Work and Pensions, 8,820,545 jobs could be wiped out by 2030 because of AI, particularly in the retail sector. Aside from the strangely specific number of job losses predicted, it’s worth noting that it won’t just be menial labour that gets replaced. Complex intellectual activities are already being replicated by expert systems, such as legal and medical advice. AI has been making inroads into healthcare to allow earlier diagnosis without the need for consultation with specialists, who are always at a premium. You can even put your job title into the Will Robots Take My Job website to see how likely you are to be replaced by AI. In reality, though, similar arguments have been made since the agrarian and industrial revolutions. On the one hand, many jobs will be automated by AI, but on the other, people can retrain, or young people educated in a different direction for the new jobs that are emerging – potentially designing and building those AI-powered robots.

3. Siri, Google Home, Cortana and Alexa are AI

Voice-activated speakers have been a Christmas hit for the last couple of years, and more people are getting used to giving the smartphones verbal commands, too. These are undeniably clever, convenient systems (when they work…), but in reality, they are just advanced natural language processing (NLP) recognition algorithms akin to dictation software like Dragon Naturally Speaking. There is no original thought going on, just a lot of pre-programmed responses to verbal commands.

4. AI is a computer version of the human brain

We now get to the main underlying myth of AI – that computers model the human brain. This could be the subject of multiple PhD dissertations, but in a nutshell (and just for starters), computers are still based on the Von Neuman machine model of the mid-1940s. This reads data from memory, operates on it, and writes the result back to memory. This is not how brains work. Even multi-core processors, or HPC datacentres full of them, are still much more serial in their operation than a brain, which in contrast has a slow frequency (around 200Hz compared to multiple Gigahertz) but is massively parallel. Not just massively parallel, but inputs and outputs are connected in complicated feedback loops, with workings that we still don’t understand completely yet. This isn’t to say that computer AI isn’t amazingly useful, or that we won’t ever fully understand the human brain. But current AI is at best a very rough simulation, not even close to a digital facsimile of the cerebrum of homo sapiens.

5. AI systems can learn for themselves

Another two-letter acronym often found alongside AI is ML (Machine Learning). The common myth is that ML is a fully autonomous process, which will potentially lead to AI that transcends human intelligence and eventually decides to get rid of us (see 1 above). However, ML still intrinsically involves teaching by humans. Every AI system needs to be fed source material chosen by people, and its outputs adjusted by human experts until they work. This is precisely the process that Google’s self-driving car system is going through right now, and this won’t stop even when it gets the green light as a commercially available system in new vehicles.

6. AI systems will be much more impartial than human beings

As a result of AI’s ML being fed by humans, there’s no reason to believe that it will be any more impervious to prejudices than the humans that taught it. Early facial recognition systems had trouble identifying ethnicities, and the Tay Twitter bot was rapidly turned into a rabid racist by the tone of social media conversations. On the other hand, an AI that has been trained to be as impartial as the best human examples will consistently be better in this respect than the worst humans, which is where there is clear value for the legal and medical professions, amongst others.

7. AI will soon be smarter than human beings, or never will

Because AI runs on computers that are not an exact replica of the human brain (see four above), this is a bit of a trick question. On the one hand, there is no sign that a general AI will transcend overall human intelligence anytime soon, because we still don’t know exactly what the latter is. But on the other hand, much more narrow AI has been beating humans for some years now, such as defeating the best human chess player, and surpassing the best players of Jeopardy!. In 2004, none of the vehicles in the DARPA Grand Challenges completed the course, but in 2005, five did, and now we have self-driving cars being tested on public roads. So AIs will likely be smarter than humans in many key areas (and already are in some), but may never be in a general, overall sense – whatever that even means.

8. The technological singularity is approaching, or will never happen

Related to seven above, there is a theory, originally presented by maths and computer science professor Vernor Vinge, that the development of artificial superintelligence will arrive around 2030 and then AI will upgrade itself beyond human understanding and the world will change unrecognisably. This has been dubbed “the singularity”. For reasons already discussed above, the date already looks massively optimistic before we even get into the details, due to our lack of understanding of the human brain. But, on the other hand, the singularity doesn’t necessarily have to involve completely human intelligence. We could be creating something that isn’t human, just loosely based on us. Nevertheless, this idea still gives computers the ability to have their own intentions, which somehow emerge spontaneously from the advanced technology. Right now, no AI can do anything other than what humans told it to do, even if your flaky desktop PC might sometimes make you believe otherwise.

9. AI is just sci-fi and nothing that should concern business

Just as AI can create new jobs as well as replace old ones, it’s a topic that should be central to all businesses that intend to survive and grow over the coming decades, rather than ignored. On the one hand, the scary sci-fi scenarios of human replacement are very distant if ever likely to happen at all. But, on the other hand, there are real opportunities to enhance business services and consumer interaction via the more limited systems that have been shown to be effective already. Business intelligence data analytics, forward resource planning, and automated customer service are just the beginning. Companies that embrace AI, whilst being realistic about its limitations, will be the ones that prosper.

Discover more about the AI solutions powered by Intel here

Slack has added some new features to its collaboration platform which aim to embrace the power of email, the very tool it aimed to kill off over five years ago.

Instead of having the two services operate alongside one another, now those in your organisation who aren’t on Slack, or have just started and haven’t yet received credentials, can still benefit from its collaboration features.

Directly addressing an individual in Slack via it’s ‘@-mention’ feature can now be utilised within email, with notifications appearing in the employee’s inbox if they are not on the platform or logged in.

Replies sent from an employee’s inbox will beam straight back to the relevant channel just as if the interaction was taking place on just the one platform.

Admins will need to tweak their company’s account to allow outside users to communicate with those inside the organisation in this way, but it’s a step closer to being a more unified collaboration tool.

This supports Slack’s existing Outlook and Gmail functionality, which allows users to forward emails into a channel where members can view and discuss the content and plan responses from inside Slack.

Another interesting announcement, made at the company’s Frontiers conference in San Franciso, relates to its ‘Workflow Builder’ tool which will enable any user within Slack to build apps for routine functions without coding knowledge.

The tool, which is launching later this year, will be capable of automating functions, such as completing and filing a benefits request form to HR or sending messages to help new starters find the right channels to join, saving other workers from sacrificing time to give a platform tutorial.

If this sounds familiar then you’d be right. Slack announced back in February two new toolkits that would also allow non-coders to build apps within Slack, however Workflow Builder appears to be geared towards routine automation rather than the more technical backend functions of the platform.

Slack’s integration with Outlook and Google Calendar is also becoming stronger as any status you set within Calendar will be automatically synced to Slack, such as being away from the office for an event or when you have a meeting booked in.

As many business meetings tend to be virtual nowadays, integration with calendars will allow other users to see who your meeting is with and provide joining options directly within Slack thanks to partnerships with Hangouts, Zooma and Webex.

There is also a change coming to Slack’s search function which, although fast and expansive, isn’t always the most intuitive or organised. Slack aims to address this by adding new features to make it easier to view unread messages quicker, allow faster navigation between channels to find the relevant person, and better functionality when sifting through channel archives. These features will be available in the coming weeks.

Slack’s five-year slog of a battle with email has proved fruitless; email still exists and seems like it’s here to stay. Google has invested into it to a greater extent recently despite the wide adoption of the platform which depends on the virality of its freemium model.

Manufacturing, lumber, distribution; these kinds of industries have been around for hundreds of years, and those who run companies in these sectors are used to doing things a certain way. Change is slow and, if business is good, can be seen as more of a risk than an opportunity.

This is the challenge that enterprise resource planning (ERP) firm Epicor aimed to tackle as it entered into its annual Insights conference, hosted this year at Mandalay Bay in Las Vegas. And, if the company’s executives are to be believed, the migration of its flagship product line-up to the public cloud is certainly the future.

This could lead to new technological possibilities, their message says, with the biggest announcements last week centring on enhanced ERP functionality prefaced by a stronger partnership with Microsoft’s Azure platform.

The most eye-catching of these was the Epicor Virtual Agent (EVA), an AI-powered digital assistant that the company’s chief product and technology officer Himanshu Pulsale insisted wasn’t «just a chatbot». Epicor’s big bet on the cloud was also met with a commitment to something it calls the ‘connected enterprise’, or in other words letting Internet of Things (IoT) devices loose across the factory floor. But this direction of travel hasn’t been embraced as warmly among a significant chunk of Epicor customers.

Just a few years ago the company was in rocky waters under its previous leadership, adopting a defensive mentality with regards to its customers, and almost apologising when they integrated any new tech into their products. But now the company is banging the drum for digital transformation and, in particular, public cloud migration.

Epicor has embarked on a decisive drive to communicate these benefits to a sceptical customer base, a small proportion of which have no interest in pursuing cloud technology whatsoever.

The software giant places the number of its customers still using Epicor ERP 9, released almost a decade ago, and similarly outdated software at roughly under 500 of 3,000 in the manufacturing space. Moreover, questions often asked throughout the conference ran along the lines of «do I need to be on cloud to use this feature or can I get it with on-prem as well?».

One of the deepest concerns among a more older generation of customers, as Epicor sees it, is that they’re being forced into using the cloud against their wishes. They are, in fact, quite comfortable with how their infrastructure sits right now. The biggest worry for Epicor is they’ll sit on whatever system they have for as long as possible, and then look at rival options – instead of upgrading – when the software is no longer supported.

Meanwhile, although Epicor’s leadership would say they’re ahead of the curve tech-wise, or at least on par with their weightier rivals (the likes of Oracle and SAP), they’d also concede this conflict has held them back. Painful upgrades and software flaws, among other issues, have clouded the company’s past.

But the overall tone at Insights 2019 was one of optimism, as Epicor seeks to finally hit the elusive billion-dollar-company mark within the next 12 months. The defensive mentality of old has been discarded, with a more proactive one picked up in its place.

But reckoning with the pace of growth has posed another headache. Epicor is a much larger firm than it was several years ago, but many of the internal processes are still unchanged from that of a small business. Internal change remains a learning process, and executives are finding they can’t whip up their conference speech a day before their keynote anymore.

These next 12 months will be especially interesting for a software firm that has put its chips on the table for public cloud. Epicor’s main predicament in future will centre on wrestling with legacy attitudes among a significant minority of customers while trying to keep its tech as fresh as the biggest players in ERP.

Microsoft’s cloud service Azure has grown 73% in the first quarter of 2019, helping the company to briefly hit a $1 trillion market cap for the first time.

The tech giant’s revenue hit $30.6 billion for the quarter, a 14% increase compared to the same period last year. Operating income hit $10.3 billion,  a 25% rise, and net income jumped 19% to $8.8 billion.

Perhaps what’s most notable about the quarterly earnings is that server products and cloud services revenue increased 27%, which the company attributed to Azure, it’s cloud computing service, which saw revenue growth of 73%.

«Leading organisations of every size in every industry trust the Microsoft cloud,» said CEO Satya Nadella. «We are accelerating our innovation across the cloud and edge so our customers can build the digital capability increasingly required to compete and grow.»

Microsoft saw growth in other services, such as LinkedIn, which had a revenue increase of 27%, and the Surface line of tablets and computers, which grew 21%. But it’s larger figures came from Azure, which has been a consistent source of growth of the company at a time when other divisions have struggled.

«Demand for our cloud offerings drove commercial cloud revenue to $9.6 billion this quarter, up 41% year-over-year,» said Amy Hood, the company’s executive VP and CFO. «We continue to drive growth in revenue and operating income with consistent execution from our sales teams and partners and targeted strategic investments.»

In the nine years since Azure’s release, the cloud platform has grown rapidly, despite failing to chip away at the market shares enjoyed by rivals AWS and Google Cloud. However, the overall health of the market has allowed Microsoft to enjoy significant gains regardless.

In 2018, Amazon raked in $ 3 billion, with a large portion of it coming from AWS. The company’s cloud division saw year on year profit growth of 45%, which continued a trend of growing by at least 40% each year. In the final quarter of the year, AWS brought in sales of £7.4 billion. The company’s first quarter results of 2019 are expected to be released next week.

Apple is spending more money on AWS cloud than any of its competitors, splashing out on average $30m a month on Amazon’s services.

According to CNBC, the company has signed up to a multi-year agreement with the cloud giant, although this may only be a stop-gap until Apple has finished building its own cloud-based infrastructure.

Although AWS and Apple could be viewed as competitors, Apple wants to make sure its customers are serviced as reliably and as fast as possible when using cloud-based services such as iCloud and it has, therefore, turned to what it thinks is the best in the business to do so.

Using AWS is an interesting move by the tech firm, although as it’s now reporting revenues based upon services including iOS App Store, AppleCare, Apple Pay and iCloud, rather than hardware shipments, having some sturdy infrastructure behind it will surely have a positive impact on those figures.

CNBC reports that many other online services companies, such as Pinterest and Lyft are also relying on AWS to deliver services, but their spending is considerably lower, despite building their whole business model upon the cloud.

Despite announcing its plans to create its own network of data centres to support this growing services business, Apple is still looking to accelerate its AWS knowledge and was recently seen advertising for an AWS tech lead to help expand its cloud footprint.

The company has said it expects to invest $10 billion on US-based data centres over five years, with $4.5 billion of that in 2019.