The only certainty in the year ahead for technology will be uncertainty. New security threats and technologies such as blockchain and artificial intelligence will ensure 2018 will be interesting. Here's a look at ZDNet's crystal ball and a few predictions.
If there ever was a time that organisations could worry only about their own security and treat it was an isolated system, those days are long over.
With the interconnected ingesting and serving of as-a-service products, mixed into the world of outsourcing and contracting, the number of vectors that bad actors can appear out of are myriad, and simply going for the cheapest option is not going to cut it.
The attack was not against the Department of Defence, or a large corporate like Lockheed Martin or Boeing, it was against a small company far lower down the supply chain. Canberra stated it didn't believe it should be responsible for the hack, but at some point, a decision was made to hand data over to a company that could not give it the protection required, and whoever made the call should wear responsibility for it.
While not everyone is handling defence information, the idea of vetting the information security practices of suppliers is a sound one, if only to protect one's own reputation.
In a plot twist that only a data center hardware vendor could have written, compute, networking and storage gear is going to need more horsepower. Suddenly servers sitting near the edge of Internet of things devices are going to be pretty cool. Why? The cloud is critical to the Internet of things, but it's costly to shuttle data back and forth when analytics is needed on the fly. Dell Technologies, Hewlett-Packard Enterprise and other vendors are aligning to this IoT to the edge theme.
Gartner sums it up in a slide:
Mazin Gilbert, AT&T's VP of Advanced Technology, said this IoT to the edge theme will gain momentum in 2018 as 5G begins to roll out. Gilbert argued in an interview that the IoT network will have a series of white boxes that'll sit near sensors and smart things to handle compute, networking and storage. "These white boxes will serve as baby clouds that will serve multiple purposes," said Gilbert. "Intelligence will have to move to the edge due to latency and applications for artificial intelligence, augmented reality and 360 degree video."
Apple will launch a touchscreen "laptop" since it has no choice
Plenty of mid-range and most high-end laptops will now come with a touchscreen as standard; even if you aren't looking for one you'll probably end up with one anyway. It's a useful feature especially when working with big documents or lots of images. But you won't find one on a MacBook.
OK, so there is the MacBook Pro 'Touch Bar' which arrived in 2016, seen as a way for Apple to introduce some touch screen features to its notebooks. But this for many it is a neat concept searching for a proper use case -- and for others it's just more trouble than it's worth.
Of course, Apple already makes plenty of touchscreen device - the iPad and iPhone. So why not a notebook too? Perhaps 2018 will be the year it decides to give it a go: and if making macOS touch friendly is too much work, perhaps we'll see the arrival of the first iOS laptop, too.
5G looms, but it's more like 4.5G
The next generation of mobile communication is slowly and deliberately coming together, and it will be known as 5G. But as far as consensus goes, that's pretty much it with 5G, everything else about it is up in the air.
The problem with 5G is that it doesn't have a definition, and that means some telco is probably going to slap the label into a slightly-faster-than-LTE connection at some point.
Gilbert noted that the companies that "own the most diverse data sets" will win in the future. In 2018, it's a safe bet that there will be data savvy companies that blow away their competition. For a company like GE or Honeywell, the data thrown off from the industrial equipment they sell is ultimately more important than the actual hardware. The ability to combine first party data with other sources will be critical. How that data is used to personalize everything from product assortment to marketing will determine the winners and losers.
Speaking during Home Depot's analyst meeting earlier this month, Kevin Hofmann, president of online at the company and chief marketing officer, said the retailer is investing heavily on its data capabilities and platform.
"Data will be at the core at what we do. Most of the U.S. is in our database," said Hofmann. Indeed, Home Depot is modeling more than 1 trillion data points a week. Some of this data is transactional and a lot of it is tailored to location. As a result, Home Depot can understand communities, neighborhoods and businesses at scale. Home Depot can also see macro themes develop. This use of data has lowered marketing expenses. For instance, Home Depot has sets of ads that are automatically triggered by weather events.
Hofmann said Home Depot is just starting, but if you listen to enough earnings calls you hear this data-as-currency theme repeatedly.
The tough part will be cleaning the data and preparing it for analysis--the grunt work enterprises have never done well. LD
Perhaps you've noticed that damn near every enterprise technology company has some AI and machine learning story. Every cloud provider has an AI twist too. This year was just the warm-up act for AI washing--the habit of making every legacy technology sound like it's trendy. You've inevitably been hit with cloud washing and now it's time for the AI wave. In 2018, AI will be mentioned so much that the term almost becomes meaningless. What can you do? Be a bit discerning and ask a few hard questions of vendors. These questions include:
Is the data differentiated from others to provide actionable insights?
Does the AI deliver something that I couldn't find myself?
Are there multiple data sources being combined what others can do?
Is the processing at a massive scale and done in a cloud architecture?
Are there quantifiable business value to the AI use cases?
What's under the hood of your algorithms and can I have my data science team kick the tires?
Show me what your AI can do when given some data from my corporation. Show me the before and after of your AI?
Are the platforms being used able to combine with the other ones we're using?
The Monday Morning Opener is our opening salvo for the week in tech. Since we run a global site, this editorial publishes on Monday at 8:00am AEST in Sydney, Australia, which is 6:00pm Eastern Time on Sunday in the US. It is written by a member of ZDNet's global editorial board, which is comprised of our lead editors across Asia, Australia, Europe, and the US.