Will AI spur revenue growth for the telcos?
- A global AI survey sponsored by Ciena highlights industry optimism
- The telcos have unique networking assets that can serve users of AI.
- Much is still to play out and telcos have a history of missed opportunities.
The leading communications service providers have been on a decade-long journey to transform their networks and grow their revenues.
To the list of technologies the operators have been embracing can now be added artificial intelligence (AI).
AI is a powerful tool for improving their business efficiency. The technology is also a revenue opportunity and service providers are studying how AI traffic will impact their networks.
“This is the single biggest question that everyone in this industry is struggling with,” says Jürgen Hatheier. “How can the service providers exploit the technology to grow revenues?”
However, some question whether AI will be an telecom opportunity.
“The current hype around AI has very little to do with telcos and is focused on hyperscalers and specifically the intra-data centre traffic driven by AI model training,” says Sterling Perrin, senior principal analyst at HeavyReading. “There is a lot of speculation that, ultimately, this traffic will spread beyond the data centre to data centre interconnect (DCI) applications. But there are too many unknowns right now.”
AI survey
Hatheier is chief technology officer, international at Ciena. He oversees 30 staff, spanning Dublin to New Zealand, that work with the operators to understand their mid- to long-term goals.
Ciena recently undertook a global survey (see note 1, bottom) about AI, similar to one it conducted two years ago that looked at the Metaverse.
Conducting such surveys complements Ciena’s direct research with the service providers. However, there is only so much time a telco’s chief strategy officer (CSO) or chief technology officer (CTO) can spend with a vendor discussing strategy, vision, and industry trends.
“The survey helps confirm what we are hearing from a smaller set,” says Hatheier.
Surveys also uncover industry and regional nuances. Hatheier cites how sometimes it is the tier-two communications service providers are the trailblazers.
Lastly, telcos have their own pace. “It takes time to implement new services and change the underlying network architecture,” says Hatheier. “So it is good to plan.”
Findings
The sectors expected to generate the most AI traffic are financial services (46 per cent of those surveyed), media and entertainment (43 per cent), and manufacturing (38 per cent). Hatheier says these industries have already been using the technology for a while, so AI is not new to them.
Sterling Perrin
For financial services, an everyday use of AI is for security, detecting fraudulent transactions and monitoring video streams to detect anomalous behavior at a site. The amount of traffic AI applications generate can vary greatly. This is common, says Hatheier; it is the use that matters here, not the industry.
“I would not break it down by the industries to say, okay, this industry is going to create more traffic than another,” says Hatheier. “For financial services, if it is transaction data, it’s a few lines of text, but if it is video for branch security, the data volumes are far more significant.”
AI is also set to change the media and entertainment sector, challenging the way content is consumed. Video streaming uses content delivery networks (CDNs) to store the most popular video content close to users. But AI promises to enable more personalised video, tailored for the end-user. Such content will make the traffic more dynamic.
Another example of personalised content is for marketing and advertising. Such personalisation tends to achieve better results, says Hatheier.
AI is also being applied in the manufacturing sector. Examples include automating supply-chain operations, predictive maintenance, and quality assurance.
Car manufacturers check a vehicle for any blemishes at the end of a production line. This usually takes several staff and lasts 10-15 minutes. Now with AI, the inspection can be completed as the cars passes by. “This is a potent application that could run on infrastructure within the manufacturing site but use a service provider’s compute assets and connectivity,” says Hatheier.
The example shows how AI produces productivity gains. However, AI also promises unique abilities that staff cannot match.
Traffic trends
If the history of telecoms is anything to go by, applications that drove traffic in the network rarely lead to revenue growth for the service providers. Hatheier cites streaming video, gaming, and augmented reality as examples.
However, the operators have assets at network edge and the metro that can benefit AI usage. They also have central offices that can act is distributed data centres for the metro and network edge.
Hatheier says users have an advantage if they consume AI applications across a fibre-based broadband network. But certain countries, such as Saudi Arabia and India, mainly use wireless for connectivity.
“AI applications will need to adapt to what is available, and if people want to consume low-latency applications, there is 5G slicing,” says Hatheier. “At the end of the day, there is no way around fibre.”
Optical networking
Government policy regarding AI and regulations to ensure data does not cross borders also play a part.
“It’s an important decision criterion, as we saw in the survey response,” says Hatheier. “So private AI and local computing will be an important decision factor.”
Another critical decision influencing where data centres are built is power. “We see all the gold rush in the Nordics right now with their renewable power and cool climates,” says Hatheier. “You don’t need to cool your servers as much, and it requires a lot of connectivity.”
However, as well as these region-specific data centre builds, there will also be builds in metropolitan areas using smaller distributed data centres.
“Let’s say there are 20 sizable edge or metro compute centres for AI, and you would need three or four to run a big training job,” says Hatheier. “You will not create a permanent end-to-end connection between them because sometimes there will not be four that need to work together, but five, seven, and 11.”
Such a metro network would require reconfigurable optical add-drop multiplexer (ROADM) technology to connect wavelengths between those clusters based on demand to keep sites busy, to avoid expensive AI clusters being idle.
These are opportunities for the CSPs. And while much is still to happen, such discussions are taking place between systems vendors and the telcos.
For Heavy Reading’s Perrin, the more telling opportunity is the telcos’ own use of AI rather than the networking opportunity.
“As a vertical industry, telecom is not typically a leading-edge adopter of any new technology due to many factors, including culture, size, legacy infrastructure and processes, and government regulations,” he says. “I don’t believe AI will be any different.”
Hatheier points to the survey’s finding of general optimism that sees AI as an opportunity rather than a challenge or business risk.
“We have seen very little differences between countries,” says Hatheier. “That may have to do with the fact that emerging countries get as much attention of data centre investment than more developed ones.”
Books in 2013 - Part 1
Gazettabyte is asking various industry figures to highlight books they have read this year and recommend, both work-related and more general titles.
Part 1:
Tiejun J. Xia (TJ), Distinguished Member of Technical Staff, Verizon
The work-related title is Optical Fiber Telecommunications, Sixth Edition, by Ivan Kaminow, Tingye Li and Alan E. Willner. This edition, published in 2013, includes almost all the latest development results of optical fibre communications.
My non-work-related book is Fortune: Secrets of Greatness by the editors of Fortune Magazine. While published in 2006, the book still sheds light on the 'secrets' of people with significant accomplishments.
Christopher N. (Nick) Del Regno, Fellow Verizon
OpenStack Cloud Computing Cookbook, by Kevin Jackson is my work-related title. While we were in the throes of interviewing candidates for our open Cloud product development positions, I figured I had better bone up on some of the technologies.
One of those was OpenStack’s Cloud Computing software. I had seen recommendations for this book and after reading it and using it, I agree. It is a good 'OpenStack for Dummies' book which walks one through quickly setting up an OpenStack-based cloud computing environment. Further, since this is more of a tutorial book, it rightly assumes that the reader would be using some lower-level virtualisation environment (e.g., VirtualBox, etc) in which to run the OpenStack Hypervisor and virtual machines, which makes single-system simulation of a data centre environment even easier.
Lastly, the fact that it is available as a Kindle edition means it can be referenced in a variety of ways in various physical locales. While this book would work for those interested in learning more about OpenStack and virtualisation, it is better suited to those of us who like to get our hands dirty.
My somewhat work-related suggestions include Brilliant Blunders: From Darwin to Einstein – Colossal Mistakes by Great Scientists That Changed Our Understanding of Life and the Universe, by Mario Livio.
I discovered this book while watching Livio’s interview on The Daily Show. I was intrigued by the subject matter, since many of the major discoveries over the past few centuries were accidental (e.g. penicillin, radioactivity, semiconductors, etc). However, this book's focus is on the major mistakes made by some of the greatest minds in history: Darwin, Lord Kelvin, Pauling, Hoyle and Einstein.
It is interesting to consider how often pride unnecessarily blinded some of these scientists to contradictions to their own work. Further, this book reinforces my belief of the importance of collaboration and friendly competition. So many key discoveries have been made throughout history when two seemingly unrelated disciplines compare notes.
Another is Beyond the Black Box: The Forensics of Airplane Crashes, by George Bibel. As a frequent flyer and an aviation buff since childhood, I have always been intrigued by the process of accident investigation. This book offers a good exploration of the crash investigation process, with many case studies of various causes. The book explores the science of the causes and the improvements resulting from various accidents and related investigations. From the use of rounded openings in the skin (as opposed to square windows) to high-temperature alloys in the engines to ways to mitigate the impact of crash forces on the human body, the book is a fascinating journey through the lessons learned and the steps to avoid future lessons.
While enumerating the ways a plane could fail might dissuade some from flying, I found the book reassuring. The application of the scientific method to identifying the cause of, and solution to, airplane crashes has made air travel incredibly safe. In exploring the advances, I’m amazed at the bravery and temerity of early air travelers.
Outside work, my reading includes Doctor Sleep, by Stephen King. The sequel to “The Shining” following the little boy (Dan Torrence) as an adult and Dan’s role-reversal now as the protective mentor of a young child with powerful shining.
I also recommend Joyland (Hard Case Crime), by Stephen King. King tries his hand at writing a hard-case crime novel with great results. Not your typical King…think Stand by Me, Hearts in Atlantis, Shawshank Redemption.
Andrew Schmitt, Principal Analyst, Optical at Infonetics Research
My work-related reading is Research at Google.
Very little signal comes out of Google on what they are doing and what they are buying. But this web page summarises public technical disclosures and has good detail on what they have done.
There are a lot of pretenders in the analyst community who think they know the size and scale of Google's data center business but the reality is this company is sealed up tight in terms of disclosure. I put something together back in 2007 that tried to size 10GbE consumption (5,000 10GbE ports a month ) but am the first to admit that getting a handle on the magnitude of their optical networking and enterprise networking business today is a challenge.
Another offending area is software-defined networking (SDN). Pundits like to talk about SDN and how Google implemented the technology in their wide area network but I would wager few have read the documents detailing how it was done. As a result, many people mistakenly assume that because Google did it in their network, other carriers can do the same thing - which is totally false. The paper on their B4 network shows the degree of control and customisation (that few others have) required for its implementation.
I also have to plug a Transmode book on packet-optical networks. It does a really good job of defining what is a widely abused marketing term, but I’m a little biased as I wrote the forward. It should be released soon.
The non-work-related reading include Nate Silver’s book: The Signal and the Noise: Why So Many Predictions Fail — but Some Don't . I am enjoying it. I think he approaches the work of analysis the right way. I’m only halfway through but it is a good read so far. The description on Amazon summarises it well.
But some very important books that shaped my thinking are from Nassim Taleb . Fooled by Randomness is by far the best read and most approachable. If you like that then go for The Black Swan. Both are excellent and do a fantastic job of outlining the cognitive biases that can result in poor outcomes. It is philosophy for engineers and you should stop taking market advice from anyone who hasn’t read at least one.
The Steve Jobs biography by Walter Isaacson was widely popular and rightfully so.
A Thread Across the Ocean is a great book about the first trans-Atlantic cable, but that is a great book only for inside folks – don’t talk about it with people outside the industry or you’ll be marked as a nerd.
If you are into crazy infrastructure projects try Colossus about the Hoover Dam and The Path Between the Seas about the Panama Canal. The latter discloses interesting facts like how an entire graduating class of French engineers died trying to build it – no joke.
Lastly, I have to disclose an affinity for some favourite fiction: Brave New World, by Aldous Huxley and The Fountainhead by Ayn Rand.
I could go on.
If anyone reading this likes these books and has more ideas please let me know!
Books in 2013 - Part 2, click here