Anyone following the markets related to the Internet of Things has seen the forecasts of tens of billions of connected devices, trillions of dollars of economic impact and the transformation of multiple industries.
Looking back to forecasts from the 2014-15 period, it seems many optimistic growth forecasts have failed to unfold while we still have yet to see a major inflection point in the markets, says Ed Maguire, insights partner, Momenta Partners.
There has been some disappointment at the pace of spending on IoT projects and concerns that Proof of Concepts have failed to translate meaningfully into production. Cisco in May 2017 found 60% of IoT initiatives stall at the Proof of Concept (PoC) stage with only 26% of companies reported having an IoT initiative that they considered a complete success.
Beyond IoT, huge advances across the technology landscape
We at Momenta advocate taking a broader perspective. Even in the absence of big inflections in spending, adoption continues at a healthy linear clip. In the last decade we’ve seen a number of technologies mature to “prime time” readiness, including Cognitive/Artificial Intelligence (IBM’s Watson, Amazon Alexa), Virtual and Augmented Reality (Facebook Oculus, Microsoft Hololens), Additive Manufacturing/3D Printing, Clean Energy (Solar, Wind and utility scale battery storage) as well as stunning advances in Autonomous Vehicles. Exponential cost curves in technology proceed unabated, powering break through across the landscape.
Exponential cost curves fuel accelerating innovations
Innovations in hardware, software, networking and connectivity continue to benefit from powerful forces driving the declining cost of sensors, components, hardware and modules. Exponential cost and performance improvements are occurring across a broad range of technologies.
|Technology||Time to double (or half)|
|Dynamic RAM memory “half pitch” feature size||5.4 years|
|Dynamic RAM memory (bits per dollar)||1.5 years|
|Average transistor price||1.6 years|
|Microprocessor cost per transistor cycle||1.1 years|
|Total bits shipped||1.1 years|
|Processor performance in MIPS||1.8 years|
|Transistors in Intel microprocessors||2.0 years|
|Microprocessor clock speed||2.7 years|
MIPS = Millions of instructions per second, a measure of processing capacity (Source: Ray Kurzweil, KurzweilAI.net)
These declining cost trendshelp drive rapid advancements in other enabling technologies such as cloud computing and Big Data analytics – while steadily improving ROI for new IoT projects. The growing variety of connectivity options and freely available open source software continues to reduce the costs of innovation- and drive the costs of failure – steeply downward.
The extraordinary advances in Cognitive Computing, Blockchain and IoT are compelling by themselves, but when we combine multiple technologies, the possibilities expand by orders of magnitude.
Innovation is accelerating in Cognitive Computing
Cognitive Computing broadly includes Machine Learning and Artificial Intelligence – systems that are able to learn and improve on their own without human intervention. Declining costs of cognitive-friendly GPUs (Graphics Processing Units) and FPGAs (Field Programmable Gate Arrays) will make it increasingly practical to embed cognitive capabilities into connected edge devices such as cameras, drones, gateways, IoT appliances, automobiles, wind turbines etc.
The technology is getting more powerful: error rates for image labeling have fallen from 28.5% to below 2.5% since 2010 (below human accuracy of 5%) in the annual ImageNet competition. There’s also active corporate engagement – machine learning patents grew at a 34% CAGR from 2013 to 2017.
Investments in Artificial Intelligence and Machine Learning are expected to continue apace- with IDC forecasting spending growing from $12 billion (€10.23 billion) in 2017 to $57.6 billion (€49.10 billion) by 2021. Devices at the edge will increasingly be able to learn and optimise real-time decision-making while leveraging deeper analyses of historical data in the cloud.
Blockchain provides the missing trust layer
There’s no technology that’s seen more hype, or which offers potentially deeper downstream ramifications for IoT than blockchain technologies such as Ethereum and Hyperledger, and distributed ledgers such as IOTA and Hashgraph. This technology provides the ability to validate identity, reduce transaction frictions, lower compliance overhead, accelerate verification processes, track value exchange and enable autonomous processes.
Corporate interest in blockchain is robust – with 2/3 of large corporations expecting to deploy in their organisations by end of 2018 according to Juniper Research. For now, there’s expected to be a lot of spending on professional services, which IDC forecasts to grow at a 71.3% annually to $10.6 billion (€9.04 billion) in 2022.
Entering the era of combinatorial innovations
The most powerful innovations ahead of us will be driven by the convergence of multiple technologies applied to solve increasingly sophisticated problems. Think of IoT as a foundational building block, which when combined in solutions with machine learning/AI and blockchain/distributed ledger technologies can power value creation far greater than the sum of the parts.
In the future, IoT, blockchain and AI will be able to enable a wealth of services and processes for systems. The value will be apparent in areas such as Smart Transportation (fees and tolls, insurance, personalisation, safety and maintenance (diagnostics, alerts), Smart Spaces (security, climate, energy consumption), Connected Health (wearables, activity monitoring, telehealth) and Industrial (supply chain and logistics, manufacturing, plant operations, agriculture etc.) At Momenta Partners, we’ve been focused on helping businesses understand how emerging technologies will help realise the promise of IoT.
For more insights into these topics, please checkout our Webinar on Emerging Technologies in IoT – AR, AI and Blockchain available on-demand.
The author of this blog is Ed Maguire, insights partner, Momenta Partners