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5 Trends in AI 2021

Artificial Intelligence innovation continues apace - with explosive growth in virtually all industries. So what did the last year bring, and what can we expect from AI in 2021?

In this article, I list five trends that I saw developing in 2020 that I expect will be even more dominant in 2021.

MLOps

MLOps (Machine Learning Operations, the practice of production Machine Learning) has been around for some time. During 2020, however, COVID-19 brought a new appreciation for the need to monitor and manage production Machine Learning instances. The massive change to operational workflows, inventory management, traffic patterns, etc. caused many AIs to behave unexpectedly. This is known in the MLOps world as Drift - when incoming data does not match what the AI was trained to expect. While drift and other challenges of production ML were known to companies that have deployed ML in production before, the changes caused by COVID caused a much broader appreciation for the need for MLOps. Similarly, as privacy regulations such as the CCPA take hold, companies that operate on customer data have an increased need for governance and risk management. Finally, the first MLOps community gathering - the Operational ML Conference - which started in 2019, also saw a significant growth of ideas, experiences, and breadth of participation in 2020.

Low Code/No Code

AutoML (automated machine learning) has been around for some time. AutoML has traditionally focused on algorithmic selection and finding the best Machine Learning or Deep Learning solution for a particular dataset. Last year saw growth in the Low-Code/No-Code movement across the board, from applications to targeted vertical AI solutions for businesses. While AutoML enabled building high-quality AI models without in-depth Data Science knowledge, modern Low-Code/No-Code platforms enable building entire production-grade AI-powered applications without deep programming knowledge.

Advanced Pre-trained Language Models

The last few years have brought substantial advances to the Natural Language Processing space, the greatest of which may be Transformers and Attention, a common application of which is BERT (Bidirectional Encoder Representations with Transformers). These models are extremely powerful and have revolutionized language translation, comprehension, summarization, and more. However, these models are extremely expensive and time-consuming to train. The good news is that pre-trained models (and sometimes APIs that allow direct access to them) can spawn a new generation of effective and extremely easy-to-build AI services. One of the largest examples of an advanced model accessible via API is GPT-3 - which has been demonstrated for use cases ranging from writing code to writing poetry.

Synthetic Content Generation (and its cousin, the Deep Fake)

NLP is not the only AI area to see substantial algorithmic innovation. Generative Adversarial Networks (GANs) have also seen innovation, demonstrating remarkable feats in creating art and fake images. Similar to transformers, GANs have also been complex to train and tune as they require large training sets. However, innovations have dramatically reduced the data sizes of creating a GAN. For example, Nvidia has demonstrated a new augmented method for GAN training that requires much less data than its predecessors. This innovation can spawn the use of GANs in everything from medical applications such as synthetic cancer histology images, to even more deep fakes.

AI for Kids

As low-code tools become prevalent, the age at which young people can build AIs is decreasing. It is now possible for an elementary or middle school student to build their own AI to do anything from classifying text to images. High Schools in the United States are starting to teach AI, with Middle Schools looking to follow. As an example - in Silicon Valleys Synopsys Science Fair 2020, 31% of the winning software projects used AI in their innovation. Even more impressively, 27% of these AIs were built by students in grades 6-8. An example winner, who went on to the national Broadcom MASTERS, was an eighth-grader who created a Convolutional Neural Network to detect Diabetic Retinopathy from eye scans.

What does all this mean?

These are not the only trends in AI. However, they are noteworthy because they point in three significant and critical directions

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Artificial Intelligence In 2021: Five Trends You May (or May Not) Expect - Forbes

CHICAGO, March 15, 2021 /PRNewswire/ -- According to the new market research report "Artificial Intelligence in Military Marketby Offering (Software, Hardware, Services), Technology (Machine Learning, Computer vision), Application, Installation Type, Platform, Region - Global Forecast to 2025",published by MarketsandMarkets,the Artificial Intelligence in Military Marketis estimated at USD 6.3 billion in 2020 and is projected to reach USD 11.6 billion by 2025, at a CAGR of 13.1% during the forecast period. An increase in funding from military research agencies and a rise in R&D activities to develop advanced AI systems are projected to drive the increased adoption of AI systems in the military sector.

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Artificial Intelligence (AI) is becoming a critical part of modern warfare as it can handle massive amounts of military data in a more efficient manner as compared to conventional systems. It improves the self-control, self-regulation, and self-actuation abilities of combat systems using inherent computing and decision-making capabilities. Some industry experts have noted that the COVID-19 pandemic has not affected the demand for Ai in Military, especially for military end use. Companies such as Lockheed Martin Corporation (US), Northrop Grumman Corporation (US), BAE Systems (UK), Rafael Advanced Defense Systems (Israel) and Thales Group (France) received contracts for the supply of AI systems to the armed forces of various nations in the first half of 2020, showcasing continuous demand during the COVID-19 crisis.

Even though the COVID-19 pandemic has caused a large-scale impact on economies across the world, leading to many challenges, the AI in military market has continued to expand. This can be seen from both, the demand and supply sides, as leading manufacturers like Lockheed Martin (US), IBM (US), Northrop Grumman (US), and others continue to invest heavily in developing AI capabilities, and governments continue to invest significantly in securing these systems. This can be attributed to governments realizing the potential of improved capabilities that these AI systems offer in terms of defense arsenal as the global AI arms race tightens.

However, even though the development of AI technology witnessed expansion, the overall building of the AI systems saw a hit. This was a result of the shortage of raw materials due to disruptions in the supply chain. Resuming manufacturing and demand depends on the level of COVID-19 exposure a country is facing, the level at which manufacturing operations are running, and import-export regulations, among other factors. Although companies may still be taking in orders, delivery schedules might not be fixed.

Increasing Threats of Cyber Attacks is driving the growth of the defense applications that leverages AI

The defense industry across countries is constantly under threat of cyberattacks. For instance, in September 2019, SolarWinds, a US technology company, was hacked, revealing sensitive data of many hospitals, universities, and US government agencies. Another notable incident was in October 2020, when the FBI and the US Cyber Command announced that a North Korean group had hacked think tanks, individual experts, and government entities of the US, Japan, and South Korea to illegally obtain intelligence, including that on nuclear policies.

Current cybersecurity technology falls short in terms of tackling advanced ransomware and spyware threats. The above mentioned SolarWinds hack was revealed when FireEye, a cybersecurity provider, was probing one of its own hacks. Such incidents indicate the increasing importance of having advanced cybersecurity capabilities. Artificial intelligence-based cybersecurity solutions that can be trained to independently gather data from various sources, analyze the data, correlate it to the signals indicating cyberattacks, and take relevant actions, can be deployed.

Browsein-depth TOC on"Artificial Intelligence in Military Market"

164 Tables 77 Figures278 Pages

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Based on platform, the space segment of theArtificial Intelligencein military market is projected to grow at the highest CAGR during the forecast period

Based on platform, the space segment of the Artificial Intelligence in military market is projected to grow at the highest CAGR during the forecast period. The space AI segment comprises CubeSat and satellites. Artificial intelligence systems for space platforms include various satellite subsystems that form the backbone of different communication systems. The integration of AI with space platforms facilitates effective communication between spacecraft and ground stations.

Software segment of theArtificial Intelligencein Military market by offering is projected to witness the highest CAGR during the forecast period

Based on offering, the Software segment is projected to witness the highest CAGR during the forecast period. Technological advances in the field of AI have resulted in the development of advanced AI software and related software development kits. AI software incorporated in computer systems is responsible for carrying out complex operations. It synthesizes the data received from hardware systems and processes it in an AI system to generate an intelligent response. Software segment is projected to witness the highest CAGR owing to the significance of AI software in strengthening the IT framework to prevent incidents of a security breach.

The North America market is projected to contribute the largest share from 2020 to 2025 in theArtificial Intelligencein Military market

The US and Canada are key countries considered for market analysis in the North American region. This region is expected to lead the market from 2020 to 2025, owing to increased investments in AI technologies by countries in this region. This market is led by the US, which is increasingly investing in AI systems to maintain its combat superiority and overcome the risk of potential threats on computer networks. The US plans to increase its spending on AI in military to gain a competitive edge over other countries.

The North America US is recognized as one of the key manufacturers, exporters, and users of AI systems worldwide and is known to have the strongest AI capabilities. Key manufacturers of Ai systems in the US include Lockheed Martin, Northrop Grumman, L3Harris Technologies, Inc., and Raytheon. The new defense strategy of the US indicates an increase in Ai spending to include advanced capabilities in existing defense systems of the US Army to counter incoming threats.

Related Reports:

Military Embedded Systems Marketby Component (Hardware, Software), Server Architecture (Blade Server, Rack-Mount Server), Platform (Land, Airborne, Naval, Space), Installation (New Installation, Upgradation), Application, Services, and Region - Global Forecast to 2025.

Network Centric Warfare (NCW) Marketby Platform (Land, Air, Naval, Unmanned), Application (ISR, Communication, Computer, Cyber, Combat, Control & Command), Mission Type, Communication Network, Architecture, and Region - Global Forecast to 2021

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Artificial Intelligence in Military Market worth $11.6 billion by 2025 - Exclusive Report by MarketsandMarkets - PRNewswire