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Dublin, Aug. 05, 2022 (GLOBE NEWSWIRE) -- The "Artificial Intelligence of Things Solutions by AIoT Market Applications and Services in and Industry Verticals 2022 - 2027" report has been added to ResearchAndMarkets.com's offering.

This AIoT market report provides an analysis of technologies, leading companies and solutions. The report also provides quantitative analysis including market sizing and forecasts for AIoT infrastructure, services, and specific solutions for the period 2022 through 2027. The report also provides an assessment of the impact of 5G upon AIoT (and vice versa) as well as blockchain and specific solutions such as Data as a Service, Decisions as a Service, and the market for AIoT in smart cities.

While it is no secret that AI is rapidly becoming integrated into many aspects of ICT, many do not understand the full extent of how it will transform communications, applications, content, and commerce. For example, the use of AI for decision-making in IoT and data analytics will be crucial for efficient and effective smart city solutions in terms of decision-making.

The convergence of AI and Internet of Things (IoT) technologies and solutions (AIoT) is leading to "thinking" networks and systems that are becoming increasingly more capable of solving a wide range of problems across a diverse number of industry verticals. AI adds value to IoT through machine learning and improved decision-making. IoT adds value to AI through connectivity, signaling, and data exchange.

AIoT is just beginning to become part of the ICT lexicon as the possibilities for the former adding value to the latter are only limited by the imagination. With AIoT, AI is embedded into infrastructure components, such as programs, chipsets and edge computing, all interconnected with IoT networks.APIs are then used to extend interoperability between components at the device level, software level and platform level. These units will focus primarily on optimizing system and network operations as well as extracting value from data.

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While early AIoT solutions are rather monolithic, it is anticipated that AIoT integration within businesses and industries will ultimately lead to more sophisticated and valuable inter-business and cross-industry solutions. These solutions will focus primarily upon optimizing system and network operations as well as extracting value from industry data through dramatically improved analytics and decision-making processes.

Industry adoption for AIoT is gaining momentum. By way of example, Advantech partnered with Momenta Ventures to launch the AIoT Ecosystem Fund, a venture capital fund with a target of $50 million USD and a focus on the digital industry. KC Liu, CEO of Advantech, stated: "Advantech is committed to enabling an intelligent planet. This starts at the industrial edge with early innovators in energy, manufacturing, smart spaces and supply chain management."

The company launched Advantech Industrial Wireless solutions with Qualcomm, NXP, DEKRA, and E Ink. "We provide AIW industrial grade wireless modules and wireless design-in services to embedded customers. This one-stop shopping service helps customers acquire leading wireless enabled AIoT products and reduce their time to market," said Andy Lin, Advantech Senior ProductManager.

Many industry verticals will be transformed through AI integration with enterprise, industrial, and consumer product and service systems. It is destined to become an integral component of business operations including supply chains, sales and marketing processes, product and service delivery, and support models.

We see AIoT evolving to become more commonplace as a standard feature from big analytics companies in terms of digital transformation for the connected enterprise. This will be realized in infrastructure, software, andSaaS managed service offerings. Recent years have witnessed rapid growth for IoT data-as-a-service offerings to become AI-enabled decisions-as-a-service-solutions, customized on a per industry and company basis. Certain data-driven verticals such as the utility and energy service industries will lead the way.

As IoT networks proliferate throughout every major industry vertical, there will be an increasingly large amount of unstructured machine data. The growing amount of human-oriented and machine-generated data will drive substantial opportunities for AI support of unstructured data analytics solutions. Data generated from IoT-supported systems will become extremely valuable, both for internal corporate needs as well as for many customer-facing functions such as product life-cycle management.

The use of AI for decision-making in IoT and data analytics will be crucial for efficient and effective decision-making, especially in the area of streaming data and real-time analytics associated with edge computing networks. Real-time data will be a key value proposition for all use cases, segments, and solutions. The ability to capture streaming data, determine valuable attributes, and make decisions in real-time will add an entirely new dimension to service logic.

In many cases, the data itself, and actionable information will be the service. AIoT infrastructure and services will, therefore, be leveraged to achieve more efficient IoT operations, improve human-machine interactions, and enhance data management and analytics, creating a foundation for IoT Data as a Service (IoTDaaS) and AI-based Decisions as a Service.

The fastest-growing 5G AIoT applications involve private networks. Accordingly, the 5GNR market for private wireless in industrial automation will reach $5.21B by 2027. Some of the largest market opportunities will be AIoT market IoTDaaS solutions. We see machine learning in edge computing as the key to realizing the full potential of IoT analytics.

Select Report Findings:

The global AIoT market will reach $83.6Billion by 2027, growing at 39.1% CAGR

The global market for IoT data as service solutions will reach $9.13B USD by 2027

The AI-enabled edge device market will be the fastest-growing segment within the AIoT

AIoT automates data processing systems, converting raw IoT data into useful information

Today's AIoT solutions are the precursor to next-generation AI Decision as a Service (AIDaaS)

AIoT solutions improve operational effectiveness and the value of machine data by up to 28% by 2027

Key Topics Covered:

1.0 Executive Summary

2.0 Introduction2.1 Defining AIoT2.2 AI in IoT vs. AIoT2.3 Artificial General Intelligence2.4 IoT Network and Functional Structure2.5 Ambient Intelligence and Smart Lifestyles2.6 Economic and Social Impact2.7 Enterprise Adoption and Investment2.8 Market Drivers and Opportunities2.9 Market Restraints and Challenges2.10 AIoT Value Chain2.10.1 Device Manufacturers2.10.2 Equipment Manufacturers2.10.3 Platform Providers2.10.4 Software and Service Providers2.10.5 User Communities

3.0 AIoT Technology and Market3.1 AIoT Market3.1.1 Equipment and Component3.1.2 Cloud Equipment and Deployment3.1.3 3D Sensing Technology3.1.4 Software and Data Analytics3.1.5 AIoT Platforms3.1.6 Deployment and Services3.2 AIoT Sub-Markets3.2.1 Supporting Device and Connected Objects3.2.2 IoT Data as a Service3.2.3 AI Decisions as a Service3.2.4 APIs and Interoperability3.2.5 Smart Objects3.2.6 Smart City Considerations3.2.7 Industrial Transformation3.2.8 Cognitive Computing and Computer Vision3.2.9 Consumer Appliances3.2.10 Domain-Specific Network Considerations3.2.11 3D Sensing Applications3.2.12 Predictive 3D Design3.3 AIoT Supporting Technologies3.3.1 Cognitive Computing3.3.2 Computer Vision3.3.3 Machine Learning Capabilities and APIs3.3.4 Neural Networks3.3.5 Context-Aware Processing3.4 AIoT Enabling Technologies and Solutions3.4.1 Edge Computing3.4.2 Blockchain Networks3.4.3 Cloud Technologies3.4.4 5G Technologies3.4.5 Digital Twin Technology and Solutions3.4.6 Smart Machines3.4.7 Cloud Robotics3.4.8 Predictive Analytics and Real-Time Processing3.4.8.1 All-Flash Array3.4.8.2 Real-Time Operating Systems3.4.9 Post Event Processing3.4.10 Haptic Technology

4.0 AIoT Applications Analysis4.1 Device Accessibility and Security4.2 Gesture Control and Facial Recognition4.3 Home Automation4.4 Wearable Device4.5 Fleet Management4.6 Intelligent Robots4.7 Augmented Reality Market4.8 Drone Traffic Monitoring4.9 Real-time Public Safety4.10 Yield Monitoring and Soil Monitoring Market4.11 HCM Operation

5.0 Analysis of Important AIoT Companies5.1 Sharp5.2 SAS5.3 DT425.4 Chania Tech Giants: Baidu, Alibaba, and Tencent5.4.1 Baidu5.4.2 Alibaba5.4.3 Tencent5.5 Xiaomi Technology5.6 NVidia5.7 Intel Corporation5.8 Qualcomm5.9 Innodisk5.10 Gopher Protocol5.11 Micron Technology5.12 ShiftPixy5.13 Uptake5.14 C3 IoT5.15 Alluvium5.16 Arundo Analytics5.17 Canvass Analytics5.18 Falkonry5.19 Interactor5.20 Google5.21 Cisco5.22 IBM Corp.5.23 Microsoft Corp.5.24 Apple Inc.5.25 Salesforce Inc.5.26 Infineon Technologies AG5.27 Amazon Inc.5.28 AB Electrolux5.29 ABB Ltd.5.30 AIBrian Inc.5.31 Analog Devices5.32 ARM Limited5.33 Atmel Corporation5.34 Ayla Networks Inc.5.35 Brighterion Inc.5.36 Buddy5.37 CloudMinds5.38 Cumulocity GmBH5.39 Cypress Semiconductor Corp5.40 Digital Reasoning Systems Inc.5.41 Echelon Corporation5.42 Enea AB5.43 Express Logic Inc.5.44 Facebook Inc.5.45 Fujitsu Ltd.5.46 Gemalto N.V.5.47 General Electric5.48 General Vision Inc.5.49 Graphcore5.50 H2O.ai5.51 Haier Group Corporation5.52 Helium Systems5.53 Hewlett Packard Enterprise5.54 Huawei Technologies5.55 Siemens AG5.56 SK Telecom5.57 SoftBank Robotics5.58 SpaceX5.59 SparkCognition5.60 STMicroelectronics5.61 Symantec Corporation5.62 Tellmeplus5.63 Tend.ai5.64 Tesla5.65 Texas Instruments5.66 Thethings.io5.67 Veros Systems5.68 Whirlpool Corporation5.69 Wind River Systems5.70 Juniper Networks5.71 Nokia Corporation5.72 Oracle Corporation5.73 PTC Corporation5.74 Losant IoT5.75 Robert Bosch GmbH5.76 Pepper5.77 Terminus5.78 Tuya Smart

6.0 AIoT Market Analysis and Forecasts 2022 - 20276.1 Global AIoT Market Outlook and Forecasts6.1.1 Aggregate AIoT Market 2022 - 20276.1.2 AIoT Market by Infrastructure and Services 2022 - 20276.1.3 AIoT Market by AI Technology 2022 - 20276.1.4 AIoT Market by Application 2022 - 20276.1.5 AIoT in Consumer, Enterprise, Industrial, and Government 2022 - 20276.1.6 AIoT Market in Cities, Suburbs, and Rural Areas 2022 - 20276.1.7 AIoT in Smart Cities 2022 - 20276.1.8 IoT Data as a Service Market 2022 - 20276.1.9 AI Decisions as a Service Market 2022 - 20276.1.10 Blockchain Support of AIoT 2022 - 20276.1.11 AIoT in 5G Networks 2022 - 20276.2 Regional AIoT Markets 2022 - 20276.3 AIoT Unit Deployment 2022 - 20276.3.1 Global AIoT Unit Deployment 2022 - 20276.3.2 AIoT Unit Deployment by Type 2022 - 20276.3.3 AIoT Unit Deployment by Region 2022 - 2027

7.0 Conclusions and Recommendations

For more information about this report visit https://www.researchandmarkets.com/r/if7nau

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Global Artificial Intelligence of Things Solutions Market Report 2022: AIoT Solutions Improve Operational Effectiveness and the Value of Machine Data...

image:Map detailing ant diversity centers in Africa, Madagascar and Mediterranean regions. view more

Credit: Kass et al., 2022, Science Advances

E. O. Wilson once referred to invertebrates as the little things that run the world, without whom the human species [wouldnt] last more than a few months. Although small, invertebrates have an outsized influence on their environments, pollinating plants, breaking down organic matter and speeding up nutrient cycling. And what they lack in stature, they make up for in diversity. With more than one million known species, insects alone vastly outnumber all other invertebrates and vertebrates combined.

Despite their importance and ubiquity, some of the most basic information about invertebrates, such as where theyre most diverse and how many of them there are, still remains a mystery. This is especially problematic for conservation scientists trying to stave off global insect declines; you cant conserve something if you dont know where to look for it.

In a new study published this Wednesday in the journal Science Advances, researchers used ants as a proxy to help close major knowledge gaps and hopefully begin reversing these declines. Working for more than a decade, researchers from institutions around the world stitched together nearly one-and-a-half million location records from research publications, online databases, museums and scientific field work. They used those records to help produce the largest global map of insect diversity ever created, which they hope will be used to direct future conservation efforts.

This is a massive undertaking for a group known to be a critical ecosystem engineer, said co-author Robert Guralnick, curator of biodiversity informatics at the Florida Museum of Natural History. It represents an enormous effort not only among all the co-authors but the many naturalists who have contributed knowledge about distributions of ants across the globe.

Creating a map large enough to account for the entirety of ant biodiversity presented several logistical challenges. All currently known ant species were included, which numbered at more than 14,000, and each one varied dramatically in the amount of data available.

The majority of the records used contained a description of the location where an ant was collected or spotted but did not always have the precise coordinates needed for mapping. Inferring the extent of an ants range from incomplete records required some clever data wrangling.

Co-author Kenneth Dudley, a research technician with the Okinawa Institute of Science and Technology built a computational workflow to estimate the coordinates from the available data, which also checked the data for errors. This allowed the researchers to make different range estimates for each species of ant depending on how much data was available. For species with less data, they constructed shapes surrounding the data points. For species with more data, the researchers predicted the distribution of each species using statistical models that they tuned to reduce as much noise as possible.

The researchers brought these estimates together to form a global map, divided into a grid of 20 km by 20 km squares, that showed an estimate of the number of ant species per square (called the species richness). They also created a map that showed the number of ant species with very small ranges per square (called the species rarity). In general, species with small ranges are particularly vulnerable to environmental changes.

However, there was another problem to overcomesampling bias.

Some areas of the world that we expected to be centers of diversity were not showing up on our map, but ants in these regions were not well-studied, explained co-first author Jamie Kass, a postdoctoral fellow at the Okinawa Institute of Science and Technology. Other areas were extremely well-sampled, for example parts of the USA and Europe, and this difference in sampling can impact our estimates of global diversity.

So, the researchers utilized machine learning to predict how their diversity would change if they sampled all areas around the world equally, and in doing so, identified areas where they estimate many unknown, unsampled species exist.

This gives us a kind of treasure map, which can guide us to where we should explore next and look for new species with restricted ranges, said senior author Evan Economo, a professor at the Okinawa Institute of Science and Technology.

When the researchers compared the rarity and richness of ant distributions to the comparatively well-studied amphibians, birds, mammals and reptiles, they found that ants were about as different from these vertebrate groups as the vertebrate groups were from each other.

This was unexpected given that ants are evolutionarily highly distant from vertebrates, and it suggests that priority areas for vertebrate diversity may also have a high diversity of invertebrate species. The authors caution, however, that ant biodiversity patterns have unique features. For example, the Mediterranean and East Asia show up as diversity centers for ants more than the vertebrates.

Finally, the researchers looked at how well-protected these areas of high ant diversity are. They found that it was a low percentageonly 15% of the top 10% of ant rarity centers had some sort of legal protection, such as a national park or reserve, which is less than existing protection for vertebrates.

Clearly, we have a lot of work to do to protect these critical areas, Economo concluded.

The global distribution of known and undiscovered ant biodiversity

3-Aug-2022

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

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Researchers use artificial intelligence to create a treasure map of undiscovered ant species - EurekAlert

DER SPIEGEL: Would it even still be realistic at all to outlaw AI-controlled weapons, for instance through a counterpart to the Nuclear Non-Proliferation Treaty, as you suggest in your new book "Machines Behaving Badly?"

Walsh: Well, outlawing them may not always work perfectly, but it can prevent worse. There are quite a few examples of weapons that were initially used but were later outlawed. Think of the widespread use of poison gas in World War I. Or think of blinding lasers, which can blind soldiers. They were outlawed by a United Nations protocol in 1998 and have almost never appeared on battlefields since, even though civilian laser technology is, as we know, widely used. For anti-personnel mines, the ban doesn't work as well, but at least 40 million of them have been destroyed due to outlawing protocols, saving the lives of many children. It's a similar story with cluster munitions: About 99 percent of the stockpile has been destroyed, even though they were used again in Syria. We can ensure that autonomous weapons become unacceptable by stigmatizing them.

DER SPIEGEL: Just four years ago, you predicted a glorious future for AI in your bestseller "It's Alive." What led to your change of heart?

Walsh: Reality happened! We've just seen a lot of unpleasant side effects of AI. Gradually, it became clearer and clearer the extent to which targeted election advertising was being used to sort of hack people's brains into voting for Donald Trump or Brexit, which often goes against their own interests. And through self-learning programs, these attacks have swelled into a perfect storm.

DER SPIEGEL: Does it give you hope that the European Union is currently working on a directive on "Trusted AI"?

Walsh: The EU is really leading the way when it comes to regulating AI. And the European market is big enough that it's worthwhile for global corporations to adapt their AI products to European rules. However, the devil is in the details. Formulating rules is one thing, but the question is how vigorously compliance with the rules will then actually be enforced.

DER SPIEGEL: There are already considerable differences of opinion in the premlinary stages, for example on the question of transparency. Can AI really be transparent and comprehensible or isn't it always, by definition, partly a black box?

Walsh: Transparency is overrated. People aren't transparent either yet we often trust them in our everyday lives. I trust my doctor, for example, even though I'm not a medical professional and can't understand her decisions in detail. And even though I have no idea what's going on inside her. But I do trust the institutions that monitor my doctor.

DER SPIEGEL: How can we make sure that an AI is working according to the rules, even though we don't know its code in detail?

Walsh: This is a tricky problem but it's not limited to AI. Modern companies are also a form of superhuman intelligence. Not even the smartest person on the planet could build an iPhone all by themself. No one is smart enough to design a power plant by themself. Every large corporation interconnects the intelligence of tens of thousands of moderately intelligent employees to form a superhumanly smart collective in other words, a kind of artificial intelligence, as it were.

DER SPIEGEL: Couldn't we just pull the plug on an AI system that misbehaves and that would be the end of it?

Walsh: No way! We can't just turn off the computers of the global banking system, then the global economy would collapse. We can't turn off the computers of air traffic control either, then traffic would collapse. We also can't turn off the computers of power plants, because then we would experience a blackout. We are totally dependent on computers, already today. This dependence is only increasing with AI. We can't get rid of it. We can only try to ensure that the values of AI are in harmony with the values of our society.

DER SPIEGEL: You once correctly predicted that a self-driving car would cause a fatal accident with a cyclist and pedestrian, which is exactly what happened one year later. What do you predict for the next five years?

Walsh: With automatic facial recognition, we will see scandals. The American startup Clearview AI has scraped millions of photos without the consent of the people involved. The company was sued for that, but just keeps going. It's incredible they haven't already been sued into bankruptcy. And one more prediction: deep fakes i.e. movies and photos manipulated with the help of AI on the internet will increase. In a few years, deep fakes will decide an election or trigger a war or even both.

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"Perhaps Even More Dangerous than Nuclear Bombs": Tech Expert Toby Walsh on Artificial Intelligence - DER SPIEGEL International Edition

I cant stop playing with Midjourney. It may signal the end of human creativity or the start of an exciting new era, but heres me, like a monkey at a typewriter chucking random words into the algorithm for an instant hit of this-shouldnt-be-as-good-as-it-is art.

For those who dont know, Midjourney is one of a number of image-generating AI algorithms that can turn written prompts into unworldly pictures, It, along with OpenAIs DALL-E 2, have been having something of a moment in the last month as people get their hands on them and try to push them to their limits. Craiyon - formerly DALL-E mini - is an older, less refined and very much wobblier platform to try too. Its worth having a go just to get a feel for what these algorithms can and cant do - though be warned, the dopamine hit of seeing some silly words turn into something strange, beautiful, terrifying or cool within seconds is quite addictive. A confused dragon playing chess. A happy apple. A rat transcends and perceives the oneness of the universe, pulsing with life. Yes Sir, I can boogie.

Within the LBB editorial team, weve been having lots of discussions about the implications of these art-generating algorithms. What are the legal and IP ramifications for those artists whose works are mined and drawn into the data set (on my Midjourney server, Klimt and HR Giger seem to be the most popular artists to replicate but what of more contemporary artists?). Will the industry use this to find unexpected new looks that go beyond the human creative habits and rules - or will we see content pulled directly from the algorithm? How long will it take for the algorithms to iron out the wonky weirdness that can sometimes take the human face way beyond the uncanny valley to a nightmarish, distorted abyss? What are the keys to writing prompts when you are after something very specific? Why does the algorithm seem to struggle when two different objects are requested in the same image?

Unlike other technologies that have shaken up the advertising industry, these image-generating algorithms are relatively accessible and easy to use (DALL-E 2s waitlist aside). The results are almost instant - and the possibilities, for now, seem limitless. Weve already seen a couple of brands have a go with campaigns that are definitely playing on the novelty and PR-angle of this new technology - and also a few really intriguing art projects too...

Agency: Rethink

The highest profile commercial campaign of the bunch is Rethinks new Heinz campaign. Its a follow up to a previous campaign, in which humans were asked to draw a bottle of ketchup and ended up all drawing a bottle of Heinz. This time around, the team asked Dall-E 2 - and the algorithm, like its human predecessors, couldnt help but create images that looked like Heinz branded bottles (albeit with a funky AI spin). In this case, the AI is used to reinforce and revisit the original idea - but how long will it take before were using AIs to generate ideas for boards or pitch images?

Agency: 10 Days

Animation: Jeremy Higgins

This artsy animated short by art director and designer Jeremy Higgins is a delight and shows how a sequence of similar AI-generated images can serve as frames in a film. The flickering effect ironically gives the animation a very hand-made stop motion style, reminding me of films that use individual oil paintings as frames. Its a really vivid encapsulation of what it feels like to be sucked into a Midjourney rabbit hole too...I also have to tip my hat to Stefan Sagmeister who shared this film on his Instagram account.

For the latest issue of Cosmopolitan, creative Karen X Cheng used Dall-E 2 to create a dramatic and imposing cover - using the prompt: 'a strong female president astronaut warrior walking on the planet Mars, digital art synthwave'. Theres a deep dive into the creative process that also examines some of the potential ramifications of the technology on the Cosmopolitan website thats well worth a read.

Studio:T&DA

Heres a cheeky sixth entry to High Five. This execution is part of a wider summer platform for BT Sport, centred around belief - in this case football pundit Robbie Savage is served up a Dall-E 2 image of striker Aleksander Mitrovi lifting the golden boot. Fulham has just been promoted to the Premier League - but though Robbie can see it, he cant quite believe it.

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High Five: Artificial Intelligence-Generated Campaigns and Experiments | LBBOnline - Little Black Book - LBBonline

Metro- A TikToker asked Dall.E mini, the popular Artificial Intelligence(AI) image generator, what the last selfies on earth would look like and the results are chilling.

In a series of videos titled Asking an Ai to show the last selfie ever taken in the apocalypse, a TikTok account called @robotoverloards, shared the disturbing images.

Each image shows a person taking a selfie set against an apocalyptic background featuring scenes of a nuclear wasteland and catastrophic weather, along with cities burning and even zombies.

Dall.Emini, now renamed toCraiyonis an AI model that can draw images from any text prompt.

The image generator uses artificial intelligence to make photos based on the text you put in.

The image generator is connected to an artificial intelligence that has, for some time, been scraping the web for images to learn what things are. Often it will draw this from the captions attached to the pictures.

What's up everybody? I'm back with my weekly "old man screaming at the clouds" rant about how artificial intelligence is going to wipe our species clean off the planet and it's blatantly telling us this and we continue to ignore it.

Look at this shit.

Does this look like a good time to anybody that's not "metal as fuck"?

No. Absolutely not.

What's worse than the disfiguration in all these beauties' selfies is the devastation in the landscapes behind them.

That shit looks like straight-up nuclear winter to my virgin eyes.

Call it skynet, Boston Robotics, Dall.E mini, whatever the fuck you want. Bottom line is its robot scum and our man Stephen Hawking told us years ago, and Elon Musk is telling us now, that A.I. is going to be the end all be all of homosapiens. That's us. And that's a fucking wrap.

p.s. - the only thing that could make a nuclear/zombie apocalypse worse is this song playing on repeat in your head

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Some Idiot Asked The Dall.E mini Artificial Intelligence Program What The Last Selfies Of Humans Will Look Like And Good News, We're Definitely Headed...