Mediaboss Marketing

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Register today!

Artificial intelligence (AI) technologies are considered essential for internet of things (IoT) hardware for digital operations, such as cameras and automation equipment, according to a survey from Samsara released today.

Samsara, which makes IoT hardware and software, surveyed more than 1,500 operations leaders for its 2022 State of Connected Operations survey, in industries including transportation, manufacturing, construction, field services and food and beverage. The survey was conducted by the independent research firm Lawless Research.

Organizations with physical operations represent more than 40% of global gross domestic product, yet theyve been historically underserved by technology, said Stephen Franchetti, Samsaras CIO.

The IoT market is booming: A March 2020 Insider Intelligence report, for example, predicted that the IoT market size would reach more than $2 trillion by 2027.

The pandemics supply chain interruptions have only underpinned the need for increased investment in IoT. For instance, in late 2021, when the effects of the pandemic were already being felt, the market research firm Gartner discovered industrial enterprises were speeding investments in industrial IoT (IIoT) platforms to improve business and industrial processes.

The IoT and IIoT acronyms are widely used interchangeably, though the IoT is generally applicable to consumer and home devices, such as thermostats and lights, while the IIoT connects physical industrial systems. It also analyzes data returned from those systems for operational improvement.

In industry, the IIoT monitors conditions on, for example, a manufacturing line and predicts which machines will soon need maintenance, among other uses. It unlocks data that was previously housed in data silos, Gartner says.

And its vital to Industry 4.0 adoption, according to McKinsey. The technology holds the key to unlocking drastic reductions in downtimes, new business models, and a better customer experience, the consulting company reports.

Ninety percent of respondents to the Samsara survey said they implemented or plan to implement AI automation technologies connected via the IoT.

AI and automation will play a significant role in the safety and efficiency of physical operations and were already seeing this with our customers today, Franchetti said.

In fact, 95% of those surveyed said AI and automation efforts led to increased employee retention, he said.

Our research found that 31% of respondents benefited from less time spent on repetitive tasks and 40% higher employee engagement as a result of AI and automation, he explained.

Franchetti pointed to Chalk Mountain Services, a transportation and logistics provider in the oilfield services industry. The company rolled out Samsaras AI Dash Cams across its fleet last year to study how drivers safely handled real-world conditions. With that information, the company changed how it rewarded, coached and protected drivers.

The changes translated to a 15% improvement in driver retention and an 86% decrease in preventable accident costs, Franchetti said.

Whats significant about our research is we found that early adopters of digital technologies are proving to be more agile and resilient, he said. While pen-and-paper management is still a stark reality for many companies, they can now clearly see the benefits of digitization from their industry peers.

The combination of AI tools and IoT hardware, particularly when it comes to connecting digital operations, shows no signs of slowing down over the next few years, so organizations should be prepared. These technologies will be widespread soon, and operations leaders should see them as a critical tool in defining their future of work, Franchetti said.

VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Learn more about membership.

See original here:
Big business benefits from artificial intelligence in IoT & IIoT hardware - VentureBeat

NEW ORLEANS (WGNO) Locals will have a chance to try the first craft beer created by an artificial intelligence platform in June.

The AI Blonde Ale will be released at a Launch Party at Nola Brewery on June 20to coincide with CVPR, the worlds premier computer vision event.

Derek Lintern, a brewer at NOLA Brewing said he is excited to have a helping hand when it comes to crafting beer.

Its state-of-the-art technology with the traditional brewing methods, its pretty unique and its a recipe I would have never done normally but I really like how it tastes its very refreshing and very easy drinking Im really happy with it, said Lintern.

The beer was an experiment between The Australian Institute for Machine Learning (AIML) and Barossa Valley Brewing (BVB), founded by DSilva.

DSilva said the idea all started with a beer.

Yeah thats how it started, it started with a beer, Im sure a lot of ideas for companies have started over a beer, this started over a beer and ended up creating a beer and a company which is great, said DSilva.

With the technology, it makes it easier for brewers to produce their products.

About 10 million people review beers every day, there are all these sites and they put it into the world basically to show people what they think of the beer. You do exactly the same thing, there are 5 questions, you scan a QR code answer 5 questions you rate the beer and instead of it going into a website maybe somebody reads maybe not. What happens is artificial intelligence picks that up and goes directly to the producer the AI then takes all that data and manipulates a recipe and then gives it to the producer here this is what the markets thinking, said DSilva.

Derek Lintern said the new technology is not meant to replace brewers, but to help with the process.

The technology helps create the recipe, but the beer is still brewed manually.

The AI beer will only be available in New Orleans for a limited time.

DSilva said he is excited to bring something new to an amazing city. I am so excited I cant think of a better place to launch a beer, said DSilva.

He added, I am really keen for people to get down here and taste the future.

Anyone interested in attending the launch of the new beer can visit NOLA Brewing from 4 p.m. to 10 p.m. on Monday, June 20.

Deep Liquid is also offering 100 customers a free AI beer with their booking with Nola Pedal Barge and Nola Bike Bar.

They are offering $100 discount tickets to any of its private tours.

That includes any of the boat tours in Bayou Bienvenue as well as our pedal bike tour in the Bywater neighborhood.

For more information call (504) 264-1056) for NolaPedalBarge and (504) 308-1041 for NolaBikeBar.

View post:
Taste of the future first artificial intelligence-created craft beer to be released at NOLA Brewing - WGNO New Orleans

Artificial intelligence (AI) is everywhere, and it has an impact on all our lives.

However, years of bold proclamations have resulted in AI becoming overhyped, with reality often falling short of the world-altering promises.

The coming years will be more about practical uses of AI, as businesses ensure return on investment by using AI to address specific cases.

Power Technologys artificial intelligence in power dashboard covers all you need to know about this emerging technology and its impact on the sector.

The power sector, especially in Europe is expected to be impacted due to gas availability and price issues. Utilities will have to look for alternate sources of gas or shift to other sources of generation. AI in power industry usage is likely to be impacted alongside many other corporate tools.

The recent ban on Russian oil and gas supplies will have a varied impact on both the buying and selling nations. Russia is an important source of energy supply for the US and European countries.

Pressure on the Western Bloc to impose more sanctions on Russian energy imports due to civilian killings in Ukraine by Russian Army. Fuel prices (such as for oil) have increased due to talks of a boycott of Russian oil.

Energy companies continue to exit or halt operations in Russia due to increasing pressure to cut ties amid civilian killings in Ukraine.

The electric vehicle and energy storage market will be impacted due to a shortage of nickel and an increase in commodity prices.

The International Energy Agency (IEA) recently published A 10-Point Plan to Reduce the European Unions Reliance on Russian Natural Gas, providing short-term measures and claiming that the EU could cut Russian gas imports by more than 33%.

It also advocates for gas-to-coal switching that could account for the majority of the potential reduction in gas demand.

GlobalData estimates that the global AI platform market will be worth $52bn in 2024, up from $28bn in 2019.

Total spending on AI technology is certainly higher, but it is difficult to estimate. There are two main reasons for this.

Firstly, AI is an intrinsic part of many applications and functions, making it almost impossible to identify revenue explicitly generated by AI.

Secondly, the range of sub-sets and technologies that make up AI can be challenging to locate and track. In general, valuations of the overall AI market range from a few billion dollars to several trillion, depending on the source.

Rather than attempting to size the market, some companies have tried to forecast its economic impact. A PwC report in 2017 estimated that AI would add $15.7 trillion to the global economy by 2030 and boost global GDP by up to 14%.

Global AI platform revenue will reach $52bn by 2024, up from $28bn in 2019.

The competitive landscape for AI is highly fragmented. Companies are investing considerable sums, and there is a swath of innovative AI start-ups that possess innovative expertise. When it comes to the use of artificial intelligence in power industry terms, the competition is constant.

Yet, there is no denying that companies with access to large repositories of data to power AI models are leading the development of AI.

Big Tech excels in this regard, and several tech giants set the overall tone in AI. GAFAM (Google, Apple, Facebook, Amazon, and Microsoft), BAT (Baidu, Alibaba, and Tencent), early-mover IBM, and the two hardware giants Intel and Nvidia are key players within the field.

All industries are feeling the impact of AI, with established incumbents coming up against game-changing disruption from AI platforms developed either by technology giants such as Amazon, Google, and Microsoft; or AI-focused start-ups, such as Lemonade, Trax, and Butterfly Network.

It is not only companies that are making AI investment a priority, but countries as well.

China is the most obvious example, having pledged to become the world leader in AI by 2030, but governments in several nations are backing large spending projects to make sure they do not miss out on AIs positive effects.

The US remains the dominant player in the development of AI technologies, accounting for almost one-third of AI platform revenues in 2019, according to GlobalData estimates.

In a 2019 report from the Center for Data Innovation that compared China, the European Union (EU), and the US in terms of their relative standing in the AI economy, the US came out on top in four out of the six categories of metrics that were examined, including talent, research, development, and hardware.

China led in data and adoption, but its advantage in AI adoption was due to a strong position in a limited number of AI technologies such as facial recognition and smart surveillance.

These are related to the governments extensive use of surveillance and are unlikely to create benefits across the economy.

The US and Europe have a sizable lead in terms of access to high-quality talent and research, and the US has the most AI start-ups and a more developed private equity and venture capital ecosystem.

Therefore, while China is making considerable investments, the USs structural advantages may even enable it to extend its lead.

Discussions about the race for AI dominance tend to focus on the US and China, but other countries are also in the race. Japan has long been at the forefront of AI when it comes to robotics.

The Japanese government released its AI strategy in 2017, and the country boasts a major AI investor in the form of Softbank, which, in 2019, created a $108bn fund to invest in AI companies and opened the Beyond AI institute in Tokyo, a $184m initiative to accelerate AI research in Japan.

In the UK, AI companies secured a record 1.3bn ($1.7bn) of investments in 2019, according to a study by Crunchbase and Tech Nation.

The UK has the second-highest number of AI companies globally, after the US, but most of those companies are small, making them a popular target for acquisition by the tech giants.

Germany is a powerhouse when it comes to the uses of AI in the manufacturing, automotive, and industrial sectors. In 2018, France announced that it would invest 1.5bn ($1.8bn) in AI research until the end of 2022.

Other countries that consider AI an important strategic initiative include South Korea, Russia, Canada, Israel, India, Sweden, Australia, and Singapore.

To best track the emergence and use of artificial intelligence in power, GlobalData tracks patent filings and grants, as well as companies that hold most patents in the field of artificial intelligence.

Power Technology monitors live power company job postings mentioning artificial intelligence or those requiring similar skills.

Jobs postings by power companies mentioning artificial intelligence in recent months. AI jobs tracker in the power sector looks at jobs posted, closed and active in the sector.

As illustrated by the value chain, big data extremely large, diverse data sets that, when analysed in aggregate, reveal patterns, trends, and associations, especially relating to human behaviour and interactions plays a significant role in the development of AI technology.

Big data is produced by all forms of digital activity: phone calls, emails, sensors, payments, social media posts, and much more.

It is also produced by machines, both hardware and software, in the form of machine-to-machine exchanges of data.

These exchanges are particularly important in the IoT (Internet of Things) era, where devices talk to each other without any form of human prompting.

Once collected, big data is typically managed in data centres, either in the public cloud, in corporate data centres, or on end devices. Big data is covered in more detail in our Big Data report.

Continued here:
Artificial intelligence companies leading the way in the power industry - Power Technology

Dublin, June 14, 2022 (GLOBE NEWSWIRE) -- The "Global Artificial Intelligence in Supply Chain Market (2022-2027) by Offering, Technology, Application, Industry, Geography, Competitive Analysis, and the Impact of Covid-19 with Ansoff Analysis" report has been added to ResearchAndMarkets.com's offering.

The Global Artificial Intelligence in Supply Chain Market is estimated to be USD 3.3 Bn in 2022 and is projected to reach USD 10.49 Bn by 2027, growing at a CAGR of 26.02%.

Market Dynamics

Market dynamics are forces that impact the prices and behaviors of the Global Artificial Intelligence in Supply Chain Market stakeholders. These forces create pricing signals which result from the changes in the supply and demand curves for a given product or service. Forces of Market Dynamics may be related to macro-economic and micro-economic factors. There are dynamic market forces other than price, demand, and supply. Human emotions can also drive decisions, influence the market, and create price signals.

As the market dynamics impact the supply and demand curves, decision-makers aim to determine the best way to use various financial tools to stem various strategies for speeding the growth and reducing the risks.

Company Profiles

The report provides a detailed analysis of the competitors in the market. It covers the financial performance analysis for the publicly listed companies in the market. The report also offers detailed information on the companies' recent development and competitive scenario. Some of the companies covered in this report are CH Robinson, FedEx, Google, Koch Industries, Microsoft, NVIDIA, Oracle, Splice Machine, Xilinx, etc.

Countries Studied

Competitive Quadrant

The report includes Competitive Quadrant, a proprietary tool to analyze and evaluate the position of companies based on their Industry Position score and Market Performance score. The tool uses various factors for categorizing the players into four categories. Some of these factors considered for analysis are financial performance over the last 3 years, growth strategies, innovation score, new product launches, investments, growth in market share, etc.

Ansoff Analysis

The report presents a detailed Ansoff matrix analysis for the Global Artificial Intelligence in Supply Chain Market. Ansoff Matrix, also known as Product/Market Expansion Grid, is a strategic tool used to design strategies for the growth of the company. The matrix can be used to evaluate approaches in four strategies viz. Market Development, Market Penetration, Product Development and Diversification. The matrix is also used for risk analysis to understand the risk involved with each approach.

The report analyses the Global Artificial Intelligence in Supply Chain Market using the Ansoff Matrix to provide the best approaches a company can take to improve its market position.

Based on the SWOT analysis conducted on the industry and industry players, the analyst has devised suitable strategies for market growth.

Why buy this report?

Key Topics Covered:

1 Report Description

2 Research Methodology

3 Executive Summary

4 Market Dynamics4.1 Drivers4.1.1 Increasing Focus on Customer-Centric Marketing Strategies4.1.2 Increasing Use of Digital Network and Social Media for Marketing4.1.3 AI Benefits in Customer Acquisition and Lead Generation4.2 Restraints4.2.1 Lack of AI Professionals4.3 Opportunities4.3.1 Growing Cloud-Based Applications Adoption4.3.2 Increasing Scope in Marketing Analysis4.4 Challenges4.4.1 Slow Digitization Rate Affecting in Emerging Markets

5 Market Analysis5.1 Regulatory Scenario5.2 Porter's Five Forces Analysis5.3 Impact of COVID-195.4 Ansoff Matrix Analysis

6 Global Artificial Intelligence in Supply Chain Market, By Offering6.1 Introduction6.2 Hardware6.2.1 Memory6.2.2 Network6.2.3 Processors6.3 Services6.3.1 Deployment & Integration6.3.2 Support & Maintenance6.4 Software

7 Global Artificial Intelligence in Supply Chain Market, By Technology7.1 Introduction7.2 Computer Vision7.3 Context-Aware Computing7.4 Machine Learning7.4.1 Reinforcement Learning7.4.2 Supervised Learning7.4.3 Unsupervised Learning7.5 Natural Language Processing (NLP)

8 Global Artificial Intelligence in Supply Chain Market, By Application8.1 Introduction8.2 Fleet Management8.3 Freight Brokerage8.4 Risk Management8.5 Supply Chain Planning8.6 Virtual Assistant8.7 Warehouse Management

9 Global Artificial Intelligence in Supply Chain Market, By Industry9.1 Introduction9.2 Aerospace9.3 Automotive9.4 Consumer-Packaged Goods9.5 Food & Beverages9.6 Healthcare9.7 Manufacturing9.8 Retail

10 Americas' Artificial Intelligence in Supply Chain Market10.1 Introduction10.2 Argentina10.3 Brazil10.4 Canada10.5 Chile10.6 Colombia10.7 Mexico10.8 Peru10.9 United States10.10 Rest of Americas

11 Europe's Artificial Intelligence in Supply Chain Market11.1 Introduction11.2 Austria11.3 Belgium11.4 Denmark11.5 Finland11.6 France11.7 Germany11.8 Italy11.9 Netherlands11.10 Norway11.11 Poland11.12 Russia11.13 Spain11.14 Sweden11.15 Switzerland11.16 United Kingdom11.17 Rest of Europe

12 Middle East and Africa's Artificial Intelligence in Supply Chain Market12.1 Introduction12.2 Egypt12.3 Israel12.4 Qatar12.5 Saudi Arabia12.6 South Africa12.7 United Arab Emirates12.8 Rest of MEA

13 APAC's Artificial Intelligence in Supply Chain Market13.1 Introduction13.2 Australia13.3 Bangladesh13.4 China13.5 India13.6 Indonesia13.7 Japan13.8 Malaysia13.9 Philippines13.10 Singapore13.11 South Korea13.12 Sri Lanka13.13 Thailand13.14 Taiwan13.15 Rest of Asia-Pacific

14 Competitive Landscape14.1 Competitive Quadrant14.2 Market Share Analysis14.3 Strategic Initiatives14.3.1 M&A and Investments14.3.2 Partnerships and Collaborations14.3.3 Product Developments and Improvements

15 Company Profiles 15.1 Alibaba Group Holding15.2 Amazoncom15.3 American Software15.4 CH Robinson15.5 C315.6 Deutsche Post15.7 E2open15.8 Echo GlobalLogistics15.9 FedEx 15.10 Google 15.11 HAVI Group15.12 Intel 15.13 IBM15.14 Koch Industries 15.15 Microsoft 15.16 NVIDIA15.17 Oracle 15.18 Project4415.19 Relex Solution15.20 Samsung Electronics15.21 SAP America15.22 Splice Machine15.23 TTEC Holdings15.24 Xilinx

16 Appendix

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

View original post here:
The Worldwide Artificial Intelligence in Supply Chain Industry is Expected to Reach $10 Billion by 2027 - GlobeNewswire

image:Anant Madabhushi view more

Credit: CWRU

CLEVELANDCollaboration between pharmaceutical companies and the Center for Computational Imaging and Personalized Diagnostics (CCIPD) at Case Western Reserve University has led to the development of artificial intelligence (AI) tools to benefit patients with non-small cell lung cancer (NSCLC) based on an analysis of routine tissue biopsy images, according to new research.

This year, more than 236,000 adults in the United States will be diagnosed with lung cancerabout 82% of them with non-small cell lung cancer, according to the American Society of Clinical Oncology.

Researchers at the CCIPD used AI to identify biomarkers from biopsy images for patients with NSCLC, as well as gynecologic cancers, that help predict the response to immunotherapy and clinical outcomes, including survival.

We have shown that the spatial interplay of features relating to the cancer nuclei and tumor-infiltrating lymphocytes drives a signal that allows us to identify which patients are going to respond to immunotherapy and which ones will not, said Anant Madabhushi, CCIPD director and Donnell Institute Professor of Biomedical Engineering at Case Western Reserve.

The study was published this month in the journal Science Advances.

Immunotherapy is expensive, and studies show that only 20-30% of patients respond to the treatment, according to National Institutes of Health and other sources. These findings validate that the AI technologies developed by the CCIPD can help clinicians determine how best to treat patients with NSCLC and gynecologic cancers, including cervical, endometrial and ovarian cancer, Madabhushi said.

The study, drawn from a retrospective analysis of data, also revealed new biomarker information regarding a protein called PD-L1 that helps prevent immune cells from attacking non-harmful cells in the body.

Patients with high PD-L1 often receive immunotherapy as part of their treatment for NSCLC, while patients with low PD-L1 are often not offered immunotherapy, or its coupled with chemotherapy.

Our work has identified a subset of patients with low PD-L1 who respond very well to immunotherapy and may not require immunotherapy plus chemotherapy, Madabhushi said. This could potentially help these patients avoid the toxicity associated with chemotherapy while also having a favorable response to immunotherapy.

The multi-site, multi-institutional study examined three common immunotherapy drugs (called checkpoint inhibitor agents) that target PD-L1: atezolizumab, nivolumab and pembrolizumab. The AI tools consistently predicted the response and clinical outcomes for all three immunotherapies.

The study is part of broader research conducted at CCIPD to develop and apply novel AI and machine-learning approaches to diagnose and predict the therapy response for various diseases and cancers, including breast, prostate, head and neck, brain, colorectal, gynecologic and skin.

The study coincides with Case Western Reserve recently signing a license agreement with Picture Health to commercialize AI tools to benefit patients with NSCLC and other cancers.

###

Case Western Reserve University is one of the country's leading private research institutions. Located in Cleveland, we offer a unique combination of forward-thinking educational opportunities in an inspiring cultural setting. Our leading-edge faculty engage in teaching and research in a collaborative, hands-on environment. Our nationally recognized programs include arts and sciences, dental medicine, engineering, law, management, medicine, nursing and social work. About 5,800 undergraduate and 6,300 graduate students comprise our student body. Visitcase.eduto see how Case Western Reserve thinks beyond the possible.

Spatial interplay patterns of cancer nuclei and tumor-infiltrating lymphocytes (TILs) predict clinical benefit for immune checkpoint inhibitors

1-Jun-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.

Read the original:
Artificial intelligence tool predicts response to immunotherapy in lung and gynecologic cancer patients - EurekAlert