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Pentagon Names Chief Digital and Artificial Intelligence Officer - Nextgov

But few people had enough mastery of the language to manually transcribe the audio. Inspired by voice assistants like Siri, Mahelona began looking into natural-language processing. Teaching the computer to speak Mori became absolutely necessary, Jones says.

But Te Hiku faced a chicken-and-egg problem. To build a te reo speech recognition model, it needed an abundance of transcribed audio. To transcribe the audio, it needed the advanced speakers whose small numbers it was trying to compensate for in the first place. There were, however, plenty of beginning and intermediate speakers who could read te reo words aloud better than they could recognize them in a recording.

So Jones and Mahelona, along with Te Hiku COO Suzanne Duncan, devised a clever solution: rather than transcribe existing audio, they would ask people to record themselves reading a series of sentences designed to capture the full range of sounds in the language. To an algorithm, the resulting data set would serve the same function. From those thousands of pairs of spoken and written sentences, it would learn to recognize te reo syllables in audio.

The team announced a competition. Jones, Mahelona, and Duncan contacted every Mori community group they could find, including traditional kapa haka dance troupes and waka ama canoe-racing teams, and revealed that whichever one submitted the most recordings would win a $5,000 grand prize.

The entire community mobilized. Competition got heated. One Mori community member, Te Mihinga Komene, an educator and advocate of using digital technologies to revitalize te reo, recorded 4,000 phrases alone.

Money wasnt the only motivator. People bought into Te Hikus vision and trusted it to safeguard their data. Te Hiku Media said, What you give us, were here as kaitiaki [guardians]. We look after it, but you still own your audio, says Te Mihinga. Thats important. Those values define who we are as Mori.

Within 10 days, Te Hiku amassed 310 hours of speech-text pairs from some 200,000 recordings made by roughly 2,500 people, an unheard-of level of engagement among researchers in the AI community. No one couldve done it except for a Mori organization, says Caleb Moses, a Mori data scientist who joined the project after learning about it on social media.

The amount of data was still small compared with the thousands of hours typically used to train English language models, but it was enough to get started. Using the data to bootstrap an existing open-source model from the Mozilla Foundation, Te Hiku created its very first te reo speech recognition model with 86% accuracy.

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A new vision of artificial intelligence for the people - MIT Technology Review

NEW YORK, April 26, 2022 (GLOBE NEWSWIRE) -- BrainBox AI, a pioneer in autonomous artificial intelligence, today announces its agreement with Mountain Development Corp. to bring its cutting-edge technology to two office buildings in New Jersey. BrainBox AIs technology will manage the HVAC controls of 140,000 sq. ft for the real estate company, making the buildings smarter and greener while improving tenant comfort.

Mountain Development Corp., a leader in Class A office properties, is a full-service real estate company and is renown in the New Jersey commercial real estate circle. In early 2021, BrainBox AIs technology was installed at 26 Main St in Chatham, New Jersey, a 65,000 sq. ft. premium office space and 777 Passaic Avenue, a 75,000 sq. ft. Class A building in Clifton, New Jersey. Initial results have shown meaningful energy savings and operating cost reductions.

Our goal is to make a tangible impact on the commercial real estate industry while mitigating the impact of buildings on climate change, said Sam Ramadori, Chief Executive Officer of BrainBox AI. Our technology enables building owners and operators to save money and the environment simultaneously, a win-win solution for all. We are excited to work with one of the biggest players in New Jerseys real estate industry to make buildings more intelligent and save Mountain Development Corp. money both in the short and long term.

BrainBox AI creates value with savings in energy costs of up to 25%, up to 40% reduction in carbon footprint and improved occupant comfort. Building operators can also see an extension in the service life of the HVAC equipment with lower runtimes up to 50%. Its scalability and ease of implementation allow for both individual building and portfolio-wide impact.

Were constantly seeking out new and innovative ways to increase our profit outcome through the enhancement of our building operations. Its crucial that we do so while also improving our tenants overall experience, which can be a fine line at times. Were thrilled to team up with BrainBox AI as they allow us to deliver on these vital operational objectives. Their technology yields positive results in reducing our energy spend while simultaneously improving the tenant experience. Moreover, theyre reducing our carbon emissions and helping the real estate industry move one step closer to our net-zero carbon goals." said Nicholas Mazza, Director of Operations at Mountain Development Corp.

This announcement comes as BrainBox AI continues its expansion across the Northeast and Mid-Atlantic United States, with the Company recently announcing the inaugural installation of its real estate technology in New York City.

About BrainBox AI

Founded in 2017, BrainBox AI was created to address the dilemma currently facing the built environment, its energy consumption and significant contribution to climate change. As innovators of the global energy transition, BrainBox AIs game-changing HVAC technology leverages AI to make buildings smarter, greener, and more efficient. Working together with our trusted global partners, BrainBox AI supports real estate clients in various sectors, including office buildings, hotels, commercial retail, grocery stores, airports, and more.

Headquartered in Montreal, Canada, a global AI hub, our workforce of over 150 employees, bring with them talent from all sectors with the common thread of being in business to heal our planet.BrainBox AI works in collaboration with research partners including the US Department of Energys National Renewable Energy Laboratory (NREL), the Institute for Data Valorization (IVADO) as well as educational institutions including Montreals Institute for Learning Algorithms (MILA) and McGill University. For more information visit: http://www.brainboxai.com

About Mountain Development Corp.

Founded in 1979, Mountain Development Corp. (MDC) is a full-service real estate company with more than 40 years experience developing, acquiring, building, repositioning, managing, leasing and financing commercial property. MDC is an active acquirer of a broad range of opportunistic and value-added real estate investments, together with select core projects, capable of generating attractive, risk-adjusted returns for both its principals and select partners.

For media inquiries:

BrainBox AIRebecca BenderMontieth & Companyrbender@montiethco.com

Mountain Development Corp.Nicholas Mazza, RPADirector of Operations nmazza@mountaindevelopment.com

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BrainBox AI Brings Artificial Intelligence to Mountain Development Corp. with Installations in Two of its Commercial Office Buildings - GlobeNewswire

From mobile work to security and maintenance, perhaps no company has done more for the advancement of technology in todays society than SkyNet, a promising start up out of Austin, Texas that has made great strides during the COVID-19 pandemic. Last year, their T-400 model of home assistant swept the country, combining at home personal assistants with a walking talking android that actually helped with chores and tasks around the house.

We had the opportunity to sit down with Barry Snow, the CEO of the skyrocketing company, about SkyNets future and some of the backlash to what some have called unnecessarily violent home assistants.

~~~~

Hard Drive: Hey Barry, thanks for doing this interview.

Barry Snow: Oh hey man, no problem at all. Thanks for having me. Can I have one of those waters?

HD: Yeah, go ahead. So, your company was already gaining steam a few years ago, but it really seems that during the pandemic you pulled ahead of a lot of your peers with your home androids. Do you attribute this to the pandemic, or do you think SkyNet was going to be a major player in artificial intelligence and home securities no matter what?

BS: Man, this is good water. Thats a great question. I look at it this way SkyNet has already made many successful pivots in its short existence, which is the key to longevity in just about any industry.

A lot of people forget, but do you remember in 1992 when our former Director of Special Projects Miles Dyson blew our old building right to hell? A lot of people said we wouldnt recover from that, but we have. We built a new headquarters, and instead of trying to recreate weird robot shit that we found in an explosion one day, we started focusing on our own work with AI, alloy production, and laserbeams.

HD: I did want to ask you about the laser beams. A lot of people have said theres not a very convincing reason why the T-500 models should come equipped with lasers for opening packages and tricky bags of chips. Would you like to respond to that?

BS: Yes, and thank you for allowing me to do so. Look, weve all read the stories and seen the news clips. House fire in Tacoma. Bridge lasered in half in Miami. Just horrible stuff. But, to think that things like houses catching on fire and bridges falling apart like butter werent happening before we entered the corporate world and started putting lasers on Roombas is a little nave now, isnt it? Our work is so vast that it feels really manipulative to focus on the handful of unfortunate incidents when in fact over 10 percent of households now have a Skynet assistant in their homes. Youre gonna have a few house fires!

The future models are going to be even more exciting. The T-800s are a little ways away, but they can do anything you want. Anything. You can say, Hey T-800, go to the store and get me some soda, and let me tell you something, this thing is not coming back to your house without a big ol bottle of soda. Theyll follow any orders you want!

HD: Wow, you seem really excited about these T-800s.

BS: Oh yeah, I really really am. When you see them, youll understand. Were calling them Terminators.

The new Skynet T-800. Terminate housework!

You like that? I came up with that.

HD: Thats really good! Getting back to them doing anything you tell them to, certainly there are limits to that though, right? You wouldnt want to be able to tell your SkyNet Home Assistant to go hurt somebody or something.

BS: Hm. Thats interesting. Hadnt thought of that.

[This was followed by a long and uncomfortable pause.]

This is really good water, by the way.

Were there any more questions?

HD: Um. Whats next for SkyNet?

BS: The world! No, no, Im just joking. Were really excited about getting the Housework Terminators out into homes over the next few years. We just have to iron out a few details. We learned from product testing that we have to make these things turn on their masters if they try to have sex with them. You can warn them, and tell them about the erotic auto-defense programs weve implemented, but until they get slugged in the mouth theyre just not gonna stop trying to fuck these things. So thats not cool. Thats been a bit of a hiccup.

But, were really close to solving that, and then I think were off to the races! Were working on some interesting things for the T-1000 too, like a new liquid metal android that does shit you wouldnt believe. He can make his arm into a can opener, a wine bottle opener, an envelope opener, a lot of little things that we just couldnt quite do with the 800s. Which are still incredible, by the way. But the T-1000s are gonna blow your mind.

So yeah, the liquid metal, and were also looking at ways to disrupt the fabric of time, and we are really trying to get our laser guns a little more promo, to be honest. Do you want one of our laser gun prototypes?

HD: Sure!

BS: Here you go.

HD: Wow, awesome. Thank you. Do I charge this, or?

BS: Yeah, USB. No big whoop.

Im glad youre excited about it. A lot of people have warned us against some of our recent pursuits, saying that the writing on the wall couldnt be more ominous and that these things couldnt possibly benefit humanity. But hey, you know our slogan around here, SkyNet Judgment Day is Coming and It Will Be All Our Fault.

Hmm, actually maybe that doesnt apply here.

HD: No, not really. Its snappy, though. Say, your robot assistant is frightening me. Would you like to say anything to conclude this interview?

BS: Kids, dont forget to ask for a T-800 for Christmas! Thank you for speaking with me. Oh, dont forget your laser gun, Mark.

HD: Oh whoops, thank you.

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Exclusive: We Interviewed the CEO of SkyNet About Their Recent Breakthroughs in Artificial Intelligence - Hard Drive

From Accenture:

A team of volunteers from Accenture has built an artificial intelligence (AI)-based solution that helps extract information on victims of Nazi persecution from documents in the Arolsen Archives 40 times faster than previous efforts.

The Arolsen Archives preserve the worlds largest collection of documents on Nazi persecution 110 million documents and digital objects, a portion of which are part of UNESCOs Memory of the World program to keep the memory of the crimes of the German terror regime alive. An essential part of the Archives work is to make these documents accessible to all who wish to search for traces of Holocaust victims and survivors, persecution of minorities and forced labor.

Every document maintained in the archives needs to be reviewed and its information (e.g., the family name and birth date on a prisoner registration form) put into a database. To facilitate this process, the Arolsen Archives established #everynamecounts, a crowdsourcing project for volunteers to extract information from documents manually.

Translating, reading, transcribing, cataloging and validating these documents by hand could take decades. Each document is indexed independently by three volunteers and, if the entries dont match, reviewed for accuracy by an Arolsen Archives employee. In effect, it can take up to four people to index and validate four documents in one hour.

[Clip]

Even though the AI does the heavy lifting, human oversight of the process remains important not just to ensure accuracy but also to keep the AI solution learning. By reviewing and correcting information, volunteers teach the solution to recognize handwriting characters and abbreviations that were typical for the time. Thanks to their inputs, the AI has gradually improved its precision by 10% within the form field of mothers last name. For the religion field, the AI is now operating at 99% confidence.

Since Accenture implemented the AI solution in December 2021, the solution has indexed more than 160,000 names of Nazi persecution victims, extracted information from more than 18,000 documents, and clustered more than 60,000 documents into similar groups to improve identification and analysis

Learn More, Read the Complete Announcement

See Also: 26 Million Documents About Victims of Nazi Persecution Online (April 16, 2020)

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Arolsen Archives' #everynamecounts Project Uses Artificial Intelligence to Help Uncover Information on Victims of Nazi Persecution - LJ INFOdocket

April 26, 2022 06:01 AM Eastern Daylight Time

WASHINGTON--(BUSINESS WIRE)--Stanford Institute for Human-Centered Artificial Intelligence:

What:

Presented by the U.S. Department of Commerce, National Institute of Standards and Technology, Stanford Institute for Human-Centered Artificial Intelligence (HAI) and FinRegLab, the Symposium will feature a group of presenters and panelists working to develop policies and frameworks to evaluate and assess the goals of improving the trustworthiness, inclusiveness, and equity of artificial intelligence (AI) deployment.

The Symposium is designed to address how AI relates to ensuring inclusive economic growth, supporting diversity and financial inclusion, and mitigating risks such as bias and unfairness.

When:

April 27, 2022 from 9:00am-4:00pm ET

Where:

Auditorium, Herbert C. Hoover Building, 1401 Constitution Ave. NW, Washington, D.C. 20230

Who:

Leaders in government, industry, civil society organizations, and academia will explore potential opportunities and challenges posed by AI deployment across different economic sectors, with a particular focus on financial services and health data. Speakers include Don Graves, Deputy Secretary of Commerce; Joni Ernst, Iowa Senator; Michael Hsu, Acting Comptroller of the Currency for the Office of the Comptroller of the Currency; Susan Athey, Professor at Stanford Graduate School of Business and Associate Director of HAI; and Daniel E. Ho, Professor of Law and Political Science at Stanford and Associate Director of HAI.

Contact:

Accredited members of the press interested in attending the Symposium should contact Jeremy Edwards at JEdwards@doc.gov or Stacy Pea at stacy.pena@stanford.edu.

For more information on the Symposium, please visit the event page here.

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Artificial Intelligence & the Economy: Charting a Path for Responsible and Inclusive AI U.S. Department of Commerce, National Institute of...

Alzheimer's disease is the main cause of dementia worldwide. Although there is no cure, early detection is considered crucial for being able to develop effective treatments that act before its progress is irreversible.

Mild cognitive impairment is a phase that precedes the disease, but not everyone who suffers from it ends up developing Alzheimer's. A study led by scientists at the Universitat Oberta de Catalunya (UOC) and published in the IEEE Journal of Biomedical and Health Informatics, has succeeded in precisely distinguishing between people whose deterioration is stable and those who will progress to having the disease. The new technique, which uses specific artificial intelligence methods to compare magnetic resonance images, is more effective than the other methods currently in use.

Fine-tuning the diagnosis

Alzheimer's disease affects more than 50 million people worldwide, and the ageing of the population means that there may be many more sufferers in the coming decades. Although it usually develops without any symptoms over many years, it is generally preceded by what is known as mild cognitive impairment, which is much milder than the impairment presented by people with Alzheimer's, but more severe than would be expected for someone of their age. "These patients may progress and worsen or remain in the same condition as time passes. That is why it is important to distinguish between progressive and stable cognitive impairment in order to prevent the rapid progression of the disease," said Mona Ashtari-Majlan, a UOC researcher in the AI for Human Wellbeing (AIWELL) group, which is affiliated to the eHealth Center and the Faculty of Computer Science, Multimedia and Telecommunications. She is a student on the doctoral programme in Network and Information Technologies, supervised by David Masip, and the lead author of the article.

Identifying these cases correctly could help to improve the quality of clinical trials used to test treatments, which increasingly seek to target the initial phases of the disease. To do so, the researchers used a method involving a multi-stream convolutional neural network, which is a technique based on artificial intelligence and deep learning that is very useful for image recognition and classification.

"We first compared MRIs from patients with Alzheimer's disease and healthy people to find distinct landmarks," explained Ashtari-Majlan. After training the system, they fine-tuned the proposed architecture with resonance images from people who had already been diagnosed with stable or progressive cognitive impairment with much smaller differences. In total, almost 700 images from publicly available datasets were used.

According to Ashtari-Majlan, the process "overcomes the complexity of learning caused by the subtle structural changes that occur between the two forms of mild cognitive impairment, which are much smaller than those between a normal brain and a brain affected by the disease. Furthermore, the proposed method could address the small sample size problem, where the number of MRIs for mild cognitive impairment cases is lower than for Alzheimer's."

The new method enables the two forms of mild cognitive impairment to be distinguished and classified with an accuracy rate close to 85%. "The evaluation criteria show that our proposed method outperforms existing ones," she said, including more conventional and other deep learning-based methods, even when they are combined with biomarkers such as age and cognitive tests. In addition, "we can share our implementation with anyone wishing to reproduce the results and compare their methods with ours. We believe that this method can help professionals to expand the research," she concluded.

This research contributes to achieving Sustainable Development Goal (SDG) 3, Ensure healthy lives and well-being for all at all ages.

UOC R&I

The UOC's research and innovation (R&I) is helping overcome pressing challenges faced by global societies in the 21st century, by studyinginteractions between technology and human & social scienceswith a specific focus on thenetwork society, e-learning and e-health.

Over 500 researchers and51 research groupswork among the University'sseven faculties and two research centres: the Internet Interdisciplinary Institute (IN3) and the eHealth Center (eHC).

The University also cultivatesonline learning innovations at its eLearning Innovation Center (eLinC), as well asUOC community entrepreneurship and knowledge transfervia theHubbikplatform.

The United Nations'2030 Agendafor Sustainable Development andopen knowledgeserve as strategic pillars for the UOC's teaching, research and innovation. More information:research.uoc.edu#UOC25years

IEEE Journal of Biomedical and Health Informatics

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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Artificial intelligence aids to diagnose mild cognitive impairment that progresses to Alzheimer's - EurekAlert

New York, April 25, 2022 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Artificial Intelligence in Manufacturing Market by Offering, Industry, Application, Technology, & Region - Global Forecast to 2027" - https://www.reportlinker.com/p05048444/?utm_source=GNW GPU/CPU manufacturers, such as NVIDIA, AMD, Intel, Qualcomm, Huawei, and Samsung, have significantly invested in AI hardware for the development of chipsets that are compatible with AI-based technologies and solutions.

Apart from CPUs and GPUs, application-specific integrated circuits (ASICs) and field-programmable gate arrays (FPGAs) are being developed for AI applications. For instance, Google has built a new ASIC called tensor processing unit (TPU).Compute-intensive chipset is among the critical parameters for processing AI algorithms; the faster the chipset, the quicker it can process data required to create an AI system.Currently, AI chipsets are mostly deployed in data centers/high-end servers as end computers are currently incapable of handling such huge workloads and do not have enough power and time frame.

NVIDIA has a range of GPUs that offer GPU memory bandwidth based on application. For example, GeForce GTX Titan X offers memory bandwidth of 336.5 GB/s and is mostly deployed in desktops, while Tesla V100 16 GB offers memory bandwidth of 900 GB/s and is used in AI applications.

Application of AI for intelligent business processesRigid and rule-based software currently governs a majority of business processes in an organization, offering limited abilities to handle critical problems.These processes are time-consuming and require employees to work on repetitive tasks, hampering the productivity of the employees and the overall performance of the organization.

Machine Learning and Natural Language Processing tools generated on AI platforms can help enterprises overcome such challenges with self-learning algorithms, which can reveal new patterns and solutions.Most organizations use enterprise software, which make the use of rule-based processing to automate business processes.

This task-based automation has helped organizations in improving their productivity in a few specific processes but such rule-based software cannot self-learn and improve with experience.The integration of AI tools, such as NLP and ML, generated on AI platform for enterprise software systems, enable the software to gain mastery while solving individual processes.

This software would be able to provide improved performance and productivity to enterprises over time, instead of providing a one-time boost. All these factors are said to have fueled the demand for intelligent business processes and act as opportunities for the growth of the AI in manufacturing market.

Increasing global demand for energy and power is influencing energy and power companies to adopt AI-based solutions

The increasing global demand for energy and power is influencing energy and power companies to adopt AI-based solutions that can help boost production output with minimum maintenance and reduced downtime.Maintenance and inspection are the major issues, along with material movement, in a thermal plant as the material needs to travel a long distance inside the plant.

Besides, equipment used in this industry, such as turbines, conveyer belts, grids, and voltage transformers, are costly.Moreover, there are issues related to fuel mix, ambient temperature, air quality, moisture, load, weather forecast models, and market pricing in the power industry.

By using AI-based technologies, these issues can be resolved and predicted in the early stages.AI-based technologies used in energy plants comprise physics insights, engineering design knowledge, and new inspection technologies, which are ideal for predictive maintenance and machinery inspections.

The AI technologies work in 2 layers. First, by recognizing the pattern, and second, by learning the models. Early-stage pattern recognition notifies about impending failures.

The breakup of primaries conducted during the study is depicted below: By Company Type: Tier 1 55 %, Tier 2 25%, and Tier 3 20% By Designation: C-Level Executives 60%, Directors 20%, and Others 20% By Region: North America 40%, Europe 30%, APAC 20%, South America 7% and Middle East and Africa - 3%The key players operating in the artificial intelligence in Manufacturing market include NVIDIA (US), IBM (US), Intel (US), Siemens (Germany), General Electric (US), Google (US), Microsoft Corporation (US), and Micron Technology (US).

Research CoverageThe report segments the Artificial intelligence in Manufacturing market and forecasts its size, by value, based on region (North America, Europe, Asia Pacific, and RoW), Application ( predictive maintenance and machinery inspection, inventory optimization, production planning, field services, quality control, cybersecurity, industrial robots and reclamation), Technology (machine learning, natural language processing, context-aware computing, computer vision), Offering ( hardware, software and services) and Industry (automotive, energy & power, semiconductor & electronics, pharmaceutical, heavy metals & machine manufacturing, food & beverage and others (textile, aerospace and mining)).The report also provides a comprehensive review of market drivers, restraints, opportunities, and challenges in the head-up display market.

The report also covers qualitative aspects in addition to the quantitative aspects of these markets.

Key Benefits of Buying This Report This report includes market statistics pertaining to the offering, technology, industry, application, and region. An in-depth value chain analysis has been done to provide deep insight into the artificial intelligence in manufacturing market. Major market drivers, restraints, challenges, and opportunities have been detailed in this report. Illustrative segmentation, analyses, and forecasts for the market based on offering, technology, industry, application, and region have been conducted to provide an overall view of the the artificial intelligence in manufacturing market. The report includes an in-depth analysis and ranking of key players.Read the full report: https://www.reportlinker.com/p05048444/?utm_source=GNW

About ReportlinkerReportLinker is an award-winning market research solution. Reportlinker finds and organizes the latest industry data so you get all the market research you need - instantly, in one place.

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Artificial intelligence in Manufacturing market size is valued at USD 2.3 billion in 2022 and is anticipated to be USD 16.3 billion by 2027; growing...

Photo by Marta Branco on Pexels

This post contains sponsored advertising content. This content is for informational purposes only and is not intended to be investing advice.

The cryptocurrency boom of 2021 changed lives.

The markets unprecedented rise allowed a substitute teacher to buy her dream home and travel the world and turned ordinary 20-year-olds into multimillionaires.

Case studies like these are part of the reason why 16% of Americans invested in cryptocurrency in 2021 and why enterprises like Marathon Digital Holdings Inc. MARA and Riot Blockchain Inc. RIOT continue their bullish stance on crypto mining.

But there are holes in the cryptocurrency story. Operating under a pseudonym, Jake tells BBC that he lost millions of pounds trading cryptocurrency and is in treatment at one of the only hospitals in the United Kingdom for crypto gambling.

Because of the human tendency to advertise wins while covering up losses, there are likely plenty more Jakes in the cryptocurrency boom. The truth is: Trading is as tough and unforgiving as it is generous and rewarding. Without the right guidance, amateurs are likely to get whipsawed between these two extremes, often relying purely on luck to come out ahead.

Vantage Point is an artificial intelligence (AI) system that is meant to help predict major market reversals in advance. Armed with a proven accuracy rating of up to 87.4%, the system reportedly works with cryptocurrencies, too.

As the King of Cryptocurrencies, Bitcoins BTC/USD incredible rise in 2021 set the stage for many of the smaller cryptocurrencies as well as businesses and technology sectors tied to its value. Satoshis brainchild rose from approximately $28,000 per Bitcoin to a high of roughly $69,000 between January and December 2021, experiencing an incredible 150% rise.

Want to learn more about BTCs forecast? Click here

If speculators rejoiced over Bitcoins rise, they wouldve likely been delirious over the rise of Dogecoin DOGE/USD. Following the trend set by Bitcoin, the meme-sponsored cryptocurrency rose from $0.0045 a coin to $0.7549 a coin in a five-month period. This change represented a hold your breath 16,963% appreciation in the assets value. A $1 investment in Doge throughout this move wouldve turned into roughly $169.

Curious to see where DOGE is headed next? Click here

Cardano ADA/USD joined Bitcoin and Dogecoin in the 2021 bull market, exhibiting yet another incredible rise in the cryptocurrency space. Between January and September 2021, the assets price increased by 1,793%, giving early investors a return nearly 18 times greater than their principal in a nine-month period.

Will ADA trend bullish or bearish? Learn more.

If youre interested in joining the 35,000 investors who have reportedly benefitted from VantagePoints trading service, you can join a free trading webinar here.

This post contains sponsored advertising content. This content is for informational purposes only and is not intended to be investing advice.

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Could This Artificial Intelligence Software Help Predict The Next Crypto Move? - Benzinga

DUBLIN--(BUSINESS WIRE)--The "Global Artificial Intelligence of Things (AIoT) in Telecommunications Growth Opportunities" report has been added to ResearchAndMarkets.com's offering.

This report examines the strategic position of telecommunication service providers (TSPs) in using artificial intelligence (AI) and the Internet of Things (IoT) to offer enterprises Artificial Intelligence of Things (AIoT) solutions. TSPs play a vital role in deploying enterprise AIoT solutions amid the increasing deployment of 5G networks, edge infrastructure capabilities, and location-based data at their disposal.

Given their network and connectivity capabilities and AI and services focus, TSPs are in a unique position to monetize AIoT opportunities. They increasingly offer solutions by industry vertical as part of their AIoT focus.

The report highlights TSPs' role as system integrators to provide value-added solutions and services to progress beyond connectivity and move up the value chain.

The report provides stakeholders insights by identifying AI growth drivers that will facilitate AIoT solutions deployment and opportunities in AI advisory and consulting services, edge infrastructure adoption, and building specific industry vertical solutions.

Key Topics Covered:

1. Strategic Imperatives

2. Growth Environment

3. Growth Opportunity Analysis

4. Growth Opportunity Universe

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/3zzes1

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