The White House is pushing to dedicate an additional billion dollars to fund artificial intelligence research, effectively doubling the budget for that purpose outside of Defense Department spending, Reuters reported today, citing people briefed on the plan. Investment in quantum computing would also receive a major boost.

The 2021 budget proposal would reportedly increase AI R&D funding to nearly $2 billion, and quantum to about $860 million, over the next two years.

The U.S. is engaged in what some describe as a race with China in the field of AI, though unlike most races this one has no real finish line. Instead, any serious lead means opportunities in business and military applications that may grow to become the next globe-spanning monopoly, a la Google or Facebook which themselves, as quasi-sovereign powers, invest heavily in the field for their own purposes.

Simply doubling the budget isnt a magic bullet to take the lead, if anyone can be said to have it, but deploying AI to new fields is not without cost and an increase in grants and other direct funding will almost certainly enable the technology to be applied more widely. Machine learning has proven to be useful for a huge variety of purposes and for many researchers and labs is a natural next step but expertise and processing power cost money.

Its not clear how the funds would be disbursed; Its possible existing programs like federal Small Business Innovation Research awards could be expanded with this topic in mind, or direct funding to research centers like the National Labs could be increased.

Research into quantum computing and related fields is likewise costly. Googles milestone last fall of achieving quantum superiority, or so the claim goes, is only the beginning for the science and neither the hardware nor software involved have much in the way of precedents.

Furthermore quantum computers as they exist today and for the foreseeable future have very few valuable applications, meaning pursuing them is only an investment in the most optimistic sense. However, government funding via SBIR and grants like those are intended to de-risk exactly this kind of research.

The proposed budget for NASA is also expected to receive a large increase in order to accelerate and reinforce various efforts within the Artemis Moon landing program. It was not immediately clear how these funds would be raised or from where they would be reallocated.

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White House reportedly aims to double AI research budget to $2B - TechCrunch

The "Artificial Intelligence (AI) in the Global Freight Transportation Industry, Forecast to 2025" report has been added to ResearchAndMarkets.com's offering.

This study analyses the key trends and applications of artificial intelligence in the freight transportation industry by mode of transport i.e. road, rail, air, and ocean freight transportation. This research also analyses the disruptive impact of artificial intelligence on freight transportation business operations and discusses its adoption prospects until 2025.

Market Insights

With increased trade flow, the fleet population in freight transportation has become denser, and expectations of customers have evolved beyond recognition, resulting in complex transport operations, requiring operational flexibility from freight operators. Human errors in operations, underutilized assets, low workforce productivity, inefficient operational planning, inability to match supply with demand, and trimmed profit margins are key prevailing concerns with freight operators.

The emergence of digital technologies and the rapid technological advancements in digitization have transformed the business and operational landscape of the global freight transportation industry. It is essential for freight operators to embrace such operational complexity and evolve by adopting technologies to turn complexity into an advantage.

Today, the world is connected more than ever, and the growth of data generation has been exponential with smart devices and process automation. Data-driven insights help freight operators move forward and gain a competitive advantage over their peers. Artificial intelligence enables freight operators to harness data more effectively for actionable insights.

Artificial intelligence-powered systems in conjunction with other digital technologies such as internet of things and big data analytics utilize data to its full potential to anticipate events for freight operators, aiding them to avoid risks and create innovative solutions. Machine learning algorithms based on neural networks powered by artificial intelligence would unlock multiple benefits for companies operating in the freight transportation industry.

AI brings changes to the supply chain with autonomous vehicles, helping fleet operators reduce operating cost with and fuel consumption and plan optimized routes for service. The freight operators that are enhancing their capabilities with artificial intelligence are reaping its benefits by increasing efficiency with predictive intelligence. Artificial intelligence also enriches the relationship between the shipper and carrier with personalized service offerings.

Advanced sensor fusion with artificial intelligence supports the integration of smart infrastructure and operating assets and the freight operators in the development of connected freight ecosystem, aiding autonomous fleet management. The transformation of the logistics industry due to artificial intelligence is imperative in the near future; however, the readiness and openness of freight operators for an AI-based data-driven environment will determine how well this industry copes with challenges.

Key Topics Covered:

1. Executive Summary

2. Research Scope and Methodology

3. AI in Logistics Industry

4. AI in Freight Forwarding

5. AI in Freight Transportation

6. Stature of AI Adoption in Freight Transportation

7. Growth Opportunities and Companies to Action

8. The Last Word

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/nusb51

View source version on businesswire.com: https://www.businesswire.com/news/home/20200207005450/en/

Contacts

ResearchAndMarkets.comLaura Wood, Senior Press Managerpress@researchandmarkets.com For E.S.T Office Hours Call 1-917-300-0470For U.S./CAN Toll Free Call 1-800-526-8630For GMT Office Hours Call +353-1-416-8900

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Global Forecast on Artificial Intelligence (AI) in the Freight Transportation Industry (2020 to 2025) - Disruptive Impact of AI on Freight...

The "5G, Artificial Intelligence, Data Analytics, and IoT Convergence: The 5G and AIoT Market for Solutions, Applications and Services 2020 - 2025" report has been added to ResearchAndMarkets.com's offering.

This research evaluates applications and services associated with the convergence of AI and IoT (AIoT) with data analytics and emerging 5G networks. The AIoT market constitutes solutions, applications, and services involving AI in IoT systems and IoT support of various AI facilitated use cases.

This research assesses the major players, strategies, solutions, and services. It also provides forecasts for 5G and AIoT solutions, applications and services from 2020 through 2025.

Report Findings:

The combination of Artificial Intelligence (AI) and the Internet of Things (IoT) has the potential to dramatically accelerate the benefits of digital transformation for consumer, enterprise, industrial, and government market segments. The author sees the Artificial Intelligence of Things (AIoT) as transformational for both technologies as AI adds value to IoT through machine learning and decision making and IoT adds value to AI through connectivity and data exchange.

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.

It is important to recognize that intelligence within IoT technology market is not inherent but rather must be carefully planned. AIoT market elements will be found embedded within software programs, chipsets, and platforms as well as human-facing devices such as appliances, which may rely upon a combination of local and cloud-based intelligence.

Just like the human nervous system, IoT networks will have both autonomic and cognitive functional components that provide intelligent control as well as nerve end-points that act like nerve endings for neural transport (detection and triggering of communications) and nerve channels that connect the overall system. The big difference is that the IoT technology market will benefit from engineering design in terms of AI and cognitive computing placement in both centralized and edge computing locations.

Taking the convergence of AI and IoT one step further, the publisher coined the term AIoT5G to refer to the convergence of AI, IoT, 5G. The convergence of these technologies will attract innovation that will create further advancements in various industry verticals and other technologies such as robotics and virtual reality.

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.

There will be a positive feedback loop created and sustained by leveraging the interdependent capabilities of AIoT5G. AI will work in conjunction with IoT to substantially improve smart city supply chains. Metropolitan area supply chains represent complex systems of organizations, people, activities, information, and resources involved in moving a product or service from supplier to customer.

Research Benefits

Key Topics Covered

1. Executive Summary

2. Introduction

3. AIoT Technology and Market

4. AIoT Applications Analysis

5. Analysis of Important AIoT Companies

6. AIoT Market Analysis and Forecasts 2020-2025

7. Conclusions and Recommendations

Artificial Intelligence in Big Data Analytics and IoT: Market for Data Capture, Information and Decision Support Services 2020-2025

1. Executive Summary

2. Introduction

3. Overview

4. AI Technology in Big Data and IoT

5. AI Technology Application and Use Case

6. AI Technology Impact on Vertical Market

7. AI Predictive Analytics in Vertical Industry

8. Company Analysis

9. AI in Big Data and IoT Market Analysis and Forecasts 2020-2025

Story continues

10. Conclusions and Recommendations

11. Appendix

5G Applications and Services Market by Service Provider Type, Connection Type, Deployment Type, Use Cases, 5G Service Category, Computing as a Service, and Industry Verticals 2020-2025

1. Executive Summary

2. Introduction

3. LTE and 5G Technology and Capabilities Overview

4. LTE and 5G Technology and Business Dynamics

5. Company Analysis

6. LTE and 5G Application Market Analysis and Forecasts

7. Conclusions and Recommendations

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/rigm8o

View source version on businesswire.com: https://www.businesswire.com/news/home/20200207005390/en/

Contacts

ResearchAndMarkets.comLaura Wood, Senior Press Managerpress@researchandmarkets.com For E.S.T Office Hours Call 1-917-300-0470For U.S./CAN Toll Free Call 1-800-526-8630For GMT Office Hours Call +353-1-416-8900

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2020-2025 Worldwide 5G, Artificial Intelligence, Data Analytics, and IoT Convergence: Embedded AI Software and Systems in Support of IoT Will Surpass...

The role AI plays in your life is a matter of choice (but only to a certain extent).

It doesnt seem too long ago that artificial intelligence (AI) was mostly the stuff of science fiction. Today it seems to be everywhere: in our home appliances, in our cars, in the workplace, even on our wrists.

To some extent, our use of AI is still a matter of personal choice. But because AI is becoming increasing ubiquitous, we need to make a lot of conscious decisions.

Regardless of the choices we make, we need to stay educated on the evolution of this science. A thoughtful primer on this is Rhonda Scharfs bookAlexa Is Stealing Your Job: The Impact of Artificial Intelligence on Your Future.

My conversation with Rhonda provides some good tips what we should know and what we can do.

Rodger Dean Duncan:AI today is similar to the introduction of the desktop computer three decades ago. Many people resisted computers and got left behind. Whats the best argument for AI today?

Rhonda Scharf

Rhonda Scharf:Artificial Intelligence is not going away. When the desktop computer was introduced in the 1980s, many people felt it was a fad, and it would disappear over time.

Hazel, a woman I worked with, was willing to bet her career on it.When the company I worked at insisted we transition to desktops or leave the company, she rolled the dice and called their bluff. She lost. She believed there was no way a company could exist without tried-and-true manual systems and that computers were a big waste of time and money.

We are in precisely that situation again.

If you can write instructions for a task so that someone can follow them, then AI can replicate those actions.

Duncan:So whats the implication?

Scharf:Not only can your company exist without you performing these tasks, it will also (eventually) be more profitable (with fewer errors) because of it.

By refusing to learn about AIand by refusing to adapt and be flexibleyoure rolling the dice that AI will not take over the tasks you currently do. Call yourself Hazel, and youll soon be out of a job.

AI is alive and well in the workplace, only many people dont realize it. Being nave and refusing to acknowledge what is right under your nose is a recipe for disaster. Take a look around at how much AI we already have in our lives. Artificial Intelligence is not going away. Adapt or become unemployed.

Duncan:Most people have grown comfortable with the idea of letting machines replace humans to do monotonous, heavy, repetitive, and dangerous tasks. But the notion of having AI make decisions and predictions about the future often evokes skepticism or even fear. What do you say to people who have such concerns?

Scharf:Movies like2001: A Space Odyessyand its AI character, HAL 9000, have planted the seeds of fear and mass destruction in our minds. We are afraid of what computers can do on their own. AI learns from its experiences and will make decisions on its owncalculated, logical, and statistically accurate decisions.

What AI doesnt do is make emotional decisions. Take AI stock trading as an example. Without any emotions involved, the robo-advisers can determine the optimal price to buy and sell specific stocks. They dont get emotionally tied into one more day and potentially lose profits. AI can evaluate millions of data points and make conclusions instantly that neither humans nor computers can do. As quickly as the market changes, AI changes its course of action based on the data.

Im not about to have AI make life-or-death decisions for me. The same way we now trust machines to handle monotonous, heavy, repetitive, and dangerous tasks, I will rely on AI to do some heavy thinking and bring me logical conclusions, quickly and efficiently.

If you don't want to be left behind, you'd better get educated on AI.

Duncan:What do you tell people who have privacy concerns about AI applications?

Scharf:The privacy concerns are real, but you gave up your privacy when you got your first mobile phone (for some this was as early as 1996). It could track you. Technically, that impacted your privacy 20-plus years ago.

Once the Blackberry was introduced in 1999, followed by the iPhone eight years later, your privacy became severely compromised. Your phone knows where you are, and it knows what youre doing. Even if you keep your Bluetooth off, your device and its apps know a lot about you.

If you wear any technology whatsoever, you are giving up your privacy. According to a 2014 study by GlobalWebIndex, 71% of people ages 16 to 24 want wearable tech. That was over five years ago before we had much wearable technology.

In the same study, 64% of internet users aged 16 to 64 said theyve either already used a piece of wearable tech or were keen to do so in the future.

Fast forward five years, and half of Americans use fitness trackers daily. More than 96% of Americans have a cell phone of some kind.

People may say they have privacy concerns, but when it comes to using technology that improves our lives, we forgo privacy for convenience.

Next: Artificial Intelligence, Privacy, And The Choices You Must Make

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What Role Will (Or Does) Artificial Intelligence Play In Your Life? - Forbes

Artificial intelligence is all the rage, and theres good money to be made in an industry thats still largely emerging from its infancy. But, the problems that AI solves are not easy, and to work in the AI industry you will need a strong and focused set of skills.

Heres the good news: We live in a society where a shocking number of people would rather have a robot boss than a human one. We would rather be led by machines.

This means that most of us are accepting of the idea of artificial intelligence, or AI.

In many sectors, machines have already taken over monotonous jobs. Manufacturing is a prime example. Auto and aerospace manufacturers use machines heavily in their assembly lines. In fact, machines completely transformed the way that our cars are built.

Artificial intelligence isnt just a fad. Its here to stay.

And, that means the industry will need a skilled workforce to build, test and deploy more and more artificial brains around the world. Get in early and youll stand to make a lot of money.

Not to mention help change the world.

If you are interested in a career in artificial intelligence, then youre in the right place.

Artificial intelligence attempts to mimic (and surpass) the power of the human brain using nothing but machines. Machine learning is another common term in AI.

The primary goals of artificial intelligence are:

Artificial intelligence attempts to build machines that think and reason rather than operate in a relatively confined space with pre-built routines, procedures and outcomes. Smart AI systems recognize patterns and remember past events and learn from them, making each subsequent decision smarter, logical and more organic.

AI is a giant paradigm shift in modern computing and requires a deeply scientific and logical approach to design computer systems that think and learn. In other words, build robots that arent just robots.

And believe it or not, AI capabilities are all over the place.

A few examples of artificial intelligence systems include speech recognition (available on many cell phones and smart home devices), email spam blockers, plagiarism checkers, language translation services (like Google Translate) and the auto-pilot system on airplanes.

Companies like Google, Microsoft, Apple, Amazon, Facebook, Accenture, Boeing and so many others are hiring for artificial intelligence roles. AI salaries are typically higher than average because good AI talent can be hard to find.

Artificial intelligence is everywhere in society, and the industry is growing rapidly in 2020. Here is exactly what you need to know to pursue a career in AI.

Artificial intelligence is highly scientific. After all, mimicking the human brain using machines is a very tough problem to solve, much less master. The skills that you will need to pursue AI as a career are varied, but all of them require a great deal of education, training and focus.

That said, there is a wide variety of career types available in AI and machine learning, and they range from higher-level research to low-level programming and implementation.

For example, researchers use their breadth of knowledge in theory and study to reveal new types of systems and capabilities. Researchers hypothesize new or different ways for machines to think and test their research for real-world feasibility.

Algorithm developers take AI research and transform that research into repeatable processes through mathematical formulas that can be implemented using hardware and software.

Software developers and computer scientists use those algorithms to write sophisticated pieces of software that analyze, interpret and make decisions.

Hardware technicians build pieces of equipment (like robots) to interact with the world. Robots use its internal software to move and operate.

Most careers in artificial intelligence require coursework and experience in a variety of math and science-related topics like:

Want a career in AI? Then read. A lot.

Read papers and case studies. Experiment with technologies like Map-Reduce, PHP, MySQL, Postgres and Big Data, especially if you are targeting a computer science-related career in AI. Expose yourself to as many technologies as you can.

Pro tip: Browse through AI job opportunities. Read the job descriptions and especially the requirements to get a feel for specific qualifications that you need for that job.

For example, some might need experience in low-level programming languages like Python or MatLab. Others, especially in the healthcare industry, need expertise in data services like Spark and Blockchain.

Regardless of the type of job that youre after in artificial intelligence, there is no better way to figure out the exact skills you need than to read job requisitions and stay as up-to-date in the industry as possible.

Use the Job Search tool here on The Ladders to find AI and machine learning jobs.

Though the types of careers in the AI industry are varied, most professionals in AI possess five key skills and capabilities, regardless of their individual roles.

Most AI professionals:

Are highly critical thinkers. They take nothing at face value and are naturally curious. They believe in trial and error and must test and experiment before making a concrete decision.

Like to push the envelope. AI is all about pushing the boundaries. Pegging the capabilities of hardware and software to their max, always looking for more. More ways to improve existing systems. More ideas for inventing new ways to live.

Live naturally-curious lives. Always wanting to know more, artificial intelligence pros want to know how things work. They dont just look. They observe. They dont hear. They listen.

Dont get easily overwhelmed. They understand that artificial intelligence is highly technical, but also realize that venturing into uncharted waters is difficult and mysterious. They enjoy the process rather than getting frustrated by it.

Love math and science. AI is highly technical and its a natural good fit for those who are gifted and interested in hard sciences and mathematics.

Artificial intelligence is not just about replacing the human component of the industry. Its also about making it easier to make decisions based on observable patterns, use logic and reasoning to form conclusions and build pathways to boost efficiency and production.

It is not an easy discipline, but thats also why salaries in the AI industry are much higher than average. It takes the right type of person with the right skill set to excel.

Are you the type of person whos right for a career in AI? If you have many of these skill sets, then you just might be.

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These are the exact skills you need to get a job in artificial intelligence - Ladders

An artificial intelligence tool has been developed to help predict the structure of the universe and aid research into the mysteries of dark energy and dark matter.

Researchers in Japan used two of the world's fastest astrophysical simulation supercomputers, known as ATERUI and ATERUI II, to create an aptly-named "Dark Emulator" tool, which is able to ingest vast quantities of data and produce analysis of the universe in seconds.

The AI could play a role in studying the nature of dark energy, which seems to make up a large amount of the universe but remains an enigma.

Read more

When observed from a distance, the team noted how the universe appears to consist of clusters of galaxies and massive voids that appear to be empty.

But as noted by NASA, leading models of the universe indicate it is made of entities that cannot be seen. Dark matter is suspected of helping to hold galaxy clusters in place gravitationally, while dark energy is believed to play a role in how the universe is expanding.

According to the researchers responsible for Dark Emulator, the AI tool is able to study possibilities about the "origin of cosmic structures" and how dark matter distribution may have changed over time, using data from some of the top observational surveys conducted about space.

"We built an extraordinarily large database using a supercomputer, which took us three years to finish, but now we can recreate it on a laptop in a matter of seconds," said Associate Prof. Takahiro Nishimichi, of the Yukawa Institute for Theoretical Physics.

"Using this result, I hope we can work our way towards uncovering the greatest mystery of modern physics, which is to uncover what dark energy is. I also think this method we've developed will be useful in other fields such as natural sciences or social sciences."

Nishimichi added: "I feel like there is great potential in data science."

The teams, which included experts from the Kavli Institute for the Physics and Mathematics of the Universe and the National Astronomical Observatory of Japan, said in a media release this week that Dark Emulator had already shown promising results during extensive tests.

In seconds, the tool predicted some of effects and patterns found in previous research projects, including the Hyper Suprime-Cam Survey and Sloan Digital Sky Survey. The emulator "learns" from huge quantities of data and "guesses outcomes for new sets of characteristics."

As with all AI tools, data is key. The scientists said the supercomputers have essentially created "hundreds of virtual universes" to play with, and Dark Emulator predicts the outcome of new characteristics based on data, without having to start new simulations every time.

Running simulations through a supercomputer without the AI would take days, researchers noted. Details of the initial study were published in The Astrophysical Journal last October. The team said they hope to input data from upcoming space surveys throughout the next decade.

While work on this one study remains ongoing, there is little argument within the scientific community that understanding dark energy remains a key objective.

"Determining the nature of dark energy [and] its possible history over cosmic time is perhaps the most important quest of astronomy for the next decade and lies at the intersection of cosmology, astrophysics, and fundamental physics," NASA says in a fact-sheet on its website.

Read the original:
AI Tool Created to Study the Universe, Unlock the Mysteries of Dark Energy - Newsweek

In this weeks roundup from the Association for Unmanned Vehicle Systems International, which highlights some of the latest news and headlines in unmanned vehicles and robotics, studying autonomous vehicle operation in Canadian winters, the foundation is laid out for ZM Interactive customers to conduct beyond-line-of-sight drone flights, and unmanned surface vehicles conduct seabed surveys on offshore wind farm turbines.

Scale AI open-sources data set to help in the development of autonomous vehicles capable of driving in wintry weather

This week, a startup called Scale AI open-sourced Canadian Adverse Driving Conditions (CADC), which is a data set that contains more than 56,000 images in conditions including snow created with the University of Waterloo and the University of Toronto.

The move is designed to help in the development of autonomous vehicles capable of driving in wintry weather, as Scale AI claims that CADC is the first corpora with snowy sensor samples to focus specifically on real-world driving in snowy weather.

Snow is hard to drive in as many drivers are well aware. But wintry conditions are especially hard for self-driving cars because of the way snow affects the critical hardware and AI algorithms that power them, explains Scale AI CEO Alexandr Wang in a blog post, via VentureBeat.

A skilled human driver can handle the same road in all weathers but todays AV models cant generalize their experience in the same way. To do so, they need much more data.

According to Scale AI, the routes captured in CADC were chosen based on levels of traffic and the variety of objects such as cars, pedestrians, animals, and most importantly, snowfall. Teams of engineers used an autonomous vehicle platform called Autonomoose to drive a Lincoln MKZ Hybrid mounted with a suite of lidar, inertial sensors, GPS, and vision sensors (including eight wide-angle cameras) along 12.4 miles of Waterloo roads.

Combining human work and review with smart tools, statistical confidence checks, and machine learning checks, Scale AIs data annotation platform was used to label each of the resulting camera images, 7,000 lidar sweeps, and 75 scenes of 50-100 frames. The company says that the accuracy is consistently higher than what a human or synthetic labeling technique could achieve independently, as measured against seven different annotation quality areas.

For University of Waterloo professor Krzysztof Czarnecki, his hope is that the data set will put the wider research community on equal footing with companies that testing self-driving cars in winter conditions, including Alphabets Waymo, Argo, and Yandex.

We want to engage the research community to generate new ideas and enable innovation, Czarnecki says. This is how you can solve really hard problems, the problems that are just too big for anyone to solve on their own.

ZM Interactive selects Iris Automation as detect and avoid provider for its UAS

ZM Interactive (ZMI) has selected Iris Automation as the detect and avoid (DAA) provider for its drones, which will allow ZMI customers to conduct beyond visual line of sight (BVLOS) operations.

ZMI manufactures the xFold drone, which is an industrial, military-grade UAS that comes in various sizes and configurations. Its frame can change between a x4 (Quad), x6 (Hexa), X8 (octo) and X12 (Dodeca) configurations in minutes, and it has a heavy payload capability of more than 300 pounds, making the UAS ideal for a wide range of commercial, industrial, military and emergency response applications. Some of its use cases include aerial cinematography, 3-D Mapping and inspections, and cargo delivery.

Having selected Iris Automation as its DAA provider, ZMI will provide the option of equipping its UAS platforms with Iris Automations Casia system. Described as a turnkey solution, Casia detects, tracks and classifies other aircraft and makes informed decisions about the threat they could potentially pose to the UAS. To avoid collisions, Casia triggers automated maneuvers, and alerts the pilot in command of the mission.

This collaboration between Iris Automation and ZMI allows xFold drone customers to use their drones to their full potential, explains Iris Automation CEO Alexander Harmsen.

Having drones pre-equipped with the option for advanced BVLOS capabilities is a basic requirement the industry will soon expect to see on all drones out-of-the-box.

Under its partnership with ZMI, Iris says that it will also offer customers with Casia onboard regulatory support for Part 107 waiver writing and regulatory approval processes to secure the permissions needed to conduct their unique BVLOS operations.

XOCEAN's XO-450 USV conducts seabed surveys for Greater Gabbard Offshore Wind Farm

Considered a first for the offshore wind sector, XOCEANs XO-450 USV recently conducted seabed surveys on seven of the turbines at the Greater Gabbard Offshore Wind Farm, a joint venture between SSE Renewables and innogy.

To validate data collection before the vessel departed the work locations, experts located in the United Kingdom monitored the data collected from shore in real-time throughout the survey.

According to XOCEAN, the survey demonstrates the highly flexible and collaborative nature of this technology, which ultimately allows industry experts to have direct access to real time data, from any location.

We are constantly looking for innovative ways in which we can operate our fleet of renewables assets, says Jeremy Williamson, SSE Renewables Head of Operations.

XOCEANs vessel will allow us to carry out our work in a more efficient, and most importantly for SSE Renewables and our partners innogy, in the safest way possible. Were really interested to see how this sort of work can help improve our industry and look forward to working with XOCEAN in future.

XOCEAN says that its USVs offer a number of benefits, including keeping operators safe as they remain onshore, efficiency with operations 24 hours a day, seven days a week, and environmental benefits with ultra-low emission. These benefits result in significant economic savings, the company adds.

Our USV platform has demonstrated itself to be a safe, reliable and low carbon solution for the collection of ocean data, says James Ives, CEO of XOCEAN.

We are delighted to be working with SSE and innogy on this ground-breaking project.

Share your vision-related news by contactingDennis Scimeca, Associate Editor, Vision Systems Design

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Artificial intelligence assists in the study of autonomous vehicle performance in winter conditions - Vision Systems Design

CHICAGO--(BUSINESS WIRE)--Stats Perform, the revolutionary leader in sports AI and data, announced that Chief Scientist Dr. Patrick Lucey will deliver keynote remarks at the Association for the Advancement of Artificial Intelligence (AAAI-20) Workshop in Team Sport in New York on Saturday, February 8.

Dr. Luceys presentation Interactive Sports Analytics will examine new ways to break down player or team performance using big data and AI software. The presentation will include examples of how coaches can draw up and search for specific plays and, using AI and Stats Performs decades of tracking and multi-agent trajectory data, simulate likely outcomes specific to a particular opponent and the players involved. In addition, Dr. Lucey will demonstrate the capabilities of new body-pose data made possible through Stats Performs state of the art AutoSTATS technology.

We have reached an exciting moment in sports where coaches and analysts can now leverage big data and AI to generate advanced insights on play development and likely outcomes, Dr. Lucey said. Imagine a coach drawing up an Xs and Os play, the same way he would on chalkboard, on an iPad and simulating likely outcomes based on different sets of offensive and defensive opponents in-play. Imagine then being able to search that play and find video of every time a near similar play was run. With AI and big data, we are already making that happen at Stats Perform and I cant wait to meet and discuss this with the illustrious group of researchers at the AAAI Workshop.

The AAAI Workshop in Team Sport is one of the leading conferences for AI in team sports with participation from some of the leading global research institutions. The 34th AAAI Conference will include a research paper and poster track.

About Stats Perform

Stats Perform collects the richest sports data in the world and transforms it through revolutionary artificial intelligence (AI) to unlock the most in-depth insights for media and technology, betting and team performance. With company roots dating back almost 40 years, Stats Perform embraces and solves the dynamic nature of sport be that for digital and broadcast media with differentiated storytelling, tech companies with reliable and fast data to power their innovations, sportsbooks with in-play betting and integrity services, or teams with first-of-its-kind AI analysis software. As the leading sports data and AI company, Stats Perform works with the top global sports media, tech companies, sportsbooks, teams and leagues. For more information, visitStatsPerform.com

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Stats Perform's Chief Scientist of Artificial Intelligence to Deliver Keynote at AI in Team Sports Conference - Business Wire

For decades, humanity predicted and waited for something that we know of now as Artificial Intelligence. These days, you see AI in almost anything, starting with your cell phone and ending with smart houses. Of course, one thing that we still wait for is the creation of robots that are going to be so human-like that it will be difficult to tell a real person from an artificial one. However, that sort of AI is mainly fiction.

On the other hand, it is safe to say that the kind of AI that we have now influenced almost every sphere of our lives, and education is not an exception. However, for one reason or another, the role of AI in education has been mainly underestimated, so we at CustomWritings.com, a professional essay writing company, decided to change that. We are going to list all the main aspects that AI improved in modern education.

You cant imagine how long it takes a regular teacher to go through all the tests and grade them all. That is when AI comes is more than helpful. Many programs allow teachers to take a break from grading while the system checks all the multiple-choice and fill-in-the-blank tests. When it comes to essay checking, things are a little different since such programs are not developed yet, but they are being worked on.

It is not a secret that every student has a particular learning technique, and not always a teacher can provide him or her with a necessary educational approach. That is when various kinds of educational software step in. These days you can choose a program or a system that helps you most while the teachers help is also provided when required.

Teachers are not gods, and at times, they also make mistakes. When some essential information or concept skips the teachers mind, the students are to make equal mistakes in the upcoming tests. That is when such useful course providers as Coursera step in. The system notices the patterned mistake and improves it while notifying both the teacher and the student about the mistake.

When you do not understand one point in the study, you cant move to the other. That is why many students tend to use the services of tutors so that all explained well. At the same point, not every student can afford a tutor. That is when AI tutoring systems come in. They are not ideal or too creative and complex, but they are developed to provide that basic knowledge that will help you move forward from the place that you are stuck.

The constant access to all the miracles of technology that we have on offer now has changed the way we perceive the information. It is neither good nor bad, per se. It is different. Such an AI involvement in the information perception process may result in something entirely innovative in the future. It will surely affect all the spheres, and education is clearly not an exception.

It goes without saying that no AI can substitute a real teacher. However, the scientists and developers are working on improving the AI educational systems so that they can take off all the unnecessary load of teachers.

At times it seems that there is rarely anything worse than standing in front of the class and being unable to answer the set question. The very same goes for the negative grades that you get when all the peers seem to succeed with any set task. Things like that will not have a chance in the future. When you are learning using a set program, you do not have to fail so everyone can see that. Whenever you do fail, the system will correct the mistake explaining why you failed in the first place. This is probably one of the best features that AI can bring into the educational process.

When a person fails, the AI system may not. All the data that is necessary for successful research, as well as the educational process required by every student, is never easy to gather and then sort it out accordingly. For a powerful AI system, such a task is not that difficult to understand and carry out. When you have all the data gathered in one place, you can come up with the best courses, attract the most promising student, implement the best learning techniques that correspond to the needs of modern students, etc.

It happens so very often that you cant go to the college that you like just because you cant afford traveling to the city it is situated in or anything of the kind. With the development of AI, such things may become extinct. The thing is that with the ever-developing technologies soon, you will be able to access anything from any place, and that will make education affordable for all those who are willing to learn.

To sum all up, it is safe to say that there are many changes that AI has already brought into the education system. However, that is clearly not all that we can reap from its developments. Many changes are waiting in the future as well.

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Important role of Artificial Intelligence in education - PC-Tablet

Spending on Artificial Intelligence (AI) is expected to more than double from $35 billion in 2019 to $79 billion in 2022, according to IDC forecasts. But as we enter the fourth industrial revolution powered by AI, technologists have divided themselves into utopian and alarmists camps. Thats a false and dangerous dichotomy. We need to adopt a pragmatic mindset that sees AI as both a risk and a way to manage risk.

From killer robots to racism, todays headlines provide AI alarmists with ample fodder. The risks associated with AI grow as technology improves and proliferates. But unlike other paradigm-shifting technologies like the printing press, mass production, or digital commerce, its the invisible aspects of AI that we most need to worry about: algorithms that learn from patterns and can trigger costly errors and, left unchecked, can pull projects and organizations in entirely wrong directions with catastrophic consequences.

For the first time in history, a single person can customize a message for billions and share it with them within a matter of days. A software engineer can create an army of AI-powered bots, each pretending to be a different person, promoting biased content on behalf of political or commercial interests or worse, attack vulnerable systems.

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The doomsday scenarios arent a fait accompli, but they do underscore the need for AI systems that engage with humans in transparent ways. Every time a new technology is introduced, it creates new challenges, safety issues, and potential hazards. For example, when pharmaceuticals were first introduced, there were no safety tests, quality standards, childproof caps or tamper-resistant packages. AI is a new technology and will undergo a similar evolution.

To trust an AI system, we must have confidence in its decisions. Increasingly, bankers are asking important questions about how AI will affect consumers. The Defense Department has signaled that it understands the importance of empowering ethicists to guide AI technologies.

Meanwhile, were beginning to include AI in our long-overdue conversations about criminal justice. These are all good signs, but we need to rapidly scale our ethical inquiries by using supervisory AI systems to provide visibility and control over production AI systems.

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AI systems must reflect our values. We can do this through investment, education, and policy. But first, we must dispense with the utopian and alarmist positions. Utopians assume that every AI solution will automatically be an improvement over what came before it, and therefore miss the opportunity to address critical questions about values before deployment.

At the opposite end of the spectrum, alarmists assume the worst and therefore fail to show up to the debate. A pragmatic approach that sees AI as both a risk and a way to manage risk by pairing AI with other AI is the prerequisite mental model for grappling with the issues raised by the fourth industrial revolution.

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Why Artificial Intelligence is Both a Risk and a Way to Manage Risk - AiThority