Archive for the ‘Artificial Intelligence’ Category

Christian pastor says China’s AI tech is ‘demonic’ as it will ‘control everything’ – Daily Star

A Christian pastor launched a scathing rant after finding out about artificial intelligence technology that aims to prosecute criminals in China.

The AI tech, which was developed and tested by the Shanghai Pudong Peoples Procuratorate, can charge a suspect with more than 97% accuracy based on a description in a criminal case.

While it may seem to be a futuristic method for tackling crime and keeping people safe, Pastor Tom Hughes was less than enthused and made wild claims that the advancements are 'demonic' and are out to 'control' people.

In a video posted to his YouTube channel yesterday (May 12), he explained: "Folks when I look at the department of homeland security information, with the direction that they are going with, in 2022, it is coming and then to see that in China they've got an AI prosecutor to be able to prosecute people in real-time.

"They're claiming with 97% accuracy, they'll be able to prosecute people for crimes. Listen, this stuff is demonic. This artificial intelligence is going to be controlling every single thing that we say and that we do.

"[Pastor] Matt Ward wrote about this back in 2018 and he said when he was projecting what was going to be coming in the future. He said that by 2022 we will see this in place. Folks we are watching it now."

The advancement was first announced in December 2021 as Professor Shi Yong, director of the Chinese Academy of Sciences big data and knowledge management laboratory claims it will help as reduce prosecutors daily workload.

However, prosecutors have had their concerns about the risk of mistakes.

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A prosecutor from Guangzhou said: The accuracy of 97 per cent may be high from a technological point of view, but there will always be a chance of a mistake.

Who will take responsibility when it happens? The prosecutor, the machine or the designer of the algorithm? AI may help detect a mistake, but it cannot replace humans in making a decision."

But China is continuing to use AI in nearly every sector of the government to try to improve efficiency, reduce corruption and strengthen control, according to the South China Morning Post.

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Christian pastor says China's AI tech is 'demonic' as it will 'control everything' - Daily Star

Vatic Investments Appoints Li Deng, Ph.D., as Chief Artificial Intelligence Officer and Global Head of Ma – Benzinga

Vatic Investments ("Vatic" or the "Firm"), a systematic quantitative investment manager, announced today the appointment of Li Deng, Ph.D., as Chief Artificial Intelligence Officer and Global Head of Machine Learning, effective May 9, 2022. Dr. Deng will report to James Chiu, Founder and Chief Executive Officer of Vatic.

Recognized as one of the world's leading experts in AI, speech technology and machine learning, Dr. Deng was previously Chief Artificial Intelligence Officer and Head of Machine Learning at Citadel LLC. Before that, he was the Chief Scientist of AI, Founder of Deep Learning Technology Center, and Partner Research Manager at Microsoft for over 17 years. Prior to Microsoft, Dr. Deng worked for nearly a decade as a tenured professor at the University of Waterloo. He earned his Bachelor's degree from the University of Science and Technology of China, and his Master's and Ph.D. degrees in Electrical and Computer Engineering from the University of Wisconsin-Madison. Since 2000, Dr. Deng has also been an Affiliate Full Professor at the University of Washington, Seattle, and a Fellow of the Academy of Engineering of Canada, the Academy of Sciences (Washington State), the IEEE, Acoustical Society of America, and ISCA, among other technical societies.

During his nearly 30-year career in academia, technology and finance, Dr. Deng has published more than 350 academic papers and authored several books on machine learning and AI, as well as lectured at many of the world's top universities, institutes and finance summits. In 2012, he published a groundbreaking paper on deep neural networks for speech recognition with Dr. Geoffrey Hinton, a cognitive psychologist and computer scientist who is recognized as the "Godfather of Deep Learning." The paper has received about 11,000 academic citations as of May 2022.

In recognition of his pioneering AI research on disrupting speech recognition using large-scale deep learning, Dr. Deng has been honored with many of the AI industry's highest awards, including the IEEE SPS Technical Achievement Award for "Outstanding Contributions to Automatic Speech Recognition & Deep Learning" (2015) and, separately, the IEEE SPS "Industrial Leader Award" (2019). Most recently, he was presented with the AI-2000 Most Influential Scholar Award.

"We are thrilled to attract a technologist and talent of Li's caliber. He has dedicated his life to the study of machine learning, signal generation and modeling of financial markets," said James Chiu, Founder and Chief Executive Officer of Vatic. "Vatic's momentum and ability to attract the world's top academic and financial talent is rooted in the special culture we are creating. Our mission is centered on rigorous research, intense collaboration and removing trading silos to allow the best ideas and strategies to always rise to the top. We welcome Li to our growing Vatic family."

"I'm excited to join the world-class team of investment professionals at Vatic," Dr. Deng said. "The Firm's intention to continue building an intensely collaborative environment is a key factor in the efficiency of research and in creating sustainable trading strategies both short and long term. We aim to continue bringing in the best AI and machine learning talent in the world to work collaboratively with the investment professional as a joint team in our unique culture at Vatic."

About Vatic Investments

Vatic Investments is a systematic quantitative investment management firm where traders, AI researchers and technologists collaborate to develop autonomous trading agents and state-of-the-art investment software. The firm is data-driven, with machine learning and cutting-edge technology piloting its trading strategies. Learn more at http://www.vaticinvestments.com.

View source version on businesswire.com: https://www.businesswire.com/news/home/20220512005310/en/

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Vatic Investments Appoints Li Deng, Ph.D., as Chief Artificial Intelligence Officer and Global Head of Ma - Benzinga

The Rise Of Artificial Intelligence: Will Robots Actually Replace People? – Forbes

Will robots replace human workers?

Robots and artificial intelligence (AI) are expected to permeate our daily lives by 2025. This could have huge implications on several business sectors, most notably health care, customer service, and logistics. Already, AI is responsible for medical research breakthroughs and climate research, not to mention self-driving cars.

Will robots replace human workers?

The answer to that seems to be divided. According to PEW research, about half (48%) of experts surveyed felt that robots and digital agents will displace a significant number of blue- and white-collar jobs. Their concern is that this will increase income inequality and create a mass of virtually unemployable people. The other half (52%) expect robotics and AI to create more jobs than they take. This latter half believes that while AI will replace humans, these experts have faith in human ingenuity to create new jobs, industries, and new ways of making a living much like at the dawn of the Industrial Revolution.

Of interest in the PEW study, both groups are concerned that our educational institutions are not adequately preparing people for the job market of tomorrow.

What is artificial intelligence?

AI in its simplest form stands for artificial intelligence designed to mimic human intelligence to perform tasks. Advocates of AI see this as a positive step forward. It will make it easier for businesses to identify and rectify problems. AI will potentially improve recruitment, cybersecurity, marketing, and standard operating processes.

AI can process large amounts of data and execute complex algorithms quickly and accurately. Each year, AI is getting "smarter" and increasing business efficiency.

What will it be like to work with robots?

Leading expert Martina Mara, Professor of Robopsychology at Johannes Kepler University Linz, suggests we ask a different question: What do we want the future of work to look like? How do we want robots to change our lives? She reminds us that robots are developed by people. While robots can work 24/7, they cannot generalize or contextualize. They have no soft skills.

They're hard wired, literally, to perform highly specific and clearly structured tasks. This is great news for humans we get to pass off the mundane repetitive tasks and adopt those that require critical thinking and problem solving based on human intuition.

AI is evolving and technology is having an increasingly bigger role, but it will complement and augment most jobs, not replace them. In a study involving 1500 companies, researchers found that the most significant performance improvements occurred when humans and machines worked together. Humans perform three crucial roles: they train machines what to do, explain outcomes especially when those are counterintuitive or controversial, and they sustain responsible use of machines. Robots need us just as much as we need them.

Robots are used to do the heavy lifting, literally. In manufacturing, cobots, context-aware robots, perform repetitive actions dominated by heavy lifting, while their human coworker completes complementary tasks that require more dexterity and judgment.

Whether you are pro-bot or anti-bot, you may not have a choice. Rosie the Robot who worked for the Jetsons is probably still far away, but we already have robots that will vacuum our floors and AI has been used in the customer service industry for years.

We need to begin to look at how we can improve technology-related skills while at the same time promoting characteristically human skills. Creativity, intuition, initiative, and critical thinking are human skills that will not likely translate to robots at least not soon. We should already be thinking of how we as employers and employees can harness robots to augment the work we do.

If not already, it won't be long before your next coworker is a robot.

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The Rise Of Artificial Intelligence: Will Robots Actually Replace People? - Forbes

How Artificial Intelligence Can Help Fight Fires in the West – Governing

(TNS) With wildfires becoming bigger and more destructive as the West dries out and heats up, agencies and officials tasked with preventing and battling the blazes could soon have a new tool to add to their arsenal of prescribed burns, pick axes, chain saws and aircraft.

The high-tech help could come way of an area not normally associated with fighting wildfires: artificial intelligence. And space.

Lockheed Martin Space, based in Jefferson County, Colo., is tapping decades of experience of managing satellites, exploring space and providing information for the U.S. military to offer more accurate data quicker to ground crews. They are talking to the U.S. Forest Service, university researchers and a Colorado state agency about how their their technology could help.

The scenario that wildland fire operators and commanders work in is very similar to that of the organizations and folks who defend our homeland and allies. Its a dynamic environment across multiple activities and responsibilities, said Dan Lordan, senior manager for AI integration at Lockheed Martins Artificial Intelligence Center.

Lockheed Martin aims to use its technology developed over years in other areas to reduce the time it takes to gather information and make decisions about wildfires, said Rich Carter, business development director for Lockheed Martin Spaces Mission Solutions.

The concept of a regular fire season has all but vanished as drought and warmer temperatures make Western lands ripe for ignition. At the end of December, the Marshall fire burned 991 homes and killed two people in Boulder County. The Denver area just experienced its third driest-ever April with only 0.06 of an inch of moisture, according to the National Weather Service.

Colorado had the highest number of fire-weather alerts in April than any other April in the past 15 years. Crews have quickly contained wind-driven fires that forced evacuations along the Front Range and on the Eastern Plains. But six families in Monte Vista lost their homes in April when a fire burned part of the southern Colorado town.

Since 2014, the Colorado Division of Fire Prevention and Control has flown planes equipped with infrared and color sensors to detect wildfires and provide the most up-to-date information possible to crews on the ground. The onboard equipment is integrated with the Colorado Wildfire Information System, a database that provides images and details to local fire managers.

Last year we found almost 200 new fires that nobody knew anything about, said Bruce Dikken, unit chief for the agencys multi-mission aircraft program. I dont know if any of those 200 fires would have become big fires. I know they didnt become big fires because we found them.

When the two Pilatus PC-12 airplanes began flying in 2014, Colorado was the only state with such a program conveying the information in near real time, Dikken said. Lockheed Martin representatives have spent time in the air on the planes recently to see if its AI can speed up the process.

We dont find every single fire that we fly over and it can certainly be faster if we could employ some kind of technology that might, for instance, automatically draw the fire perimeter, Dikken said. Right now, its very much a manual process.

Something like the 2020Cameron Peakfire, which at 208,663 acres is Colorados largest wildfire, could take hours to map, Dikken said.

And often the people on the planes are tracking several fires at the same time. Dikken said the faster they can collect and process the data on a fires perimeter, the faster they can move to the next fire. If it takes a couple of hours to map a fire, what I drew at the beginning may be a little bit different now, he said.

Lordan said Lockheed Martin engineers who have flown with the state crews, using the video and images gathered on the flights, have been able to produce fire maps in as little as 15 minutes.

The company has talked to the state about possibly carrying an additional computer that could help crunch all that information and transmit the map of the fire while still in flight to crews on the ground, Dikken said. The agency is waiting to hear the results of Lockheed Martins experiences aboard the aircraft and how the AI might help the state, he added.

They have a strong interest in applying their skills and capabilities to the wildland fire problem, and I think that would be welcome, Finney said.

The lab in Missoula has been involved in fire research since 1960 and developed most of the fire-management tools used for operations and planning, Finney said. Were pretty well situated to understand where new things and capabilities might be of use in the future and some of these things certainly might be.

However, Lockheed Martin is focused on technology and thats not really been where the most effective use of our efforts would be, Finney said.

Prevention and mitigation and preemptive kind of management activities are where the great opportunities are to change the trajectory were on, Finney said. Improving reactive management is unlikely to yield huge benefits because the underlying source of the problem is the fuel structure across large landscapes as well as climate change.

Logging and prescribed burns, or fires started under controlled conditions, are some of the management practices used to get rid of fuel sources or create a more diverse landscape. But those methods have sometimes met resistance, Finney said.

As bad as the Cameron Peak fire was, Finney said the prescribed burns the Arapaho and Roosevelt National Forests did through the years blunted the blazes intensity and changed the flames movement in spots.

Unfortunately, they hadnt had time to finish their planned work, Finney said.

Lordan said the value of artificial intelligence, whether in preventing fires or responding to a fire, is producing accurate and timely information for fire managers, what he called actionable intelligence.

One example, Lordan said, is information gathered and managed by federal agencies on the types and conditions of vegetation across the country. He said updates are done every two to three two years. Lockheed Martin uses data from satellites managed by the European Space Agency that updates the information about every five days.

Lockheed is working with Nvidia, a California software company, to produce a digital simulation of a wildfire based on an areas topography, condition of the vegetation, wind and weather to help forecast where and how it will burn. After the fact, the companies used the information about the Cameron Peak fire, plugging in the more timely satellite data on fuel conditions, and generated a video simulation that Lordan said was similar to the actual fires behavior and movement.

While appreciating the help technology provides, both Dikken with the state of Colorado and Finney with the Forest Service said there will always be a need for ground-truthing by people.

Applying AI to fighting wildfires isnt about taking people out of the loop, Lockheed Martin spokesman Chip Eschenfelder said. Somebody will always be in the loop, but people currently in the loop are besieged by so much data they cant sort through it fast enough. Thats where this is coming from.

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How Artificial Intelligence Can Help Fight Fires in the West - Governing

The Genesis of Artificial Intelligence and Digital Twins – InformationWeek

Artificial intelligence, machine learning, and digital twins -- why are we hearing so much about them and why do they suddenly seem critical? The simplest explanation is this: When something is too complex for a human to easily process or there is too little time for a human to make a critical decision, the only choice is to remove the human. That requires the ability to replicate the thought process a human might go through, which requires a lot of data and a deep understanding of the decision environment.

So why now? For decades, we saw huge advancements come primarily from the integration and shrinking of electronics. Smaller products, consuming less power, and offering dramatic increases in functionality per square inch were the hallmarks of technology progress.

Software applications also have evolved over the decades, one of the most notable ways being the dramatic acceleration of the application adoption cycle. In the past two decades alone, users have shifted at alarmingly fast rates from treating applications as novelties, to using them as a convenience, and then to expecting them to work flawlessly all the time. At each adoption stage, a users expectation rises, meaning the product must evolve and mature at very fast, scalable rates.

The combination of the hardware and software trends formed a convergence of product development requirements. New critical need applications suddenly must feature higher capacity of real-time processing, time-sensitive decision-making, high to very high availability, and expectations that platform-generated decisions be correct, every time.

While most people think of AI primarily as an end-user resource, AI has become necessary for faster product design and development. From the earliest stage of a chipset design or layout of a circuit through end-product validation, emulators have become necessary for building complex interfaces and environments. These emulators, known as digital twins, are a virtual manifestation of a process, environmental condition, or protocol capable of serving as a known good signal. In test terms, a digital twin can be a simple signal generator, a full protocol generator or a complete environment emulator. Digital twins allow developers to rapidly create a significantly wider range of test conditions to validate their product before shipping. High-performance digital twins typically contain their own AI engines for troubleshooting and regression testing new product designs.

The shift to AI-driven development and digital twins has become necessary due to the amount of functionality and autonomous decision-making expected in new products. Basic design principles specify features and functionality of a product, then set up tests to validate them. The sheer number and complexity of interface standards makes that virtually impossible to construct by hand. By using digital twins, a much wider set of functional tests can be programmed in much less time. AI functionality then automates test processes based on what it discovers and predicts actions that might be needed. To understand this better, its useful to understand the core of what makes any AI possible.

In its simplest form, software decision-making starts with algorithms. Basic algorithms run a set of calculations, and if you know what constitutes acceptable results, you can create a finite state machine using decision tree outcomes. This would hardly be considered intelligent. By adding a notation of state, however, and inserting a feedback loop, your basic algorithm can make outcome decisions a function of the current conditions compared to the current state. Combine this while evolving the decision tree into a behavior tree and you have formed the genesis of AI.

The need for AI and digital twins is real, and when you question the veracity of one -- yours or someone elses -- go back to its genesis, otherwise known as the data. Data source(s) are the foundation of any digital assessment tool, and those sources determine the potential of an algorithms modeling accuracy. If multiple data-rich sources are available, then the accuracy potential is high. If only basic data is available, the resulting algorithm or digital twin will not be accurate. This is something you can assess yourself.

We are at the early stage of AI, which means lots of products will be making lots of claims. Understanding what a product is supposed to deliver will allow you to assess it. Understanding which data sources it processes will tell you how accurately it can deliver the results the vendor promises. Digital twins are much further along in maturity -- especially those that emulate specific elements rather than entire ecosystems. Remember, though, that the more finite the environment, the more likely the digital twin will accurately replicate it.

We all want to understand how something works and how it produces its outcomes. With an understanding of the basic elements inside every AI system and digital twin, you can ask questions about their fundamental elements. If you get stuck, use the steps as a guide for questions to ask of the vendor. Most will share all or some of the key background or parameters to help you understand. I they dont, their competitors will.

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The Genesis of Artificial Intelligence and Digital Twins - InformationWeek