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IRVINE, CA, Aug. 05, 2021 (GLOBE NEWSWIRE) -- via NewMediaWire -- Vita Mobile Systems, Inc. (OTC PINK: VMSI), a technology company focused on digital imaging in mobile devices, collection and management of big data and development of artificial intelligence, today announced the acquisition of My2Tum through a share exchange agreement. My2Tum brings proprietary Artificial Intelligence (AI) technology that allows users to find up-to-date health and safety information by location, complementing VMSIs own geolocation-based social application platforms.

The significance of this acquisition is immense, and bringing on My2Tum is a huge step forward for VMSI, stated Sean Guerrero, CEO of Vita Mobile Systems. The pandemic has made it clear that accurate and timely health and safety information for locations around the world is crucial for both business and personal needs. For example, businesses could leverage this data to better support their employees and deliver to their customers, and individuals would be able to travel anywhere in the world with the confidence and the assurance that is required to make their trip a successful one.

Pursuing a similar goal of providing the most up-to-date geolocation-based information has made My2Tum a perfect synergistic acquisition for VMSI. We are excited to launch our first My2Tum product, as part of our VMSI portfolio, which is slated to be introduced to the public this fall, continued Guerrero. This acquisition strengthens both the future of VMSI and its management team. As we incorporate My2Tum into VMSI, we anticipate strategic management changes and plan to announce those changes once the expected appointments take place.

To learn more about VITA please visit the Vita Mobile Systems website at http://www.vitamobilesystems.com.

About Vita Mobile Systems, Inc.(www.vitamobilesystems.com)

Vita Mobile Systems, Inc. (OTC PINK: VMSI) is a technology company focusing on digital imaging in mobile devices, collection of big data and development of artificial intelligence. Vita Mobile Systems is currently finalizing their first geolocation-based, social media app "VITA" for release on both iOS and Android. Comprised of a strong foundation of successful entrepreneurs, Vita Mobile Systems has developed proprietary algorithms and tools which gather, categorize, analyze and augment digital content. Over the years, Vita Mobile Systems has used these proprietary marketing, social media, and data collection tools to generate significant amounts of internet traffic for advertising networks. Vita Mobile Systems aims to create a monumental library of crowdsourced content, a massive catalogue of predictive big data, and platform for ultra-targeted advertising. The company expects to establish a strong foundation within the multibillion-dollar industry of driving big data and targeted advertising through its process of cataloging, meta-tagging, analyzing, and predicting trends of everyday people in everyday life.

Cautionary Language Concerning Forward-Looking Statements:

This press release contains forward-looking statements. The words or phrases "would be," "will allow," "intends to," "will likely result," "are expected to," "will continue," "is anticipated," "estimate," "project," or similar expressions are intended to identify "forward-looking statements." Actual results could differ materially from those projected by VITA. The public filings, if any, of Vita Mobile Systems, Inc. (OTC Pink: VMSI) may be accessed at http://www.otcmarkets.com. Statements made herein are as of the date of this press release and should not be relied upon as of any subsequent date. VITA cautions readers not to place reliance on such statements. Unless otherwise required by applicable law, VITA does not undertake, and VITA specifically disclaims any obligation, to update any forward-looking statements to reflect occurrences, developments, unanticipated events or circumstances after the date of such statement.

Contact:

Vita Mobile Systems, Inc.

2640 Main St.

Irvine, CA 92614

949-864-6902

info@vitamobilesystems.com

Investor Relations:

949-864-6902

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Vita Mobile Systems Acquires Artificial Intelligence Company with Location-based Health and Safety Software Platform - GlobeNewswire

In the invite to its AI Day, Tesla is teasing the use of artificial intelligence beyond its electric vehicle fleet.

What do you think theyre talking about?

As we have reported over the last week, Tesla is preparing for its upcoming AI Day on August 19.

Over the last few years, Tesla started holding events, not really to unveil new products, but to present new technologies that it has been working on in certain fields.

For example, it held a Tesla Autonomy Day in 2019 and a Tesla Battery Day last year.

Tesla AI Day is expected to be similar, and CEO Elon Musk said that they will discuss advancements in both AI hardware and software, specifically with the automakers new Dojo supercomputer and its neural nets.

Now Tesla has sent out invites to the event and confirmed presentations regarding those technologies, but the most interesting part is that Tesla teased an inside look at Teslas use of AI in things other than vehicles:

This invite-only event will feature a keynote by Elon, hardware and software demos from Tesla engineers, test rides in Model S Plaid, and more. Attendees will be among the first to see our latest developments in supercomputing and neural network training. They will also get an inside look at whats next for AI at Tesla beyond our vehicle fleet.

Musk has often hyped Teslas AI team as one of the best in the world, but it has always been mostly about the automakers self-driving effort.

The automaker has been known to also use AI in non-consumer products, like in its energy software Autobidder, and the automaker has also been extensively using AI in manufacturing.

Gavin Hall, Tesla staff machine learning and controls engineer, describes his work integrating AI in Tesla Gigafactories:

At the Tesla Gigafactory, I develop the supervisory machine learning algorithms used in automated computer vision tasks and the real-time control optimization strategies of factory systems with respect to energy costs, setpoint errors, and equipment downtime.

Our machine vision solutions use deep learning via convolutional neural network variants for classification, detection and segmentation, while our control system cloud architecture combines AI, big data, control theory, and industrial control by leveraging Python to use continuous deep reinforcement learning, model predictive control, state estimation, and recurrent supervised learning models to forecast loads and plan the optimal sequence of control actions sent to PLCs.

That may or may not be what Tesla is hinting at, but we wont know until August 19.

Thats interesting. It could be some backend applications, but for some reason, I think it could also be related to new consumer products.

When you think about it, if Tesla can truly solve self-driving, it is safe to assume that some of these computer vision developments would apply to other products.

Its interesting that Tesla is apparently partnering with roboticist Dennis Hong, which could be part of what the automaker is talking about here.

Hong is known for working on humanoid robots, so it would be quite surprising for Tesla to get into that space at this point.

But it wouldnt be shocking to see Tesla working on some kinds of new robots. Maybe well finally see the Tesla robot snake charger?

What do you think? Let us know in the comment section below.

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Tesla teases future products using artificial intelligence not related to its electric vehicle fleet - Electrek

Americans have good reason to be skeptical of artificial intelligence. Tesla crashes have dented the dream of self-driving cars. Mysterious algorithms predict job applicants performance based on little more than video interviews. Similar technologies may soon be headed to the classroom, as administrators use learning analytics platforms to scrutinize students written work and emotional states. Financial technology companies are using social media and other sensitive data to set interest rates and repayment terms.

Even in areas where A.I. seems to be an unqualified good, like machine learning to better spot melanoma, researchers are worried that current data sets do not adequately represent all patients racial backgrounds.

U.S. authorities are starting to respond. Massachusetts passed a nuanced law this spring limiting the use of facial recognition in criminal investigations. Other jurisdictions have taken a stronger stance, prohibiting the use of such technology entirely or requiring consent before biometric data is collected. But the rise of A.I. requires a more coordinated nationwide response, guided by first principles that clearly identify the threats that substandard or unproven A.I. poses. The United States can learn from the European Unions proposed A.I. regulation.

In April, the European Union released a new proposal for a systematic regulation of artificial intelligence. If enacted, it will change the terms of the debate by forbidding some forms of A.I., regardless of their ostensible benefits. Some forms of manipulative advertising will be banned, as will real-time indiscriminate facial recognition by public authorities for law enforcement purposes.

The list of prohibited A.I. uses is not comprehensive enough for example, many forms of nonconsensual A.I.-driven emotion recognition, mental health diagnoses, ethnicity attribution and lie detection should also be banned. But the broader principle that some uses of technology are simply too harmful to be permitted should drive global debates on A.I. regulation.

The proposed regulation also deems a wide variety of A.I. high risk, acknowledging that A.I. presents two types of problems. First, there is the danger of malfunctioning A.I. harming people or things a threat to physical safety. Under the proposed E.U. regulation, standardization bodies with long experience in technical fields are mandated to synthesize best practices for companies which will then need to comply with those practices or justify why they have chosen an alternative approach.

Second, there is a risk of discrimination or lack of fair process in sensitive areas of evaluation, including education, employment, social assistance and credit scoring. This is a risk to fundamental rights, amply demonstrated in the United States in works like Cathy ONeils Weapons of Math Destruction and Ruha Benjamins Race After Technology. Here, the E.U. is insisting on formal documentation from companies to demonstrate fair and nondiscriminatory practices. National supervisory authorities in each member state can impose hefty fines if businesses fail to comply.

To be sure, Europes proposal is far from perfect, and the E.U. is not alone in considering the problems of artificial intelligence. The United States is starting to grope toward basic standards of A.I. regulation as well. In April, the Federal Trade Commission clarified a 2020 guidance document on A.I., stating that U.S. law prohibits the sale or use of racially biased algorithms.

However, the problems posed by unsafe or discriminatory A.I. do not appear to be a high-level Biden administration priority. As a remarkable coalition of civil rights and technology policy organizations complained this month: Since assuming office, this administration has not pursued a public and proactive agenda on the civil rights implications of A.I. In fact, the Trump administrations executive orders and regulatory guidance on A.I. remain in force, which constrains agencies across the federal government in setting policy priorities.

Things are somewhat better on the state level. A more robust proposal is now under discussion in California to regulate public contracts for the provision of A.I.-based products and services. Legislators in Washington State are discussing a similar proposal. The proposed California law has some elements in common with the European approach and with the Canadian model of Algorithmic Impact Assessment, designed to mitigate bias and unfairness in emerging A.I. for public administration. Despite its limited scope, the California proposal would require tech companies that provide A.I. to state agencies to prepare a detailed data management plan, to make algorithms explainable even to a nonexpert audience and to prevent discriminatory biases.

The states can accomplish a lot on their own. However, the real challenge now is national leadership. The Biden administration should harmonize the U.S. approach with that of Europe, committing to require high quality data, documentation and traceability, transparency, human oversight, accuracy and robustness for high-risk A.I. systems, as the proposed European A.I. Act puts it. For example, if a machine is going to decide whether or not you are hired for a job, at the very least you deserve regulatory oversight to ensure that it is using proper data, that it has actually performed well and in a nondiscriminatory way in the past and that you can appeal to someone if you can demonstrate it has made a mistake. And if the system is based on pseudoscientific claptrap, you should not be judged by it at all.

Federal agencies like the Equal Employment Opportunity Commission can either address these problems under existing law or propose statutory language to grant them the authority to do so. But they need to act more aggressively now, while the technology is still developing. The White House needs to bring agency leaders together to learn from experts about best practices, and solicit comments from those affected by A.I. This approach would both democratize and professionalize U.S. technology policy in crucial areas.

A.I. developers should not simply move fast and break things, to quote an early Facebook motto. Real technological advance depends on respect for fundamental rights, ensuring safety and banning particularly treacherous uses of artificial intelligence. The E.U. is now laying the intellectual foundations for such protections, in a wide spectrum of areas where advanced computation is now (or will be) deployed to make life-or-death decisions about the allocation of public assistance services, the targets of policing and the cost of credit. While its regulation will never be adopted verbatim by the United States, there is much to learn from its comprehensive approach.

Frank Pasquale is a professor at Brooklyn Law School and the author of New Laws of Robotics: Defending Human Expertise in the Age of AI. Gianclaudio Malgieri is an associate professor at the EDHEC Augmented Law Institute in France.

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Opinion | If You Dont Trust A.I. Yet, Youre Not Wrong - The New York Times

What better time for a next-generation version of art to come crashing into the art world than 2021? After all, this is the unprecedented year that saw an explosion of demand and sales of NFTs or non-fungible tokens, which are inextricably tied to crypto-currency and blockchain technology. Specifically, were now talking about art created byartficial intelligence yes, the machines are taking over art too.

In 2018, ChristiessoldPortrait of Edmond de Belamy(2018), the first-ever original work of art created using artificial intelligence to come to auction (it sold for $432,500 against a high estimate of $10,000), Inspired by reports of the sale, Ben Kovalis and two like-minded childhood friends from Israel, Eyal Fisher and Guy Haimovitz, launched the Art AI Galleryone year later, in late 2019. It involves collections of curated work made using an algorithm that was created over the course of six months and then refined over the next year and a half.

The Christies auction was amazing to us because we are enthusiastic about art but also tech savvy, Kovalis told Artnet News in a phone interview from London. He and his friends were stunned first by the fact that AI could create art and then by the fact that it could garner the type of price it did, he said.

We were enthusiastic. We were already speaking about opening a startup company togetherwhich is the dream of every Israeli guy between the ages of 20 and 30, he said with a laugh.

Last month, the group introduced Artifly, which takes its algorithm development work a step further. Customers scroll through a selection of artwork and click the designs they like, in order to show Artifly your style. Then, the user clicks a button reading Make My Art, Artifly (the name of which is meant to evoke the phrase Art on the Fly) becomes familiar with your selectionsand then near instantly, in about a minute, it creates a brand-new personalized artwork. The user then has the option, though not the obligation, to buy a bespoke piece of AI art.

Obvious Arts [ ())] + [( (()))], Portrait of Edmond de Belamy,Generative Adversarial Network print on canvas (2018).

At the time of the 2018 auction of Obvious, Fisher was working onimage processing and analysis for his PhD in mathematical genomics at Cambridge University. He was inspired by the headlines about the Christies sale to start working on algorithms.

Bold (2021). Image courtesy of Art AI Gallery and Artifly.

He thought that hecould create an algorithm that would make way more beautiful and very engaging art, says Kovalis. The idea is not to create a single one and sell it for $100,000 but to create thousands and tens of thousands of them and still keep them one of a kind, so anyone can enjoy them.

Kovalis has extensive background in e-commerce, having formerly been a VP in the high-tech sector, managing large international operations.

The company founders say that the most common question they face is, so you want to replace human artists with robots? Kovalis has a readymade response: Definitely notfirst of all because we dont think that it is possible to replace artists. Thisis simply something that enhances art.He also emphasizes just how much human effort is still required for the process. You need a lot of sweat, and tears and human involvement to make an AI algorithm that creates something beautiful.

Selection of four potential artworks generated by Artifly.

He compares the use of AI to musicians starting to use synthesizers in the 1980s to create a new type of music. Not everyone liked the synthesizer. Many did, many didnt, but it developed into something that helped create pop music. Today, music is the same music that we know and love, it just has some technology in it. This is the same thing that were doing with art.

As for cost, the prices of the works hover around a few hundred dollars at most. It remains to be seen whether a secondary or resale market develops based on the individual certificates of authenticity that can accompany such transactions. And it also remains to be seen whether or not values begin to creep up as they do over time for works sold by galleries and auction houses.

Screenshot of a custom artwork created by Artifly.

For many people,Kovalis says, there is a learning curve when it comes to becoming comfortable with AI-created art. People can be a bit scared at first. They know about self-drivingcars, but seeing an AI that creates art is the wild frontier.

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Artificial Intelligence May Have Cracked the Code to Creating Low-Priced Works on Canvas - artnet News

DUBLIN, Aug. 5, 2021 /PRNewswire/ -- The "Global Warehouse Automation Market: Insights & Forecast with Potential Impact of COVID-19 (2021-2025)" report has been added to ResearchAndMarkets.com's offering.

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The global warehouse automation market is likely to record growth at a CAGR of 13.6% during the period spanning 2021-2025, and reach US$30.99 billion in 2025.

Growth in the global warehouse automation market was supported by several factors like surging adoption of industrial IoT, rising urbanization and growing e-commerce sales. The market is predicted to experience growth in the future years that is likely to be driven by increasing use of artificial intelligence and rising adoption of robotics in warehouse automation. However, lacking availability of skilled labor force and mechanical challenges associated with warehouse automation would impose constraints on the market growth.

The global warehouse automation market by technology can be segmented as follows: MRO services, AGV & AMR, storage systems, picking systems, WMS/WES/WCS, palletizing & depalletizing, sortation systems, AIDC, conveyor systems and overhead systems. In 2020, the market was dominated by MRO services, which was followed by AGV & AMR, storage systems, picking systems, WMS/WES/WCS, palletizing & depalletizing, sortation systems, AIDC, conveyor systems and overhead systems.

The global warehouse automation market on the basis of geography can be segmented into the following: North America, Asia Pacific, Europe, Latin America and Middle East & Africa. The market in 2020 was dominated by North America. This was followed by Asia Pacific, Europe, Latin America and Middle East & Africa.

Scope of the Report

The report provides a comprehensive analysis of the global warehouse automation market with potential impact of COVID-19.

The global market has been analyzed.

The market dynamics such as growth drivers, market trends and challenges are analyzed in-depth.

The competitive landscape of the market, along with the company profiles of leading players (Honeywell International, Muratec, Kion Group, Daifuku, KUKA Group and KNAPP Group) are also presented in detail.

Key Topics Covered:

Story continues

1. Market Overview1.1 Warehouse Automation - Introduction1.2 Types of Warehouse Automation1.3 Automating a Warehouse1.4 Categories of Warehouse Automation1.5 Steps to Automate a Warehouse1.6 Benefits of Warehouse Automation

2. Impact of COVID-192.1 COVID-19 Impact on Warehouses2.2 Growth in e-Grocery Industry

3. Market Analysis3.1 Global Warehouse Automation Market by Value3.2 Global Warehouse Automation Market Forecast by Value3.3 Global Warehouse Automation Market by Technology3.3.1 Global MRO Services Warehouse Automation Market by Value 3.3.2 Global MRO Services Warehouse Automation Market Forecast by Value 3.3.3 Global AGV & AMR Warehouse Automation Market by Value3.3.4 Global AGV & AMR Warehouse Automation Market Forecast by Value 3.3.5 Global Picking System Warehouse Automation Market by Value 3.3.6 Global Picking System Warehouse Automation Market Forecast by Value 3.3.7 Global Storage System Warehouse Automation Market by Value 3.3.8 Global Storage System Warehouse Automation Market Forecast by Value 3.3.9 Global WMS/WES/WCS Warehouse Automation Market by Value3.3.10 Global WMS/WES/WCS Warehouse Automation Market Forecast by Value3.3.11 Global Palletizing & Depalletizing Warehouse Automation Market by Value3.3.12 Global Palletizing & De-palletizing Warehouse Automation Market Forecast by Value3.3.13 Global Sortation Systems Warehouse Automation Market by Value3.3.14 Global Sortation Systems Warehouse Automation Market Forecast by Value3.3.15 Global AIDC Warehouse Automation Market by Value3.3.16 Global AIDC Warehouse Automation Market Forecast by Value3.3.17 Global Conveyor Systems Warehouse Automation Market by Value3.3.18 Global Conveyor Systems Warehouse Automation Market Forecast by Value3.3.19 Global Overhead Systems Warehouse Automation Market by Value3.3.20 Global Overhead Systems Warehouse Automation Market Forecast by Value3.4 Global Warehouse Automation Market by Region

4. Regional Market4.1 North America4.1.1 North America Warehouse Automation Market by Value4.1.2 North America Warehouse Automation Market Forecast by Value4.1.3 The US Warehouse Automation Market by Value4.1.4 The US Warehouse Automation Market Forecast by Value4.2 Asia Pacific4.3 Europe4.4 Latin America4.5 Middle East & Africa

5. Market Dynamics5.1 Growth Drivers5.1.1 Increasing Adoption of Industrial IoT 5.1.2 Upsurge in e-Commerce Sales 5.1.3 Surging Urbanization5.1.4 Increasing Warehouse Labor Costs5.1.5 Rising Consumer Demand for Quick Delivery5.2 Key Trends & Developments5.2.1 Expanding Use of Artificial Intelligence5.2.2 Increasing Adoption of Robotics in Warehouse Automation5.3 Challenges5.3.1 Lack of Skilled Labor & Project Execution Resources5.3.2 Mechanical Challenges of Warehouse Automation

6. Competitive Landscape6.1 Global Market6.1.1 Revenue Comparison - Key Players 6.1.2 Market Capitalization Comparison - Key Players 6.1.3 Research & Development Expenses Comparison - Key Players 6.1.4 Global Warehouse Automation Market Share - Key Players

7. Company Profiles7.1 Business Overview7.2 Financial Overview 7.3 Business Strategies

Daifuku

Honeywell International

Kion Group (Dematic)

KNAPP Group

KUKA Group (Swisslog)

Muratec

For more information about this report visit https://www.researchandmarkets.com/r/lg4hrl

Media Contact:

Research and Markets Laura Wood, Senior Manager press@researchandmarkets.com

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Global Warehouse Automation Markets 2021-2025 - Expanding Use of Artificial Intelligence & Increasing Adoption of Robotics in Warehouse Automation...