Reliance Industries Limited (RIL), on Friday, posted the proceedings of its Q2 FY 2022-23 earnings call on the metaverse. This is the first time in corporate India that a company has used metaverse to engage with its stakeholders.
The RIL metaverse was produced in collaboration with GMetri, a no-code metaverse creation platform. To access it, one doesn’t need to wear AR/VR headgear.
The metaverse contains nearly an hour of results commentary, where Group Joint CFO V. Srikanth covers consolidated financials and business summary, Reliance Jio Infocomm Ltd (RJIL) President Kiran Thomas covers Jio Platforms and digital services, and RJIL Head of Strategy Anshuman Thakur covers Jio digital services/financials. It also features Senior Vice President, E&P, Sanjay Roy, covering Hydrocarbons – Exploration & Production and Strategy and Business Development head Gaurav Jain covering Reliance Retail.
Using it, analysts worldwide tracking the company can toggle with graphics and slides placed on different screens through the multiple buckets in the presentation of the results. They can also download the RIL Q2 22-23 media release and the media and analyst call transcript in PDF formats. The RIL metaverse also features a special section containing quotations from RIL Managing Director and Chairman Mukesh Ambani.
The metaverse is a virtual space built with the idea of immersing users within the online experience, mainly via virtual and augmented reality, while enabling them to interact with each other virtually. Due to its ongoing evolution, the term ‘metaverse’ currently has no single definition.
Automation in industrial engineering defines fast, reliable processing, designing, implementing, and maintaining industrial systems and products. Automation allows one to carry out complex tasks in industries by strengthening and rapidly processing them daily, as premium products need premium attention while manufacturing. It makes tasks easier with reliable and cutting-edge technology. As the demand for consistent, perfect, and safe solutions from industrial automation is rising, Industrial automation companies are coming up with innovations and state-of-art products. Here is a list of the top 10 industrial automation companies in 2022.
1. Siemens
Siemens is one of the top engineering companies based in Munich, Germany, with branch offices in over 100 countries. It is a German multinational conglomerate company and the largest industrial manufacturing company in Europe. Siemens’ objective is to create technology that will add real value to customer needs, from resource-efficient factories, resilient supply chains, and smarter buildings and grids to cleaner and more comfortable transportation. The company believes in standing for reliability, engineering quality, and innovation. It is a pioneer in infrastructure, energy solutions, automation, and the software industry. In 1867, Siemens’ founder Werner von Siemens supervised the set up of the first telegraph line between London and Calcutta, which started the partnership of Siemens in India. The company’s primary production is in the industries of infrastructure, energy, and automobile, including turbo compressors, steam turbines, high-voltage switchgear (circuit breakers, disconnectors, and gas-insulated switchgear), switchboards, and remote monitoring systems (RMS), and more. Siemens combines the real and digital worlds to empower their customers in transforming their industries and markets with digitization and IoT energy-efficient production.
2. ABB Ltd
ABB Ltd (ASEA Brown Boveri Limited) is one of the top automation companies in India that mainly focus on robotics, heavy electrical equipment, and automation technologies. The company values a more productive and sustainable future and implements the idea by transforming society and industry. ABB Ltd is a Swiss multinational corporation headquartered in Zürich, Switzerland, which has been in business since 1988. The company was established when Allmänna Svenska Elektriska Aktiebolaget (ASEA) merged with Brown Boveri & Cie. Also, ABB Ltd ranked 341st in the Fortune Global 500 list of 2018 and has been recorded as a global fortune 500 for 24 years. The production of the company is popular among various industries, including aluminum, automotive, buildings, infrastructure, cement, chemical, data centers, energy efficiency, food and beverage, OEM and panel builders, and oil and gas. To date, ABB has established offices in over 100 countries and has 105,000 employees, as reported in 2021.
3. Mitsubishi Electric
Mitsubishi Electric is a Japanese multinational electronics and electrical equipment manufacturing company established in 1920. It is a core company of the Mitsubishi group, a Japanese autonomous multinational group of companies. Japan is always ahead in the technology and development department with numerous innovative ideas, and Mitsubishi Electric reflects the same. The company has proposed and worked on many more innovations than any other top industrial automation company. The innovations of Mitsubishi include micro working robots, Ceiling-mounted horizontal-type robots, compact SCARA robots, and vertical-type and horizontal-type robots. In 2021, the company reported the financial results for fiscal of a net profit of 193.1 billion yen. Mitsubishi Electric provides reliable factory automation solutions along with a consideration of the next generation of manufacturing via its advanced engineering techniques. The company is a supplier of controllers, drive products, visualization, industrial robots, processing machine, and power monitoring products to many industrial automation companies. Additionally, Mitsubishi supplies to other automation companies like T.Vs and fighter jets.
Emerson Electric Co is an American multinational corporation based in Ferguson, Missouri, U.S., and counts in the Fortune 500 companies list. It was established by John Wesley Emerson in 1890, which services focus on electrical equipments and still stands tall among the automation companies in 2022. The company is one of the top automation manufacturers, providing automation services to empower and strengthen industries. Emerson says, “We help customers in the world’s most essential industries solve the biggest challenges of modern life.” It has around 200 production plants worldwide to provide services to industrial, commercial, and consumer markets. The automation solutions Emerson provides measurement instrumentation, solenoids & pneumatics, control & safety systems, asset management, operations & business management, and even more. Then, these automation solutions, in collaboration with automation businesses, develop complete solutions for the customers according to their industry experience. The Emerson company has two core business platforms, automation solutions, and commercial & residential solutions, which help to easily identify and confront challenges in a complex and unpredictable marketplace.
5. Rockwell Automation
Rockwell Automation is an American industrial automation company founded in 1903 and headquartered in Milwaukee, Wisconsin, U.S. The company is associated with the brands Allen-Bradley, FactoryTalk software, and LifecycleIQ services and is the biggest organization in the American market. Rockwell focuses on architecture and software segments in the production line and delivers automation solutions to customers across the globe with offices in over 100 countries. It is a fortune 500 company and reported financial results in fiscal 2021 with global sales at $7 billion. The company’s tagline is “Innovation, productivity, and sustainability starts here,” and its most advanced automation technologies provide world-class automation solutions among the top industrial automation companies. Rockwell Automation provides various products, including advanced process control, condition monitoring & I/O, distributed control systems, human-machine interface, industrial sensors, manufacturing execution systems, and more. However, the major production of the company is software segments, automation systems, and construction execution systems.
6. Honeywell Automation India Ltd
Honeywell Automation India Ltd (HAIL) is a leading integrated automation and software solution provider based in Hadapsar, Pune. It was established in 1984 as a joint venture of the Tata Group and Honeywell for manufacturing, design, and engineering facilities. HAIL is one of the leading industrial automation companies in India and is a fortune India 500 company. It has offices across India in 20 locations, including Bengaluru, Chennai, Dehradun, Delhi, Gurugram, Hyderabad, Kolkata, Madurai, Mumbai, Pune, and Vadodara. Honeywell has three state-of-art manufacturing facilities and four global technology development and innovation centers. It is a pioneer company in process automation control in the field of aerospace engineering. Additionally, Honeywell provides process, software, and building solutions with environmental and combustion controls.
7. Schneider Electric
Schneider Electric is a French multinational company that offers both software and hardware focusing on energy management and digital automation systems. It is a fortune global 500 company that was established in 1836 and based in Rueil-Malmaison, France. Along with being a top industrial automation company, it is a research company too, and the parent company of Square D, APC, and others. The company combines energy technologies, real-time automation, software, and services to provide state-of-art products to homes, buildings, data centers, infrastructure, and industries. The various products of Schneider Electric include Tricones – a safety system, DCS – EcoStruxure Foxboro, industrial communication, interface, measurement and control relays, sensor and RFID system, and so on. As the company’s mission is to be the digital partner for sustainability and efficiency, they develop connected technologies and solutions to manage energy and process in safe and reliable ways. Recently, Schneider was highlighted for its innovation with EcoStruxure, which will modernize the monitoring and management of complex and hybrid infrastructure.
Yokogawa Electric Co. is a Japanese multinational electrical engineering and software company which is based in Tokyo, Japan, and founded in 1915. The company operates in information technologies, industrial automation, test, control, and measurement. Yokogawa has some popular and state-of-art products such as production control systems, test and measurements, pressure transmitters, oxygen analyzers, and more. Its Indian partner group, Yokogawa India Limited (YIL), was established in 1987 and stands today as a comprehensive solutions provider of enterprise technology solutions and holds an honorable position among the top industrial automation companies. YIL has built the global engineering center and manufacturing center in Bengaluru, Karnataka, and has a solid marketing and service network over India.
The three smart control systems Yokogawa have are PLC (programmable logic controller), DCS (distributed control system), and SCADA (supervisory control and data acquisition), which perform great and ease the automation process. Additionally, Yokogawa has brought some innovations in the field of industrial automation, these are synaptic business automation, OpreX, and CENTUM VP. Synaptic business automation allows enterprises to automate industrial processes and factory management. OpreX enables users to transform and digitalize their businesses. And CENTUM VP is a factory automation security architecture that consists of field control stations, a control network, and human-machine interfaces.
9. Omron Automation
Omron Automation is one of the leading industrial automation companies that creates, sells, and services integrated automation solutions. It is a Japanese electronics company based in Kyoto, Japa, and was established in 1933 by Kazuma Tateishi. Although the primary business of Omron accounts for the manufacturing and sale of automation components, equipment, and systems, Omron is widely popular for its medical devices. These medical devices include digital thermometers, blood pressure monitors, and nebulizers. In 2007, the company had a milestone when it became one of the earliest producers of automated teller machines with magnetic stripe card readers, known as the IEEE Milestone. Omron has a lot to offer with the manufacture and sale of various automated equipment and systems. Some of its products are sensors (E3NC, E32-LT11N, etc.), switches (pushbutton, indicators level switches, etc.), relays (G2RV-SR and G7SA), control components, safety components (OS32C, F3SG-SR/ PG series), and more.
10. Danahar Industrial Ltd
Danahar Industrial Ltd is an American multinational science and technology innovator corporation headquartered in Washington D.C., U.S. The company is a fortune 500 which was established in 1984, constituting an idea of discrete manufacturing businesses. Then, with the adaptation of kaizen, the Japanese philosophy of continuous improvement, Danahar was transformed into the Danahar Business System (DBS). And today, the company is committed to helping clients solve their complex challenges and improving their quality of life. Danahar provides its services and products to transform the fields of life sciences, diagnostics, and environmental and applied solutions. The company designs, manufactures and markets professional, medical, industrial, and commercial products and services innovatively. The innovations include globally helping scientists to understand chronic disease and infection by working at the molecular level and developing new therapies. The company ensures the freshness and safety of food, pharmaceuticals, and consumer goods. And to provide important tools and software for clinicians to improve diagnosis and enhance patient care.
Generative adversarial networks (GANs) have been the most promising AI algorithms in recent years. These are one of the newest fields in machine learning, reaching new heights for their malleable applications in computer vision, data science, or any domain. There are numerous applications for the large-scale, effective production of GANs images, which are used to solve various image-to-image translations. Now, let’s talk about generative adversarial networks (GANs) and the top GANs images produced in image generation projects.
What is Generative Adversarial Network?
A generative Adversarial Network is a generative modeling approach. GAN takes two neural networks to compete in the form of a zero-sum game to give predictions more accurately. These two neural networks are called the generator and the discriminator, which enables an unsupervised learning module. Unsupervised learning is a learning algorithm that learns patterns from untagged data. Similar to mimicry in evolutionary biology, the neural network is expected to learn and find hidden patterns or data groupings in the data. GAN is a class of machine-learning models introduced by Ian Goodfellow and his colleagues in 2014.
The GANs became popular among researchers quickly because of their property to generate new data with the same statistics as the input training set. It can be applied to images, videos, textual data, and more, proving useful for semi-supervised, fully supervised, and reinforcement learning. The base idea of a GAN is to have an indirect training approach via a generator and discriminator. The generator is a convolutional neural network that works to fool the discriminator by artificially producing outputs. And the discriminator is a deconvolutional neural network responsible for telling how realistic the input seems, which gets updated dynamically.
The research with GAN has been at its peak since it was introduced as the innovations of GAN follow great success in computer vision. The most popular GAN architectures are CycleGAN, StyleGAN, pixelRNN, text-2-image, DiscoGAN, and IsGAN. Various real-world applications of GANs deal with images, audio, videos, and text data, including realistic image generation, improving the quality of photographs, audio synthesis, transfer learning, and many more. In recent times, there has been a tremendous success in the production of GANs images, including Deepfake Apps, and with some more fine-tuning, GANs will give state-of-art results.
Image generation and image synthesis are one of the most important aspects of GANs application which can be applied in many fields. The few projects mentioned below are one of the best GANs images produced in the last few years.
Anime Characters
GANs are changing the way of generating realistic anime characters and bringing out the potential of complex GAN architecture to build entire anime series with the help of AI. In the paper “Towards the Automatic Anime Characters Creation with Generative Adversarial Networks,” Yanghua Jin and his team trained and used GAN to generate the faces of anime characters or Japanese comic book characters in 2017. The outcome of the project was remarkable, which led people to conduct more experiments on the image generation of faces of anime characters and the generation of pokemon characters. Many GAN models are used to generate cartoon characters, such as DCGAN, StyleGAN, and so on.
Fake Human Faces
Facial recognition has many use cases, and the development has been in progress for the last couple of years, where researchers are using different techniques and facial recognition datasets to train models. Researchers need massive datasets of human faces to understand the recognition process, and the generation of fake human faces helps these projects. NVIDIA researchers published a paper, “Progressive Growing of GANs for Improved Quality, Stability, and Variation,” in 2018, where they proposed a new training methodology for GANs operating on the generation of feasible human face photographs. The paper’s outcome is so realistic-looking that it can fool anyone easily. Additionally, the paper presented the generation of objects and scenes as well.
Image Style Transfer
Image style transfer is an interesting technique in computer vision that combines two images. This technique consists of a model taking two images, called content and reference images, and the output is a whole new image containing the object of the content image and the style of the reference image. Here by style, it means brush strokes, colors, and textures of the image. Researchers are still trying to find the best ways and use cases of style transfer. This technique is included in the image-to-image translation and is also known as domain adaptation. There are many research work on image style transfer using GANs, and most have produced good results. A remarkable study is the paper “P²-GAN: EFFICIENT STYLE TRANSFER USING SINGLE STYLE IMAGE.” Zhentan Zheng and Jianyi Liu put forth a novel patch permutation GAN (P²-GAN), which proves efficient in learning stroke styles from paintings or single style images. The paper concludes with an effective and precise P²-GAN network simulating the expected stroke style and avoiding the difficulty of collecting image sets with the same style.
Text-to-Image (text-2-image) Synthesis
Generating realistic images is challenging, but using GANs makes the process a reality rather than theories. Although we got problems with image-to-image generation or translation, the synthesis of text-to-image realistic images using GANs is more complex and difficult. The process of synthesis needs a strong GAN structure along with the base images provided. There are many papers on the task which have computed impressive outcomes. In 2016, Han Zhang and his team from the Chinese University of Hong Kong presented “StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks,” explaining the use of GANs. Mainly, the StackGAN to generate realistic photographs from textual data of simple objects such as birds and flowers. Also, the paper “Generative Adversarial Text to Image Synthesis” and “TAC-GAN – Text Conditioned Auxiliary Classifier Generative Adversarial Network” present the study of generating realistic images through text-to-image synthesis with the help of GANs.
Image-to-Image Translation
Image-to-image translation includes many tasks, such as the translation of semantic images to photographs, satellite photographs to google maps, black and white photographs to color, and more. Many papers have been published demonstrating the use of GANs for image-to-image translation, and one of the popular papers is “Image-to-Image Translation with Conditional Adversarial Networks” by Berkeley AI Research group in 2016. This paper has an investigational approach toward conditional adversarial networks if they serve as a general-purpose solution to image-to-image translation problems. They use a unique pix2pix approach for various image-to-image translation tasks. Additionally, the paper titled “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks” presents the famous CycleGAN and a set of impressive image-to-image translation cases like translation from photograph to artistic painting style, photographs from summer to winter, and translation of horse to zebra.
List of top Generative Adversarial Networks Images
These are the top images made by GANs from research papers for image generation using GANs. The list consists of GANs images produced in the papers mentioned earlier and a few other interesting papers with significant outputs.
1. Cartoon Face Images
Credit: Towards the Automatic Anime Characters Creation with Generative Adversarial Networks
The image shown is from the anime character faces generation project in the paper “Towards the Automatic Anime Characters Creation with Generative Adversarial Networks.” The image is generated with the fixed noise part and random attributes. For more information, check out the paper.
2. Forged Face Images
Credit: Progressive Growing of GANs for Improved Quality, Stability, and Variation
The image shown is made by GAN from the paper “Progressive Growing of GANs for Improved Quality, Stability, and Variation.” The GANs image shown is the images generated using the CelebA dataset with high resolution.
The image shown is made by GAN from the paper “Progressive Growing of GANs for Improved Quality, Stability, and Variation.” The GANs image shown is the images generated using the CelebA dataset with high resolution.
Credit: A Style-Based Generator Architecture for Generative Adversarial Networks
This GANs image is from a famous paper, “A Style-Based Generator Architecture for Generative Adversarial Networks,” which is associated with the generation of the Flicker Faces HQ dataset. The paper studies an alternative generator architecture for GAN with some style transfer literature. The image presented here includes the images synthesized by mixing two latent codes at various scales. And each subset of styles controls meaningful high-level attributes of the image.
This GANs image is from a famous paper, “A Style-Based Generator Architecture for Generative Adversarial Networks,” which is associated with the generation of the Flicker Faces HQ dataset. The paper studies an alternative generator architecture for GAN with some style transfer literature. The image presented here includes the images synthesized by mixing two latent codes at various scales. And each subset of styles controls meaningful high-level attributes of the image.
3. Artificial Flower Images
Credit: Text-to-Image-to-Text Translation using Cycle Consistent Adversarial Networks
The text-2-image synthesis is a topic of interest for many researchers. Here the image shown is the GANs image from the paper “Text-to-Image-to-Text Translation using Cycle Consistent Adversarial Networks,” which is a result of GAN trained with cycle loss and frozen weight of image captioning network. Check out the paper for a better understanding.
The text-2-image synthesis is a topic of interest for many researchers. Here the image shown is the GANs image from the paper “Text-to-Image-to-Text Translation using Cycle Consistent Adversarial Networks,” which is a result of GAN trained with cycle loss and frozen weight of image captioning network. Check out the paper for a better understanding.
4. Artificial Bird Images
Credit: StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
As mentioned above, the paper “StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks” provides a significant output in text-2-image synthesis. The GANs image here is the image generated by StackGAN, which is very photo-realistic.
5. Drawing Real Objects and Vice-versa
Credit: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
As mentioned in the image-to-image translation, the paper “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks” has one of the best GANs images generated to date. Here, the above image is the result of CycleGAN on paired datasets used in pix2pix.
As mentioned in the image-to-image translation, the paper “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks” has one of the best GANs images generated to date. Here, the above image is the result of CycleGAN on paired datasets used in pix2pix.
6. Fake Paintings
Credit: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
The image shown is from the paper “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks” and is the collection style transfer II, showcasing the successful style transfer into the artistic styles of Monet, Van Gogh, Cezanne, and Ukiyo-e. The paper has also applied methods to solve image-to-image translation problems and can be improved in the future.
The image shown is from the paper “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks” and is the collection style transfer II, showcasing the successful style transfer into the artistic styles of Monet, Van Gogh, Cezanne, and Ukiyo-e. The paper has also applied methods to solve image-to-image translation problems and can be improved in the future.
7. Altering Photographs
Credit: P²-GAN: EFFICIENT STYLE TRANSFER USING SINGLE STYLE IMAGE
This is a GANs image from the paper “P²-GAN: EFFICIENT STYLE TRANSFER USING SINGLE STYLE IMAGE.” It shows a comparative image of the style transfer from a single style image using various methods, including JohnsonNet, TextureNetIN, MGAN, and P²-GAN.
This is a GANs image from the paper “P²-GAN: EFFICIENT STYLE TRANSFER USING SINGLE STYLE IMAGE.” It shows a comparative image of the style transfer from a single style image using various methods, including JohnsonNet, TextureNetIN, MGAN, and P²-GAN.
The new era of connectivity has resulted in producing massive amounts of data globally, and we need data centers to handle it. Data centers centralize IT operations and hardware for data distribution, processing, storage, and more. According to the United States International Trade Commission, a report in 2021 revealed that there are over 8,000 data centers around the world. And the majority of data centers are located in six countries, including the US, the UK, Germany, China, Canada, and the Netherlands. For a decade, Government and corporate organizations have been spending hundreds to billions on the construction of data centers in light of the data industry’s rapid expansion. Some data center operators believe that the bigger is better. Here is a list of the largest data centers in the world that will help us determine how much of this is accurate. The list includes the world’s biggest data centers that have been established and are currently operational.
1. China Telecom – Inner Mongolia Information Park
The Inner Mongolia Information Park is the world’s largest data center, with 10,763,910 (10.7 million) square feet, and sits on the Beijin-Tianjin economic circle radiation belt. The data center is owned by China Telecom Corporation Limited, which contains a cloud computing data center, call centers, a data warehouse, offices, and living quarters. Additionally, the data center secures over 50% market share in the Chinese data center market. China Telecom is one of the largest providers of integrated telecommunication services around the world. The company was established in 2012, headquartered in Hong Kong, China, and now has a presence in 41 countries and regions. It offers a high-performing global network for international carriers, overseas customers, and multinational enterprises with the vast resource of 47 submarine cables, 95T in intercontinental capacity, and 230 points-of-presence (PoPs) spread worldwide. China Telecom provides a wide range of services, including a portfolio of high-quality, integrated communications solutions, broadband, internet data centers, multi-domestic MVNO (mobile virtual network operator), ICT services, global IoT connectivity service, and more.
2. China Mobile – Hohhot Data Center
The Hohhot Data Center is part of the Inner Mongolia Information Park, contributed by China Mobile International Limited (CMI). CMI is a subsidiary of China Mobile, a Chinese state-owned mobile telecommunications company. The CMI company was established in 2010 to provide better services in the demanding international telecommunications market. Along with the support of China Mobile, CMI has turned to a trusted partner delivering comprehensive international telecom services and solutions. As the telecom needs to transfer and process massive data, the company invested in the Hohhot Data center, one of the world’s largest data centers. The data center is spread over 7,750,015 (7.5 million) square feet that consist of numerous modules which expand the already giant facility and provides concentrated network management, enterprise services, and research and development innovations, including TD-LTE 4G networking and cloud computing.
3. Switch – The Citadel Campus
The Citadel Campus Data Center is one of the prime data centers owned by Switch, located in Tahoe Reno, Nevada. The data center acquires 7.2 million square feet and has up to 650 MW of power using only renewable energy. With its innovative design, development, and mission-critical operations, Switch has one of the world’s largest data centers, the Citadel Campus data center. The data center has its fiber network, a proprietary tri-redundant UPS power system, and a 24×7 DDoS (distributed denial of service) attack mitigation platform. Switch is a global technology and data center service provider founded in 2000 by Rob Roy that develops and operates SUPERNAP data center facilities. Also, the company provides co-location, telecommunications, cloud services, and content ecosystems. Switch empowers the ideas of intelligence and sustainable growth of the Internet and has raised industry standards for data center design, construction and operation to a level of Tier 5 Platinum or Tier Elite.
Utah Data Center (aka Bumblehive) is the first intelligence community comprehensive national cyber security initiative (IC CNCI) data center built under the National Security Agency (NSA) of the United States Intelligence Community. It was built to support the intelligence community’s efforts to monitor, strengthen, and protect the nation. The data center scales around 1.1 million square feet in Utah, the United States and serves as the massive data repository for the NSA. Although the data capacity size of the Utah data center is classified, it will expand in the future and claims to have an ultimate capacity of alottabytes. Additionally, the data center is powered by massively code-breaking supercomputers and uses NSA’s PRISM data, which makes it the most powerful data center in the world.
5. Digital Realty – Lakeside Technology Center
Digital Realty’s Lakeside Technology Center is a data center located in Chicago, Illinois, which is one of the largest data centers in the world. The data center was built in 1917, covering an area of 1.1 million square feet, and it uses 53 generators and 8.5 million gallons of coolant annually, a unique cooling for buildings. The industrial strength of the data center is 100MW, provided by four fiber vaults and three electric power feeds. Digital Realty Trust, Inc, a real estate investment trust, owns the data center and serves tech giants like IBM and Facebook. The trust operates in over 225 data center sites worldwide, including Asia, the United States, Europe, Canada, and Australia. Digital Realty is riding the waves of digital transformation by innovating ideas around data and introducing a PlatformDIGITAL, where companies and data come together despite any size. The platform has embarked on a new initiative around data where businesses, partners, and creators can go faster, invent, and expand globally.
6. Tulip Data Center
Tulip Data Center, or Tulip Data City, is one of the largest data centers in the world, located in Bangalore, India. The data center was built in 2012 and was over 1 million square feet owned by Tulip Telecom Ltd, an Indian telecommunications service provider. It was set up in collaboration with IBM to support the connection for the 2,000 locations Tulip has reached within India. The data center has four towers, each tower consists of seven floors, of which five are assigned as data center space, and the rest are housing facilities. In total, the four towers houses 20 enterprise modular data centers and, at full capacity can have the industrial strength of 100MW power. The design of the data center is aimed at getting Seismic Zone 4 specifications and the widest range of physical security features, video camera surveillance, and security breach alarms. Over the past decade, some of the top data centers in India have been built, and more hyper-scale data centers are planned by tech giants like Microsoft and AWS.
Metro Data Center is a mega data center campus owned by Quality Technology Services (QTS), a leading provider of data center solutions, and is located in Atlanta, Georgia. The facility is spread over 990,000 (0.99 million) square feet consisting of buildings with the support of 46 generators and 24 independent UPS systems. Two discrete substations in the data center help achieve electrical redundancy and power three on-site 40MVA (megavolt ampere) transformers. The data center has an automated management system controlling the critical power system and an automated control system operating air temperature, humidity, and water pressure. Metro Data Center is the biggest data center among the 25 data centers under QTS company. QTS is a real state investment trust company that has a diverse footprint spamming more than 7 million square feet of QTS Mega Data Centers. The company dedicates to providing hardened, redundant, flexible, and scalable hybrid colocation and hyper-scale data center solutions along with innovative software-driven data centers and network services.
8. SDC – Integrate Seattle
Integrate Seattle is a flagship data center of Sabey Data Centers (SDC) located in Seattle, Washington State. The data center has a high-performance design and is built upon the foundations of sustainability, security, and durability. It has a Tier III standard with hydroelectric power and reliable features, including up to 1500kW of critical power per suite, electrical backup systems, 2.5MW capacity generators, and aggregate power of over 90MVA through redundant feeds. Overall, Integrate Seattle has every deployment need, such as low-cost renewable power, efficient cooling, robust connectivity, operational excellence, convenient location, and room to grow. The data center is one of the biggest data centers in the world under SDC. SDC company is the longest-lived multi-tenant and a leading provider of data centers around the world. The company owns, develops, and operates all of its data centers with its large financial partners. SDC is known for its commitment to client satisfaction, for which they provide every service, including design, construction, commission, operation, and support.
Waymo, a company that develops autonomous vehicles, has been testing its vehicles in Phoenix and San Francisco for some time now, as well as offering customers in the Phoenix area free rides. In the upcoming months, the company plans to introduce self-driving robotaxi service in major districts of Los Angeles. The self-driving technology division of Alphabet Inc. is now focused on three markets.
Since 2019, Waymo has occasionally visited Los Angeles to map neighborhoods, including downtown, Miracle Mile, Koreatown, Santa Monica, Westwood, and West Hollywood. According to the new suggested plans, more than a dozen Waymo autonomous cars would initially be in Los Angeles before expanding from there. This week, Waymo will begin rolling out a fleet of electric Jaguar I-Pace SUVs with laser lidar units, cameras, radar, and other sensors that will initially exclusively carry Waymo staff.
Saswat Panigrahi, the chief product officer at Waymo, stated that the company would start public testing after it has gathered the necessary approvals and feedback. He opted not to disclose the number of vehicles involved in the new initiative or the launch date for a paid transportation service for the general public.
The Los Angeles metro area, which has a population of over 13 million people, presents a lucrative business opportunity since it is the third-largest ride-hailing market in the United States and could be worth US$2 billion in 2022. Waymo is teaming with regional organizations Mothers Against Drunk Driving’s California chapter and Los Angeles County Bicycle Coalition in the lead-up to its eventual launch.
Waymo opens the driverless ride service to the general public in the US city of Los Angeles
The expansion into a third city happens as predictions for the widespread use of self-driving cars become less optimistic, including critics questioning the future of the Alphabet company. According to Waymo, Los Angeles is still far bigger and more complicated than the places where it has previously worked.
In terms of geography, San Francisco is much more congested, which is one of the reasons robotaxi firms have been testing there, although Phoenix is typically regarded as having superior planning and road signs.
On the other hand, Los Angeles has a more intricate network of municipal streets and highways; not all are in good condition or have obvious markers. Additionally, it is thought that the traffic situation is far worse than in San Francisco. Waymo still has to win approval from two regulatory organizations, the California Public Utilities Commission and the California Department of Motor Vehicles, which govern autonomous car testing and deployment.
Testing of autonomous vehicles—both with and without safety operators—is governed by the California Department of Motor Vehicles. Companies wishing to test AVs without a human driver at the wheel must get a driverless testing permit. A deployment permit is the final step with the Department of Motor Vehicles.
The California Public Utilities Commission has “drivered” and “driverless” permits that allow businesses to provide rides in their self-driving cars. Waymo needs a license from the California Public Utilities Commission in order to charge for rides.
Waymo has joined its rival Motional, an autonomous vehicle initiative developed jointly by Aptiv and Hyundai, in operating in Los Angeles County. Motional teamed up with Uber Eats to start performing limited driverless food deliveries in Santa Monica in May of this year.
Stability AI, creator of Stable Diffusion and DreamStudio, recently announced that it had secured US$101 million in a fundraising round to support the creation of open-source systems. Leading the investment round were O’Shaughnessy Ventures LLC, Coatue, and Lightspeed Venture Partners. The London-based company will use these funds to accelerate the development of open AI models for language, image, audio, 3D, video, and for consumer and global enterprise use cases.
Unveiled in August, Stable Diffusion is an open-source text-to-image generator similar to OpenAI’s DALL-E. Like most of its contemporaries, it promises to make it possible for billions of people to produce beautiful art instantly. The model itself draws inspiration from the work of CompVis and RunwayML, a video editing business well-known for its widely used latent diffusion model, as well as ideas from Katherine Crowson, lead generative AI developer at Stability AI, who developed conditional diffusion models, Dall-E 2 by OpenAI, Imagen by Google, and academics at Ludwig Maximilian University of Munich.
With the debut of independent research lab Midjourney’s self-titled product in July and OpenAI’s DALL-E 2 in April, AI image generators have become increasingly popular this year. In May, Google also unveiled Imagen, a text-to-image technology that is not yet accessible to the general public.
Despite being an image generator, Stable Diffusion does not leverage the auto-regressive method utilized by systems like DALL-E 2. To generate visual output, auto-regressive algorithms employ probability distributions. Stable Diffusion creates visuals using latent diffusion models (LDMs). The latent diffusion model employs diffusion algorithms but reconstructs the image rather than just compressing it. Images are created in this scenario by denoising data from neural networks known as autoencoders in a latent representation space, which is the information required to represent particular data that is embedded closely together. The whole image is then created by decoding the representation.
Because Stable Diffusion is open source, users can get over any prohibitions that are in place, unlike DALL-E and Midjourney, which have measures in place to prohibit the creation of graphic or pornographic images. The open source designation distinguishes it from its competitors because Stability AI has made all the information about its AI model, including the model’s weights, available for anybody to read and use.
Stability AI’s 4,000 A100 Ezra-1 AI ultracluster was used to train the model. With more than 10,000 beta testers producing 1.7 million photographs every day, the company has been pushing the model through extensive testing.
The main dataset was trained using LAION(Large-scale Artificial Intelligence Open Network)-Aesthetics, a subset of LAION-5B that was constructed using a new CLIP-based model that filtered LAION-5B based on the scores of Stable Diffusion’s alpha testers for how “beautiful” a picture was. Stable Diffusion can quickly produce 512 x 512-pixel images on consumer GPUs with less than 10 GB of VRAM. This revolutionizes image production by allowing researchers and, eventually, the general public to use the tool in a number of settings.
On the grim side, private medical information and copyrighted works were both included in the dataset used to train Stable Diffusion. Fearing copyright infringement lawsuits, Getty Images prohibited the submission of content created by systems like Stable Diffusion. Even U.S. House Representative Anna G. Eshoo recently criticized stability AI in a letter to the National Security Advisor (NSA) and the Office of Science and Technology Policy (OSTP), urging them to address the release of “unsafe AI models” that do not filter the content posted on their platforms.
DreamStudio, a new suite of generative media tools built to allow everyone the power of infinite imagination and the seamless simplicity of visual expression through a mix of natural language processing and novel input controls for rapid creation, is another Stability AI’s consumer-facing product. Stability AI also offers financial support to an organization called Harmonai. Late in September, Harmonai unveiled Dance Diffusion, an algorithm and collection of tools that can create musical clips by learning from hundreds of hours of pre-existing music.
AI translation primarily focuses on written languages. However, around half of the world’s 7,000+ living languages are mainly oral i.e. without a standard or widely used writing system. As a result, it is impossible to build machine translation tools using standard techniques as they require large amounts of written text to train the AI models.
To address this challenge, Meta has built the first-ever AI-powered translation system for a primarily oral language, Hokkien, which is widely spoken within the Chinese diaspora. Meta’s technology allows Hokkien speakers to converse with English speakers.
The open-sourced AI translation system is part of Meta’s Universal Speech Translator (UST) project. The project is developing new AI methods that will eventually allow real-time speech-to-speech translation for all extant languages. Meta believes that spoken communication can help break down barriers and bring people closer wherever they are. Recently, Zuckerberg announced that the company plans to build a universal language translator for the metaverse.
Meta’s AI researchers overcame many complex challenges from traditional machine translation systems to develop the new system, including data gathering, evaluation, and model design. Meta is open-sourcing not just their Hokkien translation models but also the evaluation datasets so that others can reproduce and build on their work.
Moreover, the techniques can be extended further to other written and unwritten languages. Meta is also releasing SpeechMatrix, a large corpus of speech-to-speech translations mined with the data mining technique called LASER. Researchers will be able to create their own speech-to-speech translation (S2ST) systems and build on Meta’s work.
This Interpol Metaverse enables registered users to tour virtually the Interpol General Secretariat headquarters in Lyon without any physical boundaries. It also allows one to interact with other officers through their avatars and take immersive training courses in forensic investigation and other policing skills.
According to Interpol, as the figure of metaverse users grows and the technology develops further, the list of possible crimes will expand to potentially include crimes against children, counterfeiting, ransomware, phishing, data theft, money laundering, financial fraud, and sexual harassment. In May this year, UAE’s AI Minister demanded laws and actions against crimes in the metaverse.
For law enforcement, some of these threats may present significant challenges as not all acts criminalized in the physical world are considered as crimes when committed in the virtual world.
According to Madan Oberoi, Interpol’s Executive Director of Technology and Innovation, by identifying these risks from the outset, one can work with stakeholders to build the necessary governance frameworks and cut off future crimes before they are fully formed.
During an interactive session and a follow-up panel discussion on Thursday in Delhi, Interpol also announced the creation of an expert group on metaverse to represent the reservations of law enforcement on the global stage, thus ensuring the new virtual world is secure by design.
According to the Global Crime Trend report of Interpol, crimes have increasingly moved online as digitalization has increased.
Totality Corp, the NFT Gaming company, announced that it would take Diwali celebrations to the metaverse for its users and community members this year.
The platform Totality Corp creates NFTs and tokens based on Indian culture and mythology. It will organize a Lakshmi Puja in the metaverse through its Zionverse app. Thus, users would be able to celebrate Diwali and experience the Laxmi puja in the metaverse.
The puja has been scheduled for five days i.e. from 21st October to 26th October. It will take place 24×7 in the metaverse. The total duration of each puja will be about 5-7 mins, which users can attend with their friends and family.
Zionverse would offer two types of rooms for celebrations, public and private. Users can explore based on their preferences. They can invite their family and friends through a QR code in the private room. However, in the public room, users can celebrate with the entire community.
Lucky users will also have the chance to enter the raffle game. Fifty lucky winners will get a chance to win digital gold worth Rs 2,00,000.
Zionverse is a digital ecosystem with many opportunities for web3 enthusiasts, game developers, gamers, and artists. The company has been undertaking such initiatives in the metaverse to transcend its community into the world of futuristic possibilities.
Meta releases the SpeechMatrix Dataset, which provides a vast collection of parallel (multilingual speech-to-speech) speech elements mined from VoxPopuli in seventeen languages while enabling researchers to generate individual speech-to-speech (S2S) systems.
Using Hokkien, the S2S system was developed under Meta’s Universal Speech Translator (UST) project. Hokkien, one of Taiwan’s official languages, is extensively spoken in the Chinese diaspora but does not have a standard written form. The company stated that Meta’s AI researchers developed translation tools for this language.
Meta said AI translation had been around for the past few years, mainly for written languages. However, more than 40% of 7,000+ languages exist orally and do not have a written standard.
The company wrote, “We plan to use our Hokkien translation system as part of a universal speech translator and will open source our model, code, and training data for the AI community to enable other researchers to build on this work.”
Hokkien speakers can now communicate with English speakers using Meta’s latest S2S translation technology. More than 8,000 hours of Hokkien speech have been mined, along with the appropriate English translations, Meta claimed, adding that the technology may be applied to other unwritten languages and eventually would function in real-time.
Even though the model is currently under development and can only translate one entire sentence simultaneously, Meta said, “It is a step towards a future where simultaneous translation between languages is achievable.”
