Elon Musk said that he expects the Neuralink brain chip to begin human trials in the next six months. During a presentation by Neuralink, Musk updated on the chip’s progress and said he plans to get one for himself. He added, “We want to be extremely careful and certain that it will work well before putting a device into a human.”
Neuralink is a neurotechnology organization that is working on brain-computer interfaces. The company develops implants and chips that focus on enhancing brain functionality. The recent brain chip being developed is designed to restore a person’s vision, even in people born blind.
It could also restore “full body functionality,” including verbal cues and physical movements for people with spinal injuries. Musk said, “We’re confident there are no physical limitations to restoring full body functionality.”
Without any supporting data, Musk claims that Neuralink’s implants may one day allow for “superhuman cognition,” allow paraplegic people to control cellphones or robotic limbs with their minds, and “cure” autism and schizophrenia.
The FDA has not yet evaluated or cleared any of Neuralink’s products for human trials, so the announcement is warranting some skepticism. The company has also come under fire for its alleged treatment, designated for monkeys, resulting in paralysis, internal bleeding, seizures, and declining psychological health.
Although superconducting qubits offer exciting prospects in practical quantum computing, the widely used qubit designs and fabrication techniques currently available do not yet deliver enough performance. In order to enhance the accuracy of quantum computing, a team of researchers from Aalto University, IQM Quantum Computers, and VTT Technical Research Center have found a novel superconducting qubit called the unimon.
It accomplished this by combining the desired characteristics of improved anharmonicity, a complete insensitivity to dc charge noise, decreased sensitivity to flux noise, and a simple structure consisting only of a single Josephson junction in a resonator.
In traditional computers, information is stored and processed as bits that can have one of two potential values: 0 or 1. Qubits, also known as quantum bits, are distinct from conventional bits as a qubit can also exist in a superposition state, or “α|0〉 + β|1〉” in which it can simultaneously have both values. A quantum computer will require at least 10,000 qubits in order to work effectively.
Some quantum processors employ either photonic qubits or trapped-ion qubits. While the former is made up of single photons of light, trapped-ion qubits use charged atoms suspended in an electromagnetic field to store and process information. Another qubit called a superconducting qubit, which has one of the most developed architectural designs, is also used. These qubits are a subset of a larger family of models that make up what we refer to as solid-state quantum computation. Solid-state qubit-based quantum computers don’t have moving components and are built using fabrication methods that were originally created for solid-state conventional computation.
Like any other type of qubit, a solid-state qubit is made by isolating a two-level quantum system. Superconductors and semiconductors have been the main focus of attempts to create solid-state qubits so far. While two semiconductor techniques, quantum dots, and single-donor systems, have shown noteworthy results, the superconducting approach is now the most advanced. As a result, superconducting circuits have become a frontrunner for implementing a scalable quantum computing platform.
A superconducting qubit is actually a circuit loop with an electrical current flowing through it. This circuit consists of metals that, when cooled below a specific critical temperature, turn into superconductors or materials that can carry current without resistance. The current is composed of “Cooper pairs,” a type of electron pairing that happens only in superconductive materials. This is created after a superconducting material hits its critical temperature and the normally repulsive attraction between electrons starts to turn slightly attractive.
Maintaining control over electron-electron interactions, as well as interactions between electrons and other degrees of freedom, is crucial for maintaining coherence. The fact that the electrons condense into Cooper pairs, which then form a single superfluid, gives superconductors an edge in this aspect. Because it requires a specific amount of energy, known as the energy gap, to separate the Cooper pairs, this superfluid can travel through the metal lattice without experiencing any resistance.
Cooper pairs need to transit via the Josephson Junction, which consists of a very thin layer of insulating material (thin layer of aluminum oxide) placed between two layers of superconducting material (layers of aluminum), before they can traverse the voltage gate to the superconducting island. Interestingly, this configuration provides Josephson Junctions with a small degree of self-capacitance, enabling the construction of a charge qubit using only a voltage gate and a Josephson Junction without a separate capacitor. Because of the “Josephson effect,” which occurs under specific circumstances when a non-superconducting material is positioned between two superconductors, Cooper pair electrons can tunnel via the Josephson Junction.
It is important to note that the 0 and 1 states that serve as the foundation for all quantum operations in a charge qubit correspond to the charge states of the island area, i.e., the lack or existence of excess Cooper pairs in the island. As a result, the superconducting island is often referred to as a “single Cooper-pair box.”
Even though superconducting qubits have already achieved quantum supremacy in some computations, current quantum computers still experience errors from noise to the point where their practical applications in fields like physics simulations, optimization, machine learning, and chemistry remain elusive. The complexity of implementable quantum calculations in this so-called noisy intermediate-scale quantum (NISQ) era is primarily constrained by errors in single- and two-qubit quantum gates.
Qubits encoded as charge states are extremely susceptible to charge noise, which also applies to Cooper Pair Box. Cooper Pair Box’s charge noise issue was resolved by creating a qubit with higher-order energy levels, the transmon (transmission-line shunted plasma oscillation qubit).
In theory, quantum error correction might totally eliminate the impact of gate faults. However, error mitigation can only do so much. Due to the two-dimensional architecture of the qubit register and its advantageous fidelity threshold of around 99%, which was previously attained with superconducting transmon qubits in 2014, surface codes are thought to be among the most convincing error correction codes for superconducting qubits. Despite recent significant advancements in the implementation of distance-2–5 surface codes on superconducting quantum processors, it is still necessary to increase the gate and readout fidelities of superconducting qubits, preferably above 99.99%, in order to enable effective quantum error correction with a reasonable qubit count.
Transmon qubits, which can be reliably manufactured and have coherence times up to several hundred microseconds, are currently used in the majority of superconducting multi-qubit processors, resulting in average gate fidelities of 99.98–99.99% for single-qubit gates and 99.8–99.9% for two-qubit gates. The transmon improves upon the original charge qubit’s Cooper pair box by adding a shunt capacitor in parallel with a Josephson junction, which exponentially reduced the sensitivity of its transition frequency to charge noise. However, due to the huge shunt capacitance, the anharmonicity is only 200–300 MHz or 5% of the usual qubit frequency. Due to the necessity to suppress leakage faults to states outside of the computational domain, this reduces the speed of quantum gates that can be implemented with transmons qubits. A high-power readout tone can even excite the transmon to unconfined states beyond the cosine potentia, although this is also restricted by the low anharmonicity of transmon qubits. To speed up qubit operations and enable larger reliabilities within the bounds of the restricted coherence time, a higher anharmonicity is needed. As a result, the team believes finding novel superconducting qubit types that boost the anharmonicity-coherence-time product is important.
Recent years have seen significant advancements to address the above problems via the creation of fluxonium qubits, plasmonium qubits, and quasicharge qubits. However, each of these also has its own disadvantages. The unimon was thus developed by researchers, which consists of a single Josephson junction shunted by a linear inductor and a capacitor in a relatively untapped parameter regime where the inductive energy is mostly canceled by the Josephson energy resulting in high anharmonicity while being fully stable against low-frequency charge noise and partially shielded from flux noise.
By integrating a single Josephson junction into the center conductor of a superconducting coplanar-waveguide (CPW) resonator grounded at both ends, the researchers successfully applied the unimon in a simple superconducting circuit. The junction is inductively shunted since there are no charge islands in the circuit. They claimed that the unimon is the only superconducting qubit with the Josephson junction shunted by a geometric inductance that offers total protection against low-frequency charge noise, aside from the relatively recent fluxonium qubit using a geometric superinductance.
According to researchers, the normal modes of the resonator with a non-zero current across the junction are transformed into anharmonic oscillators that may be employed as qubits because of the non-linearity of the Josephson junction. Since it has the largest anharmonicity, they chose the lowest anharmonic mode in this study as the qubit.
The researchers created devices that included three unimon qubits apiece in order to experimentally demonstrate the unimon. With the exception of Josephson junctions, where the superconducting leads were made of aluminum, they employed niobium as the superconducting material.
The researchers discovered that the unimon qubit could be protected from noise while only requiring a single Josephson connection and having a relatively high anharmonicity. Compared to the junction-array-based superinductors in typical fluxonium or quarton qubits, the geometric inductance of the unimon provides the potential for greater predictability and yield. Most importantly, the team attained fidelities ranging from 99.8%-99.9% for 13-nanoseconds-long single-qubit gates on three different unimon qubits. This is a groundbreaking milestone in quantum computing, bringing us closer to building solid-state superconducting qubits-based quantum computers soon.
Artificial intelligence is already making lives simpler on earth, but what about beyond our planet? What about AI in space exploration? Can AI be used in space missions and space exploration in general? Today, organizations such as NASA, ISRO, and SpaceX are already implementing AI technology to discover life on other planets and new celestial bodies and even streamline astronauts’ jobs in space. Let’s take a quick look at some ways in which AI is facilitating space exploration.
Autonomous Rovers and Robots
Autonomous rovers by NASA are one of the most essential AI applications. These rovers roam across the planet’s surfaces, currently on Mars, to make decisions and need to avoid obstacles while finding the best routes without mission control. Autonomous rovers are responsible for some of the most important discoveries made on Mars.
A sub-field of neural language processing (NLP), sentiment analysis is used by scientists to create intelligence-based assistants that can support astronauts in future missions to Mars, Moon, and more. Sentiment analysis can extract and recognize opinions from text data like forums, social media, reviews, and many more. These assistants will then understand and anticipate the crew’s needs, along with understanding emotions and mental health, so that actions can be taken in an emergency. Robots can also prove beneficial in physical tasks, such as docking, spacecraft navigation, and more.
A lander for Chandrayaan 2 called The Pragyan uses AI to communicate from the Moon. It was developed by researchers at IIT Kanpur and ISRO. The rover is a robotic vehicle with six wheels that leverages AI for in-situ payload trials.
Satellites generate massive amounts of data. AI algorithms help to process this data efficiently. Machine learning algorithms can analyze millions of images in seconds, tracking real-time changes. Automating these processes with AI technology allows satellites to independently take images when sensors detect specific signals.
Indian Space Research Organisation (ISRO) employs artificial neural networks and deep learning algorithms to classify, forecast, identify forest species, and analyze remote sensing time series data. AI implementation in ISRO has enabled it to reach the pinnacle in image processing, pattern recognition, multi-object tracking radar, a monitoring system for forest conservation, and autonomously navigating robots, which have come in handy in several missions.
Researchers from Leeds University, UK, analyzed images collected by the Gaia satellite. They applied several machine-learning techniques to the data to find over 2,000 new protostars, which are infant stars forming in dust and gas clouds. AI can also assist in remote satellite health monitoring and predicting issues for informed decision-making. AI automation can help optimize the large amounts of collected data from scientific missions like earth-observing spacecraft/rovers and deep space probes. It can also aid in evaluating the data and distributing it to end-users.
Operations in Space Missions
AI in space exploration has extensive applications. It can also help with autonomous operations in space missions. An Italian start-up, AIKO, developed a software library for enabling operations in space missions called MiRAGE. This is a part of ESA’s tech transfer program. It enables the spacecraft to perform autonomous replanning and identify both internal as well as external events to take appropriate action so the ground-based decision-making does not affect the mission objectives.
In 2018, SpaceX sent a robot called Crew Interactive Mobile Companion (CIMON) via its Dragon cargo capsule to the International Space Station (ISS). CIMON was the first AI-powered machine to venture into space. Moreover, SpaceX uses AI-powered autopilot programs that help rockets navigate themselves right from the launch to the ISS-docking station. SpaceX’s AI system also help in measuring fuel usage and reserves, parabolic flight, weather, liquid engine sloshing, and other factors that affect rocket flights.
With machine learning, it is also possible to determine safety-critical missions and evaluate operational risk analysis. Risk mitigation systems can then process vast amounts of data from normal operations as well as previous performance. After teaching a model to detect risk classification, it can conduct real-time risk assessments.
Discovery of Exoplanets
The Kepler Telescope was created to help determine the frequency of planets of earth’s size that orbit Sun-like stars. It needed both automatic and precise assessment of the candidates, even with a low signal-to-noise ratio.
Google got around the constraint alongside other scientists by developing AstroNet K2, a convolutional neural network (CNN). This CNN can determine whether the signal from the Kepler Telescope is a confirmed transiting exoplanet or just a false positive. After training the neural network model for 98% accuracy, two new exoplanets were found: Kepler 90i and Kepler 80g, which circle the Kepler 90 and Kepler 80 star systems, respectively.
Conclusion
It is evident that artificial intelligence is blazing a trail in space exploration. Besides, our desire to further explore the final frontier seems to be skyrocketing. In fact, there are already possible increases in NASA, ISRO, and SpaceX’s space exploration initiatives and budgets to fund programs that aim to return humans to the Moon and explore beyond that. Many of the AI technologies we described above will be used, and more will be developed over the next couple of years to assist space missions.
Data analytics is the science of using data and drawing insights from it for decision-making. It is an umbrella term for several kinds of analytical practices and approaches that depend on the data and the purpose of the analysis. Data analytics has become significant as it aids in the performance optimization of enterprises by studying and working with the data collected. As businesses retain a lot of data, they need a cost-effective way to store, utilize it, and use the resulting insights into their business strategy. Getting it done manually will be a very time-consuming and expensive process. This is why the inclusion of data analytics has been automated to enable seamless business operations. Several tech-driven companies provide data analytics and related services to other organizations that do not have the capability and resources to perform it on their own. This article enlists some of the top Data Analytics Companies in India.
Top Data Analytics Companies in India
Here is a list of 10 potent data analytics companies operating in India.
1. Accenture
Accenture, formerly Andersen Consulting, is one of India’s most prominent data analytics companies. It is an IT services and consulting company based out of Dublin and was established in 1989 and currently houses some of the finest data strategists, industry experts, data scientists, business intelligence professionals, and other specialized personnel. With more than 100 innovation hubs across the globe, Accenture offers full-service technology and business solutions specific to clients.
Data Analytics at Accenture
Accenture’s analytical services help organizations ensure that the data they collect is transparent, accessible, and trustworthy, as fragmented/low-grade data cannot reap any insights. Additionally, their analytical services help identify use cases hindering business progress and develop solutions to prevent that. Consequently, Accenture’s data analytics capabilities include data transformation, content analytics, Synops, business intelligence, industrialized solutions, and more.
2. Convergytics
Convergytics Solutions Pvt Ltd. is a data-driven processing and analytics startup based in Bengaluru. The company was founded in 2013 to leverage data processing and analytical facilities on a contractual basis. Convergytics provides data services that assist companies in increasing customer satisfaction, marketing ROI, and innovation to stay competitive.
Data Analytics at Convergytics
Convergytics offers analytical services for business data, marketing, digital, pricing, CRM, and social media analytics. These services cater to strategizing, managing, modeling, and tracking relevant data attributes for clients. It is one of those data analytics companies that offer lifetime value modeling, and real-time optimization for other organizations.
3. Phygital Insights
Phygital Insights is a fast-growing data analytics company based in Bangalore, India. The company provides digital services and analytics solutions to help businesses leverage data for growth, innovation, and decision-making. It has a team of highly experienced data scientists with exposure to meeting the diverse analytics needs of equally diverse businesses across industries.
Data Analytics at Phygital Insights
Phygital Insights offers comprehensive digital and analytics services covering areas in data science, business analytics, and industry analytics. Some of the services it provides include:
Digital Services: Data Engineering, Data Analytics, Digital Transformation, Business Intelligence, Cloud Computing, IoT, etc.
Analytics Services: Imarge Analytics, Marketing Analytics, Visualization & Reporting, E-Commerce Analytics, Healthcare & Life Science Analytics, Insurance Analytics, etc.
Talent Augmentation: Staffing Services, Managed Services, and Project Basis.
4. Tata Consultancy Services (TCS)
Tata Consultancy Services (TCS) is another IT services, consulting, and data analytics company based in Mumbai. It was established in 1968 to offer cognitive-powered, consulting-driven business portfolio solutions using technology and engineering services. With its Location Independent Agile delivery model, the company can deliver all its services like information enrichment, digital marketing, content analytics, creative content development, and software development to global enterprises.
Data Analytics at TCS
TCS provides data and analytics services in three major areas:
Enterprise Data Management: TCS helps collect, create, and disseminate application-specific data and metadata.
Data Integration, Reporting, & Visualization: TCS provides several proprietary and consumer-friendly tools, like dashboards, visual reports, etc., for data integration and visualization.
Analytics, Insights, & Intelligence: TCS provides generic and customized Big Data, prescriptive, and predictive analytics solutions.
5. Gramener
Data analytics companies like the ones mentioned above are largely focused on data only. However, Gramener is a unique design-centric data science company that creates customized data and artificial intelligence-based business solutions. Founded in 2010, the company describes itself as a “data storyteller,” solving complex business problems with its low-code analytics platform. Gramener aims to augment human intelligence and visual insights to enable faster decision-making.
Data Analytics at Gramener
Gramener helps organizations deal with complex data consumption problems via interactive visualization and insight generation services. The company has also established multiple AI labs to fuel innovation in data technologies, built a comic library called ComicGen for creating data stories, and introduced a low-code PaaS (platform-as-a-service) called Gramex.
6. Capgemini India Pvt Ltd.
Capgemini is a multinational data analytics company providing IT services and consultancy. It was established in 1967 to enhance customer experience, industry intelligence, and enterprise management for its clients. The company helps other organizations to adapt technologies like cloud, machine learning, artificial intelligence, and big data while considering the environmental impact of their practices.
Data Analytics at Capgemini
Capgemini masters data via Perform AI, its full-service portfolio to transform data using artificial intelligence. Like other potent data analytics companies, Capgemini also leverages a platform to ensure that organizations become data-powered while achieving sustainability. It provides collaborative data ecosystems with net zero intelligence supercharges. Capgemini also leverages Climate AI to constantly monitor the impact of artificial intelligence on organizations’ climate strategy, carbon footprint, forests, and water bodies.
7. ITC Infotech
ITC Infotech is a reputed member of the global community of data analytics companies. It is a technology services and solutions provider backed by the Business and Technology Consulting group. The company started in 2000 and aims to develop business-friendly solutions for its clients to be future-ready in digital and industry-specific technologies. ITC Infotech provides generic and customized business models for organizations across multiple industries, including consumer goods, healthcare, banking & financial services, and many others.
Data Analytics at ITC Infotech
ITC Infotech offers end-to-end automation solutions, centralized monitoring, supply chain management, merchandise connectivity, predictive analytics, etc. For trade & finance companies, ITC Infotech offers solutions to reduce the turnaround time, counter operational inefficiencies and reduce operating costs. Further, the company also offers multi-lingual helpdesk support and management solutions.
8. Concentrix India
Concentrix India is a data designing, consulting, and transformation company. It was established in 2006 with a vision to reimagine consumer experiences. The company offers all business and data services for CX design, benchmarking, digital selling, customer research, and marketing strategy.
Data Analytics at Concentrix India
Being one of the most unique data analytics companies, it offers analytical services under a few broad domains. Some of these are:
Digital transformation – Products and services like Chatbots & Virtual Assistants, Intelligent Automation, and Enterprise Moderation.
Marketing solutions – Value realization and Capability Building.
Experience design – Services like Journey Design, Human-Centered Design, and Product Realization.
Revenue growth services – B2B and B2C revenue growth models.
9. Latentview Analytics
Latentview Analytics is one of those data analytics companies that follow an -engineering first approach to analytics. The company is based in New Jersey and runs its Indian operations in Chennai and Mumbai. Latentview provides multiple analytical solutions to retail, consumer goods, and finance-related industries to embrace big data, machine learning, and other similar technologies.
Data Analytics at Latentview Analytics
Latentview’s analytical services include business, marketing, risk & compliance, and supply chain analytics. The company offers data engineering and insight-generating services. SmartInsights, Latentview’s AI-powered platform, enables organizations to predict consumer trends using insights, giving them a first-mover advantage. Latentview also offers Casper, a customized conversational analytics system that takes natural language inputs to output visual, textual, or audio insights.
10. Tredence
Tredence is a data science company catering to data analytics, bridging gaps between insights and value realization. It was founded in 2013 to provide actionable marketing, sales, and operations insights. Tredence helps organizations to envision new possibilities by adopting AI-powered data sciences across diverse industries.
Data Analytics at Tredence
Tredence offers exclusive AI consulting services to help businesses transform by experimenting with AI, supply chain management with a bird’s view of the network, data engineering, and prescriptive analytics. Its clients can also avail of customized customer analytics to enhance their consumer experience. Further, Tredence provides Industry X.0, an intelligent, interconnected system for providing industry-specific insights.
11. Analyttica
Analyttica is a newly emerging data analytics company founded in 2012. The company harnesses machine learning potential to help organizations make better data-driven decisions. With a team of over 50 people, Analyttica leverages advanced analytics via patented products like LEAPS, TREASURE HUNT, and a few others.
Data Analytics at Analyttica
Analyttica offers LEAPS and TREASURE HUNT.
LEAPS stands for Learn-Apply-Solve and is a virtual environment where clients can experience developing and running practical data applications.
TREASURE HUNT is a contextual AI Platform that provides ML and analytics frameworks based on an iterative experiential approach.
Over the years, several technological advancements have come up, like humanoid robots, supercomputers, drones, etc. Artificial intelligence (AI) is one such technology that has emerged in the last few years and has significantly impacted the world. In fact, AI is slowly becoming a norm in the majority of sectors like healthcare, defense, and security. However, the benefits of this technology can be reaped only if organizations embrace digital and technological transformations. Such transformations are planned and implemented with the help of AI research and development (R&D) centers. India has shown signs of “AI readiness” in the past few years after recognizing the need and capability of artificial intelligence to push the economy towards development. India has now become a thriving location for multinational companies to establish AI R&D centers due to the vast potential and pool of talent.
These R&D centers aim at advancing existing technologies and extending their core capabilities across all industries. This article enlists the top 10 AI R&D Centers in India.
Top 10 R&D Centers in India
Listed below are some of the most advanced AI R&D centers in India.
AI Kriya – AI Research Center at IIT Hyderabad
The artificial intelligence department at IIT-Hyderabad is actively involved in pioneering efforts in artificial intelligence via BTech, MTech, and Ph.D. programs. A Center of Research and Innovation in AI, “AI Kriya,” has been established in collaboration with JICA (Japan International Cooperation Agency) and Honeywell to aid the department in embarking on more research areas. The AI Kriya center houses multiple research labs and a mini data center to leverage computational facilities. NVIDIA DGX1 and DGX2 supercomputers with several GPU servers leverage up to 250 TFlops of GPU power and make AI Kriya a completely state-of-the-art in-house research center.
Mercedes-Benz Research and Development India (or MBRDI) was established in Bengaluru
as a captive institution for AI research, IT, and product development. The establishment follows the Mercedes-Benz AG group’s objective to tap into the top engineering talent worldwide and develop a global footprint for its R&D and IT capabilities. The center focuses on computer-aided designs and simulations (CAD and CAE) for power training, exteriors and chassis for embedded systems, telematics, and other related technologies.
Area of Research
The AI R&D center has actively developed passenger car applications in collaboration with Daimler. Several intelligent apps like AnITa (An Intelligent Transport App) have been developed focusing on transportation safety. The MBRDI center is also a part of the Mercedes Benz SAFE ROADS program to develop revolutionary safety features.
DRDO Young Scientist Labs
To influence the nation’s AI R&D, the Indian government announced the construction of five DRDO Young Scientist Labs specializing in research on AI, quantum technologies, and cognitive technologies. The laboratories in Bengaluru, Mumbai, Chennai, Kolkata, and Hyderabad are designed to produce innovations and make India self-sufficient in the field.
Area of Research
These labs are concentrated on furthering existing research on deep neural networks, reinforcement learning, cognitive surveillance, tactical spectrum sensing, online waveform adaptation, and target recognition.
Fujitsu Research of India Private Limited (FRIPL)
Fujitsu launched a new AI R&D center, “Fujitsu Research of India Private Limited (FRIPL),” on April 1, 2022, as a part of its global innovation strategy. FRIPL will concentrate on research and development of quantum software, AI, and machine learning technologies. FRIPL will initiate a combined research project with IIT Hyderabad and the Indian Institute of Science (IISc) to encourage innovation in cutting-edge AI technology as one of its first significant endeavors. The joint research projects will enhance AI and machine learning technology’s precision and robustness.
Since it is a newly established center, the research work is in its infancy.
Area of Research
In collaboration with IIT Hyderabad, the research center plans to uncover the causal relationships with higher accuracy by combining Fujitsu’s AI for a cause-and-effect relationship with IIT-H’s geometric statistical theory.
In collaboration with IISc, the researchers will dive into automating AI generation using autonomous learning responses based on state changes. The research will utilize Fujitsu’s reinforcement learning capabilities and IISc’s leading expertise in deep learning to develop automatic deep learning models with high accuracy and lesser errors.
Societal impact through Cloud and Artificial Intelligence (SCAI) by Microsoft
The Center for Societal Benefit through Cloud and Artificial Intelligence (SCAI) by Microsoft Research India is dedicated to developing, fostering, validating, and deploying technologies that will significantly impact society. The AI R&D center is devoted to building partnerships with academic institutions, start-ups, non-governmental organizations, and other groups interested in leveraging artificial intelligence and related technology for society’s betterment.
The center will collaborate with startups and academic institutions via external collaborations and with students via its SCAI Fellowship Programs to continue seeking new proposals.
Area of Research
Research is conducted via Microsoft’s Technology and Empowerment (TEM) Group to extend the benefits to underrepresented communities. High-impact projects like Digital Green (a project aimed to disseminate false information targeted to small farmers) and 99DOTS (a project based on medication adherence) have become significantly successful and grown into independent infrastructures.
Intel Design and Engineering Center in Bengaluru
Intel established its presence in Bangaluru in 1988, and a decade later, it established the Intel India Development Center (IIDC). Since then, Intel has continued to increase its R&D and innovation footprint in India, which has already invested over $8 billion. Intel has recently launched a new Design and Engineering R&D Center in the city. The new center, at Ecospace Business Park, with around 2,000 experts, aims to promote cutting-edge design and engineering work in the Internet of Things (IoT), graphics, artificial intelligence, and automotive sectors. An entire floor is allocated to high-tech R&D labs that will cater to silicon designing and validation.
Area of Research
The recently established Design and Engineering Center will expand Intel’s chip designing and production capabilities under a single roof. The company plans to look deeper into silicon designing technologies and develop more complex blueprints for the future.
Tredence Delivery and R&D Centers
The data science solutions provider, Tredence, has established delivery centers and AI R&D facilities in Gurugram, Bengaluru, and Chennai. These centers will leverage advanced analytics, data science, and engineering solutions for clients across several industries. Tredence’s ASTHA (recruit, train, and deploy) initiatives will help employees with experience by giving them opportunities in data science and data engineering. The new centers, with a hybrid work model, can accommodate more than 1400 employees, making them the company’s most prominent employment base.
Area of Research
The delivery and R&D centers will focus on enhancing existing data services and developing new ones to aid in the delivery process.
Data Analytics and Intelligence Research at IIT Delhi
Data Analytics and Intelligence Research (DAIR), a well-known AI R&D group at IIT Delhi, focuses on working with diverse fields of data and technologies in conjunction. The research center aids IIT-Delhi students in developing applications with national and international credibility. These applications are designed to answer fundamental scientific questions like the vitality of transient social networks, probabilistic graphic models, and others.
Area of Research
The group has published several papers in fields like graph mining, computer vision, and information extraction. Their publications have also been approved at prestigious machine learning conferences like IJCAI, NIPS, and KDD. In addition, DAIR has worked on critical national initiatives like analyzing the NREGA employment dataset and mining social media and political feeds for opinions.
Center of Excellence in AI at NIT Trichy
To address the research issues and challenges in social network computing, the Center of Excellence (CoE) in Social Network Computing at NIT Trichy is an interdisciplinary forum. The CoE concentrates on resolving societal difficulties in crisis management, decision support systems, and healthcare, such as those brought on by the COVID-19 pandemic. It comprises members from several departments, including Computer Science and Engineering, Computer Applications, Humanities, Mathematics, and a few others who work together and develop prototypes.
Area of Research
The AI R&D center focuses on ensuring security in social networks by working on intrusion detection and prevention, cryptography, authentication, and denial of web attacks. It also undertakes content-based social network analysis to secure personal information and data centers.
Wipro IISc Innovation Network (WIRIN)
A memorandum of understanding (MoU) between Wipro and IISc focuses on cooperation in research on robotics, autonomous systems, computer vision, machine learning, and human-machine interaction. The AI research lab has been developed as a part of this MoU to focus on deep learning, machine learning, healthcare diagnostics, and artificial intelligence. Additionally, the AI lab intends to create digital interfaces that will quickly and precisely build sophisticated diagnostic, ophthalmic imaging, and medical image reconstruction technologies.
Area of Research
The AI R&D center has completed numerous projects in diverse fields, including cognitive computing and AI, visual computing, human-computer interaction, and autonomous systems. The WIRIN initiative also sponsors several scholarship programs for the top three meritorious IISc doctoral students.
A vibrant culture of web3, metaverse, VR, blockchain and other related technologies has been thriving in Tamil Nadu. Hence, the Tamil Nadu government is trying to develop new policies to support the web3 ecosystem.
The state houses several technological advancements like AI robots in the airport, AI panic buttons for women’s safety in buses, and AI systems on train tracks to prevent animal collisions. Other than these, the government’s new policies will aim to connect emerging tech start-ups with the academic network of over 570+ engineering colleges to fester research and spur innovation.
Mano Thangraraj, Tamil Nadu’s Information Technology Minister, also spoke on the topic at the TechNext 2022 – Future of the Web 3.0 conference and said, “We have initiated interactions with the information technology (IT) sector and academia and could bring change in the sector.”
He released a report titled “Metaverse and Web 3.0 opportunities in India – Nurturing Tamil Nadu’s growth ambitions through next-gen technologies.” The report highlighted all significant IT focusing big on these technologies via design, development, research, and support services alongside XR, 5G, IoT, and AI in the state.
The state now has its artificial intelligence-generated NFT called “Netru, Indru, Nalai” (Yesterday, Today, Tomorrow). It was also launched at the TechNext 2022 Web3 conference.
Stripe, a leading payments service provider, has debuted a project that introduces fiat-to-crypto payments for web3 enterprises around the world. The offering is in the form of a customizable widget embeddable directly into a “decentralized exchange (DEX), NFT platform, or wallet.”
In order for consumers to use their Web3 applications, developers must battle rampant fraud, manage complicated KYC procedures, and somehow still provide a frictionless, high-conversion payments experience. The onramp fiat-to-crypto service will solve this problem.
Over the last few months, Stripe has expanded collaborations with crypto companies to develop projects and offer more services to support crypto payouts in over 67 countries. The company has been working to provide its Global Payments and Treasury Network access to crypto platforms. It partnered with Nifty Gateway to onboard and offer KYC service for creators, enabling them to accept payments.
The fiat-to-crypto offering is not the first attempt to familiarize with crypto payments. The payment firm has already accomplished numerous projects in the domain of blockchain, out of which many are built on Solana. Solana offers convenient and customizable on-premise services and manages know-your-customer (KYC), fraud, and compliance issues.
Audius is one of the first few projects that use Stripe’s fiat-to-crypto widget. It is a decentralized music discovery platform where Stripe’s payment widget will enable users to use their credit cards to purchase AUDIO tokens.
HELLO Labs, a production house founded by the Hollywood producer and director Paul Caslin, has innovated a reality show called “Killer Whales” for web3 innovators. The show will air in 2023 and will combine the most significant elements of shows like America’s Got Talent and Shark Tank.
An ideal episode would feature NFT and crypto projects pitching to a panel of five industry experts referred to as “Whales.” The pitches will aim to convince the whales to mentor the participants and take them to the next level.
The show will broadcast on mainstream platforms and Hello’s own web3 application. Cordell Broadus, aka Champ Medici, executive producer and a celebrity judge in the show, said, “I have been obsessed with looking for the next Steve Jobs or Elon Musk in Web3. Teaming up with Paul and his experienced team, I believe we can deliver a great show to the world.”
The show is a part of HELLO Labs’ efforts to blaze a path through crypto and entertainment and produce TV shows, games, and the company’s own NFT called Hello Token.
In conjunction with the show’s debut, HELLO Labs will also introduce an exclusive “Show Producer” NFT collection that gives owners a chance to participate in the show’s development and have a say in important choices.
In an attempt to combat misinformation, Google and YouTube have announced an investment of US$13.2M in the form of a grant given to the IFCN, the International Fact-Checking Network at the non-profit Poynter Institute. The grant will be used to set up a new Global Fact Check Fund.
Using the largest single grant against misinformation, the Global Fact Check Fund will enable fact-checkers to enhance existing operations and elevate rightful information from credible sources around the world.
The funding, according to Google, can be used by fact-checking organizations to adopt new technologies, build or expand their digital footprints, optimize their verification tools, and improve their capacity to deepen audience engagement through creative storytelling formats like audio, video, or podcasts.
Google offers a fact-check option on the top of the search results to provide users to have an additional context to what they are searching. The feature is available in select countries, and Google is working to roll it out in others.
An “Independent Fact check” box can be seen above.
Binance has been in the spotlight ever since the collapse of its rival platform, FTX, earlier this month. The Chinese-Canadian head of Binance, Changpeng Zhao, pledged to release an audit into his firm last week to defend his claims that he contributed to the collapse of FTX.
The terms of Binance’s purchase of the Japan-based Sakura Exchange BitCoin were not entirely disclosed in the joint statement on Wednesday.
But Binance said that it aims to support a responsible global environment for cryptocurrencies by offering Japanese-regulated services. “The Japanese market will play a vital role in the future of adoption of cryptocurrencies,” the general manager of Binance Japan, Takeshi Chino, said in a statement.
“We will actively work with regulators to set up our combined exchange in a compliant way for local users.” Japan has strived to strengthen its digital currencies regulation following the Tokyo-based MtGox Bitcoin exchange collapse in 2014.
