Global oil company Shell marked a significant milestone by scaling artificial intelligence predictive maintenance to over 10,000 pieces of equipment using enterprise AI software providing company C3 AI’s technology.
The announcement was recently made by C3 AI, which mentioned that Shell employed its technology to monitor and maintain equipment including upstream, manufacturing, and integrated gas assets across Shell’s global asset base, one of the largest such deployments in the energy industry.
Shell uses C3 AI’s AI predictive maintenance technology to detect equipment degradation and breakdowns before they occur. The technology considerably helps operators take preventative measures and minimize costly unplanned downtime, production delays, and environmental and human safety issues.
Additionally, asset integrity, system optimization, production optimization, safety, and sustainability are some of the many application cases Shell is looking into with the C3 AI Suite.
“Monitoring 10,000 pieces of critical equipment with AI-enabled predictive maintenance is an important milestone for Shell — an ambitious target we had set for 2021 and successfully achieved,” said Vice President of Computational Science and Digital Innovation at Shell, Dan Jeavons.
United States-based enterprise artificial intelligence software developing company C3 AI was founded by Ed Abbo, Patricia House, and Thomas Siebel in 2009. To date, the firm has raised a total funding of $228.5 million over six funding rounds from investors like TPG Growth, Sutter Hill Ventures, Breyer Capital, Pat House, and many more.
CEO of C3 AI, Thomas M. Siebel said, “We are extremely proud to have helped Shell reach this milestone, made possible by the combination of Shell’s extensive operational expertise and C3 AI’s advanced AI software.”
He further added that Shell’s global deployment of AI predictive maintenance is a tremendous success, offering considerable economic, environmental, and human safety benefits, and they look forward to continuing to collaborate with Shell in further growing AI across their organization.
Autonomous taxi developing company Pony.ai announces that it has reached a valuation of $8.5 billion after its recently held series D funding round.
This hike in the valuation of the company marks its tremendous efforts in the field of developing cutting-edge technology for robotaxis and also commercializing them. However, the company will announce more details regarding the series D funding round after its complete closure.
Pony.ai plans to use the freshly generated funds to expand its employment, research and development, form significant strategic collaborations, global testing of robotaxi and robotrucking on an ever-growing fleet, speed up development toward mass production and commercial deployment.
Co-founder and CTO of Pony.ai, Tiancheng Lou, said, “A key part of our story for our investors is our tech development path. From 2020 to the end of 2021, our key safety metrics increased tremendously, such that in most circumstances, Pony.ai’s virtual driver is now equal to or superior to a human driver.”
He further added that as they rapidly expand toward robotaxi and robotruck commercialization and mass manufacturing, they are confident in their autonomous vehicle technology preparedness.
“The success of this financing belongs to the entire Pony.ai team, who have made tremendous strides in achieving and exceeding our 2021 milestones,” Co-founder and CEO of Pony.ai James Peng.
He also mentioned that they are enthusiastic about their 2022 goals and the fast-paced worldwide development of autonomous mobility.
Full-stack autonomous driving solutions developing company Pony.ai was founded by James Peng and Tiancheng Lou in 2016. To date, the firm has raised over $1 billion from investors like Eight Road Venture, ClearVue Partners, and others.
Artificial intelligence (AI) has long been regarded as one of the most advanced areas in the computer world. The use of AI applications is continuously expanding, and tech aficionados must stay up with this fast-changing sector in order to work with AI-driven tools and apps. The majority of organizations that integrate AI into their workforce follow a similar implementation methodology. They devise a flawless proof of concept and team up with an AI vendor who pledges to launch the system on their behalf. And having a practical understanding of whatever technology you’re working on is required to excel at building industry-oriented AI solutions. Although textbooks and other study materials will offer you all of the textual information you want about any technology, working on open-source AI projects can help you master AI concepts.
In this post, we’ll go through the top 10 AI project ideas for beginners that are appropriate for novices and people who are just getting started with machine learning. In addition, this list can come in handy for data scientists who are looking to diversify their professional portfolio and expertise in various industry-related applications of AI and machine learning.
Predicting Wine Quality
It is true that the older the wine, the better it will taste. However, age isn’t the only factor that influences a wine’s flavor. You will use fixed acidity, volatile acidity, alcohol, and density to assess the quality of wine in this project.
In this AI project, you’ll create an ML model that can look at a wine’s chemical features and estimate its quality. There are roughly 4898 observations in the wine quality dataset you’ll be utilizing for this project, with 11 independent variables and one dependent variable. Fixed acidity, volatile acidity, citric acid, residual sugar, chlorides, free sulfur dioxide, total sulfur dioxide, density, pH, sulfates, and alcohol are some of the input variables. Quality is the outcome variable which is determined by sensory data with scores between 0 and 10.
In this project, you will get exposure to data visualization, data exploration, regression models, and more.
The Enron crisis and its subsequent collapse were some of the most significant business failures in history. Enron was one of America’s major energy companies in the year 2000. After being exposed for fraud, it went bankrupt in less than a year.
On the positive side, the dataset of emails from Enron was retained. The Enron email dataset consists of 500 thousand emails sent between 150 former Enron workers, the majority of whom were top executives. It’s also the only significant publicly accessible collection of genuine emails, making it more useful for natural language processing. This project on AI entails creating a machine learning model that detects fraudulent behavior using the k-means clustering technique. According to comparable patterns in the dataset, the model will divide the observations into ‘k’ number of clusters.
Boston House Pricing using Machine Learning & Python
This is one of the best AI projects for students to learn about forecasting the price of a property based on data from nearby homes. In this project, interested people can learn how to predict prices on the basis of new data.
The Boston housing dataset contains information on various houses in Boston based on criteria such as tax rates, crime rates, and the number of rooms in each property. It’s an exceptional dataset for estimating the values of various Boston homes. In this project, you can employ linear regression to create a model that can forecast the price of a new home. Since this data shows a linear connection between the input and output values and when the input is unknown, employing linear regression is the ideal choice for this project. You can also employ more nuanced methods like random forest regressor or gradient boosting to predict house prices.
Working on the Iris Flowers categorization AI project idea is one of the finest ways to experiment with machine learning concepts like classification using the iris flowers dataset. Because iris blooms come in a variety of species, the length of the sepals and petals may be used to differentiate them. This machine learning project aims to sort the flowers into one of three species: Virginica, Setosa, or Versicolor.
The iris flowers dataset includes quantitative parameters such as the length and breadth of sepals and petals. It’s ideal for learning about supervised machine learning techniques, specifically how to load and handle data, while correctly categorizing irises into one of three species.
Emojis and avatars have been ingrained in internet conversation, product reviews, brand sentiment, and a variety of other activities. It also resulted in an increase in data science research into emoji-driven storytelling.
Thanks to advances in computer vision and deep learning, it is now feasible to discern human emotions from photos. In this project, you will classify human face emotions using deep learning algorithms to filter and map matching emojis or avatars — similar to how Snapchat creates Bitmoji.
The FER2013 dataset comprises grayscale face images with a resolution of 48*48 pixels. The photos are equally spaced and centered. This dataset includes the following facial emotions viz., angry, disgust, fear, happy, sad, surprise, and natural.
The goal of this AI project is to create a convolutional neural network architecture and train it using the FER2013 dataset to recognize emotions from photos. After identifying the facial expressions in the images, you will map the emotion to an emoji or an avatar.
The MNIST digit classification AI project in Python aims to teach computers how to detect handwritten numbers. Since working with image data is more difficult than flat relational data, the MNIST dataset is ideal for someone who is just getting started in deep learning. You will utilize the MNIST datasets to train your ML model using Convolutional Neural Networks (CNNs) in this project. Despite the fact that the MNIST dataset may fit in your PC RAM (it is relatively tiny), handwritten digit identification remains a complex process. The MNIST dataset is a modified subset of two datasets gathered by the National Institute of Standards and Technology in the United States. It has 70,000 handwritten digits that have been labeled.
The MNIST dataset was created using Python’s Keras package. Therefore, you can get started with this AI project by installing Keras, importing the library, and loading the dataset.
Today, online streaming platforms are a huge hit among the millennials and gen-z. These streaming platforms also offer recommendations on what to watch next, based on a viewer’s past viewing habits and interests. This is accomplished by machine learning, and it may be a fun and simple project for people who have a working knowledge of machine learning algorithms. Working on this AI open source project idea can allow you to develop a recommendation engine (similar to those used by Amazon and Netflix) that can provide tailored suggestions for items, movies, music, and so on based on consumer preferences, requirements, and online activity.
The MovieLens 25M movie rating dataset comprises 25 million ratings and one million tag applications applied to 62,000 movies by 162,000 users, making it one of the most diversified dataset selections. It also includes tag genome data with 15 million relevance scores across 1,129 tags.
This intriguing AI project idea for beginners may help them understand how to visualize data on the Uber platform. This dataset can help you figure out how to evaluate the rides so that you can make business changes. The ride-sharing app needs to have a superior support system to fix consumer complaints as rapidly as possible, with billions of rides to manage each year.
As a result, Uber created Customer Obsession Ticket Assistant, or COTA, a “human-in-the-loop” model architecture to increase the performance of its customer support staff.
The Uber team employed deep learning to identify the influence on ticket processing time, customer happiness, and income by split-testing two versions of COTA, viz., Pre-processing transformations using Spark and Deep learning training using TensorFlow. It’s an outstanding model for deep learning projects that combines brilliant technological design with human involvement, and it should inspire you to create your own deep learning initiatives.
Artificial intelligence and machine learning technologies have already begun to permeate the healthcare business and are fast changing the face of global healthcare. Be it for early identification of Parkinson’s Disease or cancerous cells, AI has helped revolutionize the healthcare industry with its innovative solutions.
One of the commonly known healthcare datasets for AI open source project ideas is Breast Cancer Wisconsin Diagnostic Dataset. The difficulty to discern between benign (non-cancerous) and malignant (cancerous) tumors is a major issue in breast cancer detection. You’ll need to classify whether a tumor is malignant or not based on metrics like “radius mean” and “area mean” of the tumor in the dataset. While this dataset is already present in a pre-processed form, it requires extensive analysis to find optimum results at higher accuracy. Finding a minimal error rate is crucial as any miscalculation can prove lethal to patients’ lives. Make sure to have a working knowledge of random forest and XGBoost, as they are some of the most important concepts implemented in this AI project.
Because healthcare organizations have access to large patient data, you may get insight into designing diagnostic care systems that can automatically scan pictures, X-rays, and other images and deliver an accurate diagnosis of likely ailments by analyzing this data.
Voice AI is one of the trending concepts in the AI industry. Taking advantage of the demand for sophisticated voice AI algorithms that power voice assistants like Alexa to AI chatbots, you can design a project that employs AI open-source datasets using NLP. The librispeech dataset is an enormous collection of English speech data derived from audiobooks from the LibriVox project. It is the ideal dataset for voice recognition because it contains over 1000 hours of English-read talks in diverse accents. The file format of data is in the form of FLAC (Free Lossless Audio Codec) without any loss in quality or loss of any original audio data. This dataset is used in various applications, including automated speaker verification and speaker identification. The objective of this project is to develop a model that can convert audio into text automatically. You’ll create a voice recognition system that can recognize English speech and convert it to text.
Here is a comprehensive list of AI open-source project ideas. AI is still at an early stage in the tech industry domain. There are a lot of initiatives that are currently being worked upon to address some real-world challenges while simultaneously improving the existing models. This list of AI open-source project ideas covers everything from the fundamentals like linear regression to advanced techniques like transformer and LSTM. It was curated on the idea that helps both students and professionals get insight into the industry applications of AI and machine learning concepts.
On Tuesday, Alphabet Inc’s (Alphabet) Google said that it will pay $5.4 billion to acquire cybersecurity firm Mandiant Inc. According to the announcement, Mandiant will join Google’s Cloud division when the acquisition is completed. Although regulatory permission is still pending, Google anticipates the merger to finalize later this year. If it goes through, it will be Google’s second-largest acquisition ever, behind the $12.5 billion Motorola Mobility merger and the $3.2 billion Nest purchase.
Mandiant was previously under the FireEye banner before that company was sold. When FireEye Inc. sold its security-product business for $1.2 billion to a consortium led by Symphony Technology Group last year, Mandiant became a stand-alone firm again with a market valuation of $5.25 billion. In 2019 and 2020, FireEye was credited with assisting Microsoft in the discovery of the SolarWinds breach, which targeted government networks. It has also helped in the investigation of the Log4j vulnerability, and the Pulse Secure VPN vulnerabilities.
Mandiant will provide Google Cloud with a huge degree of protection, going beyond the company’s well-known incident response (IR) service. Threat intelligence, security validation, automated defense, attack surface management, and managed defense are all part of Mandiant’s platform. In terms of services, Mandiant offers strategic readiness, technical assurance, and cyber defense transformation — the process of assisting clients in developing and strengthening their security posture.
Mandiant will be paid $23 per share, which is a 57% premium over the 10-day weighted stock price average. The stock has gained over 18% in the previous year and has had a strong boost in the last few days as rumors of a possible deal began to emerge.
According to Google Cloud CEO Thomas Kurian, companies are facing unprecedented security dangers, especially while the crisis in Ukraine rages, and Mandiant provides the firm with a platform of security services to add to the Google Cloud Platform.
Following Google’s recent acquisition of Siemplify for security orchestration, automation, and response (SOAR), Gartner analyst Neil MacDonald opines the Mandiant acquisition is another obvious indicator that Google is serious about creating revenue in its security sector.
President Joe Biden could possibly sign a long-awaited executive order this week asking the Justice Department, Treasury Department, and other agencies to investigate the legal and economic implications of creating a digital currency issued by the US central bank. This might be the first real step by the White House toward regulating the digital currency. The presidential order is likely to specify what government institutions, including the Treasury Department, must undertake in order to implement cryptocurrency laws and regulations. It is also likely to request the State Department ensure that US cryptocurrency rules are consistent with those of US partners, as well as to charge the Financial Stability Oversight Council with investigating any unlawful financial issues.
The executive order would allow Biden to direct the Justice Department to investigate whether new legislation is required to create a new currency. Other departments, like the Consumer Financial Protection Bureau and the Federal Trade Commission, will investigate the potential impact on consumers. Other authorities will look at the impact of cryptocurrency on competitiveness, infrastructural requirements, Bitcoin mining’s environmental impact, and so on. To summarise, the directive will not require immediate action, but it would need authorities to report back after investigating the dangers linked with crypto assets.
The importance of cryptocurrencies in our daily lives as well as in political concerns is undoubtedly increasing. Millions of dollars in cryptocurrency donations flowed in after the Ukrainian government tweeted a call for aid. Simultaneously, there are rising concerns about Russia’s use of cryptocurrency as a means of evading sanctions.
“We will continue to look at how the sanctions work and evaluate whether or not there are liquid leakages and we have the possibility to address them. I often hear cryptocurrency mentioned and that is a channel to be watched,” Treasury Secretary Janet Yellen said last week.
The Treasury Department’s Financial Crimes Enforcement Network issued an advisory on Monday, warning financial institutions to be “vigilant” about any attempts to circumvent sanctions related to Russia’s war in Ukraine.
Then there’s the big meltdown, which sent currencies down by 10% or more, harming even the most important enterprises. There are also growing concerns about the effects of crypto mining on the environment. Several firms, including Elon Musk’s Tesla, Mark Cuban’s NBA franchise Dallas Mavericks, and movie theatre chain AMC Theatres, have begun to accept bitcoins for payment.
Yellen also stated that the Department of the Treasury will continue to collaborate with the Financial Stability Oversight Council, which met last year to review stablecoins. Last December, the committee released a paper that identified stablecoins and decentralized finance as two risk-prone areas for US financial stability.
Other initiatives to address crypto legislation have been handled by the Treasury Department, including a study on stablecoins by the President’s Working Group for Financial Markets. The report, which was released last year, requested that Congress approve legislation granting federal bank regulators express supervision authority over the stablecoin industry.
Meanwhile, the USA is also concerned that cryptocurrencies also pose threat to its national security. For instance, it’s been suggested that China manipulates cryptocurrency prices through regulatory acts to obtain a competitive advantage in adopting the digital yuan as part of its Belt and Road Initiative. North Korea is also accused of stealing cryptocurrencies to fund its nuclear weapons program.
The announcement of this executive order comes shortly after the Federal Reserve Board (FRB) released a discussion paper in January examining the benefits and drawbacks of adopting a central bank digital currency (CBDC) for the United States, which is open for public comment through May 20, 2022.
Once signed by Biden, the executive order will establish a 180-day timeframe for federal departments to submit findings on the future of money and the role of cryptocurrency in that future. After 545 days, the order will request a follow-up report on the technology’s environmental impact. Sources say Biden will be signing the order most probably by today. As soon as this happens the landscape of the crypto industry in the US will change forever with the new regulations.
The government of Telangana announces that it intends to use artificial intelligence to aid government schools in formative assessments.
Select Government school complexes in the state will be able to apply artificial intelligence-based solutions to automate time-consuming and resource-intensive tasks, including formative assessments, marking attendance, and logging mid-day food data, among others.
The new education policy of India made formative assessment mandatory for all schools, allowing teachers to evaluate each class once a week and create a report detailing who grasped the idea and who did not.
By monitoring students’ body language, expressions, attentiveness, and the types of questions they ask in class, experienced teachers can determine who is comprehending the information.
According to the plans, the artificial intelligence tool that will be deployed in schools will consider all the attributes mentioned above to help teachers better assess students’ progress. The tool will provide a report that teachers can use to plan additional support for pupils who have received a low grade.
The Prof Raj Center at IIIT-H is working to develop technology solutions for the general public, and these artificial intelligence-based tools will be used as a pilot project in selected school complexes in Moinabad.
IIIT-H Co-Innovation Professor, Ramesh Loganathan, said, “We plan to meet the concerned people once again and make specific plans for the technological interventions possible. We want to keep the technology ready for the coming academic year.”
He further added that these would be three- to six-month projects to address difficulties as soon as possible. Additionally, the government also plans to use AI-powered tools to teach English to students and slowly expand its capabilities to teach multiple other languages.
“For each lesson in English, there will be a set of sentences that the system will speak, and then the class or individual students will repeat,” added Loganathan.
Technology giant Meta announces that it has started hiring for Meta AI’s second cohort of Rotational AI program, RAISE.
It is a full-time rotational program that lasts 18 months and offers participants full-time employment with the Meta AI team. The 2022 program is being offered in Menlo Park, Seattle, New York City, and Remote in the United States.
Meta has meticulously developed this unique program to bring together a broad group of software engineers with little or no prior artificial intelligence experience from various industries and backgrounds.
All participants become full-time employees during the program, giving them access to all of the benefits of working as a software engineer at Meta. “RAISErs start together as a cohort and follow the same overall program timeline to share experiences and build connections with others in the program,” mentioned Meta in a blog.
A mandatory norm is that all the new engineering hires at Meta must first complete a 5-week Bootcamp to learn about Meta engineering. One of the most interesting aspects of RAISE is the opportunity to collaborate on a variety of artificial intelligence-related topics if participants so desire.
Meta’s program will allow selected participants to acquire hands-on experience with frameworks such as PyTorch and internal Meta tools, as well as construct state-of-the-art models and apply research to production.
Meta is currently accepting applications for the program, and interested candidates can apply from the official website of meta till 15th April 2022. Meta expects the new heroes to start the program in May 2022. Meta is also organizing a virtual session on 31st March to provide a better understanding of the RAISE program to interested participants.
On this year’s International Women’s Day, Analytics Drift takes a deep dive into highlighting how the mentioned women entrepreneurs are contributing their part into building better AI-powered today and tomorrow.
Geetha Manjunath, Niramai
AI has been a blessing to the field of medical imaging due to its ability to detect difficult-to-trace anomalies. After a personal tragedy, committed to offering early-stage breast cancer diagnosis in a non-contact, non-invasive, and privacy-conscious manner, Geetha Manjunath founded Niramai health-tech firm. Niramai is an artificial intelligence-driven diagnostic platform that uses patented thermal image processing and machine learning algorithms for reliable and accurate breast cancer screening. Women of all ages can benefit from this low-cost, easy-to-use product, making cancer screening possible in all clinics.
Thermalytix, a cloud-hosted analytics tool built by the health tech firm, employs big data analytics, artificial intelligence, and machine learning algorithms for early breast cancer detection. Thermalytix’s solution primarily consists of a high-resolution thermal sensor device that captures thermal pictures and a cloud-hosted analytics system that analyses and screens for breast cancer.
Niramai provided Home Breast Health Screening for high-risk women and cancer survivors who needed monitoring during the Covid-19 outbreak. Earlier, it had also received money from the CDC UK to create a FeverTest screening for recognizing Covid-19 symptoms. NIRAMAI FeverTest has capabilities that recognize and identify non-compliance with mask-wearing standards, which can help restrict the spread of COVID-19. Morgan Stanley, Kotak Bank, and various RMZ business parks across India were among the popular adopters of this solution.
Geetha has been listed among India’s top women achievers by Forbes in 2020.
Meghna Saraogi, StyleDotMe
Starting her career as a graphic designer, Meghna Saraogi founded StyleDotMe, which was seed-funded by the Indian Angel Network in 2016. StyleDotMe is an augmented reality (AR) platform; its flagship product, mirrAR, allows customers to try on jewelry digitally. The software was first introduced in 2017 as an in-store inventory management solution, with a web version following in January 2020. The technology enables jewelry makers to expand their reach by giving customers additional product selections, the chance to examine numerous jewelry items on themselves in rapid succession, and instant fashion guidance from experts. MirrAR can also be integrated into any platform, whether on a device like an iPad or on the web, allowing for offline and online use.
With instant polls and voting options, users can access instant fashion advice from not only friends and followers, but from professionals all across the world. StyleDotMe had teamed with jewelry company Tanishq for a virtual jewelry try-on experience zone at Delhi and Bangalore airports after launching mirrAR at Bridal Asia in August 2018. Today, its clientele includes several international and domestic brands like PC Jewellers, Farah Khan Jewellery, Amrapali, and several small retail jewelers.
Barkha Sharma, Bash.ai
While the rest of the world was gradually embracing automated solutions, Barkha Sharma saw that HR functions were becoming obsolete. Therefore, Barkha created Bash.ai in her living room in 2017 in an effort to automate HR operations and thereby aid in providing better and consistent employee experiences. Bash’s user-friendly front-end interface allows businesses to automate discussions with employees in real-time with great accuracy. It includes modules such as post-hire orientation, ticketing, HR helpdesk, employee engagement, organizing HR operations, and answering inquiries about payslips and business regulations. This allows the HR team to be more efficient, motivate employees to be more productive, and save the company money by retaining personnel.
Bash’s chatbot is available on a variety of platforms, including Facebook, Messenger, and Slack.
Pooja Rao, Qure.ai
While India has hundreds of radiologists, most of them are centered in metro or Tier I cities. As a result, residents from the suburbs are left with the option to either drive considerable distances to a healthcare center or rely on third-party radiologists at hospitals. Both of these options are unpleasant as well as ineffective.
Qure.ai, situated in Mumbai and co-founded by Pooja Rao in 2016, employs artificial intelligence to make healthcare solutions more inexpensive and accessible. It employs deep learning algorithms to analyze medical pictures and scans in seconds, such as chest X-rays, head CT scans, POQUS, chest CT scans, and so on. The startup has already worked with AstraZeneca to employ AI for lung cancer screening in 2020.
Qure.ai is also a part of NVIDIA’s Inception startup accelerator program. The AI technology qXR from Qure.ai aids triage decisions in COVID patients by monitoring illness development and providing a risk score. Last year, Qure.ai obtained its first FDA approval in the United States. Its technology has also been recognized by the World Health Organization, which has recognized AI as an effective method for diagnosing TB, particularly in places where healthcare professionals are scarce. The firm has partnered with the NITI Aayog, the Piramal Foundation’s Piramal Swasthya program, and the PATH NGO in India.
Gazal S. Kalra, an alumnus of IIT Delhi, Stanford University Graduate School of Business, and Harvard Kennedy School of Government, is a co-founder of Rivigo, a trucking AI-based logistics platform financed by Elevation Capital and Warburg Pincus, among others. During a coffee meetup with co-founder Deepak Garg, Gazal noticed that transportation is a major aspect of India’s operations for businesses as broad as manufacturing, FMCG, and eCommerce. Trucks are often outdated, exposed to harsh weather conditions where tarpaulin serves as cover, and poorly maintained, with no insight into when a truck would arrive at its destination after leaving the origination point.
Rivigo uses a relay trucking model, in which truck drivers do not run their cars for more than five hours at a time and return home the same day, owing to AI taking care of routing and pilot assignment. Rivigo’s trucks are IoT-enabled, allowing for real-time monitoring of the vehicle’s status. This helps to ensure reliability by reducing breakdowns. The IoT-based monitoring proved even more useful when Rivigo launched refrigerated vehicles for the fresh produce market. Clients of Rivigo can check the temperature in real-time and even modify it remotely using the mobile app which is available in more than ten languages.
Further, despite the high unemployment rate, people were unwilling to take up the occupation of the truck driver as they had to travel large distances to deliver the shipments and goods single-handedly, often resulting in delays and staying away from their families for a long time.
Megha Gambhir, Stupa Sports Analytics
Table tennis is a fast-paced game with a lot of spin and quick ball exchanges, which makes it difficult to analyze. Megha Gambhir had spent a significant amount of time seeing that her husband, an ardent Table Tennis fan and player, was having difficulty finding a tool to help him with his task of and tracking players’ performance. This prompted her and her husband to co-found Stupa Sports Analytics.
While there are other sport analytics companies, Stupa Sports is the world’s first AI-backed sports analytics firm for table tennis. Unlike other sports analytics systems, it also does not require high-speed cameras to gather and review player performance. Stupa uses low-cost technologies like a smartphone camera to provide AI-enabled ball tracking and video analytics. The solution offers advanced video analytics that can monitor a very tiny ball moving at over 100 kilometers per hour.
The central idea is extracting data from matches or training to the smallest detail, then processing and mining it with appropriate statistical and analytical data to produce interactive AI-enabled analysis backed up by sliced video snippets. Coaches and players can access all of this input and analysis using a mobile application. Stupa offers real-time match and training analysis, as well as ball trajectory detection, speed tracking, and heat map derivations.
In addition, Stupa has collaborated with the International Table Tennis Federation (ITTF) and has expanded into 226 nations. The USATT, Hungary, Sweden, and Portugal federations have joined forces as their exclusive analytics partner for their national teams and athletes.
Ashwini Asokan, Mad Street Den
Ashwini Asokan is the co-founder of Mad Street Den, an Artificial Intelligence (AI) startup, with a professional degree in Visual Communications from India and a Master’s in Interaction Design from the United States. Mad Street Den was co-founded by her husband, Anand Chandrasekaran and she, in 2013 with the goal of bringing a human element to AI and creating meaningful AI applications that may positively impact both the business and consumer lives. Vue.ai, the company’s first product, was created in 2016 to enable intelligent retail automation. Vue.ai includes seven different products, viz., VueTag, VueModel, VueStyle, VueCommerce, VueMail, VueFind and VueStudio, to offer retailers a unified system.
Users can utilize this AI-based system to identify face emotions or expressions, as well as capture smiles, among other things, using their smartphone cameras. This aids retail shops in lowering operating expenses, increasing product exposure, and making quicker decisions.
Blox.ai, another of its products, offers businesses machine vision and NLP- (Natural Language Processing) driven corporate solutions that address issues ranging from data organization and structure to prediction and personalization. This solution is leveraged predominately in education, entertainment, finance, and healthcare.
Niyati Agarwal, Morph.ai
Social media content and marketing have become instrumental parts of a business brand’s online visibility. To help companies with these, Morph.ai was founded by Niyati Agarwal (current Director Product and Strategy at Gupshup) and three coworkers in March 2016. Based in Gurgaon, Morph.ai has huge names like YES Bank, Estee Lauder, Yamaha, HSBC, and Manchester City Football Club among its core customers in less than two years of operation.
This B2B SaaS company enables marketers to utilize messaging as a marketing channel and create personalized interactions between businesses and consumers in order to generate up to double the high-quality leads with the same ad expenditure.
The Morph.ai chatbot achieves this by reaching out to a business’s potential consumers in real-time and automatically qualifies them with regular follow-ups, resulting in high-quality leads for the brand. Morpha.ai also allows for chat-based content marketing, where it segments and targets a brand’s audience to offer them engaging tailored content from the brand’s newsletters, YouTube, Blog, and other content channels and help lead conversion.
Global eCommerce giant Amazon has launched the #SheIsAmazon campaign to highlight female employees, associates, and partners who have overcome societal, cultural disability, and economic barriers to achieve their goals.
The announcement was made a day before International Women’s Day as a part of the company’s celebration.
Amazon is launching a coffee table book as part of the new campaign, giving people a glimpse into the professional and personal lives of these women, as well as their journeys of struggle, hope, and success.
The book mentions stories of multiple superwomen in the industry, including Ananya Ghosh, Nimisha Dhanda, Deepa Karthik, Suchitra Terdalkar, and many more.
Director, DE & I, International Markets, WW Consumer, Amazon, Swati Rustagi, said, “At Amazon, inclusion is at the heart of all our decision making, and we believe that it’s not only good for society but also for business. ‘SheIsAmazon’ is a simple effort to recognize the stellar work done by many women across Amazon India.”
She further added that every day, thousands of women break stereotypes and succeed in unconventional roles and profiles, and she is grateful to all of these remarkable women for helping to shape Amazon into an inclusive and progressive workplace.
Amazon India stated that it had made efforts to increase workplace diversity through pioneering initiatives and inclusion programs such as Amazon’s rekindle, which offers and supports opportunities for women to professionally re-integrate themselves and resume their corporate careers.
Another such initiative is ‘Amazon WoW,’ which helps engineering students build long-term careers in technology by allowing them to interact with Amazon leaders, participate in workshops, connect with alumni on career experiences, and apply for roles at Amazon.
Sindhu Mary from Amazon India Fulfillment Center said, “I am so glad to be treated as an equal at my workplace. Honestly, I want to tell all my community members that when the right platform is offered to you, grab the opportunity and give it your best.”
Global technology giant Microsoft India announces that it plans to establish a new data center region in Hyderabad.
Microsoft’s commitment to helping clients succeed in a cloud and AI-enabled digital economy is reflected in this key investment, which will become part of the world’s largest cloud infrastructure.
The Hyderabad datacenter region will join the existing network of three Indian datacenter regions, which include Pune, Mumbai, and Chennai.
According to Microsoft, the first phase of the newly announced data center region is expected to start its operation by 2025. As per IDC, Microsoft data center regions in India generated $9.5 billion in revenue between 2016 and 2020. In India, Jio, Inmobi, Infosys, TCS, Apollo Hospitals, State Bank of India, and Flipkart are among the company’s customers.
Minister of State for Skill Development & Entrepreneurship and Electronics & Information Technology of India, Rajeev Chandrasekhar, said, “Today’s commitment to the people and businesses of India will position the country among the world’s digital leaders. A Microsoft data center region provides a competitive advantage to our digital economy and is a long-term investment in our country’s potential. The cloud is transforming every industry and sector.”
He further added that investing in skill development will benefit India’s workforce now and in the future.
Microsoft says that the data center region will provide the entire Microsoft portfolio for enterprises, start-ups, developers, education, and government institutions, including cloud, data solutions, artificial intelligence, productivity tools, and customer relationship management (CRM) with advanced data security.
Additionally, Microsoft Cloud services will provide opportunities for local businesses to innovate. Microsoft is also working with the Telangana government to accelerate the adoption of cloud, artificial intelligence, IoT, and cybersecurity solutions for governance.
“The new datacenter will augment Microsoft’s cloud capabilities and capacity to support those working across the country. It will also support new entrepreneurial opportunities while meeting critical security and compliance needs,” said President of Microsoft India, Anant Maheshwari.
