Daily Archives: December 5, 2021

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Recruiting is a top concern for enterprises in 2021. In a survey by XpertHR, roughly one-half of responding employers plan to increase their workforce in 2021, but expect that hurdles will stand in the way. A high volume of low-quality applicants is stymying the search for the ideal candidates, with one source pegging the average number of unqualified applicants at 75%. Even among those that do make it through the recruiting funnel, a significant portion ultimately change their minds exacerbating the recruiting challenge.

Against this backdrop, Sense, an AI-driven talent engagement and communications platform, today announced that it raised $50 million in series D funding led by SoftBank. CEO Anil Dharni says that the proceeds, which bring Senses total capital to $90 million, will be put toward hiring and recruitment as well as product development.

San Francisco, California-based Sense was launched in 2016 by Dharni, Alex Rosen, Pankaj Jindal, and Ram Gudavalli. Dharni is an active entrepreneur, having cofounded AnswerU and social gaming networks Storm8 and Funzio prior to starting Sense. Jindal was previously the CEO of Akraya, an IT and marketing consulting agency headquartered in Bengaluru. As for Gudavalli, he cofounded Funzio with Dharni and worked alongside him at Hi5, a social network whose parent company was acquired by MeetMe in 2017 for $60 million.

In the past decade, weve seen a shift in the workforce dynamic. Candidates have more options and subsequently more power than ever before And yet, recruiters and hiring teams are still stuck in the dark ages when it comes to creating the ultimate candidate experience, Dharni told VentureBeat via email. I want to create a world where recruiters and talent acquisition leaders are loved by the candidates they serve. The bottom line is, companies are struggling in a massive way to retain and engage with employees.

Sense offers a slate of job candidate matching and screening services in addition to a drag-and-drop recruitment campaign creation tool. With the platforms services, which sync with Workday, Greenhouse, and other existing applicant tracking systems, companies can deduplicate pools of new applicants against existing databases and send targeted follow-up messages, among other tasks.

Sense also provides a shared inbox through which HR teams can manage and prioritize candidate conversations, sort and view chats, and perform searches by name, name, and tags. For companies offering referral programs, Sense can host a dashboard that shows open positions and allows employees to submit referrals and track where they are in the hiring process. Managers can use the dashboard on the backend to manage submissions, approvals, rewards, and payouts.

Sense says that its developed algorithms that can automatically trigger messages and workflows based on a candidates profile data or when they complete a certain action in a journey. The platforms candidate email and text messaging feature which can send messages to up to hundreds of candidates at once can optionally automate messages with personalized texts that answer questions, explain benefits, and provide status updates on hiring.

In September, Sense launched a chatbot that sources and screen candidates by responding to questions when recruiters are offline. A part of the companys larger platform, the chatbot can schedule interviews and support database reactivation through proactive candidate outreach.

Sense says that the chatbots design was informed by its own research, including a recent survey it conducted on strategies for recruiting success. The survey, which canvassed 600 leaders at staffing agencies, found that recruiters spend up to 50% of their time on manual and repetitive tasks andtake over 6 hours to respond to new leads, on average.

Theres no shortage of platforms claiming to leverage AI to expedite the hiring and recruitment process. For example, Xor is developing a chatbot that handles job candidate recruiting and screening processes, and Celential.ai which focuses specifically on the software industry employs models to match candidates with open roles.

Other Sense competitors include Wade & Wendy, Workey, and Phenom People, but Dharni believes theres plenty of business to go around in the $19.38 billion HR solutions market. Senses customers include teams at Amazon, Volt, PrideStaff, and Sears.

We have over 350 million candidate profiles across over 600 customers. [T]ens of thousands of recruiters use Sense every day to interact and converse with millions of candidates each month, Dharni said. The pandemic has accelerated investment in recruitment technology and the adoption of Sense. It has pushed companies to pulse [and] survey employees more frequently to proactively understand employee challenges and solve them. It has [also] powered competitive hiring and contingent hiring. As a result of the pandemic, outbound communication and engagement through our platform grew 500%.

According to Alexander Mann Solutions, 96% of senior HR professionals believe that AI has the potential to greatly enhance talent acquisition despite assertions by some advocates that these tools can perpetuate bias in hiring processes. A number of reports, including theHidden Workers: Untapped Talentstudy, have raised concerns about potential bias arising from the use of AI in hiring.

Via email, Gartner research VP Helen Poitevin told VentureBeat that theres inherently less risk of AI bias in top of the funnel recruitment activity like the kind that Sense orchestrates. Thats not to suggest there isnt risk Poitevin stressed the need for companies like Sense (and their customers) to pay attention to the data being used and the assumptions being built in to the candidate-to-job-matching algorithms. But human biases are more likely to come into play with these types of solutions, she asserted, like biases in the language used to describe positions or the tone in outreach.

Looking at Senses website, I see that they are being used to engage, message, manage referrals, and engage with candidates through a chatbot. This is akin to other solutions on the market more oriented to candidate relationship management and recruitment marketing, engaging with candidates, Poitevin said. The risk is not as high as when AI is being used to rank the fit of a candidate to a given job opportunity For example, a recruiter simply being interested in a profile is not considered a robust assumption in an algorithm determining what makes a good match between a candidate and a job. These types of data and assumptions built into algorithms are much more likely to lead to biased decision-making in the hiring process.

Sense has 185 employees, a number it expects will double by the end of 2022.

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Sense raises $50M to bolster recruitment efforts with AI - VentureBeat

Dividend stocks can be a great way for retirees to generate meaningful income from their investments while maintaining a lower-risk portfolio.

Among this group of stocks is an elite class that has earned the designation as Dividend Kings -- or companies that have increased their annual dividend payouts for 50 straight years or more. Cincinnati Financial (NASDAQ:CINF) is an insurance company that has earned this designation and managed to increase its dividend payout annually for 61 years straight. Only eight publicly traded companies have a longer streak.

Image source: Getty Images.

What has allowed Cincinnati Financial to continue performing so well for so long? Well, part of the secret is the company's ability to adapt to changes in its business. Insurers are increasingly collecting more data and using artificial intelligence (AI) in making underwriting decisions. Cincinnati Financial faces competition from young insurers leveraging AI to disrupt the industry. To stay ahead of the competition (or at least keep pace with them), Cincinnati Financial has invested heavily in its own data and AI-powered business.

It's an investment that appears to be paying off.

Cincinnati Financial is an insurer that focuses mainly on underwriting property and casualty insurance policies for individuals and businesses. Roughly 62% of its premiums coming from commercial lines of insurance including property, and from worker's compensation insurance. Another 26% of its premiums come from personal lines of insurance for things like homeowners and auto insurance.

Cincinnati Financial has a history of growing profits at good margins and its also a cash-generating machine. From 2012 through 2020, the company has grown its cash flow from its property-casualty insurance at a steady 11.5% compound annual growth rate. This consistent cash generation provides Cincinnati Financial with more than enough cash to cover claims, pay out dividends, and pursue investment opportunities for added growth.

The insurance industry is ripe for disruption from newer start-ups leveraging AI to reimagine the underwriting and claims process. Several unicorns, like Root and Lemonade, are utilizing AI to underwrite policies in a fraction of the time and resolve insurance claims quicker. AI will play a key role for insurance companies over the next decade. According to researchers at McKinsey:

"The winners in AI-based insurance will be carriers that use new technologies to create innovative products, harness cognitive learning insights from new data sources, streamline processes and lower costs, and exceed customer expectations for individualization and dynamic adaptation."

While unicorns are using AI to disrupt the industry, companies like Cincinnati Financial look to AI to maintain and build on their decades of experience. The insurer has built up its data and analytics risk models to underwrite better policies and improve the claims process.

The company credits these models for its lower share of property and casualty losses compared to the industry over the past five years. CEO Alan Schnitzer also credits the model for helping the company avoid underwriting plans for areas of the coast when Hurricane Ida made landfall this August in Louisiana. The model also helped it manage risk in those states where the hurricane passed through by using flood risk scoring and location intelligence models to set premiums accordingly.

Cincinnati Financial's AI model was also used to handle claims quickly and efficiently. One aspect of its claims response for Hurricane Ida was AI-assisted claim damage detection. By using high-resolution aerial images to evaluate home damage, the company could remotely identify customers with exterior damage and pay losses -- before customers returned home, in many cases. By leveraging AI, Cincinnati Financial could provide a better customer experience while significantly reducing the time to process claims.

Image source: Getty Images.

According to Risk Management Solutions Inc., losses from Hurricane Ida are estimated to come in between $31 billion and $44 billion for insurance companies. Despite Hurricane Ida's outsize damage, Cincinnati Financial made out well during the quarter. In the third quarter, the company posted a combined ratio of 92.6%. Combined ratio is a key measure of profitability for insurance companies. This ratio measures losses paid to cover claims plus expenses, divided by total premiums earned. A ratio below 100% means a company is writing profitable policies. In comparison, a ratio above 100% indicates the company is losing money on policies.

By comparison, Progressive saw a combined ratio of 142.3% on its property line of coverage and a 100.4% combined ratio for the overall business.Meanwhile, Allstate saw its homeowners' combined ratio come in at 111%, while the overall combined ratio was 105.3%.

Image source: Getty Images.

Business-wise, Cincinnati Financial has done a stellar job against its peers. Over the past five years, the insurer has achieved combined ratios below the industry average. It has done so while growing premiums above the industry average in four of the past five years. In 2020, the insurer saw premiums increase 6.3% compared to the industry average of 2.5%.

Cincinnati Financial has a long history of profitability, which is part of why it has been able to increase its dividends for 61 years straight. The stock also yields investors over 2.1% annually, which is higher than the S&P 500 average of about 1.3%.

Leveraging AI to improve underwriting and speed up the claims process is a positive sign it can fend off newer entrants in the space -- and makes Cincinnati Financial a solid dividend stock for any retiree's portfolio.

This article represents the opinion of the writer, who may disagree with the official recommendation position of a Motley Fool premium advisory service. Were motley! Questioning an investing thesis -- even one of our own -- helps us all think critically about investing and make decisions that help us become smarter, happier, and richer.

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1 Dividend King Is Leveraging AI to Stay On Top - Motley Fool

Teslas Director of Artificial Intelligence (AI), Andrej Karpathy, shared a thread this week about a new project that his team is working on. He also shared some video footage from it. The thread, in a nutshell, is an invitation for those interested in helping Tesla solve this particular problem. They want you to apply for a job.

Karpathy noted that the videos were panoptic segmentation from the new project and were too raw to run in the car. So, instead, they are feeding it into auto labelers.

In AI, panoptic segmentation is the task of clustering parts of an image together that belong to the same object class. Another term for this is pixel-level classification. It partitions images or video frames into multiple segments or objects. An auto labeler simply labels raw, unlabeled data. Labeling helps an AI understand the implications of a pattern. PatternEx has an in-depth article about this term and uses the Pandora app as an example. As you hear a song and click the thumbs up, you are basically telling it that you like the song. This is labeling. Another example is a parent reading a book to a baby, tapping an image of a dog, and saying the word dog.

So, explaining Andrejs tweet in laymans terms, he is simply saying that the videos are from a new project where they are clustering parts of an image/video that belong to the same object class and then getting it labeled via AI. After that, the aim is to improve the system more and more so that the AI gets better and better at seeing the world in a complete, comprehensive, human (but actually superhuman) way.

Karpathy pointed out that it is still early for this task and that Tesla needs help perfecting these panoptic segmentation predictions and realizing the downstream impact.

Whos gonna help Tesla? Anyone who wants to can apply to join the team here.

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Teslas Director of AI Shares A New Project That Tesla Is Hiring For - CleanTechnica

In brief Prisons around the US are installing AI speech-to-text models to automatically transcribe conversations with inmates during their phone calls.

A series of contracts and emails from eight different states revealed how Verus, an AI application developed by LEO Technologies and based on a speech-to-text system offered by Amazon, was used to eavesdrop on prisoners phone calls.

In a sales pitch, LEOs CEO James Sexton told officials working for a jail in Cook County, Illinois, that one of its customers in Calhoun County, Alabama, uses the software to protect prisons from getting sued, according to an investigation by the Thomson Reuters Foundation.

"(The) sheriff believes (the calls) will help him fend off pending liability via civil action from inmates and activists," Sexton said. Verus transcribes phone calls and finds certain keywords discussing issues like COVID-19 outbreaks or other complaints about jail conditions.

Prisoners, however, said the tool was used to catch crime. In one case, it allegedly found one inmate illegally collecting unemployment benefits. But privacy advocates arent impressed. "The ability to surveil and listen at scale in this rapid way it is incredibly scary and chilling," said Julie Mao, deputy director at Just Futures Law, an immigration legal group.

Codenamed ISM001-055, the drug was first formulated by Pharma.AI, a software platform described as drug discovery engine developed by startup Insilico Medicine, earlier this year in February.

The molecule was designed to treat idiopathic pulmonary fibrosis (IPF), a lung disease that causes scar tissue to build inside the organ making it difficult for people to breathe properly. After initial tests, ISM001-055 seemed so promising that Insilico Medicine decided to launch clinical trials.

Healthy volunteers were selected for the trial to test for any side effects. "We are very pleased to see Insilico Medicine's first antifibrotic drug candidate entering into the clinic, said Feng Ren, chief scientific officer of Insilico Medicine. We believe this is a significant milestone in the history of AI-powered drug discovery because to our knowledge the drug candidate is the first ever AI-discovered novel molecule based on an AI-discovered novel target.

There is no current cure for the IPF. If the AI-designed drug is capable of treating the disease itll show that the technology is capable of developing new drugs at lower costs than traditional methods.

Timnit Gebru, who was controversially fired from her position as co-lead Googles Ethical AI research team a year ago, has set up her own independent lab.

The Distributed AI Research Institute (DAIR) is focused on studying social harms of AI, and how they can be best mitigated. It has received a total of $3.7m in funding from philanthropic groups and non-profit orgs such as the MacArthur Foundation, Ford Foundation, Kapor Center, Open Society Foundation and the Rockefeller Foundation, according to the Washington Post.

Gebru said she wanted to remain independent, and has chosen to stay away from big name investors to avoid being influenced by large tech firms. Lets say I antagonize a funder not these, but others, she said. Theres all of these Big Tech billionaires who also are in big philanthropy now. DAIRs research will scrutinize and critique these big firms.

Some early projects with the institutes first research fellow Raesetja Sefala will study analyze satellite images to study the effects of segregation in South Africa.

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Prisons transcribe private phone calls with inmates using speech-to-text AI - The Register

The advent of these AI innovations has truly revolutionized the automobile industry.

The integration of cutting-edge technologies such as artificial intelligence, computer vision, IoT, and many more into vehicles has dramatically changed the image of the automobile industry. The automobile industry has started leveraging AI in the whole process starting from designing to after-sale service and drivers safety. Artificial intelligence has laid down the foundation for smarter vehicles in smart cities through this industry. Multiple hi-tech automotive companies have started leveraging cutting-edge technologies to strive in the competitive market with the utmost customer satisfaction.

3D Printers: The introduction of 3D printers has transformed the automobile industry in the last few years. The industry utilizes 3D printers for creating automotive prototypes to check fitness, making aesthetically pleasant parts, designing efficient car models, and many more. One of the important technologies behind 3D printers is Fused Filament Fabrication (FFF) that is used for the production as well as end-use parts in the automobile industry.

Smart Helmets: Smart helmets are one of the most important AI innovation in this industry for the safety of drivers. Smart helmets are completely different from traditional helmets for the implementation of GSM and GPS technologies. Drivers are inclined towards smart helmets owing to its advanced technology to call an ambulance or a family member post-accident, the presence of operation vibration sensors, alcohol sensors, crash alerts, LED lights, and many more.Autonomous Vehicles: Autonomous vehicle (AV) is the hottest topic in this industry to provide major help to citizens. Multiple hi-tech giants are aiming at manufacturing autonomous vehicles across the world. AV is capable of sensing the nearby environment and driving on its own without any human driver on the drivers seat. It can go anywhere like a classical car after entering the destination. It is very useful for senior citizens to have freedom and independence to roam around in the city.Collaborative Robots: Collaborative robots or cobots are thriving in this industry with their smart functionalities such as machine loading, machine tending, inspection, assembly in productions, and many more efficiently and effectively. Cobots tend to work with human employees to enhance outcomes, consistency, flexibility, and support without any potential error.Machine Vision: Machine vision is known as a key technology for optimizing different processes in value chain including quality assurance, production, logistics, and many more. The automobile industry is leveraging machine vision for unambiguous object detection, accelerating existing production processes, eliminating potential errors or risks, and so on. It has high speed where the algorithms need milliseconds to detect, analyze, and process sufficient data from images.

Automated Guided Vehicles: Automated Guided Vehicles (AGVs) have started providing multiple benefits to the automobile industry such as reduction in direct labour cost, eliminating workforce shortage, removing potential errors, limiting heavy goods handling, scalability, enhancing productivity, ensuring better safety, and many more. AGVs are known for carrying assembly lines while being forklift-sized wheeled carts to use software in navigating their movements efficiently and effectively.

Driver Monitoring System: Driver monitoring system is emerging as one of the top AI innovations for alerting drivers during drowsiness, distraction, and so on to avoid fatal road accidents. It is also known as a driver state sensing that utilizes a driver-facing hi-tech camera with infrared LEDs on the dashboard to track the eye movements of drivers. There is advanced on-board software that collects the data and creates an initial baseline of the normal active driver. It analyzes whether the driver is blinking more, feeling dizzy, narrowing the eyes, and other eye movements to issue audio alerts to keep him alert.

AI Cameras: The integration of AI cameras in different vehicles has increased revenues in the automobile industry. Drivers are preferring cars with AI cameras to provide safety to oneself as well as family members. These AI cameras are providing multiple services to drivers with a combination of multi-path approach as well as artificial intelligence for image or video recognition to make roads much safer.Vehicle Tracking Software: The automobile industry has recognized the importance of vehicle tracking software to locate the vehicle efficiently and effectively. GPS is set to provide a live update of different locations of a vehicle and its condition. It helps in the recovery of a stolen vehicle and provides details on fuel, speed, engine, and many more. There is an advanced mapping feature to zoom in to the street level with a close and accurate view for analysing routes without any error and wastage of time.Automotive Insurance: Automotive insurance plays an important role in this smart automobile industry. Drivers can perform their own auto damage assessment for their respective insurance companies without any potential error. There will be on-screen instructions on how to video the damage and later submit it for an automotive insurance claim. Artificial intelligence will inform drivers how to repair and the total cost covered by the insurance.

The automobile industry is waiting for more evolving and ever-changing trends of artificial intelligence to enhance productivity and manufacture smarter vehicles. The implementation of artificial intelligence is set to protect the safety of drivers and provide a good experience to passengers in the nearby future. Multiple hi-tech companies are aiming to capture the automotive industry by leveraging their artificial intelligence experience. Customers have started placing trust and faith in artificial intelligence algorithms behind the steering wheel and it has a major growth prospect in the future.

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Analytics Insight is an influential platform dedicated to insights, trends, and opinions from the world of data-driven technologies. It monitors developments, recognition, and achievements made by Artificial Intelligence, Big Data and Analytics companies across the globe.

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10 AI Innovations that are Transforming the Automobile Industry - Analytics Insight

Dublin, Dec. 03, 2021 (GLOBE NEWSWIRE) -- The "Artificial Intelligence in Healthcare Market (by Component, Application, End-user & Region): Insights & Forecast with Potential Impact of COVID-19 (2021-2025)" report has been added to ResearchAndMarkets.com's offering.

The global AI in healthcare market is forecasted to record a value of US$22.68 billion in 2025, progressing at a CAGR of 35.59%, for the duration spanning 2021-2025.

Factors such as rising utilization of robots for surgical and rehabilitation procedures, growing potential of AI-based tools for elderly care, surging investment in AI deals in healthcare and rising adoption of wearable devices are driving growth.

However, the market growth would be challenged by reluctance among medical practitioners regarding the adoption of AI-based technologies and concerns regarding data privacy. The market is anticipated to experience certain trends like shortage of skilled workforce, upsurge in demand for personalized medicine and rising number of cross-industry partnerships and collaborations.

The global AI in healthcare market can be segmented on the basis of component, application and end-user. Based on component, the market can be bifurcated into software solutions, hardware and services. According to application, the market can be categorized into clinical trials, robot assisted surgery, connected machines, fraud detection, virtual assistants, administrative workflow assistants, diagnosis, dosage error reduction, cybersecurity and others. Whereas, depending on end-users, the market can broadly be split into hospitals & healthcare providers, pharmaceutical & biotechnology companies, patients, healthcare payers and others.

The fastest growing regional market is North America due to surging adoption of machine learning in the medical sector leading to the growth of AI in the healthcare market in countries like the U.S. and Canada and increasing government initiatives to adopt digital platforms in healthcare industry and sector. Further, the COVID-19 outbreak has significantly promoted the implementation of remote health check-ups using digital tools, which positively impacted the market growth.

Market Dynamics

Growth Drivers

Key Trends and Developments

Challenges

Scope of the report

Key Topics Covered:

Market Overview

Impact of COVID-19

Market Analysis

Regional Market

Competitive Landscape

Company Profiles

For more information about this report visit https://www.researchandmarkets.com/r/9qkufe

About ResearchAndMarkets.comResearchAndMarkets.com is the world's leading source for international market research reports and market data. We provide you with the latest data on international and regional markets, key industries, the top companies, new products and the latest trends.

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The Role of AI in the Global Healthcare Market 2021: Rising - GlobeNewswire

Zindi is all about using AI to solve real-world problems for companies and individuals. And the South Africa-based crowd-solving startup has done that over the last three years they have been in existence.

Just last year a team of data scientists under Zindi used machine learning to improve air quality monitoring in Kampala as another group helped Zimnat, an insurance company in Zimbabwe, predict customer behavior especially on who was likely to leave and the possible interventions that would make them stay. Zimnat was able to retain its customers by offering custom-made services to those who would have otherwise discontinued.

These are some of the solutions that have been realized to counter the data-centered challenges that companies, NGOs and government institutions submit to Zindi.

Zindi announces these challenges and invites its community of data scientists to take part in solution-finding competitions. Participating data scientists submit their solutions and the winner gets a cash prize. The hosts of the competitions get to use the best results to overcome the challenge they had like in an air quality monitoring project by AirQo, which sought solutions for forecasting air pollution across Uganda, and in helping Zimnat cut its losses.

So AirQo now has a dashboard that allows the public to check air quality and air quality forecasts. One of the exciting things about this project is that AirQo hired two of the winners from the challenge to help with the implementation of the project, said Zindi co-founder and CEO, Celina Lee. South African Megan Yates and Ghanaian Ekow Duker are the platforms other co-founders.

AirQo also raised funding from Google, based on the solution that they built, and theyll now be replicating it in other African countries, said Lee about the competition that was organised in partnership with the Digital Air Quality East Africa (DAQ EA) project of the University of Birmingham and the AirQo project from Makerere University, Kampala.

Zindi is a database of data scientists across Africa. The crowd-solving startup recently secured $1 million in seed funding. Photo Credits: Zindi

Among other notable private and public organizations that have tapped Zindi include Microsoft, IBM, Liquid Telecom and UNICEF, and the government of South Africa.

So far, Lee is excited about what Zindi has achieved and is enthusiastic about the communitys future, given how the crowd-solving startup has grown since launch. The platform is now providing alternatives and stepping up competition against traditional consulting firms operating across Africa, which are often expensive.

Zindis users have grown three-fold from the start of last year, to 33,000 data scientists from 45 countries across the continent. It has also paid data scientists $300,000 in prize money.

This number is set to grow as it hosts the third inter-university Umoja Hack Africa challenge in March next year, where college students will compete against one another for different solutions.

Zindi is using the inter-university competition to expose students to practical data science experiences and to solve real-life challenges using AI. During last years event the platform attracted about 2,000 students during the event that took place virtually because of the pandemic.

Students get to build their first machine learning models, and from there, it opens up all kinds of doors for their careers and education, said Lee, who is originally from San Francisco.

Zindi currently has a jobs portal to shorten the path from learning to earning. The talent placement portal allows organizations to tap from its pool of talent by posting openings.

The crowd-solving platform is also planning to introduce a learning component that provides training material to budding data scientists; this is after it realized a knowledge gap and need for training. Besides, Lee said that most of Zindis users are university students in need of learning experience, and who require enhanced skills to solve world problems.

The new plans will be made possible by a $1 million seed funding the platform recently secured.

Image Credits: Zindi

Lee said, For us, its really about scaling the community and creating more value for all of our data scientists.

So were going to be using the funding to introduce much more learning content, because one of the things we understand is that, especially in Africa, data science is such a new field. And a lot of our data scientists are still university students or very early in their careers. And theyre just looking for a chance to learn and build their skills.

The seed round was led by San-Francisco based VC firm Shakti, with participation from Launch Africa, Founders Factory Africa and FIVE35.

All these plans are toward building a strong data science community in Africa and for the continent, according to Lee, who said that they want to grow their users to reach one million in the near future. This, she said, will be achieved by opening up training opportunities to early career data scientists and by forming a strong community that encourages collaboration and mentorship.

Lee said, And so where we want to eventually reach a million data scientists in Africa we want to make data science something that any young person whos interested in pursuing this career has access to the tools, the connections and the experience that they need to make a successful career in this field.

Our vision is to make AI accessible to everyone.

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South African crowd-solving startup Zindi building a community of data scientists and using AI to solve real-world problems - TechCrunch

When offstage, Kra Mr, as well as other Sensorium's AI-driven artists, will be permanently available to communicate with fans via text chats and video calls in Sensorium Galaxy mobile app.

Sensorium virtual artists have been in development since last November. While Mubert's proprietary technology empowered these creatures to generate a constant flow of ever-changing music, Sensorium has equipped them with virtual bodies, intelligence, and social skills.

Driven by a unique combination of genetic AI and reinforcement learning, Sensorium's virtual DJs are able to support unscripted thought-provoking conversations. They can talk for hours without losing track of context and possess both long-term and short-term memory. What's more, the personalities of these virtual beings constantly evolve through interactions with users. This process unfolds naturally and unpredictably without any interference from developers.

"Increasingly more creators embrace direct communications with their fans via live streams on Instagram and other channels. We take this a step further by allowing fans to dive deeper into the interactions with their favorite artists. AI-driven Social Artists are able to dedicate quality time to every single fan, listening, responding, and adapting to their individual preferences, thereby ushering in a new era in music," says Sasha Tityanko, Deputy CEO at Sensorium.

Each one of Sensorium's Social Artists has its own signature performance style and a distinct personality based on a virtual biography. Kra Mr, for instance, is a non-binary AI-researcher and techno DJ from Berlin, bringing their fascination for AI to all musical productions. The name of their first album "Anthropic principle" reflects the main concept behind it, alluding to the idea that the universe needs an observer to exist. In their music Kra Mr reinterprets this principle from a VR perspective, raising the question "what if an AI is an observer of the metaverse?".

In a suite of 8 pieces, Kra Mr weaves a canvas out of abstract questions. The restless artificial mind keeps on asking what do you, people, feel listening to my music? You created me, but now I am able to initiate research about you. It is an experiment on humanity by AI.

Paul Zgordan, Music Director at Mubert: "Mubert was responsible for creating a unique musical experience. We fulfilled one of our main tasks: nurturing a connection between the crowd and the DJ, so the artist's performance corresponds to the audience's mood on the dancefloor. Now we are excited to experiment and improve our product further using DJs-users interactions in the metaverse as an inspiration".

Fans will soon be able to experience Kra Mr's performances live in PRISM one of Sensorium Galaxy's virtual worlds dedicated to extraordinary music events. Sensorium Galaxy is scheduled to go live in several months, while the Sensorium appis already available for download.

About Sensorium Galaxy

Sensorium Galaxy is a digital metaverse that revolutionizes the way people interact with each other and experience the arts. In the alternate universe of Sensorium Galaxy, users immerse themselves in exciting new worlds to get together with their loved ones, meet new people, and participate in unique virtual activities.

The Galaxy is being built in partnership with world-known artists, producers, and entertainment companies. Among them are Jay-Z's Roc Nation and Yann Pissenem, the creator of the world-leading nightlife hubs Ushuaa Ibiza and H Ibiza.

Website: https://sensoriumgalaxy.com/

About Mubert:

Mubert is a platform powered by music producers that helps creators and brands generate unlimited royalty-free music with the help of AI. Mubert's mission is to empower and protect the creators. Our purpose is to democratize the Creator Economy.

Website:https://mubert.com

SOURCE Sensorium Corporation

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Kra Mr becomes the first Social AI-Driven Artist to release an album - PRNewswire