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What are the benefits of Artificial Intelligence in Government? – Entrepreneur

June28, 20216 min read

Opinions expressed by Entrepreneur contributors are their own.

The continuous progress of technology has led to different government organizations having to modify their structures, as well as the way in which they execute their processes.

Nowadays, applying tools such as Artificial Intelligence (AI ) in government is essential, since AI makes all operations more efficient , allows citizens to listen better, have greater sensitivity about what they are asking for, what they need, and know the general feeling you have.

In other words, it can be said that Artificial Intelligence is an extraordinary content source for the public sector and, above all, it is a great value .

Many developed and developing countries are already implementing AI in different activities within the Public Administration. An example of this is what the Government of Finland is doing, which is conducting tests with what is considered, so far, the most ambitious public assistant based on Artificial Intelligence in the world: AuroraAI .

The objective of this program is to offer citizens personalized services, and filter them according to the specific needs of each person at different times in their lives. Likewise, work is being done to integrate public and business services into a single platform. For example, if AuroraAI detects that a citizen wants to change jobs, it would offer them jobs that match their profile, both in the public and private sectors.

According to Christian Pealoza , doctor in Cognitive Neuroscience, there are three categories into which the main current benefits of Artificial Intelligence in government can be grouped. These are:

Even so, if we have to analyze the exploitation of Artificial Intelligence by government sectors in Latin America, we must emphasize that for many of them the use of AI is still at a very early stage, so they have a long way to go. go through and many technological challenges to face.

The governments already have a part of the road traveled, they are not completely at zero. Most, for example, already have a demographic database. However, there is still much to refine to make certain public policy decisions, says John Salazar , commercial director of Forest Rim Technology for Latin America.

AI in LatAm governments has a long way to go and many technological challenges to face / Image: Depositphotos.com

It should be noted that the application of Artificial Intelligence revolves around techniques such as machine learning and deep learning, artificial vision, voice recognition and robotics . When these are implemented, they become real and tangible benefits for the government . The best? This technology makes results are obtained faster, thus also saving time and avoiding tedious tasks.

At this point, it is essential to emphasize that for AI to work in any organization, it is essential to have the right data , as well as to ensure its accuracy and to label it appropriately for learning.

That is why, first of all, Governments must have the ability to control the data cycle, which consists of collecting data, generating data, storing it, sharing it and, finally, knowing how to use it.

The most important thing is that governments take this data and, with that information, begin to generate policies and public development plans. Because we realize that many governments, especially those in Latin America, do not use data to make decisions and, therefore, do not generate trust or value in citizens , emphasizes Salazar.

Specifically, the Government of Mexico needs to realize how to use and exploit this data, something that is already happening in the United States in a greater way. As an example, the United States Citizenship and Immigration Services (USCIS) uses a virtual assistant, generated by a computer called Emma , to answer questions and direct people to the correct area of the website.

In short, we can see that currently there are many governments that need to exploit the documentation they have. They need to take advantage of all that data to make better decisions and achieve better results.

What's more, data should be the mainstay of current public policies since, as mentioned above, they generate enormous value .

For all this, it is key to continue working so that, day by day, governments are integrating and adopting this technology, so that they develop this culture of working with data, structuring it and managing it, in order to do something that is efficient and productive for the citizenship.

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KPMG Automates, Accelerates and Enhances Artificial Intelligence Workflows with Red Hat OpenShift – Business Wire

RALEIGH, N.C. & NEW YORK--(BUSINESS WIRE)--Red Hat and KPMG LLP today announced an ongoing collaboration to augment the KPMG Ignite AI platform with Red Hat OpenShift as a foundational technology. Building on Red Hat OpenShift, KPMG Ignite provides the agility, scalability and flexibility needed to deploy AI at scale, and enables Ignite to be deployed more consistently across the hybrid cloud.

According to the KPMG recent AI study, Thriving in an AI World, the rate of AI adoption skyrocketed in many industries because of COVID-19, but many leaders feel this uptick is moving too quickly. The study indicates however, that organizations who prioritize AI in their operations can better know and serve their customers, automate repetitive operations, better inform business strategy and drive greater innovation. To capitalize on these benefits, many of KPMG clients as well as KPMG itself seek to embed AI through multiple IT functions into their overall organizational technology fabric providing better management and analysis of their AI data.

To help meet this need, KPMG offers the Ignite AI platform. Ignite is a U.S.-patented portfolio of AI capabilities that brings together machine learning, document ingestion and optical character recognition capabilities to help analyze and decipher both structured and unstructured data. Ignite focuses on automating, accelerating and enhancing existing AI solutions so organizations can achieve real value from data to make better business decisions across an entire organization.

KPMG chose Red Hat OpenShift as an enabler of AI across a broad set of modern footprints, providing more flexibility for clients to work across the hybrid cloud, from private clouds to multiple public cloud environments. As the underlying Kubernetes platform, Red Hat OpenShift is a key element for Ignite, based on its ability to provide greater agility, flexibility, portability and scalability for nearly any AI workload in almost every enterprise IT deployment. OpenShift also provides security features and application controls, along with robust, native continuous integration and continuous deployment (CI/CD) capabilities, helping to more quickly operationalize AI capabilities into production with greater security.

This flexibility is necessary to more rapidly develop, deploy and run machine learning (ML) models and associated intelligent applications in production while mitigating risk of being locked into a single cloud provider or hardware stack. Additionally, with the foundation of Red Hat OpenShift, data scientists using the platform can focus on ML modeling and deployment without having to act as IT operations teams or systems administrators.

KPMG has also formed a strategic alliance with Red Hat to provide and enhance these hybrid multi-cloud experiences for clients, bringing greater choice, control and freedom of open source to fuel digital acceleration. This innovative technology approach affords organizations the flexibility of working with and across several of its cloud alliance partners.

Supporting Quotes

Joe Fernandes, vice president and general manager, Cloud Platforms, Red HatAI solutions are changing the way we do business, enabling organizations to better serve their customers and get more done quicker but they must be built on a hybrid cloud platform that can help deliver stable, production-ready innovation. With Red Hat OpenShift, KPMG Ignite has a hybrid cloud platform with the flexibility and scalability required to accelerate AI/ML initiatives from pilot to production, helping advance their clients' digital transformation initiatives.

Kevin Martelli, principal, software engineering, KPMG LLPWhen determining the underlying technology platforms for Ignite, we needed technology that was flexible and easy-to-use that offers enterprise-grade security across a hybrid cloud. With Red Hat OpenShift, containers and Kubernetes are at the center of Ignite, providing data scientists and developers the much-needed agility, flexibility, consistency, portability, and scalability to train, test, and deploy machine learning models anywhere.

Additional Resources

Connect with Red Hat

About Red Hat, Inc.

Red Hat is the worlds leading provider of enterprise open source software solutions, using a community-powered approach to deliver reliable and high-performing Linux, hybrid cloud, container, and Kubernetes technologies. Red Hat helps customers integrate new and existing IT applications, develop cloud-native applications, standardize on our industry-leading operating system, and automate, secure, and manage complex environments. Award-winning support, training, and consulting services make Red Hat a trusted adviser to the Fortune 500. As a strategic partner to cloud providers, system integrators, application vendors, customers, and open source communities, Red Hat can help organizations prepare for the digital future.

Forward-Looking Statements

Certain statements contained in this press release may constitute "forward-looking statements" within the meaning of the Private Securities Litigation Reform Act of 1995. Forward-looking statements provide current expectations of future events based on certain assumptions and include any statement that does not directly relate to any historical or current fact. Actual results may differ materially from those indicated by such forward-looking statements. The forward-looking statements included in this press release represent the Company's views as of the date of this press release and these views could change. However, while the Company or its parent International Business Machines Corporation (NYSE:IBM) may elect to update these forward-looking statements at some point in the future, the Company specifically disclaims any obligation to do so. These forward-looking statements should not be relied upon as representing the Company's views as of any date subsequent to the date of this press release.

Red Hat, the Red Hat logo and OpenShift are trademarks or registered trademarks of Red Hat, Inc. or its subsidiaries in the U.S. and other countries.

About KPMG LLP

KPMG LLP is the U.S. firm of the KPMG global organization of independent professional services firms providing audit, tax and advisory services. The KPMG global organization operates in 146 countries and territories and has close to 227,000 people working in member firms around the world. Each KPMG firm is a legally distinct and separate entity and describes itself as such. KPMG International Limited is a private English company limited by guarantee. KPMG International Limited and its related entities do not provide services to clients. Some or all of the services described herein may not be permissible for KPMG audit clients and their affiliates or related entities.

KPMG is widely recognized for being a great place to work and build a career. Our people share a sense of purpose in the work we do, and a strong commitment to community service, inclusion and diversity, and eradicating childhood illiteracy. Learn more at http://www.kpmg.com/us.

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GitHub and OpenAI release Copilot, an artificial intelligence tool to automatically complete code snippets based on the OpenAI Codex neural network…

GitHub, owned by Microsoft, and OpenAI, Inc. have launched a technology preview of a new artificial intelligence tool called Copilot. It became part of the popular source editor Visual Studio Code and is designed to automatically complete code snippets. That is, yes, the developers got into the regiment of intellectual assistants.

According to GitHub, Copilot doesnt take snippets of source code its seen before and almost copied it. Instead, the system analyzes the written code and generates new appropriate code, including individual functions that were previously used. Examples on the projects website include autowriting code for importing tweets, plotting a scatter plot, or getting a Goodreads rating.

GitHub sees the development as an evolutionary development of the concept of pair programming the two work together on a project to effectively catch each others bugs in order to speed up the process. In Copilot, one of the programmers is the virtual assistant.

Copilot is built on a new algorithm called the OpenAI Codex, which CTO Greg Brockman at OpenAI called a descendant of GPT-3, a popular neural network model capable of creating text that is sometimes indistinguishable from human-typed text. The system was trained using terabytes of open source code from GitHub, as well as samples of English scripts. And if GPT-3 generates texts in English, then OpenAI Codex generates code. Copilot works best with Python, JavaScript, TypeScript, Ruby and Go, according to GitHub CEO and Xamarin IDE founder Nat Friedman.

In fact, this is the first major product since Microsoft invested $1 billion in developing OpenAI. It will initially be available as a browser and Visual Studio Code plugin, but the OpenAI API will be released in August 2021 so that third-party developers can take advantage of Codex in their applications.

So far, Copilot is in a limited technical beta, but those who wish can register on the projects website to access it.

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GitHub and OpenAI release Copilot, an artificial intelligence tool to automatically complete code snippets based on the OpenAI Codex neural network...

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p3rceive Announces Integration of Natural Language Generation Into Its Artificial Intelligence Stack – Business Wire

CHICAGO--(BUSINESS WIRE)--p3rceive (p3), the innovative sales capacity planning tool that offers users a dynamic, multi-variable, probability-based model of future sales, today announced the introduction of natural language generation capabilities into its artificial intelligence stack. p3 is now the first platform to generate human readable text from the analytics generated through its sales capacity planning tool.

p3erceive is now able to turn its numbers and charts into executable insights by creating a usable executive summary from the 10,000 probable outcomes for each change in a sales variable generated by p3s powerful Bayesian statistical math engine.

Analytics in isolation can be difficult to interpret. For an executive to make the best possible decision, a reporting stack needs to be fully understandable, said Kurt Johnson, Founder of p3rceive and Co-founder of 11.2 Ventures (www.11-2ventures.com). p3rceive uses artificial intelligence to solve this issue by giving consumers the answer in a story format.

Dmitry Valbe, Co-founder and CTO of 11.2 Ventures, and former Head of Data Science and Client Analytics at Nuveen Investments, commented, Its important for executive teams to be on the same page regarding their sales operations and to be able to quickly make decisions and implement their growth strategies. Simplifying the transition from mathematics to actions is what the company set out to accomplish with p3s new features.

p3rceive is one of the first companies generated by 11.2 Ventures, LLC, the Chicago-based venture builder studio (VBS). The VBS model was developed to improve the success rate of early-stage startups by seeding, growing, and launching its own companies in-house. Drawing on the expertise of its management team and executive board, 11.2 Ventures was engineered to overcome each of the major causes behind the dismal tech startup failure rateincluding poor market fit and ineffective leadership teams. p3rceive is the result of 11.2s co-founders combined market expertise, collaborative leadership, and focused management.

About p3rceive

p3rceive is a sales capacity planning tool that offers its users a dynamic, multi-variable, probability-based model of future saleswhile also identifying the specific allocation of resources needed to get there. Tying a companys sales revenue range to its unique inputsnot just sales hours but also the legal teams time; not just production but also distributionp3rceive instantly maps out 10,000 probable outcomes for each change in a sales variable and gives the probability that the desired outcome will be reached. Harnessing Bayesian statistics and powerful math, this software allows sales executives and the C-suite to calibrate resources with certainty rather than intuition, making p3rceive the first software to accurately modeland optimize forgrowth. For more, please visit https://p3rceive.com.

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Artificial Intelligence Startup LLENA (AI) Health Solutions Inc. tackles food deserts, partners with Southern University to support (USDA/NIFA)…

SAN MATEO, Calif., June 28, 2021 /PRNewswire/ --LLENA (AI) Health Solutions Inc. today announced apartnership with Southern University in Baton Rouge, Louisianato support their "Center of Excellence for Nutrition, Health, Wellness, and Quality of Life" initiative to address diet-related health disparities in African Americans by increasing the capacities of 1890 institutions through nutrition research, teaching and extension.The Southern University Agricultural Research and Extension Center is one ofthe 1890 Centers of Excellence grantrecipients to receive funding from the U.S. Department ofAgriculture's National Institute of Food and Agriculture(USDA/NIFA). The 1890 Universities Foundation mobilizes and manages resources to facilitate broad based programs, initiatives and approaches across the 1890 universities system.

LLENA (AI) will provide artificial intelligence insights & targeted research in the areas of food insecurity, food deserts and COVID-19 in underserved and local communities under the direct leadership of Dr. Fatemeh Malekian, Professor of Food Science, Project Director and Director of the Southern Institute for Food, Nutrition, and Wellness at the SU Ag Center.LLENA (AI) will leverage its proprietary Artificial Intelligence (AI) that creates an individualized GI (glycemic index) value meal based on blood sugar, blood pressure and other preferences. African Americans remain the least healthy ethnic group in the USA. Diet is a key contributor to disparities in many chronic diseases and conditions.

Southern University alumnaand LLENA (AI) CEOCharlotta Carter is excited to empower her community. "As an HBCU grad, we areexcited to work with SUAREC to bring needed AI Technology fighting chronic illness in underserved communities. Working with Dr. Fatemeh Malekian on this pilot program, delivering real COVID proofsolutions is an amazing opportunity to give back. A multi-state university collaboration featuring training, education, business skills and podcasts while leveraging LLENA (AI) technology is ahomerun in fighting food insecurity & food deserts. LLENA (AI) is the key interface (Hub) to allow the community easy access to the resources needed to manage a healthy lifestyle. Thisinnovative nutritional outreach program is a giant step to help eradicate type 2 diabetes!"

About:

Southern University Agricultural Research and Extension Center

Southern University Agricultural Research & Extension Center Linking Citizens of Louisiana with Opportunities for Success. The SUAREC provides service to the citizens of Louisiana in a manner that is useful in addressing their scientific, technological, social, economic and cultural needs in order to enhance their overall quality of life.

Visit:https://www.suagcenter.com/

LLENA (AI) Health Solutions Inc.

Learn to Love Eating Nutritiously Always, LLENA (AI) Health Solutions Inc. is a digital diabetes management platform with personalized recommendations powered by proprietary artificial intelligence.https://llenafood.life

LLENA (AI) certification helps clients reach locally targeted consumers who are ready to eat healthy:https://llenafood.life/restaurant-registration/

SOURCE LLENA (AI)

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Global Artificial Intelligence in Healthcare: Deals and Agreements by Leading Players From 2010-2021 – ResearchAndMarkets.com – Business Wire

DUBLIN--(BUSINESS WIRE)--The "Global Artificial Intelligence (AI) Partnering Terms and Agreements 2010 to 2021" report has been added to ResearchAndMarkets.com's offering.

The Global Artificial Intelligence (AI) Partnering Terms and Agreements 2010 to 2021 report provides an understanding and access to the artificial intelligence partnering deals and agreements entered into by the world's leading healthcare companies.

The Global Artificial Intelligence (AI) Partnering Terms and Agreements 2010 to 2021 report provides an understanding and access to the artificial intelligence partnering deals and agreements entered into by the world's leading healthcare companies.

The report provides a detailed understanding and analysis of how and why companies enter artificial intelligence partnering deals. The majority of deals are early development stage whereby the licensee obtains a right or an option right to license the licensor's artificial intelligence technology or product candidates. These deals tend to be multicomponent, starting with collaborative R&D, and commercialization of outcomes.

This report provides details of the latest artificial intelligence, oligonucletides including aptamers agreements announced in the healthcare sectors.

Understanding the flexibility of a prospective partner's negotiated deals terms provides critical insight into the negotiation process in terms of what you can expect to achieve during the negotiation of terms. Whilst many smaller companies will be seeking details of the payments clauses, the devil is in the detail in terms of how payments are triggered - contract documents provide this insight where press releases and databases do not.

For example, analyzing actual company deals and agreements allows assessment of the following:

The initial chapters of this report provide an orientation of artificial intelligence dealmaking and business activities. Chapter 1 provides an introduction to the report, whilst chapter 2 provides an overview of the trends in artificial intelligence dealmaking since 2010, including details of average headline, upfront, milestone and royalty terms.

Chapter 3 provides a review of the leading artificial intelligence deals since 2010. Deals are listed by headline value, signed by big pharma, most active artificial intelligence dealmaking companies. Where the deal has an agreement contract published at the SEC a link provides online access to the contract.

Chapter 4 provides a comprehensive listing of the top 25 most active companies in artificial intelligence dealmaking with a brief summary followed by a comprehensive listing of artificial intelligence deals, as well as contract documents available in the public domain. Where available, each deal title links via Weblink to an online version of the actual contract document, providing easy access to each contract document on demand.

Chapter 5 provides a comprehensive and detailed review of artificial intelligence partnering deals signed and announced since Jan 2010, where a contract document is available in the public domain. The chapter is organized by company A-Z, deal type (collaborative R&D, co-promotion, licensing, etc.), and specific therapy focus. Each deal title links via Weblink to an online version of the deal record and where available, the contract document, providing easy access to each contract document on demand.

Chapter 6 lists artificial intelligence deals by technology type.

Chapter 7 provides a comprehensive and detailed review of artificial intelligence partnering deals signed and announced since Jan 2010. The chapter is organized by specific artificial intelligence technology type in focus. Each deal title links via Weblink to an online version of the deal record and where available, the contract document, providing easy access to each contract document on demand.

In addition, a comprehensive appendix is provided organized by artificial intelligence partnering company A-Z, deal type definitions and artificial intelligence partnering agreements example. Each deal title links via Weblink to an online version of the deal record and where available, the contract document, providing easy access to each contract document on demand.

The report also includes numerous tables and figures that illustrate the trends and activities in artificial intelligence partnering and dealmaking since 2010.

In conclusion, this report provides everything a prospective dealmaker needs to know about partnering in the research, development and commercialization of artificial intelligence technologies and products.

Key Topics Covered:

Executive Summary

Chapter 1 - Introduction

Chapter 2 - Trends in artificial intelligence dealmaking

Chapter 3 - Leading artificial intelligence deals

Chapter 4 - Most active artificial intelligence dealmakers

Chapter 5 - Artificial intelligence contracts dealmaking directory

Chapter 6 - Artificial intelligence dealmaking by technology type

Chapter 7 - Partnering resource center

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

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The Global Artificial Intelligence-based Cybersecurity Market is expected to grow by $ 18.94 bn during 2021-2025, decelerating at a CAGR of over 22%…

Global Artificial Intelligence-based Cybersecurity Market 2021-2025 The analyst has been monitoring the artificial intelligence-based cybersecurity market and it is poised to grow by $ 18.

New York, June 30, 2021 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Global Artificial Intelligence-based Cybersecurity Market 2021-2025" - https://www.reportlinker.com/p05445291/?utm_source=GNW 94 bn during 2021-2025, decelerating at a CAGR of over 22% during the forecast period. Our report on artificial intelligence-based cybersecurity market provides a holistic analysis, market size and forecast, trends, growth drivers, and challenges, as well as vendor analysis covering around 25 vendors.The report offers an up-to-date analysis regarding the current global market scenario, latest trends and drivers, and the overall market environment. The market is driven by the increasing demand for cloud-based applications, regulatory compliance, and rapid increase in use of mobile and other connected devices. In addition, increasing demand for cloud-based applications is anticipated to boost the growth of the market as well.The artificial intelligence-based cybersecurity market analysis include end-user segment and geographic landscape.

The artificial intelligence-based cybersecurity market is segmented as below:By End-user BFSI Government ICT Healthcare Others

By Geography APAC North America Europe South America MEA

This study identifies the increased application of artificial intelligence (AI), deep learning (DL), and machine learning (ML) technologies as one of the prime reasons driving the artificial intelligence-based cybersecurity market growth during the next few years. Also, heavy investments in cybersecurity and rising adoption of chatbots to combat cyberattacks will lead to sizable demand in the market.

The analyst presents a detailed picture of the market by the way of study, synthesis, and summation of data from multiple sources by an analysis of key parameters. Our report on artificial intelligence-based cybersecurity market covers the following areas: Artificial intelligence-based cybersecurity market sizing Artificial intelligence-based cybersecurity market forecast Artificial intelligence-based cybersecurity market industry analysis

This robust vendor analysis is designed to help clients improve their market position, and in line with this, this report provides a detailed analysis of several leading artificial intelligence-based cybersecurity market vendors that include Amazon.com Inc., AO Kaspersky Lab, Broadcom Inc., Cisco Systems Inc., Dell Technologies Inc., Fortinet Inc., Hewlett Packard Enterprise Co., Intel Corp., International Business Machines Corp., and Check Point Software Technologies Ltd. Also, the artificial intelligence-based cybersecurity market analysis report includes information on upcoming trends and challenges that will influence market growth. This is to help companies strategize and leverage all forthcoming growth opportunities.The study was conducted using an objective combination of primary and secondary information including inputs from key participants in the industry. The report contains a comprehensive market and vendor landscape in addition to an analysis of the key vendors.

The analyst presents a detailed picture of the market by the way of study, synthesis, and summation of data from multiple sources by an analysis of key parameters such as profit, pricing, competition, and promotions. It presents various market facets by identifying the key industry influencers. The data presented is comprehensive, reliable, and a result of extensive research - both primary and secondary. Technavios market research reports provide a complete competitive landscape and an in-depth vendor selection methodology and analysis using qualitative and quantitative research to forecast the accurate market growth.Read the full report: https://www.reportlinker.com/p05445291/?utm_source=GNW

About ReportlinkerReportLinker is an award-winning market research solution. Reportlinker finds and organizes the latest industry data so you get all the market research you need - instantly, in one place.

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FlipHealth app uses Artificial Intelligence to give fast diagnosis – The New Indian Express

By Express News Service

HYDERABAD: The maxim health is wealth could not have rung truer in any other year than the pandemic year. With humanitys search to find ways to dodge the virus, newer tools are being developed to increase the accessibility of affordable healthcare.

A Hyderabad-based startup, FlipHealth, is trying to bridge the gap between doctors and patients with their app that takes the help of Artificial Intelligence (AI) to save consultation time. Talking to Express, the companys CEO, G Vishnu Kalyan Reddy, said: Its a platform to provide digital medical care with the help of Artificial Intelligence. We provide consultations on more than 18 specialities to people."

"Before a patient consults a doctor, our AI system, which can recognise more than 600 symptoms, makes an assessment report. The system diagnoses diseases with 98.6 percent accuracy and suggests possible diagnostic tests the patient might require. In the case of Covid-19, it can determine the risk the user faces. This report goes a long way in saving diagnosis and consultation time.

Talking about how they came up with the idea to build the product, the CEO added: Covid- 19 pandemic has exposed how broken our healthcare system is. By offering patients unlimited consultations at Rs 99 per month, we want to increase the accessibility of medical services in the country, especially in tier-1 and tier-2 cities. This is a revolutionary concept as doctor consultations cost at least Rs 500 in big cities, but we are inspired by what apps like Babylon Health and K Health did in the UK and the US respectively.

They helped those countries in tackling the pandemic and we thought that its high time that India too had such a model. The app has been downloaded 4,17,926 times till now, and we will be launching it in regional languages soon to expand our reach. The app, incubated at T-Hub, is the brainchild of G Vishnu Kalyan Reddy, S Sukhvinder Singh (COO) and Venkatesh G (CTO). They want to provide accessible and af fordable healthcare.

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Using Artificial Intelligence to Train Next Generation of Truckers – Trucks.com

Editors note:Written by John Carione, the vice president of marketing at IntelliShift, a fleet and safety management company.This is one in a series of periodic guest columns by industry thought leaders.

For most freight companies, the answer to the troublesome driver shortage lies in Gen Z younger individuals who have never yet sat behind the wheel of a cab. While regulatory measures have traditionally required certain age limits in commercial vehicle operation, Congress is currently reviewing a bill that would ease these rules. The DRIVE-Safe Act, a bipartisan bill, would allow individuals under the age of 21 to cross state lines through a two-step apprenticeship program, greatly increasing the pool of potential driving candidates when its needed the most.

Yet this change doesnt come without several concerns, key among them, experience and safety. Understandably, a first-time truck driver may not have the skill to maintain proper safety procedures the same way a 10-year veteran would. That puts a significant onus on fleets to find ways to support these drivers through technology, implementing systems like artificial intelligence (AI) and predictive analytics to offer guidance in real time and help new drivers develop their skills.

Here are some of the most impactful ways technology is reducing risk and helping new drivers hit the road:

In any industry, one of the most powerful ways to develop new talent is a system of coaching and mentorship. Under the auspices of a seasoned co-worker, a new employee can pick up tips and best practices to correct mistakes and develop positive habits. In the trucking world, its slightly more complicated as drivers make their journeys solo. Theres no wizened guide offering tips from the passenger seat.

As a result, more fleets are implementing video systems powered by AI. Via a combination of intelligent monitoring, G-force sensors and dual-facing video, this technology can detect and alert drivers to risky behaviors, identifying distractions as well as providing forward-collision warnings. Importantly, in the event an accident does occur, records of the event can ensure accuracy in terms of liability cases, and protect drivers and fleets from false claims.

Providing an in-cab system for new drivers can improve their driving skills and ultimately their safety metrics. It helps identify behaviors that might be acceptable in a personal vehicle capacity, but have the potential for risk when operating a commercial rig. Importantly, these solutions are tracked and rated over time, so new drivers get a sense of their own progress in skill development. Together, it creates a system of coaching that can prevent accidents and build strong drivers.

One of the foundational benefits of analytics is its ability to synthesize a tremendous amount of disparate information and glean key insights and learnings. From a fleet perspective, this could mean identifying consistent issues with certain truck technology or inefficient delivery routes. From a new driver perspective, however, it can revolutionize a fleets approach to early training and development an approach that only improves the longer it is implemented.

Consider, for example, a new class of drivers, each of whom is subjected to the standard training practices in accordance with company policy and industry regulation. When they finally start driving, fleet analytics can discover patterns in the mistakes new drivers are making. That offers companies insight into how they can improve training and development. It also can provide a roadmap for adjustments in hiring and onboarding drivers.

John Carione

Notably, this approach can only work if the data that informs analytics is flowing without disruption. If analytics arent fed correct data streams, the recommendations they provide are fundamentally flawed. Breaking down data siloes is a key consideration when leveraging analytics to help new drivers in the future.

The American Trucking Associations has long tracked the need for talent with its annual Driver Shortage Analysis. The trade group estimates the driver deficit will reach 160,000 by 2028. Implementing the DRIVE-Safe Act will go a long way in closing that gap, but the responsibility for training and protecting the next generation of drivers will ultimately fall on the fleets who hand them the keys.

It is vital then, given freights unmatched role in supporting economic growth across multiple industries, that this core demographic is given the necessary support to hit the road as quickly as possible without sacrificing important safety skills. Through the smart deployment of technology, new drivers can be empowered to ensure business needs are met and the roads remain safe and secure.

Trucks.comwelcomes divergent thoughts and opinions on transport technology and trucking industry issues. Use the comments section to cite yours. Qualified opinion leaders are welcome to offer suggestions for opinion columns. Contact info@trucks.com.

Trucks.com June 1, 2021

High Definition maps can help autonomous trucks better understand the road ahead, allowing self-driving rigs to anticipate, navigate and/or avoid tricky situations. But these benefits only accrue if HD maps have the right data and the right tools to stay up-to-date.

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Big whoop Critical Race Theory | News, Sports, Jobs – The Express – Lock Haven Express

Politicians are making a big whoop of critical race theory.

People might call me such a theorist judging by a seminar I just taught at Lock Haven University, but I would struggle to explain critical race theory.

I dont use the phrase myself.

If those politicians define it, they are probably not defining it well. It sounds like they just put a foggy label on something they dont like.

It might assuage our fear of the concept, however, if I explain some of the seminar I just taught. Seminars at Lock Haven, by the way, are upper level courses with open topics. It enables faculty to teach a subject without trudging through a convoluted bureaucracy. It makes the university nimbler.

I called my seminar Whiteness and White People.

White people are very important to understand in American society. Not only are there a lot of them, but they have power.

At the start, we wove ideas from two good books: The Wages of Whiteness and Black Rednecks and White Liberals. Look them up.

Slavery was worldwide and much older than our nation. The same philosophies from western civilization that led to American independence, however, also was the beginning of a long fight against that slavery.

The Founding Fathers of our nation wrestled with the contradictions between slavery and their freedom from Britain and they knew it could lead to civil war. The forefathers had foresight.

The Quakers ended slavery among themselves in 1776 not a coincidental date. And Britain ended slavery in 1808.

In North America, racism did not so much lead to slavery. Slavery led to how we constructed race and racism.

I will forgive you for freaking out over the term socially constructed. It has gotten some bad press from folks such as Tucker Carlson and Jordan Peterson, but it is rooted in old and sound Symbolic Interactionism. Centuries ago, the English saw the Irish as a different race and acted upon them as though they were. And that is how it happens. The Irish later became white.

You should look up that good book too, How the Irish Became White.

So to make ourselves OK with slavery in the free world, we worked on whiteness and blackness.

This was made worse by Irish immigration. That group was oppressed by the British and immigrated with few skills at a time when it was becoming difficult to own land or start a shop.

They could have seen themselves as also unfree and chosen to side with slaves.

Instead, they played up the racial differences and took whiteness like a paycheck. We often associate black faced minstrels with the Irish during the 19th century. Many stereotypes of blackness crystalized during this time.

We failed our ideals also after reconstruction when northerners did not have the political will of presidents Lincoln or Grant.

Grant created the department of justice to crush the Ku Klux Klan and it did.

The Klan was much larger 50 years later because by then nearly all European immigrants were claiming whiteness.

It was a short circuit to citizenship.

Damn Democrats.

Just a few decades ago, whiteness remained an emotional thing. It meant you were a good American without needing to do all the work of being a good American.

That was valuable.

Many whites obsessed about stereotyping blackness.

Watermelon is good to eat. Why did we snicker in my youth like Beavis and Butthead about blacks eating watermelon?

See there?

Whites are weird when you study them.

We read one of my favorite ethnographies by anthropologist John Hartigan called Racial Situations.

He studied three different groups of whites in Detroit. Whites are a minority there and their experiences give whiteness some clarity.

We learned that rednecky whites often appear racist when they are actually inclusive of others.

We learned that wealthier whites can be both colorblind and exclusive of others. Wealthier ones are a tad slicker.

Its complicated.

Our university library put it on the shelf.

Students appreciated looking closely at Amish culture or at how Germany embraced a black sociologist a few years before they murdered millions of Jews.

My students did not become anti-American.

They pointed out the spaces between who we say we are and who we are.

Such self-examination is a very American thing to do.

Greg Walker is professor and chair of Sociology, Anthropology and Geography at Lock Haven University. Those books are available in Stevenson Library at Lock Haven University.

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