Tag: technology

Retail news wrap

Retail News Wrap | Weekly Snippets 

✅ Urban Vyapari’s AI-powered POS software and devices are all set to take the future of the retail and restaurant business to the next level. https://www.ahmedabadmirror.com/urban-vyapari-launches-ai-powered-pos-software-and-devices-to-revolutionize-retail-and-restaurant-industries/81860175.html ✅ ShelfSet, an all-new innovation powered by AI tech is ready to make the retail and beverage distribution game easier for users. https://www.digitaljournal.com/business/shelfset-revolutionizing-retail-and-beverage-distribution-with-innovative-ai/article ✅ Kama Capital’s latest AI tech is here to empower smarter investments, data-driven strategies and unparalleled success in the dynamic retail trading market of the Middle East. https://www.financemagnates.com/forex/kama-capital-deploys-ai-to-enhance-retail-trading-in-the-middle-east/ ✅ Reliance Trends is powering it’s retail foorprint with a brand-new tech-enabled store. Expect personalised recommendations, interactive displays, and seamless checkouts in the days to come. https://www.indianretailer.com/article/technology-e-commerce/ecommerce/retail-india-news-how-titans-jewelry-biz-keeps-growing

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Banking & Finance News Wrap

Banking & Finance News Wrap | Weekly Snippets

✅ AI and machine learning join forces with financial crime programs to take security to new heights. It’s time to stay one step ahead of fraudsters and safeguard your assets. https://www.securitymagazine.com/articles/99596-ai-and-machine-learning-have-been-added-to-financial-crime-programs ✅ Emirates NBD and Microsoft are reshaping the banking industry, making it more seamless, secure, and customer-centric with the use of new age tech. https://ibsintelligence.com/ibsi-news/group-chief-operating-officer-emirates-nbd/ ✅ Mastercard’s latest AI-powered fraud risk solution is teaming up with nine UK banks to stay one step ahead of fraudsters.  https://www.fintechfutures.com/2023/07/nine-uk-banks-tap-mastercard-ai-to-fight-payment-fraud/ ✅ Elon Musk takes us on a journey into the uncharted territories of artificial intelligence with his new AI startup. Led by a team of handpicked experts, Elon’s AI startup holds the potential to transform various industries.  https://finance.yahoo.com/news/elon-musk-unveils-ai-startup-211512549.html

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Insurance News Wrap

Insurance News Wrap | Weekly Snippets

✅ ZhongAn has unveiled its groundbreaking roadmap for AI and AIGC integration into the insurance industry that aims at enhancing efficiency, accuracy, and customer experience.https://technode.global/prnasia/zhongan-unveils-roadmap-for-ai-and-aigc-integration-into-insurance-sector-at-waic2023/ ✅ Trufla and Goose Digital are joining forces to drive digital innovation in the brokerage industry. This partnership will equip brokers with cutting-edge technology and strategic expertise.https://www.insurancebusinessmag.com/ca/news/technology/trufla-partners-with-goose-digital-to-drive-digital-transformation-for-brokers-452048.aspx ✅ Corvus Insurance has unlocked a new era of underwriting excellence. With advanced algorithms and predictive analytics, the tech is streamlining operations, reducing risks, and empowering insurers with invaluable insights.https://fintech.global/2023/06/30/corvus-insurance-unveils-ai-driven-automation-features-for-enhanced-underwriting-efficiency/ ✅ Sedgwick is driving innovation in the insurance industry. From smart technology to real-time data analysis, they’re staying at the forefront of industry trends to provide their end users with the best coverage and service.https://www.asiainsurancereview.com/Magazine/ReadMagazineArticle/aid/47056/Sedgwick-adapts-through-technology-driven-solutions-as-claims-process-goes-through-seismic-transformation

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LIFE SCIENCE & PHARMA NEWS WWRAP

Life Science & Pharma News Wrap | Weekly Snippets

✅ NanoTemper Technologies launches a Biotinylated Target Labeling Kit that aims at transforming the way scientists in the pharma landscape approach challenging drug targets.https://ow.ly/Bon150P5YtC ✅ Nvidia is driving advancements for a healthier future in the pharma and healthcare landscape with Generative AI. https://ow.ly/STL850P5YtJ ✅ MeitY-nasscom CoE is all set to host an exclusive forum on the transformative power of AI in the healthcare domain.https://ow.ly/fmBH50P5YtE ✅ Scientists have developed an advanced genetic technology to combat malaria-spreading mosquitoes. This advancement brings us one step closer to eliminating malaria and saving millions of lives worldwide.https://ow.ly/GC4Y50P5YtF

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Transforming Banking Experiences with Generative AI

Transforming Banking Experiences with Generative AI

Digital transformation is the cornerstone of almost every industry today and banking is no exception. Generative AI and machine learning are technological innovations that are fast revamping the entire banking landscape in the recent scenario, redefining automation for financial services, personalisation and customer engagement and overall operations including risk management. Generative AI is a specialised category of AI (artificial intelligence) which helps in the generation of fresh ideas and content along with pattern-based solutions that are gleaned from pre-existing information. It is thus suitable for diverse applications throughout the banking sector. It can enable intelligent decision-making along with better risk management, fraud detection, and real-time decisions. Here is a deeper look at the same.   How is generative AI used in banking? Generative AI and machine learning can enable the analysis of huge volumes of data sets and then generate responses accordingly. Trends and patterns can be easily identified and the information leveraged to take informed decisions accordingly. Here are some of the core aspects worth noting in this regard:  Customer service with generative AI Customer engagement and service can be radically transformed with the help of generative AI. Here are some points worth noting:  Risk management with generative AI Generative AI will be a huge game-changer and harbinger of digital transformation in the near future. Chatbots and virtual assistants will steadily take over the customer support space with human resources focusing on more crucial duties. Loan processing and other duties will be streamlined and customer experiences will be more personalized and fulfilling. FAQs 1.How can banks effectively adopt generative AI technologies? Banks can adopt generative AI technologies for identifying potential frauds, managing risks, predicting future risks, and also automating customer evaluation including credit and financial history checks. Banks can also use these technologies for improving customer service and enabling higher personalization. 2.Are there any challenges or risks associated with implementing generative AI in banking? There are challenges like data privacy and the need to use synthetic data in the right manner for avoiding breaches and security hassles. Generative AI models may sometimes have higher complexity and interpretation may be tough in some cases. Maintaining transparency and adhering to legal/regulatory mechanisms are other challenges in this regard. 3.How can generative AI help banks make better financial decisions? Generative AI can enable banks to take better decisions through analyzing customer data and offering insights in real-time. Naturally, banks can take more accurate and informed decisions about sanctioning loans and other customer-facing aspects. 4.Can generative AI replace human bankers in the future? While generative AI will automate and streamline repetitive tasks in the future and possibly take care of customer communication and support, it will not be a full replacement for human beings. It will help in policy-building, decision-making, fraud detection, risk management, and personalization. However, human bankers will always be required for taking care of more crucial and complex tasks

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Blockchain beyond cryptocurrency

Blockchain beyond cryptocurrency

Blockchain has revolutionised new-age applications including cryptocurrency. But what are the applications of blockchain outside of cryptocurrency? We all know about the application of blockchain in cryptocurrency but what about its usage beyond this arena? Here’s looking at the possibilities. A simple guide to blockchain Blockchain is a distributed and shared ledger that enables decentralised control. A blockchain comprises blocks or units that are linked through chains. Every chain has encrypted data that is made up with data from the earlier block to build the entire network. Blockchains are available as both private and public ledgers and specific implementation procedures enable any party to take part while the others will require access and invitation rights. Some of the major rights of blockchain include provenance, encryption and immutability. There are no limits to the kinds of businesses and industries that may benefit from using blockchain technology. Applications of blockchain technologies Blockchain technology has diverse applications, right from digital identity and digital voting to use cases in the healthcare industry. Bitcoin is already expanding its presence throughout the global finance segment while smart contracts are also being used as replacements for escrow and also for managing digital identity. Public blockchains are already available, enabling any individual to participate while corporate blockchains leverage private ledgers, thereby restricting authorisation and access alike. Financial services are already considering the utilisation of blockchains with its immutability and security being favourable for meeting needs in both insurance and banking. Healthcare companies are already using them to store health data or records while open-source versions of databases are already enabling better access to patient data, thereby enabling superior coordination and communication. FAQs This technology enhances cybersecurity greatly with its core aspects of decentralisation, consensus and cryptography, thereby enabling higher transaction-based trust. Blockchain ensures security control at the highest level for ensuring data confidentiality. Encrypted data in the blockchain makes sure that threats are mitigated without hackers retrieving or reading information in a suitable manner. Digital identity is enabled immaculately by blockchain technology. It is a self-sovereign identity that cannot be altered and offers more security than conventional systems of identity. It can fully transform the manner in which identities are used for linking to various online services. Blockchain makes sure that this information can be easily traced, audited, and verified, in a matter of seconds. Individuals can curate their personal profiles and control the sharing of their data. Issuers can also verify credentials swiftly with these technologies. Digital voting is a procedure where voters can leverage a technology-centric process for voting, minus some of the conventional issues of the voting process. The blockchain-based system is fully decentralised and open, while ensuring higher protection of voters. Voter identity stays anonymous and there are decentralised nodes available for electronic voting in this system. Some of the inherent challenges to the implementation of blockchain beyond cryptocurrency include concerns regarding privacy and security. Some other issues include scalability, interoperability, security, consumption of energy and higher complexity levels.

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Exploring the potential of analytics in improving insurance claims processing and customer experience

Exploring The Potential Of Analytics In Improving Insurance claims processing and customer experience

Insurance claim processing is a tedious job, at least from a conventional perspective. At the same time, customer experience is another pain point for most insurers, not just with regard to claims processing and other procedures, but also several accompanying aspects. The digital evolution and transformation of insurers have led to several positives, including higher accuracy, efficiency, and speed for almost every division. Highly advanced predictive and data analytics enable insurance companies to take decisions driven majorly by data. AI has already empowered insurers with the necessary insights for discovering new opportunities, tackling threats, and ensuring better productivity at multiple levels. Data analytics has thoroughly transformed every aspect of the process, right from customer communication and engagement, to claims, applications, underwriting, and also pricing. With proper data visualisation and analytics, underwriting procedures are automated and made more accurate by insurance companies. They thus identify customer risks through advanced predictive modelling and other tools. At the same time, this enables fixing premiums or pricing for at-risk customers based on prevailing guidelines and slabs of the insurance company. The insurance industry has only scratched the surface of the vast analytics-driven possibilities for future progress and prosperity. Here is a closer look at how it enables improved claims processing and enhanced customer experiences in turn. Claims Processing & Other Aspects- How They Can Be Improved Data analytics can contribute greatly towards various aspects, right from fraud detection to smooth processing of claims. Here are some of them: Automated Claim Payments- Many insurance companies often require extensive inspections and assessments of damages for claims. This leads to longer wait times for customers and a drop in their satisfaction levels. Retention rates may also go down as a result. Data analytics and other AI tools can help in streamlining claim payments based on an accurate and speedy assessment of damages. Claim Development Modeling- Predictive modelling is what insurance companies can use for building a more accurate and automatic system for understanding how much any claim will eventually cost. This is necessary, since claim amounts may sometimes change from the initial filing till the complete payment. The prediction of the final claim is important since it has a direct impact on the company’s financial statements. Companies can view which policies get more customers and their segmentation, along with claim trends, and trending reasons for the same. Detecting Fraudulent Claims- Fraud detection is another area where insurance companies witness the benefits of deploying data analytics. These claims are expensive for companies and they do not often have resources for the investigation of each and every one. Accurate and effective predictive modelling can help in prioritising and identifying any fraudulent activity for action. Insurers will find the age group from where most frauds are reported. Insurance companies can accurately detect fraudulent activity and plug the gaps to minimise their losses, without hampering customer experiences through challenging claims which are innocent or genuine. Intelligent management of cases- Insurance claims processing becomes a breeze with automated and intelligent management of individual cases. Automated and digital customer claim management and journeys with AI and analytics help greatly in lowering manual processes and touch-points, while enabling higher satisfaction and retention with a quicker claims process. Better front and back-office processes- Data analytics and other AI tools can help greatly in transforming both front and back-office systems. These include calculation, underwriting, loss value estimation, reporting, verification of damage or repair estimates, invoicing, and so on. Better customer communication- AI can be used to fully automate customer communication throughout every stage of the claim process, thereby enhancing customer experience greatly. Hence, analytics can enhance the entire spectrum of processing claims and the whole customer journey/experience associated with it. AI can help in inferring claim possibilities including litigation, losses, fraud, and so on. Algorithms can also categorise or segment claims based on complexity and several important attributes. AI can also support the optimal handling of claims in several cases. Hence, it is fast becoming imperative for insurance companies globally today. FAQs How can analytics solutions help insurance companies detect and prevent fraud? Analytics solutions can help insurance companies identify fraudulent behaviour patterns and activities, narrow them down, and detect such transactions swiftly before or after completion. This helps insurance companies plug gaps and take swift action.  How does it improve customer experience? Analytics and big data have a huge role to play in enhancing customer experience through automated and timely communication, quicker processing of claims through automated verification and assessment, and also intelligent management of cases.  How do insurance companies protect customer data collected by IoT devices? Insurance companies take several measures to safeguard data gathered from IoT devices. These include encryption of data and there are several types that companies may pick from. Insurers also emphasise proper data storage and governance under applicable regulations.  What is the potential impact of analytics on insurance premiums and pricing? Analytics has a profound impact on pricing and premiums. It helps insurance companies estimate customer risks and then automate premium/pricing calculations accordingly. Data is analysed from several sources in order to gather insights on segment-wise risks and the best possible pricing for the same, keeping the policy type and other aspects in mind.

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The role of telehealth in the modern healthcare landscape

The Role Of Telehealth In The Modern Healthcare Landscape

Telehealth is contributing immensely towards reshaping the entire contemporary healthcare landscape, as we know it. Telehealth meaning is the provision of remote healthcare via telecommunications and other technologies. It can be called a form of virtual care or digital healthcare.  The term gained traction throughout the 1980s and ever since, the sector has expanded considerably, including many new technologies and devices for the transmission of medical data on a real-time basis worldwide. This has enabled the entire healthcare industry to provide services to those under-served or un-served. It is also being deployed now by both private and public providers of healthcare services, with goals including efficient emergency care, treating mental illness, enhancing long-term outcomes for patients, and more. The indispensable functions of telehealth in the healthcare sector  Telehealth is steadily becoming indispensable for the modern healthcare industry, especially with regard to expanding the scope and accessibility of healthcare for more people. Here are some of its vital functions-  Better Multi-Area Expertise- Telehealth enables superior expertise in almost all departments. The usage of medical devices for tracking patient health remotely has naturally ensured higher convenience for providers and patients alike. Telemedicine is thus supplementing in-person or regular visitors to doctors, enabling the creation of more intensive plans for treatments. It may also ensure extra care that would be unavailable otherwise.  Telehealth solutions have ushered in expertise across multiple areas. For instance, a community or group without access to a cardiac care specialist may remotely get the same in case of any requirement. It will not fully do away with visits to the doctor but rather work in tandem with the same for treatment cycles. Healthcare providers and doctors will be able to better monitor and track patients within these cycles while keeping them on track with their treatments. Practitioners will also get access to invaluable data for supporting treatments.  Helping Underserved Patients- Telemedicine consultations have revolutionized access to healthcare for underserved patients. The biggest advantage of telehealth is its capability of ensuring instant access to healthcare, which would have been impossible otherwise. Many communities are under-served or un-served altogether.  Telehealth creates the interface between patients and healthcare providers, ensuring that suitable advice is given along with ensuring health tracking and more specializations that patients would not otherwise obtain. Communities grappling with emergencies or natural disasters can also use telehealth for additional access to critical care solutions. It has already transformed emergency care in recent years.  Ensuring Affordable Solutions for Patients- Telehealth is not just affordable, but it makes things more convenient for patients. Many health insurers are now offering reimbursements for telehealth in tandem with Medicare solutions. Patients are now seeing it as a more affordable way to get healthcare access. Wearables are also contributing towards better health tracking, data gathering, and also evaluating chronic ailments, thereby reducing future costs of patients.  Revolutionizing Mental Healthcare Access- Mental healthcare is one of the biggest segments benefiting from easy access to telemedicine, with easy tracking, access to practitioners and experts, quick consultations, community access, prescriptions, therapy sessions, and more.  How Telehealth will look in the Future Telehealth will evolve greatly in the near future as per expectations. Here are some of the key points worth noting in this regard.  Telemedicine will eventually turn into a standardized solution throughout multiple care-based settings. With patients getting more used to the higher access ensured by telemedicine consultations, it will naturally witness steady growth in the future. More than 1 billion telemedicine visits were reportedly in the works by the end of 2020 alone.  Patients will naturally appreciate personalized experiences, while endeavouring to choose their healthcare providers, platforms, providers/doctors, and hospitals, on the basis of telemedicine access and consultations. Patient wait times will slide hugely and patients will choose those health systems offering virtual care or digital healthcare access.  Healthcare players integrating telehealth will witness significant growth in patient retention and loyalty, along with scaling up their growth in revenues and business alike. More patients now seek telemedicine-based solutions.  Telemedicine could be a future beacon for preventive care. It will enable easy access to follow-up consultations, tracking, specialists, quicker diagnosis, and treatment guidance. Hence, there will be lesser readmissions in the hospital system along with inpatient stays and other issues. The costs will come down and preventive care will be the emphasis for most patients.  Hospital wait times will come down considerably, while there will be round-the-clock access to medical specialists. Hospitals will have speciality centres with networks of physicians and customers can get instant access to the same through telehealth platforms. These facilities will also ensure accessibility towards more focused care solutions for patients. It will go a long way towards greatly enhancing focused care and overall patient experiences along with lowering hiring costs for full-time staff members.  As can be seen, remote healthcare or telehealth is here to stay. And for good reason.  FAQs What is the meaning of telehealth, and how do they work? Telehealth means remote, virtual, or digital healthcare, including tracking, consultations, medical advice, treatment solutions, and diagnosis. This works through dedicated online or mobile platforms.  What are some potential challenges and limitations of telehealth? Challenges include proper internet connectivity, technological hesitation amongst a section of the under-served population globally, and so on.  How can telehealth be used to improve access to healthcare in underserved communities? Telehealth can be a godsend for better healthcare access in underserved communities. People can easily find specializations that they desire in emergencies and also for regular consultations and follow-up care. They can also avoid visits and long-distance travel to hospitals by consulting physicians/practitioners via digital or virtual platforms and getting all necessary medical care and advice.  What impact is telehealth having on the overall cost of healthcare? Telehealth has greatly lowered the overall cost of obtaining healthcare, considering that people no longer need to wait in line at hospitals and go for more expensive procedures or spend money on admissions. Preventive care and tracking are now readily possible via telehealth and this has lowered overall

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Hackathon Diaries #5 - Fraud Detection in Discharge Summary

Hackathon Diaries #5 – Fraud Detection in Discharge Summary

It’s time for the 5th edition of Hackathon Diaries. This time around, we are thrilled to present a project that is both timely and crucial – Fraud Detection in Discharge Summary. With healthcare fraud on the rise, there is a pressing need for innovative solutions that can identify and prevent fraudulent activities in the healthcare sector.  Our team of talented developers and data scientists have come together to tackle this challenge head-on and develop a system that can effectively detect fraudulent activities in discharge summaries. So, fasten your seatbelts and get ready for an exciting journey as we take you through our journey of building this game-changing solution. Fraud Detection in Discharge Summary Are you ready for a game-changer in the world of healthcare fraud detection? Our team of talented developers has come up with an innovative solution that will leave fraudsters shaking in their boots – the Fraud Detection in Discharge Summary project. By analysing a patient’s discharge summary, our system can quickly identify any suspicious or fraudulent activity and flag it for further investigation.  Say goodbye to financial losses due to fraudulent healthcare practices – our cutting-edge technology will help ensure that healthcare remains transparent and trustworthy for all.  The Team (Data Wizards) Arghya Chakraborty Anirban Bhattacharya Arindam Mukherjee Sourav Mukherjee Saurav Mandal Problem Statement Calling all healthcare warriors. Are you ready to take on one of the biggest problems facing insurance companies today? Providers falsifying or exaggerating hospital discharge summaries to receive higher reimbursement rates from insurers is costing them a fortune – and compromising the integrity of medical records. Besides financial Losses for insurance companies, the overall procedure consumes a good amount of time and also demands extensive levels of manual interventions. Proposed Solution The proposed solution is based on cutting-edge AI technology and is divided into two phases, each designed to accurately identify fraudulent activity and notify the relevant stakeholders. In Phase 1, the team developed an AI model that analyses contextual data and structural patterns within discharge summaries to identify any signs of fraud. This model is designed to identify inconsistencies and irregularities that may indicate fraudulent activity, and immediately notify the necessary parties to take action. Phase 1.1 focuses on the development phase, where the AI model will be trained to recognise and prevent fraud in handwritten discharge summaries. The implementation of AI-based content prevention techniques will be done to identify and flag any fraudulent activity. In Phase 2 (our future scope), the solution was taken to the next level by identifying discrepancies between discharge summaries and medical billings. The AI model is further trained on historic data to identify inconsistencies between provided discharge summaries and ideal discharge summaries. This would help identify fraudulent medical billing practices and notify the relevant stakeholders, helping to prevent further financial losses due to healthcare fraud. With this innovative solution, insurance organisations can rest assured that fraudulent activity in healthcare will be quickly and accurately identified to take appropriate actions to prevent further losses. Tech Stack Front-end: Django/Flask, HTML, CSS, and JS Back-end: Core Python, OCR, OpenCV, Database The Workflow How We Stand Out The solution is a first-of-its-kind that collects different fraud detection models under one umbrella, making it easier and more efficient. It boasts a blazing-fast processing time, taking an average of just 2.5 seconds per analysis. That means you can quickly identify and prevent fraudulent activity in real-time, without having to wait hours or days for results. Don’t settle for outdated and inefficient fraud detection methods – upgrade to our innovative solution today and take control of the fight against healthcare fraud.

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How the Large Language Models like GPT are revolutionising the AI space in all domains (BFSI, Pharma, and HealthCare)

How the Large Language Models like GPT are revolutionising the AI space in all domains (BFSI, Pharma, and HealthCare)

Large language models or LLMs are ushering in a widespread AI revolution throughout multiple business and industry domains. DALL-E-2 set the cat amongst the pigeons in the AI segment in July 2022, developed by OpenAI, before ChatGPT came into the picture. This has put the spotlight firmly on the invaluable role increasingly played by LLMs (large language models) across diverse sectors. Here’s examining the phenomenon in greater detail.  LLMs make a sizeable impact worldwide With natural language processing, machine learning, deep learning, and predictive analytics among other advanced tools, LLM neural networks are steadily widening the scope of impact of AI across the BFSI (banking, financial services, and insurance), pharma, healthcare, robotics, and gaming sectors among others.  Large language models are learning-based algorithms which can identify, summarise, predict, translate, and generate languages with the help of massive text-based datasets with negligible supervision and training. They are also taking care of varied tasks including answering queries, identifying and generating images, sounds, and text with accuracy, and also taking care of things like text-to-text, text-to-video, text-to-3D, and digital biology. LLMs are highly flexible while being able to successfully provide deep domain queries along with translating languages, understanding and summarising documents, writing text, and also computing various programs as per experts.  ChatGPT heralded a major shift in LLM usage since it works as a foundation of transformer neural networks and generative AI. It is now disrupting several enterprise applications simultaneously. These models are now combining scalable and easy architectures with AI hardware, customisable systems, frameworks, and automation with AI-based specialised infrastructure, making it possible to deploy and scale up the usage of LLMs throughout several mainstream enterprise and commercial applications via private and public clouds, and also through APIs.  How LLMs are disrupting sectors like healthcare, pharma, BFSI, and more Large language models are increasingly being hailed as massive disruptors throughout multiple sectors. Here are some aspects worth noting in this regard:  Pharma and Life Sciences:  Healthcare:  The impact of ChatGPT and other tools in healthcare becomes even more important when you consider how close to 1/3rd of adults in the U.S. alone, looking for medical advice online for self-diagnosis, with just 50% of them subsequently taking advice from physicians.  BFS:  Insurance:  The future should witness higher LLM adoption throughout varied business sectors. AI will be a never-ending blank canvas on which businesses will function more efficiently and smartly towards future growth and customer satisfaction alike. The practical value and potential of LLMs go far beyond image and text generation. They can be major new-gen disruptors in almost every space.  FAQs What are large language models? Large language models or LLMs are specialised language frameworks that have neural networks with multiple parameters that are trained on vast amounts of unlabelled text with the usage of self-supervised learning.  How are they limited and what are the challenges they encounter? LLMs have to be contextual and relevant to various industries, which necessitates better training. Personal data security risks, inconsistencies in accuracy, limited levels of controllability, and lack of proper training data are limitations and challenges that need to be overcome.  How cost-effective are the Large Language Models? While building an LLM does require sizeable costs, the end-savings for the organisation are considerable, right from saving costs on human resources and functions to automating diverse tasks.  What are some potential ethical concerns surrounding the use of large language models in various industries? Some concerns include data privacy, security, consent management, and so on. At the same time, there are concerns regarding these models replicating several stereotypes and biases since they are trained using vast datasets. This may lead to discriminatory or inaccurate results at times in their language. 

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