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Applications & Awareness in Technology

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Home/Science & Technology/Applications & Awareness in Technology/Page 51

Mains Answer Writing Latest Questions

Fareeha Nezam
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Fareeha NezamBegginer
Asked: July 20, 2024In: , , ,
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What types of data are essential for developing AI models in biotech?

artificial intelligencebiotechdataquestiontechnology
  1. Paras Dongre
    Paras Dongre Begginer

    In biotech, developing AI models requires a variety of essential data types to ensure accuracy and effectiveness. Here’s an overview: Genomic Data: DNA Sequences: Information about genetic makeup and variations. RNA Sequences: Data on gene expression levels. Proteomic Data: Protein Structures: DetaiRead more

    In biotech, developing AI models requires a variety of essential data types to ensure accuracy and effectiveness. Here’s an overview:

    Genomic Data:

    DNA Sequences: Information about genetic makeup and variations.

    RNA Sequences: Data on gene expression levels.

    Proteomic Data:

    Protein Structures: Details about protein shapes and interactions.

    Protein Expression: Quantitative data on protein levels in cells.

    Clinical Data:

    Electronic Health Records (EHRs): Patient histories, diagnoses, treatments, and outcomes.

    Clinical Trials: Data from experimental studies on drug efficacy and safety.

    Biomedical Imaging:

    MRI and CT Scans: Images for analyzing physiological and anatomical structures.

    Microscopy: High-resolution images for cellular and molecular analysis.

    Pharmacological Data:

    Drug Compounds: Information on chemical properties and interactions.

    Dosage and Efficacy: Data on drug response and side effects.

    Environmental and Lifestyle Data:

    Environmental Exposures: Information on factors like pollution or diet that affect health.

    Lifestyle Factors: Data on exercise, nutrition, and habits impacting health outcomes.

    Pathological Data:

    Biopsy Results: Tissue sample analysis for disease diagnosis.

    Histopathology Images: Images of tissue samples for detecting abnormalities.

    These data types are crucial for training AI models to identify patterns, predict outcomes, and assist in developing treatments and personalized medicine. Integrating diverse datasets enhances model robustness and applicability in real-world biotech applications.

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Sholanki Paul
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Sholanki PaulBegginer
Asked: September 3, 2024In:
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artificial intelligence
  1. Anita Dhruw
    Anita Dhruw Legend

    AI has its advantages as well as limitations have been identified and given below. Positive Aspects: 1. Efficiency and Productivity: Outsourcing of such tasks promise the possibility of processing huge amount of data within short span of time with better quantifiable performance in many disciplines.Read more

    AI has its advantages as well as limitations have been identified and given below.

    Positive Aspects:
    1. Efficiency and Productivity: Outsourcing of such tasks promise the possibility of processing huge amount of data within short span of time with better quantifiable performance in many disciplines.
    2. Enhanced Decision-Making: AI can work with huge chunks of information that can be useful for the organizations after the analysis is done.
    3. Personalization: AI allows customized feelings including the services of electronic business, streaming, and publicizing to suggest products depending on clients’ propensity.
    4. Inventing: The advanced inside developments such as in healthcare and autonomous vehicle and smart cities to mention some solutions from AI in solving complicated issues.
    5. 24/7 Availability: People get tired, but not AI. They are always employed; hence, a customer support has an operation throughout the day.
    Negative influences:
    1. Job displacement: AI could lead to job losses in certain sectors where machines replace human labor.
    2. Bias and Discrimination: The AI system is likely to perpetuate and even intensify the same biases in case biased data is fed into the learning process.     This means, for example, discrimination in employment and in police treatment of the populace.
    3. Privacy Issues: AI collection and monitoring of personal information may tend to cause serious privacy violations based on the principle that when information is collected for later use it may be misused or not protected as required.
    4. Over-reliance on technology: Using the AI systems cause a dependency that lowers the thinking and problem solving abilities within individuals and among organizations.
    5. Security risks: AI technologies should not be in the wrong hands that is why the developing of subversive materials like deep fakes or cyber attacks that endanger the security and people’s trust.

    Both these and the above mentioned negative aspects are inextricably linked to the proper definition of artificial intelligence and its further application.

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Team
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TeamSupreme
Asked: August 22, 2024In:
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Roadmap for Answer Writing 1. Introduction Overview of Biotechnology: Introduce biotechnology as the application of biological systems to develop products and solutions. Significance: Highlight its potential to uplift impoverished communities through advancements in various sectors. 2. Body A. Key Research and Development Achievements in Applied ...

upsc: bio-technology
  1. Team
    Best Answer
    Team Supreme

    Model Answer Introduction Biotechnology, the application of biological systems for product development, is a rapidly growing field in India. Its advancements have the potential to significantly uplift impoverished communities, particularly through breakthroughs in healthcare, agriculture, and enviroRead more

    Model Answer

    Introduction

    Biotechnology, the application of biological systems for product development, is a rapidly growing field in India. Its advancements have the potential to significantly uplift impoverished communities, particularly through breakthroughs in healthcare, agriculture, and environmental management.

    Body

    Healthcare Advancements

    Biotechnology has transformed healthcare with the development of affordable biosimilar drugs, reducing treatment costs. For instance, Biocon, an Indian biotech firm, has developed affordable insulin, making diabetes management more accessible for low-income patients.

    Disease Diagnostics

    Innovations like Molbio’s Truenat provide quick, accurate, and cost-effective diagnostics for diseases such as tuberculosis, which disproportionately affect economically disadvantaged populations.

    Agricultural Improvements

    Biotechnological innovations have led to genetically modified (GM) crops like Bt Cotton, enhancing yield and pest resistance. These advancements help poor farmers increase their productivity and income, contributing to food security.

    Soil and Water Conservation

    Biotechnology has enabled the development of drought-resistant and saline-tolerant crops, ensuring food security for marginalized farmers in water-scarce regions.

    Environmental Management

    Environmental sustainability is supported through bioremediation techniques. Engineered microbes are used to clean up oil spills, offering cost-effective solutions for pollution in impoverished areas.

    Biofertilizers and Biopesticides

    Biofertilizers, like Rhizobium for leguminous crops, reduce reliance on expensive chemical inputs, increasing yields and lowering costs for farmers.

    Nutrition Enhancement

    Biofortified crops, such as Golden Rice enriched with Vitamin A, can combat malnutrition prevalent in poorer sections of society.

    Waste Management

    Biotechnological innovations like bio-digesters convert organic waste into biogas, providing a low-cost energy source for poor households.

    Livestock and Aquaculture

    Biotechnology enhances livestock productivity through artificial insemination and improves aquaculture with disease management and faster-growing GM fish, providing income sources for poor communities.

    Conclusion

    Biotechnology has vast applications across healthcare, agriculture, and environmental management, offering significant opportunities to uplift poorer sections of society. By focusing on widespread implementation and access to these advancements, India can leverage biotechnology to reduce poverty and enhance quality of life.

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Anonymous
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Anonymous
Asked: July 16, 2024In:
  • 1

What are the main goals of NASA’s Artemis program?

  1. Sakshi Jadhav
    Sakshi Jadhav Begginer

    NASA’s Artemis program aims to return humans to the Moon and lay the groundwork for future manned missions to Mars. Initiated in 2017, the program's primary objectives include establishing a sustainable human presence on the Moon by the end of the decade and leveraging lunar exploration to prepare fRead more

    NASA’s Artemis program aims to return humans to the Moon and lay the groundwork for future manned missions to Mars. Initiated in 2017, the program’s primary objectives include establishing a sustainable human presence on the Moon by the end of the decade and leveraging lunar exploration to prepare for human missions to Mars. Artemis I, an uncrewed test flight, and Artemis II, the first crewed mission, serve as critical precursors to Artemis III, which will land astronauts on the lunar surface for the first time since 1972. One of the key goals of Artemis is to explore the lunar South Pole, an area rich in water ice, which can be used for life support and fuel production, thus enabling longer missions.

    The program also aims to develop new technologies, capabilities, and business approaches, fostering international partnerships and commercial opportunities. By establishing the Lunar Gateway, a space station orbiting the Moon, Artemis intends to create a staging point for deeper space exploration and research. This orbital platform will facilitate sustained lunar exploration, provide a habitat for astronauts, and serve as a hub for scientific investigations. Moreover, Artemis emphasizes inclusivity by planning to land the first woman and the next man on the Moon, inspiring a new generation of scientists, engineers, and explorers. Through Artemis, NASA seeks to expand human understanding of the Moon, utilize its resources, and demonstrate new technological advancements, ultimately paving the way for human exploration of Mars and beyond.

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Mohd Hashir
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Mohd HashirBegginer
Asked: July 20, 2024In:
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artificial intelligence
  1. Utkarsh Sinha
    Utkarsh Sinha Begginer

    AI and ML: A Double-Edged Sword for Cybersecurity Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing various industries, and cybersecurity is no exception. These technologies offer immense potential to enhance security measures, but they also pose new challenges. Benefits ofRead more

    AI and ML: A Double-Edged Sword for Cybersecurity

    Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing various industries, and cybersecurity is no exception. These technologies offer immense potential to enhance security measures, but they also pose new challenges.

    Benefits of AI and ML in Cybersecurity

    • Enhanced Threat Detection: AI and ML algorithms can analyze vast amounts of data to identify patterns indicative of malicious activity. They can detect threats that traditional security systems might miss, such as zero-day attacks and advanced persistent threats (APTs).
    • Improved Incident Response: AI-powered systems can automate routine tasks, allowing security teams to focus on critical issues. These systems can also analyze incident data to identify root causes and recommend remediation steps.
    • Predictive Analytics: By learning from past attacks and vulnerabilities, AI can predict potential threats and help organizations proactively protect their systems.
    • Automation of Repetitive Tasks: AI can automate tasks like vulnerability scanning, patch management, and log analysis, freeing up security teams to focus on strategic initiatives.

    Challenges of Integrating AI and ML in Cybersecurity

    • Data Quality and Privacy: AI models rely on high-quality data to function effectively. Organizations must ensure data privacy and security while gathering and processing necessary information.
    • Skill Gap: Implementing AI and ML requires specialized expertise. Many organizations may face challenges in finding and retaining skilled cybersecurity professionals with AI and ML knowledge.
    • Adversarial Attacks: Cybercriminals can also leverage AI to create more sophisticated attacks, such as adversarial machine learning, which can manipulate AI models to make incorrect decisions.
    • Explainability: AI models can be complex and difficult to understand. This lack of transparency can hinder trust and make it challenging to explain decisions made by the system.

    Integrating AI and ML into Cybersecurity Frameworks

    To effectively leverage AI and ML, organizations should consider the following steps:

    • Identify Critical Areas: Determine where AI and ML can provide the most significant impact, such as threat detection, incident response, or fraud prevention.
    • Data Preparation: Ensure high-quality, relevant data is available for training AI models.
    • Model Development and Testing: Collaborate with data scientists and cybersecurity experts to develop and test AI models rigorously.
    • Continuous Monitoring and Improvement: Monitor AI models’ performance and update them regularly to adapt to evolving threats.
    • Human-Machine Collaboration: Foster a collaborative environment between humans and AI, leveraging human expertise to complement AI capabilities.
    • Ethical Considerations: Develop guidelines for ethical AI use, including data privacy, bias mitigation, and transparency.
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Venu Gurija
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Venu GurijaBegginer
Asked: July 16, 2024In:
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What are the best practices for ensuring the privacy and security of data used in AI systems, especially in sensitive sectors like healthcare and education?

artificial intelligence
  1. KiruthikaArun kumar
    KiruthikaArun kumar Begginer

    A comprehensive approach that incorporates the below practices is needed. They are : Data Anonymization Remove personally identifiable information from datasets so individuals cannot be readily identified and apply data masking and tokenization. Encryption Encrypt data using encryption protocols (e.Read more

    A comprehensive approach that incorporates the below practices is needed. They are :

    1. Data Anonymization

    Remove personally identifiable information from datasets so individuals cannot be readily identified and apply data masking and tokenization.

    1. Encryption

    Encrypt data using encryption protocols (e.g., TLS/SSL) to protect it from unauthorized access.

    1. Access Control
    • Role-Based Access Control : Grant access based on user roles.
    • Least Privilege Principle: Ensure users have the minimum level of access.
    • Maintain Audit Logs
    1. Data Quality Management processes to maintain the accuracy, completeness, and consistency of data.
    2. Compliance with Legal and Regulatory Requirements
    • HIPAA (Health Insurance Portability and Accountability Act): For healthcare data, ensure compliance with HIPAA regulations regarding the protection of patient information.
    • FERPA (Family Educational Rights and Privacy Act): For educational data, comply with FERPA regulations that protect student privacy.
    1. Incorporate Security and Privacy-by-Design using privacy-preserving ML measures.
    2. Regular security Audits and privacy Risk Assessments
    3. Employee Training and awareness Programs about the latest threats.
    4. Incident Response Planning to address data and security breaches.

    The incident response plan is regularly tested through simulations and test drills.

    By implementing these best practices, they can ensure compliance and maintain the trust of their stakeholders.

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Shreeyash Patil
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Shreeyash PatilBegginer
Asked: July 19, 2024In:
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codingcomputer engineeingcomputers upscipv4ipv6softwaresoftware engineeringupsc
  1. Anusree Sanalkumar
    Anusree Sanalkumar Begginer

    1. Address Length IPv4: Uses 32-bit addresses, so we have around 4.3 billion unique addresses. IPv6: Uses 128-bit addresses, so it can provide a huge number of addresses—about 340 undecillion. 2. Address Format IPv4: Addresses are written with four numbers separated by dots. IPv6: Addresses are writRead more

    1. Address Length

    • IPv4: Uses 32-bit addresses, so we have around 4.3 billion unique addresses.
    • IPv6: Uses 128-bit addresses, so it can provide a huge number of addresses—about 340 undecillion.

    2. Address Format

    • IPv4: Addresses are written with four numbers separated by dots.
    • IPv6: Addresses are written with eight groups of four letters and numbers separated by colons.

    3. Header Complexity

    • IPv4: The header has many parts, which can make it a bit complicated.
    • IPv6: The header is simpler and faster to process.

    4. Address Configuration

    • IPv4: You can set addresses manually or use DHCP to do it automatically.
    • IPv6: Can automatically assign addresses by itself and also uses DHCPv6.

    5. NAT (Network Address Translation)

    • IPv4: Often uses NAT because there aren’t enough addresses for every device.
    • IPv6: Doesn’t need NAT because it has plenty of addresses for all devices.

    6. Security

    • IPv4: Security features are optional.
    • IPv6: Has built-in security features, making it more secure.

    7. Broadcasting

    • IPv4: Can send data to all devices on a network at once.
    • IPv6: Doesn’t use broadcasting but has other methods to send data.

    8. Fragmentation

    • IPv4: Both the sender and routers can break down large data packets.
    • IPv6: Only the sender breaks down data packets; routers don’t.

    So, IPv6 is like an upgraded version of IPv4, with more addresses, simpler setup, and better security.

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Sakshi Dubey
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Sakshi DubeyBegginer
Asked: July 15, 2024In:
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Mechanism of CRISPR-Cas9 for precise gene editing, potential applications in curing genetic diseases, modifying crops, and creating disease-resistant livestock. Ethical concerns include unintended genetic changes, ethical guidelines, and societal implications of gene editing technology.

  1. Sakshi Dubey
    Sakshi Dubey Begginer

    CRISPR-Cas9 is a revolutionary genomic editing technology that enables scientists to precisely modify DNA within cells. Here’s how it works and its potential applications and concerns: Mechanism of CRISPR-Cas9: Guide RNA: CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) RNA guidesRead more

    CRISPR-Cas9 is a revolutionary genomic editing technology that enables scientists to precisely modify DNA within cells. Here’s how it works and its potential applications and concerns:

    1. Mechanism of CRISPR-Cas9:
      • Guide RNA: CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) RNA guides Cas9 (CRISPR-associated protein 9) to the target DNA sequence.
      • DNA Cleavage: Cas9 acts as molecular scissors, cutting the DNA at the targeted location specified by the guide RNA.
      • Editing: Researchers can introduce desired changes (e.g., insertions, deletions, or replacements) at the cleaved site using DNA repair mechanisms in cells.
    2. Potential Applications:
      • Biomedical Research: Studying gene functions by creating and studying mutations.
      • Therapeutic Applications: Correcting genetic defects responsible for diseases like cystic fibrosis or sickle cell anemia.
      • Agriculture: Developing crops with improved traits, such as disease resistance or increased yield.
      • Biotechnology: Producing biofuels, pharmaceuticals, or other industrial products more efficiently.
    3. Concerns:
      • Off-Target Effects: Cas9 may unintentionally edit DNA at sites similar but not identical to the target, potentially causing unforeseen consequences.
      • Ethical Implications: Editing germline cells (sperm, eggs, embryos) raises ethical concerns about heritable genetic modifications.
      • Regulation and Oversight: Ensuring safe and responsible use of CRISPR technologies, balancing scientific progress with ethical considerations and potential risks.
      • Impact on Biodiversity: Potential unintended ecological consequences if genetically modified organisms are released into the environment.

    In summary, CRISPR-Cas9 offers unprecedented precision in genomic editing, holding promise for treating genetic disorders and advancing biotechnological applications. However, ethical, regulatory, and safety considerations must be carefully addressed to harness its potential benefits responsibly.

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Srikari.VG01
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Srikari.VG01Begginer
Asked: July 20, 2024In:
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How is artificial intelligence (AI) transforming data analytics and enhancing business intelligence?

  1. Harsh Madhavan
    Harsh Madhavan Begginer

    Artificial Intelligence (AI) is like a super-smart helper that can look at lots of information very quickly and tell us important things about it. Imagine you have a huge box of LEGO bricks, and you want to build something cool. But there are so many bricks that it's hard to know where to start. AIRead more

    Artificial Intelligence (AI) is like a super-smart helper that can look at lots of information very quickly and tell us important things about it. Imagine you have a huge box of LEGO bricks, and you want to build something cool. But there are so many bricks that it’s hard to know where to start. AI is like a super-fast robot friend who can look at all the bricks in the box, find the best ones for your project, and even suggest what you could build.

    In data analytics, AI helps businesses look at all the data they have, like sales numbers, customer information, and website visits, and find patterns and trends. For example, AI can tell a toy store which toys are selling the most and what time of year people buy certain toys. This helps the store know what to stock up on and when.

    For business intelligence, AI can help companies make smart decisions. It can predict what might happen in the future, like which new toy might become popular. This means businesses can plan better and make choices that help them grow and succeed. AI turns a lot of confusing numbers into clear, helpful advice, just like a wise friend helping you with your LEGO project.

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