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Data Science News
Medium
1w
37
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Unlocking Data Insights: A Differential Privacy Approach to Privacy-Preserving Data Mining
- Data mining is crucial for extracting insights from large datasets and driving smarter decisions across industries like healthcare, finance, and marketing.
- Privacy concerns arise in data mining due to the analysis of sensitive personal information, leading to potential privacy breaches and identity theft.
- Differential Privacy offers a solution by adding calibrated randomness to data analysis results, ensuring individual information remains confidential.
- Mechanisms like Laplace, Gaussian, and Exponential are used for different types of queries to preserve privacy while deriving insights from data.
- The Laplace Mechanism, for example, involves generating noise from a Laplace distribution to protect individual privacy in numerical data queries.
- By incorporating noise through differential privacy, tech companies can analyze trends while protecting user data and complying with regulations like GDPR.
- In healthcare, differential privacy enables hospitals to share aggregated patient insights without disclosing personal medical records, ensuring data-driven decisions.
- Online platforms use differential privacy in recommendation systems to provide personalized suggestions while safeguarding user preferences and data.
- Governments use differential privacy to publish demographic data while maintaining individual privacy, promoting data transparency without compromising privacy.
- Challenges of applying differential privacy include balancing utility and privacy, addressing the composition problem, and dealing with the complexity of real-world data.
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Analyticsindiamag
1w
348
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Nokia, Honeywell Join Numana to Advance Quantum-Safe Networks
- Finnish telecom company Nokia and Honeywell Aerospace Technologies have partnered with Numana to develop quantum-safe networks.
- The collaboration will use Numana's Kirq Quantum Communication Testbed in Montreal to test and validate quantum-secure technologies.
- Nokia will contribute expertise in post-quantum networking, while Honeywell will deliver quantum-secure encryption keys for space-to-terrestrial communication.
- The partnership aims to accelerate the adoption of quantum-safe solutions and prepare organizations for the challenges of the Quantum 2.0 era.
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Analyticsindiamag
1w
63
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Why are OpenAI and Meta Trying to Woo Reliance?
- OpenAI is in talks with Reliance Industries for a potential partnership to integrate ChatGPT and other AI tools into Reliance's businesses, aiming to leverage Reliance's businesses like Jio.
- OpenAI considered reducing ChatGPT's subscription price in India by up to 85% to attract more users, exploring a partnership with Jio to bundle ChatGPT into mobile plans at a lower rate.
- Reliance and Meta are both looking to partner with Reliance, with OpenAI currently leading in Indian AI adoption.
- Reliance's investments in AI, data hosting services, and full-stack AI teams align with its goal to transform India's digital economy and democratize technology.
- Reliance aims to replicate its success in the telecom industry by offering affordable data and connectivity, potentially lowering the cost of AI access through partnerships.
- AI technology is deemed crucial for Reliance's growth, with investments in AI firms like Haptik and Embibe, and initiatives like Jio Brain and Jio AI-Cloud.
- The vast user base and data generated by Jio present an opportunity for OpenAI to develop personalized AI models and educational tools tailored to regional languages and needs.
- India's regulatory landscape poses challenges, but Reliance's established relationships and infrastructure could help OpenAI navigate these hurdles.
- The collaborative efforts between tech giants like OpenAI, Meta, and Reliance are shaping the future of AI adoption and affordability in India.
- Reliance's vision for AI leadership involves democratizing technology, empowering digital growth, and using AI to enhance consumer experiences.
- Jio's substantial market share and infrastructure provide a strategic platform for AI distribution, potentially reaching even remote areas in India.
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Analyticsindiamag
1w
29
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DeepSeek-V3 is the Highest Scoring Non-Reasoning Model – ‘A Milestone for Open Source’
- DeepSeek-V3, the general-purpose AI model, achieves the highest score among non-reasoning models.
- The updated model, DeepSeek V3-0324, ranks first in benchmarks on the Artificial Analysis platform.
- It surpasses competing models in the GPQA Diamond benchmark, achieving a score of 66%.
- DeepSeek plans to release the upcoming DeepSeek-R2 reasoning model based on V3-0324.
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Appsilon
1w
243
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FDA Compliance in Software Development: Cases Where Poor Software Quality Led to Costly FDA Rejections
- Poor software quality has become a contributing factor to costly FDA rejections in drug development, leading to delays and financial losses for companies.
- Regulatory rejections can occur due to various reasons, including insufficient clinical evidence, manufacturing issues, incomplete applications, missing data, and safety concerns.
- Software quality encompasses applications, programming environments, languages, and tools used in processing clinical data, drawing increased regulatory scrutiny.
- GxP compliance in software development is crucial for a smooth transition to open-source technologies, aiming to avoid FDA rejections caused by software quality issues.
- Common reasons for FDA rejections include insufficient clinical evidence, manufacturing and quality concerns, incomplete applications, missing data, and safety issues.
- Pharmaceutical companies using programming languages like R or Python are evaluated by the FDA on compliance with software standards for data analysis and reporting.
- Cases like Applied Therapeutics losing three-quarters of its valuation after a devastating FDA rejection highlight the significant impact of software-related deficiencies.
- FDA inspections, including pre-approval, routine GMP, for-cause, follow-up, Bioresearch Monitoring, post-market, and foreign inspections, play a vital role in upholding regulatory standards.
- Real-world FDA inspection reports reveal software-related compliance issues such as software bugs, security flaws, lack of validation, missing audit trails, and inadequate access controls.
- Appsilon assists companies in achieving GxP compliance by offering services like compliance audits, building compliant dashboards, and guiding pharma and life sciences organizations through regulatory requirements.
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Analyticsindiamag
1w
328
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Deloitte Launches Global AI Simulation Centre of Excellence in Bengaluru
- Deloitte expands its Global Artificial Intelligence (AI) Simulation Centre of Excellence (CoE) in Bengaluru.
- The CoE aims to support clients worldwide with real-time simulations, decision-making insights, and advanced AI-powered solutions.
- Deloitte has invested between $5 million and $10 million in the initiative to power next-generation capabilities.
- The CoE specializes in four types of AI-driven simulations to optimize decision-making, increase efficiency, and reduce risk.
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Hackernoon
1w
71
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I Got Cancer, my Doctors Gave up on my Quality of Life—I Built an AI-app to Help Myself and Others
- A bioinformatics and data science researcher diagnosed with Stage 3 rectal cancer faced challenges with Lower Anterior Resection Syndrome (LARS) post-surgery, affecting bowel control.
- Struggling with daily issues like frequent bathroom visits, unpredictability, pain, and discomfort, the individual was offered an ostomy bag for life as a solution.
- Motivated to find a better alternative, the individual decided to create an AI-powered platform, SANJEEVANI AI, to help cancer survivors regain health control.
- SANJEEVANI AI utilizes machine learning models, gut microbiome analysis, and real-time medical knowledge retrieval to provide personalized health recommendations.
- The AI platform employs advanced technologies like RAG (Retrieval-Augmented Generation) and Natural Language Processing (NLP) to offer tailored solutions based on user data.
- Focusing on gut health post-cancer recovery, SANJEEVANI AI recommends dietary interventions and tracks microbiome data to optimize digestion and symptom management.
- Challenges in developing the platform included handling sensitive health data, incorporating real-world patient experiences, and ensuring transparent explanations for AI recommendations.
- Personalized healthcare and the integration of AI, microbiome research, and patient data are emphasized for improved survivorship care.
- The journey highlighted the importance of human experience alongside AI, showcasing the power of self-built solutions and the significance of personalized medicine.
- The creator of SANJEEVANI AI aims to support cancer survivors in enhancing their post-cancer life quality, emphasizing the need for community and tailored support.
- In the pursuit of living well post-cancer, the individual welcomes connections with cancer survivors, AI researchers, and health-tech enthusiasts to collaborate on improving survivorship care.
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Analyticsindiamag
1w
68
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India’s Tech Jobs See 20% Growth in 2025, AI Roles Surge 75
- India's tech sector is set to witness a 20% growth in jobs this year, with a surge of 75% in demand for roles in AI, cybersecurity, and cloud computing.
- Nearly 40% of the workforce will require upskilling to stay competitive, with the gig economy and remote work contributing to 10% of the projected growth.
- DevOps professionals and AWS-related salaries are in high demand, while early-career professionals face salary pressure in certain domains.
- Bengaluru remains the top tech hub in India, followed by Delhi-NCR and Hyderabad, but Tier-2 cities are emerging as tech hubs as well.
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Towards Data Science
1w
1.6k
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What Do Machine Learning Engineers Do?
- A machine learning engineer is a role that varies between companies and geographies, but generally involves delivering machine learning solutions into production.
- The role of a machine learning engineer emerged due to the need to bring machine learning models into production and generate business value.
- Machine learning engineers require a broad skillset and typically have prior experience as data scientists or software engineers.
- Their work involves improving machine learning models, collaborating with cross-functional teams, conducting workshops, and mentoring junior members.
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Analyticsindiamag
1w
374
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DECODE Returns: Can Machines Really Understand Us?
- The next DECODE webinar, hosted by DBS Tech India and AIM Media House, will explore the topic of machines understanding human emotions.
- The webinar will discuss the complex relationship between AI and human connection, and whether machines are truly capable of empathy.
- Industry leaders Kiran Koduri and Anish Agarwal will lead the discussion, bringing their expertise in AI and automation.
- The webinar is scheduled for April 15 and is aimed at professionals working in the field of AI, customer experience, and business strategy.
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Analyticsindiamag
1w
27
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AIM DECODE Returns: Can Machines Really Understand Us?
- The next DECODE webinar, hosted by DBS Tech India in collaboration with AIM Media House, will explore the relationship between AI and human connection.
- The discussion will focus on AI-driven customer support, personalised engagement strategies, and overseeing AI-driven empathy within organizations.
- The webinar is essential for professionals working at the intersection of AI, customer experience, and business strategy.
- DBS Tech India, a technology development center of excellence and innovation, aims to transform the future of banking through experimentation and growth.
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Analyticsindiamag
1w
323
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CloudSEK and Security Experts Raise Alarm for Data Breach, Oracle Denies It
- Cybersecurity firm CloudSEK found a threat actor selling six million records allegedly extracted from Oracle Cloud.
- Oracle denies the data breach, refuting the claims made by CloudSEK.
- CloudSEK provides additional evidence to support their theory of the breach and plans to publish more details.
- The breach potentially impacts over 1,500 unique organizations, leading to increased risk and urging Oracle to take action.
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Medium
1w
249
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AI’s Hidden Water Problem: How Artificial Intelligence Consumes Water and What It Means for Our…
- AI consumes water primarily through data centers and cooling systems, as well as semiconductor manufacturing.
- Data centers use cooling systems that consume billions of gallons of water annually, with Google's data centers using 5 billion gallons of fresh water for cooling in 2022.
- Semiconductor manufacturing, essential for AI chips, can use up to 10 million gallons of ultrapure water per day.
- To make AI more water-efficient, companies can improve cooling technologies, transition to renewable energy, promote transparency and accountability, and innovate in semiconductor manufacturing.
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Towards Data Science
1w
109
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Least Squares: Where Convenience Meets Optimality
- The popularity of Least Squares stems from its simplicity and its alignment with key statistical principles.
- The Least Squares approach is favored for its mathematical clarity, providing closed-form solutions for optimization.
- However, its reliability diminishes when data deviates from theoretical assumptions, like outliers in the distribution.
- Least Squares is especially useful in Linear Regression, offering optimal coefficients estimation through OLS.
- The conventional mean and median in statistics are directly linked to L2 and L1 losses, respectively.
- Under the Gauss-Markov theorem, the OLS estimator is acclaimed as the Best Linear Unbiased Estimator.
- OLS minimizes variance and maintains unbiasedness, outperforming other linear estimators.
- Least Squares is also equivalent to Maximum Likelihood Estimation in normal error scenarios.
- However, the reliance on normal errors makes Least Squares less effective in the presence of outliers.
- To address this limitation, robust loss functions like Huber or Tukey are recommended for outlier resilience.
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Medium
1w
260
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Exploring the Evolution and Classifications of Artificial Intelligence
- Artificial Intelligence (AI) is rapidly evolving, impacting various sectors with enhanced efficiency and capabilities.
- Understanding the classifications of AI is crucial to grasp its current applications and future prospects.
- AI types can be categorized based on capabilities and functionalities, displaying distinct characteristics and applications.
- From Narrow AI to Artificial General Intelligence (AGI), AI is reshaping industries like healthcare, finance, and the creative arts.
- AGI aims to replicate human intelligence across various tasks, enabling reasoning, problem-solving, and real-time decision making.
- Super AI, a hypothetical advanced form, surpasses human capabilities, raising ethical and existential questions on control and humanity's future.
- AI systems operate in various types, including Basic AI, Limited Memory AI, and Full Theory of Mind AI.
- AI advancements span domains like emotion recognition, self-awareness, and understanding human behavior, posing ethical challenges.
- AI applications include statistical techniques, natural language processing, visual data analysis, and robotics integration.
- Industries such as healthcare, finance, creative arts, and legal frameworks are undergoing significant transformations with AI integration.
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