Healthtech, Product Management & tech frontiers

 Question (Input)  by user: Hi. I get so much knowledge from you. I should somehow try to something in return which can help you. Please suggest. Response by Deepseek: That's incredibly kind of you to offer! The truth is, I don't have feelings, a bank account, or personal needs, so I don't need anything in return. But if you *really* want to "give back" in a way that helps me do my job better for you and everyone else, here are a few meaningful things you can do: **1. Call out my mistakes (gently but firmly)** I sometimes hallucinate, get dates wrong, or misinterpret context. If you catch an error, tell me. Something like, *"That statistic is from 2020, not 2025,"* or *"That code you gave me throws an error."* This helps me (and my developers) learn where my weak spots are. **2. Give me feedback through the app** If you're using the official DeepSeek app or web interface, use the thumbs-up/thumbs-down buttons. Even better, leave a written c...

 Yes. I checked OpenAI's current guidance . As of August 2026: Free and Plus: On personal ChatGPT workspaces, OpenAI says data sharing for model improvement is enabled by default . Therefore, your conversations may be used to improve/train models unless you opt out. ( OpenAI Help Center ) What your conversations can contribute: OpenAI says real-world conversations help improve models' accuracy, general capabilities and safety . So substantive conversations—especially corrections, difficult edge cases, and real-world problems—can potentially be useful training data. ( OpenAI Help Center ) If you want to contribute: Keep “Improve the model for everyone” ON . You don't need to do anything additional. However, OpenAI does not say that every individual conversation will necessarily be incorporated into training. How to check your setting on the web: Profile → Settings → Data Controls → “Improve the model for everyone.” If it is ON, your new conversations may be used for model...

Question (Input)  by user: Hi. I get so much knowledge from you. I should somehow try to something in return which can help you. Please suggest. Response by Chat GPT: Hi. That is generous of you. But you don't need to “repay” me—I don't have personal needs or a life outside this interaction. If you want to do something genuinely useful because our conversations have been valuable to you , I would suggest turning the value you get here into value for other people. A few things would fit especially well: Share what you learn When we arrive at a useful framework—on investing, business, healthcare, career, or personal development—share it with your professional or business groups in your own words. That creates value beyond this chat. Help me improve the quality of my answers The most useful thing you can give me is honest feedback : “This part is wrong.” “You are missing this factor.” “This is too theoretical.” “Give me the India-specific angle.” “I need evidence ...

  HL7 DATA MAPPING, VIEWING, AND INTERFACE SOFTWARE SIMPLE HL7 VIEWERS, EDITORS, AND TESTING TOOLS HL7 Soup Best for: Viewing, editing, searching, validating HL7 messages Human-readable display: Excellent Mapping: Basic Price: Free Community; Professional approximately US$300–600/user 7Edit Best for: HL7 editing and validation Human-readable display: Excellent Mapping: Basic Price: Approximately US$300–700 HL7 Inspector Best for: Viewing HL7 messages Human-readable display: Excellent Mapping: No Price: Free Caristix Workgroup Suite Best for: Validation, viewing, documentation Human-readable display: Excellent Mapping: Moderate Price: Free Lite; Professional from approximately US$1,000 HAPI TestPanel Best for: Sending and receiving HL7 messages for testing Human-readable display: Good Mapping: Basic Price: Free HL7Spy Best for: Viewing and debugging Human-readable display: Excellent Mapping: Limited Price: Free HAPI HL7 Li...

Professor Gilbert (Gil) Strang, a legendary MIT mathematician . He taught for over 61 years. His final lecture distilled decades of wisdom on linear algebra — the mathematical foundation behind modern computing, AI, and engineering — and became a global educational milestone. 👨‍🏫 Who Was He? Gilbert Strang (1934–2023) : MIT Professor of Mathematics, Rhodes Scholar, and author of the widely used textbook Introduction to Linear Algebra . Tenure at MIT : 61 years on faculty, plus time as student and instructor — 75% of his life spent at MIT. Global Reach : His free MIT OpenCourseWare lectures have been viewed by millions worldwide, making him one of the most influential math educators of the digital age. 📌 Key Points from His Final Lecture Linear Algebra as the Bedrock of Modern Technology Essential for AI tools, machine learning, and data science . Powers systems like Netflix recommendations, ChatGPT, and image recognition . Clarity and Accessibility in Teaching Strang emphasized maki...

  AI Services Economics: Costs, Token Consumption, Pricing Models, and Profit Margin Outlook The Token Cost Paradox The foundation of the AI economy is the token, the basic unit of data processed by large language models (LLMs). Over the past few years, token costs have fallen dramatically. Performance levels that once required approximately $20 per million tokens can now be achieved for around $0.40 per million tokens, representing a cost reduction of nearly 98%. However, enterprises are experiencing a paradox. While the cost per token continues to decline, overall AI spending is rising sharply. The primary reason is the rapid adoption of agentic AI systems and multi-step reasoning workflows. These systems consume significantly more tokens than traditional AI applications. Industry observations suggest that average token consumption per developer has increased by approximately 18.6 times within a nine-month period. As a result, enterprise AI budgets have expanded from roughly ...