<rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Hacker News: naikas82</title><link>https://news.ycombinator.com/user?id=naikas82</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Fri, 03 Jul 2026 07:59:09 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=naikas82" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by naikas82 in "Ask HN: What are you working on? (May 2026)"]]></title><description><![CDATA[
<p>First time posting my project. I am working on an LLM based graph visualization.<p>The App helps Product Managers, Sales Reps and Architects quickly understand an enterprise software APIs. LLM turns the raw documentation into beautiful process flows, sequence diagrams and integration requirements.<p>Hope to launch soon ;)</p>
]]></description><pubDate>Mon, 11 May 2026 08:27:22 +0000</pubDate><link>https://news.ycombinator.com/item?id=48092446</link><dc:creator>naikas82</dc:creator><comments>https://news.ycombinator.com/item?id=48092446</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48092446</guid></item><item><title><![CDATA[Ask HN: Can I publish AI-Generated of YouTube videos without IP Issues?]]></title><description><![CDATA[
<p>I used GenAI to create an audio summary of several YouTube videos, incorporating transcripts and key points from the content. The final output is an audio overview that sounds like a human summarizing the videos.<p>Before uploading this to the internet, I’m wondering about potential intellectual property (IP) concerns. Specifically:<p>- Does summarizing YouTube videos (without using direct quotes) count as fair use?
- If the AI-generated summary is transformative, does it reduce legal risk?
- Would citing the original video creators help, or do I need explicit permission?
- Are there any known cases where platforms like Spotify or YouTube took action against AI-generated summaries?<p>I’d love to hear from anyone with experience in copyright law, content creation, or platform policies.</p>
<hr>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=42997846">https://news.ycombinator.com/item?id=42997846</a></p>
<p>Points: 2</p>
<p># Comments: 1</p>
]]></description><pubDate>Mon, 10 Feb 2025 07:48:35 +0000</pubDate><link>https://news.ycombinator.com/item?id=42997846</link><dc:creator>naikas82</dc:creator><comments>https://news.ycombinator.com/item?id=42997846</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=42997846</guid></item><item><title><![CDATA[New comment by naikas82 in "Ask HN: How do you plan on making money with Open AI API?"]]></title><description><![CDATA[
<p>Make any FAQs and Tech Documentation humanish interactive. What say?</p>
]]></description><pubDate>Thu, 02 Feb 2023 07:59:58 +0000</pubDate><link>https://news.ycombinator.com/item?id=34623579</link><dc:creator>naikas82</dc:creator><comments>https://news.ycombinator.com/item?id=34623579</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=34623579</guid></item><item><title><![CDATA[New comment by naikas82 in "Ask HN: Is MBA Necessary for Product Management?"]]></title><description><![CDATA[
<p>I agree. But does the frameworks, case studies and business case analysis help in real-life? Why these courses are so expensive? Do they guarantee a certain level minimum pay/job grade?</p>
]]></description><pubDate>Sun, 20 Feb 2022 08:38:24 +0000</pubDate><link>https://news.ycombinator.com/item?id=30404231</link><dc:creator>naikas82</dc:creator><comments>https://news.ycombinator.com/item?id=30404231</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=30404231</guid></item><item><title><![CDATA[Ask HN: Is MBA Necessary for Product Management?]]></title><description><![CDATA[
<p>I see a rising trend to hire MBA grads for product management roles. As one matures in a PM role, is it important to do an MBA to advance in more executive type of roles e.g. Head/Director or Product Management? Is it a company or industry-specific culture? What is your take?</p>
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<p>Comments URL: <a href="https://news.ycombinator.com/item?id=30400981">https://news.ycombinator.com/item?id=30400981</a></p>
<p>Points: 2</p>
<p># Comments: 3</p>
]]></description><pubDate>Sat, 19 Feb 2022 22:08:42 +0000</pubDate><link>https://news.ycombinator.com/item?id=30400981</link><dc:creator>naikas82</dc:creator><comments>https://news.ycombinator.com/item?id=30400981</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=30400981</guid></item><item><title><![CDATA[New comment by naikas82 in "Ask HN: Python repo for abstractive summarization anyone?"]]></title><description><![CDATA[
<p>Thanks! Will take a look at it.</p>
]]></description><pubDate>Mon, 25 Jan 2021 09:04:49 +0000</pubDate><link>https://news.ycombinator.com/item?id=25901063</link><dc:creator>naikas82</dc:creator><comments>https://news.ycombinator.com/item?id=25901063</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=25901063</guid></item><item><title><![CDATA[Ask HN: Python repo for abstractive summarization anyone?]]></title><description><![CDATA[
<p>I noticed that I don't read the entire news article anymore. I look for most important details, but they are scattered and not always crisp. I have looked around for APIs and toolboxes. They aren't at par with what ML stacks (NLP/BERT/Deep Learning) has to offer. Can anyone suggest what is the best package/tool/API to do summarize news articles, say in 5 bullet points.</p>
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<p>Comments URL: <a href="https://news.ycombinator.com/item?id=25895767">https://news.ycombinator.com/item?id=25895767</a></p>
<p>Points: 3</p>
<p># Comments: 2</p>
]]></description><pubDate>Sun, 24 Jan 2021 20:44:14 +0000</pubDate><link>https://news.ycombinator.com/item?id=25895767</link><dc:creator>naikas82</dc:creator><comments>https://news.ycombinator.com/item?id=25895767</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=25895767</guid></item><item><title><![CDATA[New comment by naikas82 in "Show HN: Streamlit App to understand financial terms"]]></title><description><![CDATA[
<p>Thanks. Will do it now ;)</p>
]]></description><pubDate>Wed, 27 May 2020 06:35:26 +0000</pubDate><link>https://news.ycombinator.com/item?id=23320033</link><dc:creator>naikas82</dc:creator><comments>https://news.ycombinator.com/item?id=23320033</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=23320033</guid></item><item><title><![CDATA[New comment by naikas82 in "Show HN: Streamlit App to understand financial terms"]]></title><description><![CDATA[
<p>I built a lightweight streamlit app to understand financial terms, fundamental ratios, and performance metrics. It uses fmpcloud to pull periodic data like stock prices, annual statements, balance sheets of listed companies in the US. The explanation of the terms used in the app is taken from Investopedia.</p>
]]></description><pubDate>Sat, 23 May 2020 14:47:19 +0000</pubDate><link>https://news.ycombinator.com/item?id=23283382</link><dc:creator>naikas82</dc:creator><comments>https://news.ycombinator.com/item?id=23283382</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=23283382</guid></item><item><title><![CDATA[Show HN: Streamlit App to understand financial terms]]></title><description><![CDATA[
<p>Article URL: <a href="https://github.com/amolnaik/pynance">https://github.com/amolnaik/pynance</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=23283381">https://news.ycombinator.com/item?id=23283381</a></p>
<p>Points: 3</p>
<p># Comments: 3</p>
]]></description><pubDate>Sat, 23 May 2020 14:47:19 +0000</pubDate><link>https://github.com/amolnaik/pynance</link><dc:creator>naikas82</dc:creator><comments>https://news.ycombinator.com/item?id=23283381</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=23283381</guid></item><item><title><![CDATA[New comment by naikas82 in "Ask HN: What's your quarantine side project?"]]></title><description><![CDATA[
<p>I am working on a streamlit app that helps me understand financial statements and fundamental ratios (PB, PE ratios, EPS, etc.) of traded companies.<p>The stack is basically python + streamlit and APIs for stocks data. More about streamlit here: <a href="https://streamlit.io/" rel="nofollow">https://streamlit.io/</a><p>I am not able find lot of public domain data of German companies. Any help is appreciated.</p>
]]></description><pubDate>Thu, 14 May 2020 09:12:58 +0000</pubDate><link>https://news.ycombinator.com/item?id=23177275</link><dc:creator>naikas82</dc:creator><comments>https://news.ycombinator.com/item?id=23177275</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=23177275</guid></item><item><title><![CDATA[New comment by naikas82 in "Show HN: News Extract API – Pull structured data from online news articles"]]></title><description><![CDATA[
<p>I was looking for something like this. But with add-on to summarize the news text as close as human. Any idea???</p>
]]></description><pubDate>Tue, 21 Apr 2020 05:39:42 +0000</pubDate><link>https://news.ycombinator.com/item?id=22932312</link><dc:creator>naikas82</dc:creator><comments>https://news.ycombinator.com/item?id=22932312</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=22932312</guid></item><item><title><![CDATA[Ask HN: Looking for abstractive news summary based on machine learning]]></title><description><![CDATA[
<p>I noticed that I don't read the entire news article anymore. I look for most important details, but they are scattered and not always crisp. I have looked around for APIs and toolboxes. They aren't at par with what ML stacks (NLP/BERT/Deep Learning) has to offer. Can  anyone suggest what is the best package/tool/API to do summarize news articles, say in 5 bullet points.</p>
<hr>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=22728522">https://news.ycombinator.com/item?id=22728522</a></p>
<p>Points: 1</p>
<p># Comments: 0</p>
]]></description><pubDate>Mon, 30 Mar 2020 14:59:17 +0000</pubDate><link>https://news.ycombinator.com/item?id=22728522</link><dc:creator>naikas82</dc:creator><comments>https://news.ycombinator.com/item?id=22728522</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=22728522</guid></item><item><title><![CDATA[Ask HN: Not-so Glassdoorsy/lesser known hacks to get promoted]]></title><description><![CDATA[
<p>In my recent discussion with my manager, I was told about the "usual" (aka Inc.com, Glassdoor, etc.) rules of promotion. Be visible, prepare your case, share results. I find them odd, especially confusing. Should I work the rules out or do my job? Do I spend time in my function, or keep promoting my work internally. Why can't you just do your job, instead of wasting time in self-promotion. That way the odds are lesser, are't they?</p>
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<p>Comments URL: <a href="https://news.ycombinator.com/item?id=22387251">https://news.ycombinator.com/item?id=22387251</a></p>
<p>Points: 3</p>
<p># Comments: 2</p>
]]></description><pubDate>Fri, 21 Feb 2020 21:54:03 +0000</pubDate><link>https://news.ycombinator.com/item?id=22387251</link><dc:creator>naikas82</dc:creator><comments>https://news.ycombinator.com/item?id=22387251</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=22387251</guid></item><item><title><![CDATA[Show HN: Dupre – Streamlit UI to Identify Duplicate and Near Duplicate Images]]></title><description><![CDATA[
<p>Article URL: <a href="https://github.com/amolnaik/dupre">https://github.com/amolnaik/dupre</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=21652303">https://news.ycombinator.com/item?id=21652303</a></p>
<p>Points: 7</p>
<p># Comments: 0</p>
]]></description><pubDate>Wed, 27 Nov 2019 21:30:24 +0000</pubDate><link>https://github.com/amolnaik/dupre</link><dc:creator>naikas82</dc:creator><comments>https://news.ycombinator.com/item?id=21652303</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=21652303</guid></item></channel></rss>