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		<title>PagedAttention vs. RadixAttention: Optimizing LLM KV Cache Management</title>
		<link>https://www.analyticsvidhya.com/blog/2026/08/pagedattention-radixattention-llm-kv-cache/</link>
					<comments>https://www.analyticsvidhya.com/blog/2026/08/pagedattention-radixattention-llm-kv-cache/#respond</comments>
		
		<dc:creator><![CDATA[Janvi Kumari]]></dc:creator>
		<pubDate>Fri, 21 Aug 2026 10:42:03 +0000</pubDate>
				<category><![CDATA[Beginner]]></category>
		<category><![CDATA[LLMs]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<guid isPermaLink="false">https://www.analyticsvidhya.com/?p=257000</guid>

					<description><![CDATA[<p>Modern LLMs rely on quantization, pruning, distillation, and faster attention kernels, but production performance often depends most on KV cache management. As context windows grow, the cache consumes significant GPU memory, limiting concurrency, throughput, and latency. Two breakthroughs transformed this challenge: PagedAttention improves memory allocation, while RadixAttention enables efficient prefix reuse. Together, these techniques make [&#8230;]</p>
<p>The post <a href="https://www.analyticsvidhya.com/blog/2026/08/pagedattention-radixattention-llm-kv-cache/">PagedAttention vs. RadixAttention: Optimizing LLM KV Cache Management</a> appeared first on <a href="https://www.analyticsvidhya.com">Analytics Vidhya</a>.</p>
]]></description>
		
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		<title>How to Remove Claude Watermarks from Text, Code, and Files</title>
		<link>https://www.analyticsvidhya.com/blog/2026/08/how-to-remove-claude-watermarks/</link>
					<comments>https://www.analyticsvidhya.com/blog/2026/08/how-to-remove-claude-watermarks/#respond</comments>
		
		<dc:creator><![CDATA[Vasu Deo Sankrityayan]]></dc:creator>
		<pubDate>Wed, 19 Aug 2026 05:52:55 +0000</pubDate>
				<category><![CDATA[Guide]]></category>
		<category><![CDATA[LLMs]]></category>
		<category><![CDATA[Python]]></category>
		<guid isPermaLink="false">https://www.analyticsvidhya.com/?p=257044</guid>

					<description><![CDATA[<p>Claude now marks AI-generated content. But it does not mark everything the same way. Anthropic currently uses embedded watermarks for text and signed C2PA provenance metadata for supported files. Code sits somewhere in between: it is still text, but its structure gives the watermark fewer places to work. I went into detail about Claude&#8217;s watermarks [&#8230;]</p>
<p>The post <a href="https://www.analyticsvidhya.com/blog/2026/08/how-to-remove-claude-watermarks/">How to Remove Claude Watermarks from Text, Code, and Files</a> appeared first on <a href="https://www.analyticsvidhya.com">Analytics Vidhya</a>.</p>
]]></description>
		
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		<title>How to Add Skills in Agents using LangChain</title>
		<link>https://www.analyticsvidhya.com/blog/2026/08/build-modular-agent-skills-langchain/</link>
					<comments>https://www.analyticsvidhya.com/blog/2026/08/build-modular-agent-skills-langchain/#respond</comments>
		
		<dc:creator><![CDATA[Mounish V]]></dc:creator>
		<pubDate>Tue, 18 Aug 2026 09:17:35 +0000</pubDate>
				<category><![CDATA[AI Agents]]></category>
		<category><![CDATA[Beginner]]></category>
		<category><![CDATA[Guide]]></category>
		<guid isPermaLink="false">https://www.analyticsvidhya.com/?p=257013</guid>

					<description><![CDATA[<p>Ever wondered how ChatGPT, Gemini, and other chat interfaces generate PDFs, PowerPoints, and more when all they have under the hood is an LLM? The trick isn’t a smarter model. It’s something simpler: skills which are instructions an agent loads only when needed. Next, let’s explore how skills work using LangChain and how they can make [&#8230;]</p>
<p>The post <a href="https://www.analyticsvidhya.com/blog/2026/08/build-modular-agent-skills-langchain/">How to Add Skills in Agents using LangChain</a> appeared first on <a href="https://www.analyticsvidhya.com">Analytics Vidhya</a>.</p>
]]></description>
		
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		<post-id xmlns="com-wordpress:feed-additions:1">257013</post-id>
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		<title>7 Kimi K3 Features That Make Every Other Model Feel Outdated</title>
		<link>https://www.analyticsvidhya.com/blog/2026/08/kimi-k3-features/</link>
					<comments>https://www.analyticsvidhya.com/blog/2026/08/kimi-k3-features/#respond</comments>
		
		<dc:creator><![CDATA[Riya Bansal]]></dc:creator>
		<pubDate>Mon, 17 Aug 2026 17:17:11 +0000</pubDate>
				<category><![CDATA[Beginner]]></category>
		<category><![CDATA[Listicle]]></category>
		<category><![CDATA[LLMs]]></category>
		<guid isPermaLink="false">https://www.analyticsvidhya.com/?p=256984</guid>

					<description><![CDATA[<p>Developers launch new models every week, but most barely change how you work. Kimi K3 is different—not because of benchmark charts, but because of a few small API changes that fundamentally affect how you use it. The first is reasoning_effort, which defaults to maximum, alongside 131,072 max_completion_tokens. Ask K3 to rename a variable, and it [&#8230;]</p>
<p>The post <a href="https://www.analyticsvidhya.com/blog/2026/08/kimi-k3-features/">7 Kimi K3 Features That Make Every Other Model Feel Outdated</a> appeared first on <a href="https://www.analyticsvidhya.com">Analytics Vidhya</a>.</p>
]]></description>
		
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		<title>How to Install Codex CLI: A Step-by-Step Guide</title>
		<link>https://www.analyticsvidhya.com/blog/2026/08/how-to-install-codex-cli/</link>
					<comments>https://www.analyticsvidhya.com/blog/2026/08/how-to-install-codex-cli/#respond</comments>
		
		<dc:creator><![CDATA[Vasu Deo Sankrityayan]]></dc:creator>
		<pubDate>Sat, 15 Aug 2026 10:30:00 +0000</pubDate>
				<category><![CDATA[ChatGPT]]></category>
		<category><![CDATA[Command Line]]></category>
		<guid isPermaLink="false">https://www.analyticsvidhya.com/?p=256968</guid>

					<description><![CDATA[<p>If you have already used&#160;Codex in ChatGPT, the Codex CLI will feel familiar. It brings the same AI assistance directly into your local development environment, where it can work with your repository, shell, tests, and other tools. Installation takes only one command, but the setup choices that follow are worth reviewing carefully. In this article, you’ll [&#8230;]</p>
<p>The post <a href="https://www.analyticsvidhya.com/blog/2026/08/how-to-install-codex-cli/">How to Install Codex CLI: A Step-by-Step Guide</a> appeared first on <a href="https://www.analyticsvidhya.com">Analytics Vidhya</a>.</p>
]]></description>
		
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		<post-id xmlns="com-wordpress:feed-additions:1">256968</post-id>
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		<title>NVIDIA Nemotron 3.5 Lightning: The AI Agent Workhorse</title>
		<link>https://www.analyticsvidhya.com/blog/2026/08/nvidia-nemotron-3-5-lightning/</link>
					<comments>https://www.analyticsvidhya.com/blog/2026/08/nvidia-nemotron-3-5-lightning/#respond</comments>
		
		<dc:creator><![CDATA[Harsh Mishra]]></dc:creator>
		<pubDate>Fri, 14 Aug 2026 11:08:54 +0000</pubDate>
				<category><![CDATA[AI Agents]]></category>
		<category><![CDATA[LLMs]]></category>
		<guid isPermaLink="false">https://www.analyticsvidhya.com/?p=256949</guid>

					<description><![CDATA[<p>Long-running AI agents often spend most of their time on routine execution rather than difficult reasoning. After making a plan, they may perform hundreds of tool calls, file reads, validations, commands, and formatting steps, so using a frontier reasoning model for every action can become unnecessarily slow and expensive. NVIDIA’s Nemotron 3.5 Lightning takes a [&#8230;]</p>
<p>The post <a href="https://www.analyticsvidhya.com/blog/2026/08/nvidia-nemotron-3-5-lightning/">NVIDIA Nemotron 3.5 Lightning: The AI Agent Workhorse</a> appeared first on <a href="https://www.analyticsvidhya.com">Analytics Vidhya</a>.</p>
]]></description>
		
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		<item>
		<title>How Baidu Unlimited-OCR Works: Solving Long-Document Transcription</title>
		<link>https://www.analyticsvidhya.com/blog/2026/08/baidu-unlimited-ocr-technical-breakdown/</link>
					<comments>https://www.analyticsvidhya.com/blog/2026/08/baidu-unlimited-ocr-technical-breakdown/#respond</comments>
		
		<dc:creator><![CDATA[Shaik Hamzah]]></dc:creator>
		<pubDate>Thu, 13 Aug 2026 12:10:18 +0000</pubDate>
				<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[Computer Vision]]></category>
		<category><![CDATA[LLMs]]></category>
		<guid isPermaLink="false">https://www.analyticsvidhya.com/?p=256924</guid>

					<description><![CDATA[<p>About a month ago, Baidu (often called the “Google of China&#8221;) introduced Unlimited-OCR, an advancement over DeepSeek OCR. The model was designed to transcribe long, multi-page documents with high accuracy while delivering fast and stable inference. Unlike conventional vision-language OCR systems, Unlimited-OCR addresses a major bottleneck in long-document transcription: the rapidly growing Key-Value (KV) cache, [&#8230;]</p>
<p>The post <a href="https://www.analyticsvidhya.com/blog/2026/08/baidu-unlimited-ocr-technical-breakdown/">How Baidu Unlimited-OCR Works: Solving Long-Document Transcription</a> appeared first on <a href="https://www.analyticsvidhya.com">Analytics Vidhya</a>.</p>
]]></description>
		
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		<post-id xmlns="com-wordpress:feed-additions:1">256924</post-id>
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		<title>Why You Shouldn&#8217;t Always Trust LLMs as Judges: Understanding Bias in Automated Evaluation</title>
		<link>https://www.analyticsvidhya.com/blog/2026/08/why-you-shouldnt-trust-llm-judges/</link>
					<comments>https://www.analyticsvidhya.com/blog/2026/08/why-you-shouldnt-trust-llm-judges/#respond</comments>
		
		<dc:creator><![CDATA[Soumil Jain]]></dc:creator>
		<pubDate>Wed, 12 Aug 2026 10:31:00 +0000</pubDate>
				<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[LLMs]]></category>
		<guid isPermaLink="false">https://www.analyticsvidhya.com/?p=256907</guid>

					<description><![CDATA[<p>In the rush to automate evaluation, from grading student code to ranking research papers, we have embraced Large Language Models as judges. They are fast. These units are cheap. They scale. However, at a workshop at DHS 2026, Bhaskarjit Sarmah made a point that stuck with me: “you can’t trust LLM as a judge. I [&#8230;]</p>
<p>The post <a href="https://www.analyticsvidhya.com/blog/2026/08/why-you-shouldnt-trust-llm-judges/">Why You Shouldn&#8217;t Always Trust LLMs as Judges: Understanding Bias in Automated Evaluation</a> appeared first on <a href="https://www.analyticsvidhya.com">Analytics Vidhya</a>.</p>
]]></description>
		
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		<post-id xmlns="com-wordpress:feed-additions:1">256907</post-id>
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		<item>
		<title>Claude Now Watermarks Everything It Makes</title>
		<link>https://www.analyticsvidhya.com/blog/2026/08/claude-ai-watermarking-explained/</link>
					<comments>https://www.analyticsvidhya.com/blog/2026/08/claude-ai-watermarking-explained/#respond</comments>
		
		<dc:creator><![CDATA[Vasu Deo Sankrityayan]]></dc:creator>
		<pubDate>Tue, 11 Aug 2026 12:36:46 +0000</pubDate>
				<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[LLMs]]></category>
		<guid isPermaLink="false">https://www.analyticsvidhya.com/?p=256904</guid>

					<description><![CDATA[<p>First, pick the line that applies to you. Since August 2nd, 2026, Claude marks all content during generation. For instance, text receives a hidden watermark, while files receive a signature. Anthropic committed to the EU AI Act’s Code of Practice on Transparency of AI-Generated Content. Consequently, all content generated by Claude models will carry a [&#8230;]</p>
<p>The post <a href="https://www.analyticsvidhya.com/blog/2026/08/claude-ai-watermarking-explained/">Claude Now Watermarks Everything It Makes</a> appeared first on <a href="https://www.analyticsvidhya.com">Analytics Vidhya</a>.</p>
]]></description>
		
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		<post-id xmlns="com-wordpress:feed-additions:1">256904</post-id>
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		<title>How to Install Claude Code: A Step-by-Step Guide</title>
		<link>https://www.analyticsvidhya.com/blog/2026/08/how-to-install-claude-code/</link>
					<comments>https://www.analyticsvidhya.com/blog/2026/08/how-to-install-claude-code/#respond</comments>
		
		<dc:creator><![CDATA[Vasu Deo Sankrityayan]]></dc:creator>
		<pubDate>Mon, 10 Aug 2026 18:20:22 +0000</pubDate>
				<category><![CDATA[Command Line]]></category>
		<category><![CDATA[Guide]]></category>
		<category><![CDATA[LLMs]]></category>
		<guid isPermaLink="false">https://www.analyticsvidhya.com/?p=256886</guid>

					<description><![CDATA[<p>You have probably heard by now. Claude Code burns through usage limits! But most of us live in the web app&#8230; distant from the terminal app, around which the buzz is about. Maybe that was enough to make you curious. Maybe you already knew exactly what it was and just want it running on your [&#8230;]</p>
<p>The post <a href="https://www.analyticsvidhya.com/blog/2026/08/how-to-install-claude-code/">How to Install Claude Code: A Step-by-Step Guide</a> appeared first on <a href="https://www.analyticsvidhya.com">Analytics Vidhya</a>.</p>
]]></description>
		
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