<?xml version="1.0" encoding="utf-8"?>
<rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/">
    <channel>
        <title>AI &amp; Automation Dispatches | BlogBuckett</title>
        <link>https://www.blogbuckett.page/category/ai</link>
        <description>Artificial intelligence models, neural networks, machine learning pipelines, LLMs, and autonomous AI agents.</description>
        <lastBuildDate>Wed, 12 Aug 2026 03:02:05 GMT</lastBuildDate>
        <docs>https://validator.w3.org/feed/docs/rss2.html</docs>
        <generator>https://github.com/jpmonette/feed</generator>
        <language>en</language>
        <copyright>All rights reserved 2026, BlogBuckett</copyright>
        <item>
            <title><![CDATA[Zero-Bubble MoE Routing: How Asymmetric INT3 KV Compression Unlocks Sub-10ms Token Latency]]></title>
            <link>https://www.blogbuckett.page/blog/ai/2026-08-11-zero-bubble-moe-routing-how-asymmetric-int3-kv-compression-unlocks-sub-10ms-token-latency</link>
            <guid isPermaLink="false">https://www.blogbuckett.page/blog/ai/2026-08-11-zero-bubble-moe-routing-how-asymmetric-int3-kv-compression-unlocks-sub-10ms-token-latency</guid>
            <pubDate>Tue, 11 Aug 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Discover how combining zero-bubble expert routing pipelines with non-uniform INT3 KV-cache quantization enables ultra-low latency LLM inference without sacrificing model precision.]]></description>
            <content:encoded><![CDATA[Discover how combining zero-bubble expert routing pipelines with non-uniform INT3 KV-cache quantization enables ultra-low latency LLM inference without sacrificing model precision.]]></content:encoded>
            <enclosure url="https://images.unsplash.com/photo-1618005182384-a83a8bd57fbe?auto=format&amp;fit=crop&amp;w=1200&amp;q=80" length="0" type="image//photo-1618005182384-a83a8bd57fbe"/>
        </item>
        <item>
            <title><![CDATA[Neural-Symbolic State Graphs: Leveraging Pivot Distance Metrics for Failure-Free Agent Execution]]></title>
            <link>https://www.blogbuckett.page/blog/ai/2026-08-11-neural-symbolic-state-graphs-leveraging-pivot-distance-metrics-for-failure-free-agent-execution</link>
            <guid isPermaLink="false">https://www.blogbuckett.page/blog/ai/2026-08-11-neural-symbolic-state-graphs-leveraging-pivot-distance-metrics-for-failure-free-agent-execution</guid>
            <pubDate>Tue, 11 Aug 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Autoregressive LLMs consistently collapse when executing long-horizon tasks across vast state spaces. By embedding symbolic state graphs with pivot distance metrics, autonomous agents achieve mathematically verified, deterministic pathing.]]></description>
            <content:encoded><![CDATA[Autoregressive LLMs consistently collapse when executing long-horizon tasks across vast state spaces. By embedding symbolic state graphs with pivot distance metrics, autonomous agents achieve mathematically verified, deterministic pathing.]]></content:encoded>
            <enclosure url="https://images.unsplash.com/photo-1531746790731-6c087fecd65a?auto=format&amp;fit=crop&amp;w=1200&amp;q=80" length="0" type="image//photo-1531746790731-6c087fecd65a"/>
        </item>
        <item>
            <title><![CDATA[The Sub-10ms Barrier: Fusing Sparse MoE Routing with FP4 KV-Cache Quantization]]></title>
            <link>https://www.blogbuckett.page/blog/ai/2026-08-10-the-sub-10ms-barrier-fusing-sparse-moe-routing-with-fp4-kv-cache-quantization</link>
            <guid isPermaLink="false">https://www.blogbuckett.page/blog/ai/2026-08-10-the-sub-10ms-barrier-fusing-sparse-moe-routing-with-fp4-kv-cache-quantization</guid>
            <pubDate>Mon, 10 Aug 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Discover how combining dynamic top-k Mixture-of-Experts routing with FP4 KV-cache quantization smashes the 10-millisecond latency floor for real-time LLM inference.]]></description>
            <content:encoded><![CDATA[Discover how combining dynamic top-k Mixture-of-Experts routing with FP4 KV-cache quantization smashes the 10-millisecond latency floor for real-time LLM inference.]]></content:encoded>
            <enclosure url="https://images.unsplash.com/photo-1677442136019-21780ecad995?auto=format&amp;fit=crop&amp;w=1200&amp;q=80" length="0" type="image//photo-1677442136019-21780ecad995"/>
        </item>
        <item>
            <title><![CDATA[Deterministic Consensus in Multi-Agent Swarms: Preventing Tool-Calling Cascades with Formal Guardrails]]></title>
            <link>https://www.blogbuckett.page/blog/ai/2026-08-10-deterministic-consensus-in-multi-agent-swarms-preventing-tool-calling-cascades-with-formal-guardrails</link>
            <guid isPermaLink="false">https://www.blogbuckett.page/blog/ai/2026-08-10-deterministic-consensus-in-multi-agent-swarms-preventing-tool-calling-cascades-with-formal-guardrails</guid>
            <pubDate>Mon, 10 Aug 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[As autonomous agent swarms scale to hundreds of concurrent workers, probabilistic decision-making threatens system stability. Here is how deterministic consensus engines and dynamic tool-calling guardrails prevent catastrophic API cascades.]]></description>
            <content:encoded><![CDATA[As autonomous agent swarms scale to hundreds of concurrent workers, probabilistic decision-making threatens system stability. Here is how deterministic consensus engines and dynamic tool-calling guardrails prevent catastrophic API cascades.]]></content:encoded>
            <enclosure url="https://images.unsplash.com/photo-1655720828018-edd2daec9349?auto=format&amp;fit=crop&amp;w=1200&amp;q=80" length="0" type="image//photo-1655720828018-edd2daec9349"/>
        </item>
        <item>
            <title><![CDATA[Beyond Brute-Force Prompting: How Differential Heuristics Are Revolutionizing AI Agent Pathfinding]]></title>
            <link>https://www.blogbuckett.page/blog/ai/2026-08-09-beyond-brute-force-prompting-how-differential-heuristics-are-revolutionizing-ai-agent-pathfinding</link>
            <guid isPermaLink="false">https://www.blogbuckett.page/blog/ai/2026-08-09-beyond-brute-force-prompting-how-differential-heuristics-are-revolutionizing-ai-agent-pathfinding</guid>
            <pubDate>Sun, 09 Aug 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[As autonomous AI agents face increasingly complex multi-step planning environments, classical search heuristics are making a massive comeback. Here is how modern neural-symbolic systems adapt differential heuristics to accelerate high-dimensional agent reasoning.]]></description>
            <content:encoded><![CDATA[As autonomous AI agents face increasingly complex multi-step planning environments, classical search heuristics are making a massive comeback. Here is how modern neural-symbolic systems adapt differential heuristics to accelerate high-dimensional agent reasoning.]]></content:encoded>
            <enclosure url="https://images.unsplash.com/photo-1620712943543-bcc4688e7485?auto=format&amp;fit=crop&amp;w=1200&amp;q=80" length="0" type="image//photo-1620712943543-bcc4688e7485"/>
        </item>
    </channel>
</rss>