<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Open Source on AI Brief | AI-101.tech</title><link>https://AI-101.tech/tags/open-source/</link><description>Recent content in Open Source on AI Brief | AI-101.tech</description><generator>Hugo</generator><language>en</language><lastBuildDate>Mon, 13 Apr 2026 21:00:00 +0800</lastBuildDate><atom:link href="https://AI-101.tech/tags/open-source/index.xml" rel="self" type="application/rss+xml"/><item><title>Nvidia Leads SiFive's $400M Round, Betting on Open-Source RISC-V AI Chips</title><link>https://AI-101.tech/posts/2026-04-12-nvidia-sifive-riscv-ai-chips/</link><pubDate>Mon, 13 Apr 2026 21:00:00 +0800</pubDate><guid>https://AI-101.tech/posts/2026-04-12-nvidia-sifive-riscv-ai-chips/</guid><description>&lt;h2 id="breaking-the-x86-and-arm-duopoly">Breaking the x86 and ARM Duopoly&lt;/h2>
&lt;p>SiFive&amp;rsquo;s products are based on RISC-V processor architecture — neither Intel&amp;rsquo;s x86 nor ARM. These two architectures currently almost completely monopolize the CPU supply feeding Nvidia GPU compute systems.&lt;/p>
&lt;p>RISC-V is an open-source design that anyone can inspect, modify, and use. This contrasts sharply with x86&amp;rsquo;s closed proprietary model and ARM&amp;rsquo;s licensing approach. Previously RISC-V was mainly used in IoT devices and microcontrollers, but with this funding round, SiFive is targeting AI data center CPUs.&lt;/p></description></item><item><title>Meta Drops Muse Spark: $14.3B Overhaul, But the Door to Open Source Stays Closed</title><link>https://AI-101.tech/posts/meta-muse-spark-ai-model-open-source/</link><pubDate>Fri, 10 Apr 2026 00:00:00 +0000</pubDate><guid>https://AI-101.tech/posts/meta-muse-spark-ai-model-open-source/</guid><description>&lt;p>On April 8, 2026, Meta dropped a bomb.&lt;/p>
&lt;p>Not the &amp;ldquo;we have a new model come try it&amp;rdquo; kind. The kind that made the entire open-source AI community go quiet.&lt;/p>
&lt;p>Muse Spark has arrived.&lt;/p>
&lt;p>This is Meta&amp;rsquo;s first brand-new AI model in a year, and the first product from Meta&amp;rsquo;s newly formed Superintelligence Labs. Leading the charge: Alexandr Wang, poached from Scale AI. Zuckerberg spent $14.3 billion and gave Wang nine months to tear down and rebuild the entire AI infrastructure from scratch.&lt;/p></description></item><item><title>Databricks Co-Founder Wins ACM Award, Says We Should Stop Measuring AI by Human Standards</title><link>https://AI-101.tech/posts/databricks-matei-zaharia-acm-award-agi/</link><pubDate>Thu, 09 Apr 2026 00:00:00 +0000</pubDate><guid>https://AI-101.tech/posts/databricks-matei-zaharia-acm-award-agi/</guid><description>&lt;p>Databricks co-founder and CTO Matei Zaharia almost missed the email telling him he&amp;rsquo;d won an award.&lt;/p>
&lt;p>&amp;ldquo;Yeah, it was a surprise,&amp;rdquo; he said. The message informed him he&amp;rsquo;d become the recipient of the 2026 ACM Prize in Computing.&lt;/p>
&lt;h2 id="from-spark-to-big-data-infrastructure-17-years">From Spark to Big Data Infrastructure: 17 Years&lt;/h2>
&lt;p>Flashback to 2009 — Zaharia was 28, a PhD student at UC Berkeley under Ion Stoica. He developed a technology that dramatically accelerated big data processing, named it &lt;strong>Apache Spark&lt;/strong>, and released it as open source.&lt;/p></description></item></channel></rss>