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    <title>AI :: She Codes One Day Workshop Tutorials (new)</title>
    <link>https://tutorials.shecodes.com.au/ai-fundamentals/index.html</link>
    <description>Love it or hate it, the world is moving towards AI - and rapdily.&#xA;According to McKinsey - 62% of survey respondants say their company is experimenting with AI agents. There is clearly high curiosity and experimentation. The same study found that nearly two-thirds of respondents say their organizations have not yet begun scaling AI across the enterprise.&#xA;According to a study by Lean In, women were 22% less likely than men to be regular AI users at work.</description>
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      <title>Safety &amp; Ethical Considerations</title>
      <link>https://tutorials.shecodes.com.au/ai-fundamentals/safety_and_ethical_considerations/index.html</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      <guid>https://tutorials.shecodes.com.au/ai-fundamentals/safety_and_ethical_considerations/index.html</guid>
      <description>Read these first!&#xA;1. AI Outputs Are Not Facts Unlike a search engine, your large language models (LLMs) are not necessarily ‘researching’ information - they are generating statistically plausible text - kind of like autocomplete on your phone. Just like autocomplete changes kate to late all the time, AI can make mistakes too. They hallucinate — producing confident-sounding incorrect information. Never deploy AI outputs in medical, legal, financial, or safety-critical contexts without human review.</description>
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    <item>
      <title>Let&#39;s get the language right</title>
      <link>https://tutorials.shecodes.com.au/ai-fundamentals/lets_get_the_language_right/index.html</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      <guid>https://tutorials.shecodes.com.au/ai-fundamentals/lets_get_the_language_right/index.html</guid>
      <description>Let’s build some of the language and landscape around AI.&#xA;What do we mean when we say “AI” Let’s unpack some of the common terms you might be hearing.&#xA;​ Narrow AI Machine Learning Deep Learning Large Language Models Generative AI AGI (Artificial General Intelligence) Systems designed for one specific task (spam filters, recommendation engines, face unlock). Also includes all chatbots, and is the opposite end of the spectrum to AGI we will discuss later. Most AI in the world today is narrow AI.</description>
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    <item>
      <title>Becoming a Secret Agent</title>
      <link>https://tutorials.shecodes.com.au/ai-fundamentals/becoming_a_secret_agent/index.html</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      <guid>https://tutorials.shecodes.com.au/ai-fundamentals/becoming_a_secret_agent/index.html</guid>
      <description>What Are AI Agents? An AI agent is an LLM that can take actions in the world, not just generate text. It perceives its environment, reasons about what to do, takes an action, observes the result, and repeats.&#xA;The ReAct loop (Reason + Act):&#xA;OBSERVE → THINK → ACT → OBSERVE → THINK → ACT → ... This pattern, formalised by Yao et al. (2022), underlies most modern agent frameworks.</description>
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    <item>
      <title>Colab Together</title>
      <link>https://tutorials.shecodes.com.au/ai-fundamentals/colab_together/index.html</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      <guid>https://tutorials.shecodes.com.au/ai-fundamentals/colab_together/index.html</guid>
      <description>Let’s try some things in practice To do this we are going to use a Google Colab notebook - it runs in the browser so no downloads are needed.&#xA;Click this link to load the notebook. Ensure you save a copy on your own drive to get an editable version.</description>
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