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The subject line says it all. Robot teachers have officially entered the classroom, and I’m not sure how to feel about it. 😳
🤯 MYSTERY AI LINK 🤯
This link leads to one of the most interesting things I’ve seen in AI recently.
🛠️ NEW AI TOOLS 🛠️
What’s cookin’? A rural New York school district is preparing to put a humanoid robot in the classroom this fall. Salamanca High School will use “Sally,” a seated robot from Realbotix, along with an AI avatar students can access on laptops. The robot will not replace teachers, but it will act as a teaching assistant in AI and robotics classes. Students can ask it questions, get homework help, continue past conversations using an ID code, and receive translations in more than 100 languages. The district says the system is closed off from the internet, trained on school curriculum, and designed to say “I don’t know” instead of making things up. According to the purchasing contract, the products cost the district $57,590.
🤔 Hunter’s take: This is one of those moments where you stop and say, “What in the actual world is happening?!” Robot teachers are officially here. Let that sink in for a minute. It is fascinating because it shows the real AI debate in schools is no longer “ban it or allow it.” It is becoming: who gets to shape how kids learn with it?
Image: Google
What’s cookin’? Google just introduced three new Gemini models designed to make AI agents faster, cheaper, and more reliable at scale.
Gemini 3.6 Flash: Google’s main new workhorse model, built to handle coding, document analysis, multimodal tasks, and knowledge work with fewer tokens and lower costs.
Gemini 3.5 Flash-Lite: The faster, cheaper option for high-volume tasks like search, document processing, translation, and other agent workflows that need speed at scale.
Gemini 3.5 Flash Cyber: A specialized cybersecurity model used inside CodeMender to help trusted partners find, validate, and patch software vulnerabilities more efficiently.
🤔 Hunter’s take: The big story here isn’t just “better AI.” It’s cheaper AI labor. If these models can complete more tasks with fewer tokens, fewer tool calls, and lower latency, companies can run agents more often and in more places. That’s when AI starts moving from impressive demos to everyday infrastructure.
💬 PROMPT OF THE DAY:
Give me 12 high-quality alternatives to this idea for dating messages: [paste idea]. Make each option meaningfully different. Include a short example using [my situation].
…
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✍️ Meet the Author:
Hi — I’m Hunter, a PhD candidate whose work has appeared in major academic journals and popular tech outlets. I founded FryAI to make staying ahead of AI clear, accessible, and fun.
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