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The Infinity Tech XV
🚀 Happy Monday!
Welcome to The Infinity Tech!
This week, we’re welcoming 11 new members to our growing tech community. Let’s dive into this week’s highlights with Galactic Sync – your quick and sharp roundup of the latest in Tech!
🛸 This week’s highlights:
🔹 OpenAI releases o3-pro, a souped-up version of its o3 AI reasoning model
🔹 Meta’s V-JEPA 2 model teaches AI to understand its surroundings
🔹 Multiple GCP products experienced Service issues last week
🔹 Stellar Prompts: Your new AI superpower is here!
Tech News
🔹 Multiple GCP products experienced Service issues last week
🔹 Advanced AI suffers ‘complete accuracy collapse’ in face of complex problems, study finds
🔹 France's Mistral launches Europe's first AI reasoning model
🔹 OpenAI releases o3-pro, a souped-up version of its o3 AI reasoning model
Tech Articles
🔹 Implementing Vector Search from Scratch: A Step-by-Step Tutorial
🔹How to Design My First AI Agent
🔹How Lyft Uses ML to Make 100 Million Predictions A Day
🔹9 MCP Projects for AI Engineers
🔹 Stop Building Platforms Nobody Uses: Pick the Right Kubernetes Abstraction with GitOps
Companies News
🔹 Glean raises over $150M series F funding at a $7.2B valuation
🔹 Autonomize AI Raises $28 Million Series A to Power Next-Generation Agentic AI for Healthcare and Life Sciences
🔹 Meta’s V-JEPA 2 model teaches AI to understand its surroundings
🔹Neuralink raises $650 million Series E
Open Source Repositories
🔹 RedditVideoMakerBot automates the creation of short videos from Reddit content without manual video editing. It's built using Python and Playwright, aiming to replicate the viral video style popular on platforms like TikTok and YouTube.
🔹Xray-core is an open-source platform and the best v2ray-core, written in Go. It's designed for various applications and known for its ability to penetrate everything.
🔹claude-task-master a JavaScript-based task management system, Claude Task Master, leverages AI to integrate with platforms like Cursor, Lovable, Windsurf, and Roo. It has gained significant popularity, as evidenced by its 14,858 stars and 1,528 forks on GitHub.
🔹scrapy is a fast, high-level Python framework designed for web crawling and scraping.
“Technology is best when it brings people together”
Two Simple Rules for Getting Better Results When Talking to AI
When you talk to AI, think of it like giving clear instructions to a teammate. Here are two key tips:
1. Tell It Exactly How You Want the Answer!
Right from the start, be clear about what kind of output you want from the AI. For example:
"List it for me in bullet points."
"Show it in a table format."
"Give a short, concise answer, like a tweet."
This way, the AI will prepare the response exactly in the format you want. You can think of this like defining the output format when writing an automation script; the clearer you are, the more accurate the results you'll get.
2. Break Down Big Tasks!
If you're asking the AI to do something complex, break it down into small, manageable steps. It's just like splitting a large CI/CD pipeline into smaller stages. You can do this in two ways:
Give a separate command for each step: You can tell it each phase one by one.
Specify the steps within a single command: For example:
"First, create a draft."
"Then, analyze this draft and find any missing opportunities."
"Based on these findings, prepare an updated draft."
"Finally, write the final draft."
Why is this important? AI models are very smart, but they perform much better for you when you clearly state what you want and how you want it. It's like writing a Kubernetes manifest step-by-step; the clearer you are about what each field means, the more likely you are to get the desired output.
Additional Information (Pro Tip): Some advanced AI models (like Gemini 2.5 Pro) already do this step-by-step planning automatically. However, when you manually specify the steps, you gain more control over the outcome. This is akin to designing your own custom pipeline rather than just using an automation tool's default behavior.