Hey everyone, I’m Ritvik, a 21-year-old Computer Science student from India. Over the past few months, I’ve been diving into AI, automation, and building custom tools/workflows and I’m really enjoying the process of experimenting and learning fast. At this stage, I’d love to get some hands-on experience by working on real problems that founders, small business owners, or solopreneurs are facing. I’m not looking to get paid yet just want to contribute, practice, and hopefully earn feedback, testimonials, or referrals along the way. Some areas I’m exploring: • Automating manual/repetitive tasks • AI-powered workflows & chatbots • Scrapers, dashboards, and internal tools • Data organization & research If anyone here has a project or task where I could help out (or if you can point me in the right direction), I’d be super grateful Let’s connect and build something valuable together – Ritvik

This community is amazing 🤩 I really amazed by those people's kindness, their efforts for helping others, no one is jealous of others, just appreciations and instructions. 🗿🔥 Let me know what are the thought of yours? 🤩

Automation destroys specific jobs (displacement effect), but it also makes everything cheaper, raises real incomes, and boosts demand for new goods, services, and industries (productivity effect). Historically, the second effect has always dominated, creating more jobs overall than it eliminates—hence the paradox: machines keep replacing workers, yet long-term unemployment has not risen. The current AI wave looks faster and more disruptive, but the same economic logic holds: net job creation is likely, though with painful short-term dislocations, greater inequality, and a need for serious policy intervention. Bottom line: automation is a job-killer and a job-creator at the same time—and history says the creator wins.

As of December 22, 2025, the AI landscape is buzzing with several notable developments. Here's a roundup of the top updates from today and the past few days: Duke University AI Breakthrough — Researchers unveiled a new AI system that uncovers simple, interpretable rules in highly complex systems (e.g., physics, biology, climate models). It reduces thousands of variables into compact equations while preserving accurate behavior — a major step for explainable AI in science and engineering. Chinese AI Firm MiniMax IPO — The Alibaba-backed company plans a Hong Kong IPO in early January 2026, potentially raising up to $700M. MiniMax's multimodal models (text, audio, images, video, music) have seen user growth from 3M in 2023 to 27.6M by September 2025. HTC's Open AI Smart Glasses — HTC is pushing an open-platform strategy with its VIVE Eagle AI glasses, allowing users to choose any AI model — contrasting closed ecosystems like Meta's. Insurance AI Patent Dominance — State Farm, USAA, and Allstate hold 77% of AI patents among insurers since 2014, with generative AI filings surging to 31% recently. AI Bubble Concerns — Analysts are debating if the AI boom (with massive investments in data centers and models) is nearing a turning point, amid reports of concentrated power and uneven global access. OpenAI Updates — Recent releases include GPT-5.2-Codex for advanced coding/cybersecurity, plus an Academy for news organizations to integrate AI ethically. Broader Trends — Discussions around agentic AI, verifiable models, and infrastructure (e.g., Moore Threads' new chips challenging Nvidia) continue to heat up. The field is moving fast — from explainability and hardware competition to ethical integrations