The AI race is quietly shifting… from models to chips. At first, it might sound like just another update. But it actually signals something bigger. Until now, most AI companies have depended heavily on external hardware providers.Moving towards in-house chips means more control over performance, cost, and scale. At the same time, Anthropic is still expanding infrastructure partnerships with companies like Google-showing that this isn’t a replacement, but a long-term strategy. Feels like we’re entering a phase where:→ AI companies don’t just build models→ they start owning the entire stack From software… to infrastructure. Still early, but this could define the next layer of competition in AI.

This release is part of Meta’s bigger plan to integrate smarter AI directly into the apps billions of people already use every day - Instagram, WhatsApp, Facebook, and Messenger. Instead of building standalone AI apps, they’re focusing on making AI more practical and seamless within the platforms we open multiple times a day. Muse Spark is designed to handle tool use, visual reasoning, and more complex multi-step tasks, aiming to move beyond simple chat responses toward actually useful assistance in real-life scenarios. It feels like Meta is shifting from “let’s add an AI chatbot” to “let’s make AI quietly helpful everywhere in our ecosystem.” A clear step in their long-term strategy for deeper AI integration.

A simple prompting trick is getting a lot of attention right now. A developer shared that by forcing shorter, stripped-down responses (no extra explanation, no fluff), they were able to reduce Claude’s output token usage by up to 75%. If this is true, it’s a big deal. Because in AI systems, fewer tokens = lower cost + faster responses. The idea is simple: - Don’t let the model over explain. - Guide it to be direct and concise. This also shows something important- Sometimes it’s not about better models, it’s about better prompts. Small changes → big impact. Curious to see how this evolves and how many people start optimizing prompts for cost, not just output.

Hey there. I've owned several businesses in the past. I have excelled in lead Gen, appointment setting and sales/closing. I have business consulted in the past. I'm pretty basic with AI besides a lot of ChatGPT convos lol I think AI consulting would be perfect for me. What's the fast track for learning 1 skill that I can gain and start selling it immediately? Finding clients and closing them won't be an issue. I'm lacking AI skills. Thanks!

Hello AI Friends! I'm Kirsty, 👋I"ve been dabbling with AI for the past 6 months or so. I am amazed by the world of opportunity it is creating! I'm currently searching for a new career path (having left a high stressed corporate role recently). My background is rooted in hospitality management and CRM administration. I'd love to use the experiences gained in that industry to leverage AI, but stumped right now for ideas! Im excited for the summit to meet folks at a similar stage of their AI career path, to continue learningand discover all possibilities!