BCGuy2010
4.1K posts





How can we make the migration from Gemini CLI to Antigravity CLI easier? One of my goals is to help folks move over as smoothly as possible. So far I am hearing the following gaps are holding people back... ACP, more robust headless mode, subagents, Gemini CLI extensions... anything else? I'll be working on some videos/resources this week so let me know where I can add clarity or details. 🧵I'll link a few existing resources


Introducing Ferrari Luce, the first electric Ferrari designed by LoveFrom.






Warning: The entire AI industry will likely be bottlenecked by two companies: 1. $AXTI ($700M) 2. $SMTOY ($31.7B) Which both control 60–70%+ of the world's InP substrates. Future $NVDA, $GOOGL TPU v7 pods, $META, $MSFT, $AMZN hyperscaler clusters require InP-based lasers and receivers. $AVGO, $LITE, $COHR use for EMLs for 800G/1.6T transceivers, DFB lasers, and other optical infra. Without InP substrates, the supply chain falters. After looking at TPU BOM to Maia BOM, it looks like future ASICs + GPUs + hyperscaler deployments are heavily reliant on photonics. And two vendors could freeze the global InP substrate market covering nearly all of: - Hyperscaler optics (TPU pods, etc) - Optical transceivers (5g, data) - LiDAR (robotaxis, drones, military) -Optical Modules (interconnect clusters) - Silicon photonics laser dies (Nvidia’s future co-packaged optics and Intel/Broadcom SiPh engines use InP CW laser arrays.) Since these companies make up majority of the market supply: -AXTI (est. ~30–35%) -Sumitomo (est.~30%) - JX Nippon (est. 10-15%) That’s it. (eg. 2021 industry note from Yole states that "Sumitomo Electric + AXT together had “more than 75%” of the InP substrate market") Hyperscalers/AI are moving toward photonics but the entire AI industry is fragile. If either $AXTI or $SMTOY stop supplying materials, the entire future AI buidlout gets crippled. It's even crazier that a $700m company could become the the center of it all. InP substrate will likely one of the biggest bottlenecks alongside HMB as the AI industry shifts to photonics.















$SNDK controlled pullback on low volume. Although short, and only 6 bars long, Sandisk just has been the liquid leader of the last year. First tap of the 20-DSMA as well.




📣Meet Qwen3.7-Max — our latest flagship, made for the Agent Era. A versatile foundation for agents that actually get things done: 🧑💻 Coding agent, end to end. Frontend prototypes, multi-file refactors, real debugging — nails it. 🗂️ A reliable office and productivity assistant. Get your work done through MCP integrations and multi-agent orchestration. ⏱️ Long-horizon autonomy. 35 hours straight on a kernel optimization task — 1,000+ tool calls, zero hand-holding. 🔌 Scaffold-agnostic. Claude Code, OpenClaw, Qwen Code, or your own stack. Consistent reliability everywhere. API's up on Alibaba Model Studio. You can also take it for a spin on Qwen Studio. Go build something wild!🏃🏃♂️ 📖 Blog: qwen.ai/blog?id=qwen3.7 ✅ Qwen Studio: chat.qwen.ai/?models=qwen3.… ⚡️ API:modelstudio.console.alibabacloud.com/ap-southeast-1…

Gemini 3.5 Flash ranks #1 on the APEX-Agents-AA benchmark, outperforming much larger models a whole size above it.


