

Michael Celia
1K posts

@mcelia
Lead Software Engineer (Enterprise Data) @ Triumph Financial 🔥 | Founder @precisionalgo 🚀 | Avid Chess Player ♟️ | ML Engineer before LLMs 🤖





Four Intel Arc Pro B70s in one box: 32GB of GDDR6 each, 128GB total, about $4,000 in GPUs. In our testing the quad setup more than doubles the DGX Spark and only trails a single RTX Pro 6000 that is much more expensive. Full review on the site. #IntelArc #GPUs #AIHardware @intel





AI is becoming a real budget line in the enterprise. The question isn’t who deployed the most copilots. It’s who gets the most useful work per token. As AI becomes more agentic, token efficiency becomes an architecture issue. In our benchmark testing with Claude Cowork, Glean’s remote MCP server was preferred ~2.5x more often than off-the-shelf MCP tools. Those tools used ~30% more tokens on average — and on winning outcomes, nearly 2x more: ~83K vs. ~43K. The goal isn’t less AI. It’s more useful work per token.





