Fascinating conversation @GoogleDeepMind with @jack_w_rae and Francis deSouza (COO @googlecloud) on the frontier of AI and what it'll take to get to the next generation of deployments. Interesting thoughts from Jack on reasoning + interpretability and Francis on agentic trust.

What takes 6 months in San Diego happens in 1 week in San Francisco. My co-founder @trevorjtuttle noticed that San Diego investors scheduled months out despite having availability. Every SF investor wanted to meet immediately. We closed our entire round in one week for @CTGTInc in SF. Investors created unauthorized calendar meetings. Some showed up at our door unannounced. This outcome was uniquely possible here. The SF ecosystem's velocity creates momentum in days instead of months. For startups with ambitious technical goals, this compressed timeline becomes existential. Founders, the SF advantage is real.

10 years ago, I was a kid watching Google I/O amidst periodically disconnected household utilities. I was totally captivated by the nascent applications of AI on display and trained rudimentary models on the aging hardware (an old laptop) I had access to. Today, I'm excited to announce @CTGTInc has raised $7.2M led by @GradientVC, Google's early-stage AI fund, to help enterprises scale AI beyond deep learning. The round is joined by distinguished investors including @generalcatalyst, @Liquid2V, and @ycombinator. We’re grateful to be supported by luminaries in AI, including @fchollet (Keras), @paulg (YC), @pwang (Anaconda), @mwseibel (Twitch), @mikeknoop (Zapier) and @wesmckinn (Pandas). We believe this is the most important problem to be working on today. Here's why: Since my undergraduate work, I’ve been obsessed with elucidating AI's unyielding demand for compute. AI models keep getting bigger, but the fundamental inefficiencies of deep learning remain. DeepSeek showed us that hyper-optimizing model training can push performance further, but scaling alone won’t fix the underlying problem, especially as timelines to AGI are hotly contested. This is what CTGT is solving. We've built a new kind of AI stack – one that removes the constraints of traditional deep learning by rethinking how models learn and train. It customizes, trains, and deploys models up to 500x faster with state-of-the-art accuracy on a wide variety of tasks. All without requiring massive compute. Our AI deployment and quality platform has already been used by Fortune 10 enterprises to gain more control over their AI models in real-world environments. Now, we’re expanding access to more enterprises looking to move AI from proof-of-concept to production. This is just the beginning of our journey in creating the next generation of truly intelligent AI: built from the ground up to be trustworthy and efficient, dynamically adapting to your needs. If you're interested in working at the forefront of intelligence, join us.

"[the] biggest bottleneck for AGI is compute" -@sama in our convo at the @ycombinator AI Retreat Spoke to top AI companies and leaders about "AI Beyond Deep Learning", with @CTGTInc bringing the 500x efficiency over SOTA methods needed for enterprise AI