GPUs and memory prices are at ATH, and I don't see any reason for them to slow down anytime soon. Owning intelligence has become a high luxury. Those who call AI a bubble really have no idea. The "bubble" will come at some point, but we're nowhere near there. And all those anti AI people who are "sick of it" are going to be left behind and be sorry later that they missed the train. You either join it, or others will beat you. SIMPLE. Evolution at its best.

GPUs are aging like fine wine, with rental rates up across the board since January 1st Approximate change YTD: - H200: +160% - B200: +120% - RTX PRO 6000: +65% - H100: +35% Even the 6-year-old A100 rents for more than it did at the start of the year Charts of the Week:

GPUs are expensive and setting up the infrastructure to make GPUs work for you properly is complex, making experimentation on cutting-edge models challenging for researchers and ML practitioners. Providing high quality research tooling is one of the most effective ways to improve research productivity of the wider community and Tinker API is one step towards our mission there. Tinker API is built on top of our experimental results on fine-tuning with LoRA: Beta starts and you can join the waitlist today:

96 GPUs in under 24 hours with zero waiting. That's what it took for @wonderaai to go from compute-constrained to shipping. 64 H100s and 32 H200s rapidly provisioned on @ionet. Not queued for months on a waitlist. The results: - 200,000 users in 4 months, across 171 countries - 50% month-over-month growth - Launched 3 months ahead of schedule This is what happens when your compute keeps up with how fast you can build.

Idle GPUs waiting on hard drives are burning capital, says @wd_corporation SVP Tim Rausch. At AI Infra Summit 2026, @MattKimball_MIS spoke w/ Rausch about why storage may determine how far AI can scale. They are targeting: -60-terabyte drives by 2028 -100-terabyte drives by 2030 -Read/write technology delivering up to 8x today’s throughput $WDC