Vertical integration can lead to a better cost structure for OpenAI clients.
Now that the mid to lower end models are increasingly being commoditised i think we will be seeing a price war soon in that space
Im a Fan of the key feature though, i think they should just roll that out regardless of rolling out the Username feature or not. Maybe make it 6 digit alpha numeric instead of 4 digit numeric.
@aryan34_35 Apart from lock-in's i think the real retention levers are going to be rapid product development and price.
Lock ins make customers feel a bit trapped and helpless but the other two should keep them genuinely happy
IT hardware buyers, heads up - HP raised prices 10% from April 1. Lenovo reprices any unshipped order after June 30. Check Point added 5% surcharge.
That's because, AI data centres are eating chip supply.
Indian IT teams that moved early in 2021-22 saved 18-25%, pattern repeats.
IT procurement is getting more expensive and complex in 2026. Key updates:
* Server & laptop prices up 15–20% (Dell, Lenovo, HPE)
* VMware renewals seeing up to 5x increases
* Microsoft M365 prices rising up to 33% in July
More in ProcEzy Weekly 👇
Hi Folks,
I've been speaking to a few Startups recently and seems like everyone has had some kind of challenge with IT procurement at some point.
Im curious - Whats the biggest issue you've faced while trying to buy IT hardware or software for your company ?
Trying to understand pain points from people who deal with this firsthand.
@garrytan@Replit@emergentlabs@Taskade Are people forgetting that it takes more than just coding a UI to running an app, especially something that's business critical and needs constant uptime.
Vibe code is great and all but you also need to host and maintain....cost of that vs the convenience of SaaS.
Model compression is where the real innovation is happening in AI engineering.
Smaller faster models designed to run in the edge is the precursor for affordable robotics at home.
Think having a modem sized personal assistant that stores all data in house and not in cloud, that would mitigate the privacy issues of having cloud connected AI devices as well.
Although googles TPU's are making massive progress, this post from NVIDIA clearly talks about how they are still very much ahead, a generation lead is a big deal and can take a year or so to catch up to, even with the resources of google. Such is the nature of the Hardware game.
But interesting times ahead and competition is getting hot.
We’re delighted by Google’s success — they’ve made great advances in AI and we continue to supply to Google.
NVIDIA is a generation ahead of the industry — it’s the only platform that runs every AI model and does it everywhere computing is done.
NVIDIA offers greater performance, versatility, and fungibility than ASICs, which are designed for specific AI frameworks or functions.
Google doubling down on TPU's shows how fast AI compute is fragmenting
If tpu's keep giving better price performance than gpu's then thos people who are tired of the nvidia monopoly will have a fun time.
AI hardware is finally getting some competition