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"The bottleneck is less electrons, it's delivered data center capacity." CoreWeave cofounder brannin mcbee says power isn't their main bottleneck:

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CoreWeave cofounder brannin mcbee says older GPUs and servers still have strong demand, even as new generations ramp up: "Our pricing on Ampere went up during 2025, and our pricing on Hopper stayed within 10% or so of where we started the year." "Why is that happening? I think it's largely driven by inference and the idea that—not every workload needs the latest, greatest GPUs or servers." "There are different types of workloads that need different compute, and the market is efficiently pairing the right GPUs and servers with the workloads that need them." "We see incredibly robust demand all the way back to the Ampere generation, which I believe is six years old at this point."

CoreWeave cofounder brannin mcbee says older GPUs and servers still have strong demand, even as new generations ramp up: "Our pricing on Ampere went up during 2025, and our pricing on Hopper stayed within 10% or so of where we started the year." "Why is that happening? I think it's largely driven by inference and the idea that—not every workload needs the latest, greatest GPUs or servers." "There are different types of workloads that need different compute, and the market is efficiently pairing the right GPUs and servers with the workloads that need them." "We see incredibly robust demand all the way back to the Ampere generation, which I believe is six years old at this point."

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Not long ago, a bitcoin mine. Today, Helios is an operational AI data center. First data hall delivered to CoreWeave at Helios — Galaxy's data center campus in West Texas, approved to support up to 1.6GW of capacity and one of the largest developments of its kind in North America. We're just getting started.

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Atreides Management's @gavinsbaker says the bottleneck trade is nearing its end. "That was the game for the last year. The next game is what has enduring franchise value on the other side of these bottlenecks, whenever that is."

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We think AI is the bottleneck. Ashfaq Munshi says the real choke points are underneath it — wasted GPUs, heat, power, and an aging grid.

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It's easy for robots to nail a demo. It's much harder to get them to work reliably in the real world. The bottleneck is data. At Axis Robotics we're building a compounding data engine that combines simulation, ego-centric data and DAgger correction data at scale. Watch our CEO ChrisF(✱,✱) break down the data bottleneck, why messy data can still train good models, and what it takes to get robots out of the lab with blocmates. ⬇️

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Flapping Airplanes co-founder Asher Spector explains why data efficiency is the greatest bottleneck to AI adoption: "To the extent that AI has been hard to integrate into the economy, I really think it's because models are much less data-efficient than humans. If you want it to learn a new task, or put it in a new vertical, it takes thousands of times more effort than it does to just tell a human what to do." "If you can make a model a million times more data-efficient, it's a million times easier to put into the economy. There's a ton of cool stuff that you can do in really data-constrained regimes. For example, whether it's robotics, or scientific discovery, or even something like trading, these problems have very limited data, and existing AI systems aren't quite as good at them as they are at other things. I think that learning to learn with less data is just tremendously valuable in all of these domains."

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Bloomberg reported 50% of data center projects have either been delayed or canceled. CoreWeave CTO Peter Salanki says the demand is actually surging: "If you see someone canceling something, it's not because of demand, isn't there. It's kind of the opposite. They have decided they need to build something twice as big. Three times as big and somewhere else."

Bloomberg reported 50% of data center projects have either been delayed or canceled. CoreWeave CTO Peter Salanki says the demand is actually surging: "If you see someone canceling something, it's not because of demand, isn't there. It's kind of the opposite. They have decided they need to build something twice as big. Three times as big and somewhere else."

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OpenAI member of product staff Alexander Embiricos describes the evolution of "Lord Bottleneck," an internal Codex loop developed by a single staff member that ultimately ended up creating a tight feedback and improvement loop for new user experiences: "This person on the growth team needed to figure out what experiments to run. And they needed to write code to run the experiment. Then they needed to analyze the experiment." "They started using Codex for each separate thing. So they had it run a bunch of analyses, interrogate the data, talk to Codex about the data. Then they would pick an experiment, and ask Codex to write the code. Then they would run the experiment, then ask Codex what the results of the experiment were. Then they would produce a deck." "All steps they were doing individually. They didn't start by saying, 'I'm going to automate this entire thing,' because that's hard and scary. They just started with using Codex to accelerate themselves." "Then, they started connecting all these things together into a giant skill. And one day, they just said [to Codex], 'Why don't you do this every morning?'" "They gave it a name: 'Lord Bottleneck.' Because it's solving the bottlenecks of friction for new users." "Now, every morning, Lord Bottleneck evaluates past experiments, looks at data, proposes some [new] experiments, and offers to the team to run the experiments. The team picks [what experiments to do]. Then Lord Bottleneck is like, 'Ok cool. Here's some code or whatever config that needs to be done,' runs the experiment, and they go and do the same loop the next day." "It's really serious value. I forget the numbers, but it's produced significant company value automatically through Codex."

OpenAI member of product staff Alexander Embiricos describes the evolution of "Lord Bottleneck," an internal Codex loop developed by a single staff member that ultimately ended up creating a tight feedback and improvement loop for new user experiences: "This person on the growth team needed to figure out what experiments to run. And they needed to write code to run the experiment. Then they needed to analyze the experiment." "They started using Codex for each separate thing. So they had it run a bunch of analyses, interrogate the data, talk to Codex about the data. Then they would pick an experiment, and ask Codex to write the code. Then they would run the experiment, then ask Codex what the results of the experiment were. Then they would produce a deck." "All steps they were doing individually. They didn't start by saying, 'I'm going to automate this entire thing,' because that's hard and scary. They just started with using Codex to accelerate themselves." "Then, they started connecting all these things together into a giant skill. And one day, they just said [to Codex], 'Why don't you do this every morning?'" "They gave it a name: 'Lord Bottleneck.' Because it's solving the bottlenecks of friction for new users." "Now, every morning, Lord Bottleneck evaluates past experiments, looks at data, proposes some [new] experiments, and offers to the team to run the experiments. The team picks [what experiments to do]. Then Lord Bottleneck is like, 'Ok cool. Here's some code or whatever config that needs to be done,' runs the experiment, and they go and do the same loop the next day." "It's really serious value. I forget the numbers, but it's produced significant company value automatically through Codex."

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Woman says GA power is taking her family's home and demolishing it to supply power to the current data center in Fayetteville.

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Mundo AI (Mundo AI) is building the world’s largest and highest-quality multilingual data library to help AI labs un-bottleneck their multilingual model development. Congrats on the launch Jason Liao, Naijide, @garrethleee & Kenneth!

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IN NEWS: Antimetal closes $20M in Series A funding "The mission of Antimetal is to simplify infrastructure." From co-founder and CTO Shreyas Doshi: "The bottleneck in software eng used to always be programming." "Now, it's deploying code, maintaining it, and making sure it scales." "Writing code is no longer the hard part, it's about operations and maintenance (going from 1 user to 1M)." "We go to companies, plug into their entire infra surface area (source code, cloud, ticketing system etc.), and try to understand why things are failing. We pull in data and give them these golden pathways about what's going on/why things happen."

IN NEWS: Antimetal closes $20M in Series A funding "The mission of Antimetal is to simplify infrastructure." From co-founder and CTO Shreyas Doshi: "The bottleneck in software eng used to always be programming." "Now, it's deploying code, maintaining it, and making sure it scales." "Writing code is no longer the hard part, it's about operations and maintenance (going from 1 user to 1M)." "We go to companies, plug into their entire infra surface area (source code, cloud, ticketing system etc.), and try to understand why things are failing. We pull in data and give them these golden pathways about what's going on/why things happen."

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