Inside the build in Columbus, Georgia. Axe Compute President Kyle Okamoto gives a look at the work underway to bring our 288-node @nvidia Blackwell B300 cluster online. Containment is being finished. Cabling is underway. And the cluster is designed to scale to roughly 3x its current size in the coming months. #AIInfrastructure #AIDatacenter #NVIDIA #Blackwell

AI infrastructure is about more than powering AI applications. It can help accelerate innovation in areas that matter most, including cancer research. Chris explained how Axe Compute’s former cancer research division has transitioned to @DataMEDSAI, a company expert in using AI to advance innovation in cancer research. He then emphasized how greater access to AI compute is critical in helping researchers and organizations tackle complex problems, such as finding cures to diseases like cancer, as quickly as possible. Watch the full interview: piped.video/x42YMOubH9w #AxeCompute #AI #AIInfrastructure #CancerResearch

AI factories aren't just about GPUs. They’re about connecting and moving data at scale. Axe Compute President Kyle Okamoto breaks down how @nvidia InfiniBand enables GPUs to communicate as if they were physically connected, with ~6.4 Tb/s of bandwidth. The environment also supports 20+ PB of high-speed storage. Watch the full video walkthrough: piped.video/r_N1Z5Jmxs4 #AxeCompute #AIInfrastructure #AIFactory #NVIDIA #Blackwell

AI software gets the headlines. But AI doesn’t run on software alone. It runs on power, data centers, racks, GPUs and the physical infrastructure that brings massive compute capacity online. That’s the market Axe Compute is built to serve. 🎥 Full video: piped.video/watch?v=qExyf-9W… #AI #AIInfrastructure #Compute #DataCenters

The AI infrastructure challenge isn’t just demand. It’s execution. As Kyle Okamoto discusses with @peacelonge_onX, scaling AI compute requires bringing together power, space, financing, GPUs and deployment at the speed customers need. Thanks to Peace for the conversation and for highlighting the infrastructure work happening behind the AI boom. Read the full story in @TheStreet: thestreet.com/investing/stoc…

According to a paper presented in 2024, ByteDance's MegaScale reached only 55.2% Model FLOPs Utilization training a 175-billion-parameter model across 12,288 GPUs. The fix? MegaScale's 1.34x improvement over the Megatron-LM baseline came entirely from network and communication engineering: routing changes, congestion tuning, topology redesign. Axe Compute Build stands up dedicated clusters to your exact specification, bare metal and single tenant. We configure and scale with you. Full analysis: axecompute.com/infiniband-vs…

How much AI infrastructure do you really need? @duostech CEO Doug Recker explains why 20–30MW deployments can balance speed, efficiency and scalability while getting AI infrastructure online faster. The AI compute race is also a race to deploy. 🎥 Full earnings call: piped.video/watch?v=qExyf-9W… #AI #AIInfrastructure #DataCenters #Compute

Axe Compute is getting noticed. @TheStreet takes a closer look at our AI infrastructure transformation, customer contracts, GPU deployments, and the growing demand for dedicated AI compute. Featuring insights from CEO Christopher Miglino and President Kyle Okamoto. Read the full story: thestreet.com/investing/stoc… #AxeCompute #AIInfrastructure #AI

Today we announced the sale of Helomics, our Pittsburgh-based AI oncology business, to DataMEDS AI (NASDAQ: MEDS). With this step complete, our team, capital, and operations are dedicated entirely to one goal: meeting the accelerating demand for AI compute. We are fully committed to delivering best-in-class AI compute infrastructure, giving enterprises choice across hardware, geography, and deployment speed through Axe Compute Access and Axe Compute Build. Read the full announcement: investors.axecompute.com/new…

Axe Compute is at the @HCWCO 28th Annual Global Investment Conference in New York. CEO Christopher Miglino is sharing our vision for the infrastructure powering the next wave of AI. AI needs more than models. It needs compute. #HCWConference #AIInfrastructure #AxeCompute

According to research on voice AI latency, callers expect a response within roughly 300 milliseconds, the natural pause length in ordinary human conversation. When that line is crossed the conversation feels broken, even when the answer is correct. Other research on voice AI shows that the median time-to-first-token is near 500 milliseconds, which does not include speech recognition and synthesis. Voice AI teams are looking for their own dedicated infrastructure to fill that gap. Axe Compute Build stands up dedicated clusters to the exact spec a voice workload needs, bare metal and single tenant. Full analysis: axecompute.com/voice-ai-real… Reserve capacity at portal.axecompute.com

Training is an event. Inference is a utility. That distinction defines infrastructure planning. Gartner reports global inference spending hit $23.3 billion in 2025, overtaking the $19 billion spent on training, according to CIO Dive. Deloitte's November estimate goes further: inference already accounts for half of all AI compute in 2025, rising to two thirds in 2026. At CES 2026, Lenovo's Ashley Gorakhpurwalla told Computerworld his company now forecasts an 80/20 split favoring inference, a full reversal from the last buildout cycle. Training has a start date and an end date. Inference grows with every new customer. Enterprises that size infrastructure with a training mindset overbuild for peak and underbuild for sustained load. Axe Access provisions the latest GPUs in as fast as 48 hours across numerous global locations, built for exactly this kind of continuous, usage-driven demand. Axe Build stands up dedicated capacity, bare metal and single tenant, when that continuous load needs its own dedicated footprint. Full analysis: axecompute.com/inference-shi… Reserve capacity at portal.axecompute.com.

Thank you, @weka. We’re proud to bring together technology from trusted providers like WEKA with @nvidia Blackwell B300 compute as we build production-ready AI infrastructure projects designed for demanding, large-scale workloads. #AGPU #AIFactories #AIinfrastructure #AxeBuild

The choice where your GPUs should be located determines chip access, power availability, and legal jurisdiction. According to Epoch AI's dataset of AI supercomputers, the United States holds about 75% of tracked global computing power. China holds roughly 15% in the same dataset. Europe does not register as a standalone top-tier bloc. Axe Compute gives clients choice across hardware, geography, and deployment speed. Through Axe Access and Axe Build, the client specifies the requirement and we source, configure, and scale to match it. Full analysis: axecompute.com/us-china-euro… Reserve capacity at portal.axecompute.com or write to info@axecompute.com.