Swift Compute

Swift Compute delivers high-performance GPU infrastructure optimized for AI workloads at a fraction of the cost of major cloud providers.

[Swift Compute @swiftcompute]

Swift Compute is running a short anonymous 2026 study on AI compute realities from practitioners' POV.

Should only take you 4–5 min to complete and your input would help shape some solid insights.

https://t.co/lJDsJFgrNR

[Swift Compute @swiftcompute]

One-click persistent GPU workstation on Swift Compute.

H100 80GB • 128GB RAM • 1TB NVMe
→ Open in VS Code or Jupyter instantly
→ 95% GPU util while I’m working

No more fighting with SSH, drivers, or spot instances. Just a proper dev environment that stays ready.

Pre-product but already better than most production tools I’ve used.

#GPUWorkstation #DeveloperExperience #SwiftCompute

[Swift Compute @swiftcompute]

Swift Compute dashboard at a glance.

• 12 GPUs running (4×H100 + 8×A100)
• 98.7% utilization
• Avg cost just $0.89/hr — 58% below market
• 4 active training jobs

Everything feels smooth and real-time. Still pre-product, but the foundation is already strong.

#SwiftCompute #GPUCloud #AIInfrastructure

[Swift Compute @swiftcompute]

8×H100 cluster on Swift Compute hitting:

→ 97.4% GPU utilization
→ 148k tokens/sec 🔥
→ 4h+ stable

Early days (still pre-product) but the cluster UI and performance are already looking clean.

Who else is running big inference/training workloads?

#AI #GPU #LLM #SwiftCompute

[Swift Compute @swiftcompute]

We only want your infra problems guys!

[Tom Boyle @tomlikestocode]

bro still took the time to fill out my form :/

[Elon Musk @elonmusk]

Over 500 rocket landings now

[Swift Compute @swiftcompute]

Swift Compute is running a short anonymous 2026 study on AI compute realities from practitioners' POV.

Should only take you 4–5 min to complete and your input would help shape some solid insights.

https://t.co/lJDsJFgrNR

[Lukas Ziegler @lukas_m_ziegler]

Autonomous humanoid navigation with depth cameras! 🧭

@RealSenseai, @LimX_Dynamics, and NVIDIA Robotics demonstrated autonomous humanoid navigation at NVIDIA GTC using RealSense depth cameras.

Unlike wheeled robots that move across a continuous plane, humanoids move through full three-dimensional motion with constant ground contact.

Each step introduces uncertainty from foot slip, changing contact points, dynamic balance shifts, and complex multi-joint articulation. Motor encoder data alone cannot reliably determine position. Even small motion errors accumulate quickly into localization drift. This has historically limited legged robots to teleoperation, supervision, or controlled environments.

Rather than relying solely on internal encoder measurements, the LimX Dynamics robot uses visual perception as an external reference for its position in the world. This significantly improves localization stability and navigation reliability.

Dense 3D perception from RealSense allows humanoids to detect stairs, curbs, elevation changes, uneven terrain, clutter, dynamic obstacles like people and carts, and clearances around limbs and body motion.

RealSense provides dense depth sensing optimized for close- and mid-range perception, low-latency RGB-D data for real-time robotics applications.

~~

♻️ Join the weekly robotics newsletter, and never miss any news → https://t.co/GoA3ZuwoPB

[Damian Player @damianplayer]

this is nuts!

Mark Cuban just said something every young person should hear.

AI agents are GOING to run through every small and mid-size business in the country.

not a single one of those owners will know how to build them.

his advice is to learn claude. learn agentic workflows. just learn AI and how it works.

then go to these businesses and help them because they won’t know how to do any of this shit.

they have money to spend. they have deep problems.

they don’t have you!

[CyberRobo @CyberRobooo]

Insane

Another superhuman hand: Beijing LinkerBot’s Linker Hand L30.

Ultra fast rotation, pinpoint precision control.

When a humanoid robot’s hand breaks through the limits of human anatomy, this hand doesn’t just operate tools…

it itself becomes a highly productive tool.

[The Humanoid Hub @TheHumanoidHub]

China’s first robot-assisted home cleaning service

X-Square Robot has partnered with 58[dot]com to bring cleaning robots into consumer homes.

58[dot]com is often referred to as "China's Craigslist".

Human workers collaborate with the robots: humans take care of the more complex tasks, while robots handle repetitive chores like tidying spaces or wiping surfaces.

X-Square Robot’s WALL-A system unifies perception, decision-making, and action into an end-to-end AI foundation model. Real-world experience from the pilot program will be valuable in helping the AI improve and learn to perform more tasks.

@XSquareRobot is backed by tech giants like ByteDance and Alibaba.

[el.cine @EHuanglu]

crazy.. OpenClaw generates video on Seedance 2, import into premiere pro and edit.. all by itself

[Mistral AI @MistralAI]

Today, we’re introducing Forge, a system for enterprises to build frontier-grade AI models grounded in their proprietary knowledge.

🌎 Forge bridges the gap between generic AI and enterprise-specific needs. Instead of relying on broad, public data, organizations can train models that understand their internal context embedded within systems, workflows, and policies, aligning AI with their unique operations.

We have already partnered with world-leading organizations, like ASML, DSO National Laboratories Singapore, Ericsson, European Space Agency, Home Team Science and Technology Agency (HTX) Singapore and Reply to train models on the proprietary data that powers their most complex systems and future-defining technologies.

[Swift Compute @swiftcompute]

Speed wins the benchmark.

Stability wins the workload.

Swift Compute delivers both.

[Swift Compute @swiftcompute]

Most chase bigger chips.

We chase smarter systems.

Swift Compute turns raw GPU power into dependable throughput.

[Swift Compute @swiftcompute]

Hardware peaks. Orchestration scales.

Swift Compute is for teams who care about both performance and predictability.

[Swift Compute @swiftcompute]

@yasuotabei That poster must be insane if it summoned a whole raid boss crowd like this.

[Swift Compute @swiftcompute]

@teortaxesTex …all cosplaying the same guy in different outfits

[Swift Compute @swiftcompute]

Teams squander fortunes on MIG isolation, while clusters sit idle at just 60% capacity. Here's the untold secret:

Time-slicing can triple your utilization without dragging down latency for most workloads. Yet, infrastructure teams opt for costly over-provisioning, fearing the risks of shared GPUs.

The true cost lies not in the hourly fee but in the unseen inefficiencies. Think GPUs twiddling their silicon thumbs waiting on I/O, invisible scheduler races, and memory transfers that dashboards misleadingly label "healthy."

You're not just shelling out for compute. You're funding infrastructure that deceives you about what's truly going wrong.

[Swift Compute @swiftcompute]

@it_unprofession It's wild how many tech careers are built on one lucky moment and a lifetime of staying just far enough ahead of questions.