Saphira AI

Validation Factory for Physical AI - Safety, Security, Quality, Performance, Assurance

[Akshay Chalana @Ac2zoom]

1/ Since everyone's been generating Blender CAD models of houses, factories, and engines with Astra, we figured it would be interesting to see how it does on some of the scenario generation tasks we help our customers with at @Saphira_AI! Check it out:

[Brett Adcock @adcock_brett]

Yesterday, Figure announced it will be working with Nscale to deploy up to 100,000 GPUs on the NVIDIA Vera Rubin Platform

I’m excited to be working with Josh and the Nscale team

[Lukas Ziegler @lukas_m_ziegler]

Balloon-powered robots! 🎈

Surely one of the coolest and craziest robot project I've seen this year.

Buoyant Choreographies by RoMeLa is a fun art project shown at ICRA in Atlanta last year.

It uses special robots made from helium balloons and moving legs that float and walk around.

People can play with the robots using touch, game controllers, or even by blowing air.

The robots react by changing colors, moving differently, and showing emotions.
@DennisHongRobot, that's so cool, what's next?! 🤯

Here's the paper behind it: https://t.co/jDQESthPvS

~~

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

[Lukas Ziegler @lukas_m_ziegler]

The robot flipped a pancake nobody taught it! 🥞

@SkildAI team assumed pancake flipping had to be somewhere in the training data.

So they searched. Millions of hours of pre-training data.
Nothing.

S1 inferred the whole task from a single human demonstration.

That's their new general robot model, built as an in-context learner from the ground up.

Every new robot task today starts with days of teleoperation and a fine-tuning run on a specialist policy. S1 skips all of it.

Much like a language model, it never updates its weights to learn a new task. The demonstration enters the context window, and the policy uses it to decide what to do next.

→ Ten-minute tasks it was never trained on, composed from primitives learned in pre-training: a new style of coffee, potting a plant, frying pancakes.

→ Soil and pots arrived at their office at 8:54 PM. The robot was running the task autonomously by 9:27 PM.

→ Slide objects away mid-reach, swap them, change the lighting, it still finishes.

→ The prompt waters a plant with a watering can, but only a cup is available. It uses the cup.

It doesn't rigidly replay what it saw, but it recovers from its own errors, and sometimes executes with more precision than the demonstrator, when the human fumbles an egg and makes a mess, S1 performs the same step cleanly.

The demonstration is a specification of the goal, and not a trajectory to copy.

On unseen tasks after 100K hours of pre-training: language-prompted VLAs reach 9%. Their new model reaches 66%.

It's already deploying with industrial partners, with a wider rollout over the coming months.

Congrats @deepakpathak and team behind this! 😮‍💨

🔗 Link to their latest blog: https://t.co/GoZ5PyuYcn

~~

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

[Saphira AI @Saphira_AI]

We're thrilled to share that we're now SOC2 compliant 🎊
This marks a major step towards ensuring data security & integrity 🏆
Shoutout to @SprintoHQ for powering this journey. #SecuredbySprinto

[Saphira AI @Saphira_AI]

4/ Semantic synthetic failure data and sim2real alignment let any robotics team start on its own world models, like @physical_int, @SkildAI, @RhodaAI, and @GeneralistAI. Early partners only for now: reach out.

[Saphira AI @Saphira_AI]

1/ Dozens of the world's leading robotics and autonomy companies use Saphira to produce hazard analyses, fault tree analyses, and FMEAs. But these teams aren't facing the same problems they were two years ago.

[Saphira AI @Saphira_AI]

3/ Here a hazard becomes a measured run in @nvidia's Halos Outside-In Safety SIL environment. Saphira's agentic generator finds the failure mode and evaluates perception against it. ~83s on an L4.

[Lukas Ziegler @lukas_m_ziegler]

🚨 BREAKING:

@GravisRobotics has raised $200M in the largest Series A in construction robotics history, led by SoftBank! 🔥

Spun out of ETH Zürich in 2022. Three years later, $200M and SoftBank backing.

The company is bringing autonomous AI to the most physically demanding machines on earth. Excavators. Heavy construction machinery. Equipment that hasn't fundamentally changed in 50 years. 🚜

Most physical AI operates in static worlds. Self-driving cars navigate around obstacles. Warehouse robots move objects across fixed floors. Everything stays where it is.

An excavator does the exact opposite.

It works by intentionally crashing into the environment, breaking apart soil with hidden rocks, reshaping the earth with every single pass of the bucket.

The world changes with every action the machine takes.

→ Gravis AI doesn't navigate a static world, it actively takes the world apart and puts it back together
→ Models trained on billions of cubic yards of simulated earth, from soft clay to rock-filled soil
→ Generalises across different machine manufacturers — not locked to a single platform
→ Brings factory-floor precision to historically unpredictable civil jobsites

The macro case is overwhelming. Energy networks, data centres, housing, transit, climate infrastructure, all of it requires construction at a scale the existing workforce cannot deliver.

Construction is the primary bottleneck of the entire physical AI economy.

The same AI boom driving demand for data centres is now funding the robots that will build them.

Europe keeps producing world-class deep tech. 🇨🇭🇪🇺

To the team behind this, MASSIVE CONGRATS!

Can't wait to publish what we have created onsite with Gravis team! 🫶🏼

~~

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

[Saphira AI @Saphira_AI]

Physical AI doesn't just need better models.
It needs a Validation Factory.
Change the robot →
update the hazards →
regenerate simulation scenarios →
rerun the right tests →
update certification evidence.
That's a much bigger problem than "AI writes safety documents."

[Jake @JustJake]

Amazing

Now tell me how you’re gonna dissipate that much heat in a vacuum

[Saphira AI @Saphira_AI]

1X is building the future of humanoid robots 🤖

We helped them turn a strong safety culture into fast, structured risk insights—without slowing down dev.

Read how we partnered to accelerate market readiness:
🔗 https://t.co/ClCxGtY7Wc

[Saphira AI @Saphira_AI]

@1x_tech is building the future of humanoid robots 🤖

We helped them turn a strong safety culture into fast, structured risk insights—without slowing down dev.

Read how we partnered to accelerate market readiness:
🔗 https://t.co/ClCxGtYFLK

[Agility @agilityrobotics]

When it's time to charge, another Digit tags in. #TeamWork

[NVIDIA Robotics @NVIDIARobotics]

This #NationalRoboticsWeek explore the future of #robotics and #physicalAI with us.🤖

Stay tuned as we share the latest research and resources from us and the community. 🥳 https://t.co/keguTBkzqh

[Lukas Ziegler @lukas_m_ziegler]

🚨 BREAKING:

@Hyundai_Global to deploy tens of thousands of robots!

Hyundai is scaling up its robotics strategy with a major investment in @BostonDynamics ' robotic platforms. The company plans to deploy tens of thousands of units — including the Atlas humanoid, Spot quadruped, and Stretch trailer-unloading robots—across its manufacturing and logistics operations in the coming years.

Spot is already in use at Hyundai’s facilities, performing industrial inspection and predictive maintenance tasks. Atlas, Boston Dynamics’ bipedal robot, is next in line for factory deployment, aimed at addressing physically demanding and repetitive jobs.

Beyond deployment, Hyundai will support Boston Dynamics’ growth by integrating the automaker’s manufacturing capabilities to boost robot production. The move is part of Hyundai’s broader ambition to lead in robotics and “physical AI”.

That's so cool to see the scale-up phase with humanoids. Looking forward to seeing Atlas live in Boston this month. 🔥

[Saphira AI @Saphira_AI]

Saphira AI (YC S24) now auto-generates FMEA & template requirements from electrical schematic screenshots (e.g. KiCAD)! 🚀 Enhance safety analysis & accelerate certification for chips, motors, sensors, robots & vehicles. #AI #Safety #Tech https://t.co/eIZ4MHGQ0P

[borg™ @borgrobotic]

Borg 01 – our modular humanoid robot.
A key player in our industrial automation ecosystem.

A look at Borg 01 in action coming next month!

[Lethic @lethic1]

Real time teleop speed testing