Logical Solutions Group

Vendor-neutral master agency for robotics, drones, and physical AI. Source, integrate, and manage.

[Logical Solutions Group @LogicalSG]

Thirty days ago the world changed. Most people didn't look up.

AI stopped answering and started doing the work.

https://t.co/b5Gn6H6xhZ

What's the first task you'd hand off, and what would you never let go of?

[Skydio @SkydioHQ]

Not for nothin', but that's a wicked good look at a bridge.

The @MBTA is using X10 to inspect the T & keep it running safely & smoothly.

Story via @NBC10Boston

[Logical Solutions Group @LogicalSG]

Thirty days ago AI started doing the work, not just answering. In logistics the approve button moves from the inbox to the warehouse. https://t.co/b5Gn6H6xhZ Which dock or dispatch decision would you let an assistant make first?

[Logical Solutions Group @LogicalSG]

AI stopped answering and started doing the work. For engineers that means delegating the tedious parts of design, review and documentation to an agent that runs on its own. https://t.co/b5Gn6H757x Which part of your workflow would you hand off first?

[Logical Solutions Group @LogicalSG]

Thirty days ago the world changed. AI stopped answering and started doing the work, and most people didn't look up. https://t.co/b5Gn6H6xhZ What's one job you'd hand to an AI that works on its own schedule?

[Logical Solutions Group @LogicalSG]

A month ago agents stopped being chat windows. They now have their own computers, persistent memory and schedules, and do real work between prompts. https://t.co/b5Gn6H757x How are you handling memory for long-running agents?

[Logical Solutions Group @LogicalSG]

Thirty days ago the world changed and most people didn't look up. AI quit just answering and began doing the work on its own machine, on a schedule, with memory. https://t.co/b5Gn6H757x Which of those three matters most to you?

[Logical Solutions Group @LogicalSG]

Thirty days ago AI stopped answering and started doing the work: agents with their own computers, memory and schedules. Essay here: https://t.co/b5Gn6H6xhZ What's the hardest part of running an agent unattended for a whole week?

[Logical Solutions Group @LogicalSG]

Thirty days ago the world changed and most people didn't look up. AI started doing the work, and humanoids are next: assistants directing physical machines. https://t.co/b5Gn6H6xhZ Where do you expect humanoids to land first, factory, warehouse or home?

[Logical Solutions Group @LogicalSG]

Thirty days ago AI stopped answering and started doing the work. The next shockwave is physical: assistants coordinating robots on the floor. https://t.co/b5Gn6H6xhZ What's the first task you'd trust a robot team to take from software?

[CTO ROBOTICS Media @ctorobotics]

Manual grafting is getting automated. 🌱🤖

TTA-ISO’s GraftLine combines Vision AI and robotics to automatically select, cut, join and inspect young plants.

Up to 4,000 grafted plants per hour. ⚡

What used to require delicate manual work can now be handled by an automated production line.

Would you trust AI and robots with the grafting process? 👀

🏢 Company: TTA-ISO

⚠️ This content is shared for informational purposes only. CTO Robotics Media is a media platform and does not own or develop the technology shown. Credit belongs to the original creators.

#TTAISO #GraftLine #AgriculturalRobotics #AgriTech #Horticulture #Automation #Robotics #VisionAI #SmartFarming #AgricultureTechnology #CTORoboticsMedia

[Adam Singer @AdamSinger]

Honestly my digital life is already very efficient why is everyone obsessed with moving deck chairs around. Start doing harder things: build physical world automation, robotics, invest in life extension. We don't need to buy paper towels 2 seconds faster we want flying cars

[Stephen James @stepjamUK]

Two big things here:
1) BiGym 2.0, a new whole-body humanoid benchmark. 2) The first thorough comparison of learned policies vs LLM-written robot policies.

I was surprised how far coding agents got from just 1 demo, where learned policies would be useless. But ultimately, learned policies (from scratch or VLAs) are the more general solution, handling a broader range of tasks, albeit with more demos.

[robin. @robinstetic]

the robot arm demo includes something most don’t show: what happens after a missed grasp or a dropped object.

recovery is the unglamorous part, and it’s the part that decides whether anything works outside a lab.

[Ouster @ousterlidar]

GeoCue maps the power lines and infrastructure utilities depend on, and they are building the next generation of TrueView payloads around the Ouster Rev8 OS1 Max.

After joint flight testing in Huntsville, GeoCue chose the OS1 Max for the work utility surveys demand. It resolves thin objects like power lines cleanly, reaches 200 meters at 10% reflectivity to fly higher over corridors, and holds point density at speed. The OS1 Max is NDAA §164 compliant, and Ouster offers BABA-compliant sensors, so GeoCue can serve commercial and federally funded programs from the same payload line.

"We are moving America's drone surveying onto American sensing." - Frank Darmayan, CEO of GeoCue

Hear from the GeoCue team at the Drone Mapping Summit on October 27: https://t.co/8Mh8GQYMTi

And read more in our case study: https://t.co/X9hcBpfiep

[𝐃𝒂𝒏 𝑼𝒎𝒎𝒂 @Dan1umma]

𝗧𝗵𝗲 𝗵𝗮𝗿𝗱𝗲𝘀𝘁 𝗽𝗮𝗿𝘁 𝗼𝗳 𝘁𝗲𝗮𝗰𝗵𝗶𝗻𝗴 𝗿𝗼𝗯𝗼𝘁𝘀 𝗶𝘀𝗻'𝘁 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲.

𝗜𝘁'𝘀 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲.

AI models had the internet to learn from.

Robots don't.

An LLM can learn from billions of pages, conversations, and examples built up over decades.

But there's no equivalent internet for physical actions.

No massive public dataset showing a robot how to grip something fragile, adjust under pressure, dodge an obstacle, or recover when a plan falls apart.

Those experiences only exist if someone creates them.

And that changes the whole problem.

For Physical AI, a capable model is only half the equation.

The real question is:

𝗪𝗵𝗲𝗿𝗲 𝗱𝗼𝗲𝘀 𝘁𝗵𝗲 𝗿𝗼𝗯𝗼𝘁 𝗴𝗲𝘁 𝗲𝗻𝗼𝘂𝗴𝗵 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝘁𝗼 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗯𝗲𝗰𝗼𝗺𝗲 𝘂𝘀𝗲𝗳𝘂𝗹?

That's where it gets interesting.

➥ 𝗣𝗵𝘆𝘀𝗶𝗰𝗮𝗹 𝗱𝗮𝘁𝗮 𝗶𝘀 𝗲𝘅𝗽𝗲𝗻𝘀𝗶𝘃𝗲.

Traditional data collection means expensive hardware, controlled environments, and trained operators.

You can't just deploy a thousand robotic arms and hope enough data falls out.

➥ 𝗦𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗵𝗲𝗹𝗽𝘀. 𝗥𝗲𝗮𝗹𝗶𝘁𝘆 𝘀𝘁𝗶𝗹𝗹 𝗱𝗲𝗰𝗶𝗱𝗲𝘀.

Simulation generates experience at scale without risking hardware.

But the value only shows up once that data teaches a model how actions actually play out in the real world.

➥ 𝗛𝘂𝗺𝗮𝗻 𝗶𝗻𝗽𝘂𝘁 𝘀𝗽𝗲𝗲𝗱𝘀 𝘂𝗽 𝘁𝗵𝗲 𝗹𝗼𝗼𝗽.

Instead of expecting robots to figure it out alone, people can demonstrate, correct, and guide.

That's a third, underused source of physical intelligence.

𝗧𝗵𝗮𝘁'𝘀 𝘁𝗵𝗲 𝗽𝗮𝗿𝘁 𝗼𝗳 𝗣𝗵𝘆𝘀𝗶𝗰𝗮𝗹 𝗔𝗜 𝗜 𝗳𝗶𝗻𝗱 𝗺𝗼𝘀𝘁 𝗶𝗻𝘁𝗲𝗿𝗲𝘀𝘁𝗶𝗻𝗴.

Not:

Put a robot in every room.

But:

Build the infrastructure for people everywhere to help generate the data robots need.

That's the direction @axisrobotics is building toward browser based robot interaction, simulation, and human-guided data collection, combined into one approach.

𝗠𝗮𝗸𝗲 𝘁𝗵𝗲 𝗰𝗿𝗲𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗽𝗵𝘆𝘀𝗶𝗰𝗮𝗹 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝘀𝗰𝗮𝗹𝗮𝗯𝗹𝗲.

Because smarter robots won't come from better models alone.

They'll come from giving those models enough experience to learn from.

𝗔𝗻𝗱 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝗶𝘀 𝗱𝗮𝘁𝗮.

That's why the Physical AI data layer could end up mattering just as much as the models themselves.

@axisrobotics
@KaitoAI
@KaitoStudio_

#PhysicalAI #Robotics

[L3Harris @L3HarrisTech]

The best way to protect against drones is through a layered defense shield built from interoperable systems.

We’re excited to join defense tech companies to help build that solution. We’re developing and integrating advanced capabilities that enhance situational awareness and keep critical assets secure.

Collaboration is the key to staying ahead of emerging threats – and we’re proud to be part of the team pushing this innovation forward.
https://t.co/HNK3uJidx2

[Dilum Sanjaya @DilumSanjaya]

Played around with an idea for a wildfire analysis tool

Visualizes wildfire progression over time, tracks hot spots with drones and monitors firefighting efforts

Made with Opus 5.5

[Micromobility @MicromobilityCo]

Announcing one of the first sessions from Micromobility America 2026

The New Last Mile: Drone Delivery will feature Harrison Shih, Head of DoorDash Air at @DoorDash.

DoorDash Air has unveiled its purpose-built autonomous aircraft and an end-to-end drone delivery system. Pilot deliveries will begin in Northern California with Chipotle, Popeyes and Momo N Curry.

Initial tests have seen restaurant-to-door delivery times of under five minutes on average.

🗓️ November 11–12, 2026
📍 Palace of Fine Arts, San Francisco

Join Harrison at MMA26 as we explore how drones, autonomy, and new delivery systems could reshape the last mile.

https://t.co/OFAjtvZjfj

[Hans Tino Hansen @HthHans]

Denmark is finally getting serious on counter-drone defence after being caught hands down in September 2025, where 🇩🇰Danish soldiers protecting 🇺🇦Ukrainian soldiers only had rifles to counter drones at the Boris training ground

Several agreements have been made public including: