Federal Reserve liabilities are spiking again and total assets held by the Federal Reserve have flattened, similar to February 2020
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President Trump says AI could be “much bigger than the internet” arguing that whoever leads the race will define the next era.
He added that the U.S. is currently “substantially No. 1” in AI.
He added that the U.S. is currently “substantially No. 1” in AI.
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President Trump says he will be ringing the stock market opening bells in the Oval Office on Tuesday.
This event is set to launch the "Trump Accounts" which are tax-advantaged investment accounts for children under 18, created under the One Big Beautiful Bill Act.
The U.S. Treasury deposits $1,000 for qualifying newborns, and families can add up to $5,000 annually. Funds generally remain locked in U.S. index funds until the child turns 18
This event is set to launch the "Trump Accounts" which are tax-advantaged investment accounts for children under 18, created under the One Big Beautiful Bill Act.
The U.S. Treasury deposits $1,000 for qualifying newborns, and families can add up to $5,000 annually. Funds generally remain locked in U.S. index funds until the child turns 18
🇨🇭 Global One SI - Prompt
How to invest in the AI/robotics gold rush (FULL GUIDE)
Anthropic LEAKS the optimal prompting structure for Fable 5.
This is how you save tokens while getting elite outputs
This is how you save tokens while getting elite outputs
✍1
🇨🇭 Global One SI - Prompt
The most expensive parts in humanoid robots are not the cameras. The real hardware cost is hidden in the parts that move, carry load, survive impact and repeat the same motion thousands of times without failing. Typical hardware cost range per humanoid robot:…
The humanoid robot race will be decided inside the supply chain.
A robot body looks simple from the outside.
Inside every movement depends on a stack of expensive fragile and hard-to-scale components.
• Actuator modules
➝ Convert software commands into controlled movement
➝ Drive shoulders, hips, knees, elbows, ankles and wrists
➝ Bad actuators mean weak motion, heat issues and short service life
• Dexterous hands
➝ Decide what the robot can actually do
➝ Picking tools, opening doors, carrying objects and handling small parts all depend on the hand
➝ A humanoid without useful hands is mostly a walking demo
• Harmonic drives
➝ Give precision inside the joint
➝ Reduce backlash
➝ Help the robot move smoothly under load
• Battery packs
➝ Set runtime, weight and deployment time
➝ Every extra kilogram affects balance walking efficiency and payload
➝ Long runtime is one of the hardest problems for real work
• Compute / GPU
➝ Runs onboard AI, vision, planning and safety logic
➝ The robot has to react inside the body, not only in the cloud
➝ Latency matters when the robot is walking near people
• Cameras & sensors
➝ Give vision depth balance and force feedback
➝ The robot needs to see the floor, detect objects and understand contact
➝ No perception means no useful autonomy
• Torque motors
➝ Put power inside every joint
➝ Compact motors are critical for hips, knees, shoulders and wrists
➝ More torque with less heat means longer useful operation
• AI data & training
➝ Turns teleoperation, simulation and real failures into better behavior
➝ Walking, grasping and tool use need massive task data
➝ The robot learns from the stack behind it
The market will reward the companies that can control the full body stack:
• joints
• hands
• sensors
• batteries
• compute
• training data
• manufacturing
• repair network
A robot body looks simple from the outside.
Inside every movement depends on a stack of expensive fragile and hard-to-scale components.
• Actuator modules
➝ Convert software commands into controlled movement
➝ Drive shoulders, hips, knees, elbows, ankles and wrists
➝ Bad actuators mean weak motion, heat issues and short service life
• Dexterous hands
➝ Decide what the robot can actually do
➝ Picking tools, opening doors, carrying objects and handling small parts all depend on the hand
➝ A humanoid without useful hands is mostly a walking demo
• Harmonic drives
➝ Give precision inside the joint
➝ Reduce backlash
➝ Help the robot move smoothly under load
• Battery packs
➝ Set runtime, weight and deployment time
➝ Every extra kilogram affects balance walking efficiency and payload
➝ Long runtime is one of the hardest problems for real work
• Compute / GPU
➝ Runs onboard AI, vision, planning and safety logic
➝ The robot has to react inside the body, not only in the cloud
➝ Latency matters when the robot is walking near people
• Cameras & sensors
➝ Give vision depth balance and force feedback
➝ The robot needs to see the floor, detect objects and understand contact
➝ No perception means no useful autonomy
• Torque motors
➝ Put power inside every joint
➝ Compact motors are critical for hips, knees, shoulders and wrists
➝ More torque with less heat means longer useful operation
• AI data & training
➝ Turns teleoperation, simulation and real failures into better behavior
➝ Walking, grasping and tool use need massive task data
➝ The robot learns from the stack behind it
The market will reward the companies that can control the full body stack:
• joints
• hands
• sensors
• batteries
• compute
• training data
• manufacturing
• repair network
🇨🇭 Global One SI - Prompt
Anthropic LEAKS the optimal prompting structure for Fable 5. This is how you save tokens while getting elite outputs
I found the cheat code for using Fable 5 without going broke.
Everything you need to know about cutting Fable token spend
Everything you need to know about cutting Fable token spend
✍1
🇨🇭 Global One SI - Prompt
How to invest in the AI/robotics gold rush (FULL GUIDE)
The robotics sector is about to completely take off.
Robotics is tracing the exact same growth curve as software AI, just a few years behind.
We are likely entering the beginning of exponential growth for this ecosystem.
At current capabilities, robotics intelligence is at the level of roughly GPT-2.
(Capable, but lacking real-world field deployment)
Things are about to change.
Manufacturing costs and the general robotics cost curve is rapidly declining (Issac is only $8000!).
So bullish on the future of this sector.
Robotics is tracing the exact same growth curve as software AI, just a few years behind.
We are likely entering the beginning of exponential growth for this ecosystem.
At current capabilities, robotics intelligence is at the level of roughly GPT-2.
(Capable, but lacking real-world field deployment)
Things are about to change.
Manufacturing costs and the general robotics cost curve is rapidly declining (Issac is only $8000!).
So bullish on the future of this sector.
Africa isn't scattered geology.... It's the most strategically concentrated mineral map on Earth.
🇨🇩 DRC: cobalt + copper giant
🇿🇲 Zambia: copper belt
🇿🇼 Zimbabwe: lithium surge
🇳🇦 Namibia: uranium + lithium
🇿🇦 South Africa: PGMs + manganese
🇲🇦 Morocco: phosphates
🇲🇱🇧🇫🇬🇭 Mali, Burkina Faso, Ghana: gold belts
🇬🇳 Guinea: bauxite
🇸🇱 Sierra Leone: emerging iron ore
Energy transition metals. Battery inputs.
Defense-critical minerals.
Concentrated on one continent, not scattered across it.
Africa isn't peripheral to the transition it's central to it.
🇨🇩 DRC: cobalt + copper giant
🇿🇲 Zambia: copper belt
🇿🇼 Zimbabwe: lithium surge
🇳🇦 Namibia: uranium + lithium
🇿🇦 South Africa: PGMs + manganese
🇲🇦 Morocco: phosphates
🇲🇱🇧🇫🇬🇭 Mali, Burkina Faso, Ghana: gold belts
🇬🇳 Guinea: bauxite
🇸🇱 Sierra Leone: emerging iron ore
Energy transition metals. Battery inputs.
Defense-critical minerals.
Concentrated on one continent, not scattered across it.
Africa isn't peripheral to the transition it's central to it.
🇨🇭 Global One SI - Prompt
I found the cheat code for using Fable 5 without going broke. Everything you need to know about cutting Fable token spend
Stop treating Fable 5 like every other AI model.
There are six things you need to know if you want to get the most out of Fable (save this):
1. Run Time
Every Claude model before Fable 5 worked in relatively short bursts.
Claude Fable 5 is meant to sustain output over extended periods to complete multi-day, goal-directed tasks.
This is one of the biggest shifts. Fable 5 is meant for fully autonomous work (paired with /goal or /loop).
2. It Gets Things Right First Time
One of the most reported early observations from people using Fable 5 is how rarely they need to iterate. Early testers reported single-pass implementations of systems that previously took days of iteration.
3. Clarifying Questions
To execute autonomous work loops accurately, Fable 5 may ask a series of clarifying questions before it kicks off its autonomous run.
4. Agent Management
Fable 5 is built to manage multiple parallel subagents at once (spinning up 50+ agents for complex tasks).
5. It "Sees" Better
Claude Fable 5 interprets dense technical images, web applications, and detailed screenshots with substantially higher accuracy.
For anyone using Claude to analyse charts, screenshots, documents, or visual data, the improvement here is meaningful.
6. Coding + Security Audits
It's no secret that Fable is a coding genius. This new model is especially powerful for codebase review and debugging.
There are six things you need to know if you want to get the most out of Fable (save this):
1. Run Time
Every Claude model before Fable 5 worked in relatively short bursts.
Claude Fable 5 is meant to sustain output over extended periods to complete multi-day, goal-directed tasks.
This is one of the biggest shifts. Fable 5 is meant for fully autonomous work (paired with /goal or /loop).
2. It Gets Things Right First Time
One of the most reported early observations from people using Fable 5 is how rarely they need to iterate. Early testers reported single-pass implementations of systems that previously took days of iteration.
3. Clarifying Questions
To execute autonomous work loops accurately, Fable 5 may ask a series of clarifying questions before it kicks off its autonomous run.
4. Agent Management
Fable 5 is built to manage multiple parallel subagents at once (spinning up 50+ agents for complex tasks).
5. It "Sees" Better
Claude Fable 5 interprets dense technical images, web applications, and detailed screenshots with substantially higher accuracy.
For anyone using Claude to analyse charts, screenshots, documents, or visual data, the improvement here is meaningful.
6. Coding + Security Audits
It's no secret that Fable is a coding genius. This new model is especially powerful for codebase review and debugging.
✍1
🇨🇭 Global One SI - Prompt
$AXTI/USD H2 #Indicator #Signal #Trading #GlobalOneAI Globalone.ch #Prompt #AI
$AXTI just finalized a massive 3-year Master Development and Supply Agreement with tech giant $COHR.
To secure production capacity, $COHR is giving $AXTI a $22.28 million upfront cash payment.
This is non-dilutive liquidity that will directly fund the aggressive expansion of $AXTI facility through 2028.
When a company like $COHR pays upfront to lock you in, it is the ultimate validation of your technology.
The agreement focuses on the mass production of 6-inch Indium Phosphide (InP) wafer substrates. InP is the foundational material required for laser components inside next-generation 1.6-Terabit optical transceivers.
As AI clusters grow exponentially, these optical transceivers are non-negotiable to prevent network bottlenecks. $AXTI is sitting right at the bottleneck of the global AI buildout.
Due to strict regulatory export restrictions, the market for high-end wafers is facing severe supply shortages, which previously drove prices up by up to 250%.
By securing $COHR as a primary partner, $AXTI guarantees a massive, high-margin revenue baseline for the next three years, effectively protecting its business model while riding a hyper-growth wave.
To secure production capacity, $COHR is giving $AXTI a $22.28 million upfront cash payment.
This is non-dilutive liquidity that will directly fund the aggressive expansion of $AXTI facility through 2028.
When a company like $COHR pays upfront to lock you in, it is the ultimate validation of your technology.
The agreement focuses on the mass production of 6-inch Indium Phosphide (InP) wafer substrates. InP is the foundational material required for laser components inside next-generation 1.6-Terabit optical transceivers.
As AI clusters grow exponentially, these optical transceivers are non-negotiable to prevent network bottlenecks. $AXTI is sitting right at the bottleneck of the global AI buildout.
Due to strict regulatory export restrictions, the market for high-end wafers is facing severe supply shortages, which previously drove prices up by up to 250%.
By securing $COHR as a primary partner, $AXTI guarantees a massive, high-margin revenue baseline for the next three years, effectively protecting its business model while riding a hyper-growth wave.
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Microsoft CEO Satya Nadella's new interivew: Explains how the next AI moat will not be the model you use, but the learning loop only your company can run.
He is really asking what happens to the firm when intelligence becomes something you can rent.
For a century, companies protected value through people, processes, data, routines, customer memory, and the tacit knowledge buried in daily operations.
Foundation models threaten to flatten that advantage because the same general intelligence can be used by everyone.
Nadella’s answer is that firms need their own “hill climbing machine,” a private loop where models learn from company-specific tasks, traces, evaluations, and outcomes.
That means the real asset is not just the model.
The asset is the environment that keeps improving the model in ways competitors cannot copy.
Private evals become strategic memory.
Workflow traces become training signal.
Human judgment becomes a way to steer compounding, not just correct mistakes.
This also reframes AI adoption: a company that only consumes a foundation model may gain productivity, but it may leak the deeper value of its operating knowledge.
A company that builds a disciplined learning loop can turn everyday work into accumulating IP.
The future firm may therefore be measured by how well it converts its unique activity into durable model improvement.
The frontier will not belong only to whoever owns the largest model.
It will belong to whoever owns the best loop.
He is really asking what happens to the firm when intelligence becomes something you can rent.
For a century, companies protected value through people, processes, data, routines, customer memory, and the tacit knowledge buried in daily operations.
Foundation models threaten to flatten that advantage because the same general intelligence can be used by everyone.
Nadella’s answer is that firms need their own “hill climbing machine,” a private loop where models learn from company-specific tasks, traces, evaluations, and outcomes.
That means the real asset is not just the model.
The asset is the environment that keeps improving the model in ways competitors cannot copy.
Private evals become strategic memory.
Workflow traces become training signal.
Human judgment becomes a way to steer compounding, not just correct mistakes.
This also reframes AI adoption: a company that only consumes a foundation model may gain productivity, but it may leak the deeper value of its operating knowledge.
A company that builds a disciplined learning loop can turn everyday work into accumulating IP.
The future firm may therefore be measured by how well it converts its unique activity into durable model improvement.
The frontier will not belong only to whoever owns the largest model.
It will belong to whoever owns the best loop.
✍1
🇨🇭 Global One SI - Prompt
Unemployment could hit 20% by 2028. This would be the worst job market since the 1929 Great Depression.
AI+Robots will be able to do everything, resulting in universal high income. Work will be optional.
👀1
Fable 5 is already dead.
Anthropic keeps it in subscriptions only until July 7, then it moves to usage credits. Meanwhile OpenAI is lining up GPT-5.6 Sol for broader access in the coming weeks, at roughly half the API price of Fable 5.
Terminal-Bench 2.1, OpenAI-reported:
GPT-5.6 Sol Ultra: 91.9%
GPT-5.6 Sol: 88.8%
Claude Mythos 5: 88.0%
Claude Fable 5: 84.3%
GPT-5.6 Terra: 84.3%
So Fable 5 gets pulled out of the subscription, while OpenAI drops a cheaper model that beats it or ties it with the mid-tier.
Anthropic is cooked.
Anthropic keeps it in subscriptions only until July 7, then it moves to usage credits. Meanwhile OpenAI is lining up GPT-5.6 Sol for broader access in the coming weeks, at roughly half the API price of Fable 5.
Terminal-Bench 2.1, OpenAI-reported:
GPT-5.6 Sol Ultra: 91.9%
GPT-5.6 Sol: 88.8%
Claude Mythos 5: 88.0%
Claude Fable 5: 84.3%
GPT-5.6 Terra: 84.3%
So Fable 5 gets pulled out of the subscription, while OpenAI drops a cheaper model that beats it or ties it with the mid-tier.
Anthropic is cooked.
▪️Hammack, Fed Chairman:
- Inflation remains too high, and the pressure is widespread, not just related to energy prices.
- Core inflation, especially in the services sector, remains elevated.
- The Fed may consider raising the rate if necessary to return inflation to the target of 2%.
- A higher rate could negatively affect the rest of the economy.
▪️Daley, Fed Chairman:
- The investment boom in AI raises concerns about whether it could exacerbate inflation.
- The US economy remains resilient, despite inflation being above the target level.
- It's too early to draw conclusions about the future path of the rate, and decisions will depend on incoming data.
❗️Market expectations (Fed rate #FED):
- July 29: PAUSE.
- September 16: increase by 25 bps to 3.75-4.00%.
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🇨🇭 Global One SI - Prompt
Stop treating Fable 5 like every other AI model. There are six things you need to know if you want to get the most out of Fable (save this): 1. Run Time Every Claude model before Fable 5 worked in relatively short bursts. Claude Fable 5 is meant to sustain…
I don't prompt Claude Code anymore.
I have loops running that prompt Fable, and my job is just to write loops.
This is the Boris Cherny method, and I have to say, it's extremely powerful.
Everything you need to get started with loop engineering (as a complete beginner)
I have loops running that prompt Fable, and my job is just to write loops.
This is the Boris Cherny method, and I have to say, it's extremely powerful.
Everything you need to get started with loop engineering (as a complete beginner)
✍1
ROBOTS DESIGN AROUND THE WORLD
A look at 40 robot designs from industrial arms to humanoids.
INDUSTRIAL ROBOT ARMS
• 🇨🇭 ABB
➝ IRB Series
➝ Built by ABB for factory automation
➝ Known for welding, handling and assembly lines
• 🇩🇪 KUKA
➝ KR CYBERTECH Series
➝ Built by KUKA for compact industrial workcells
➝ Used for handling, arc welding and machining tasks
• 🇨🇭 STÄUBLI
➝ TX2 Series
➝ Built by Stäubli for high-speed precision work
➝ Strong in electronics, pharma and clean production
• 🇯🇵 YASKAWA
➝ GP Series
➝ Built by Yaskawa Motoman for general handling
➝ Used where factories need speed and repeatability
• 🇯🇵 NACHI
➝ CM Series
➝ Built by NACHI for industrial automation
➝ Known for compact arms and production reliability
• 🇮🇹 COMAU
➝ Racer Series
➝ Built by Comau for fast industrial motion
➝ Used in automotive and high-volume manufacturing
• 🇯🇵 FANUC
➝ ARC Series
➝ Built by FANUC for arc welding
➝ Recognized for yellow factory robots and rugged uptime
• 🇯🇵 Mitsubishi Electric
➝ RV-FR Series
➝ Built by Mitsubishi Electric for flexible factory automation
➝ Used for assembly, inspection and machine tending
COBOTS
• 🇩🇰 Universal Robots
➝ UR10e Series
➝ Built by Universal Robots for human-side automation
➝ Popular because it is easy to deploy in small factories
• 🇩🇪 Agile Robots
➝ Diana Series
➝ Built by Agile Robots for collaborative manipulation
➝ Designed for precise arm motion near people
• 🇩🇪 NEURA Robotics
➝ Lara Series
➝ Built by NEURA Robotics for cognitive robotics
➝ Built for safer human robot collaboration
• 🇯🇵 DENSO
➝ COBOTTA Series
➝ Built by DENSO for compact workbench automation
➝ Useful for labs, small parts and repetitive tasks
• 🇯🇵 OMRON
➝ TM-RT Series
➝ Built by OMRON for collaborative factory work
➝ Focused on vision-guided handling and inspection
• 🇨🇦 Kinova
➝ Gen3
➝ Built by Kinova for lightweight robotic manipulation
➝ Used in research, assistive robotics and mobile platforms
• 🇨🇳 DOBOT
➝ CR Series
➝ Built by DOBOT for affordable collaborative automation
➝ Made for pick and place, packing and small production lines
• 🇰🇷 DOOSAN
➝ CRX Series
➝ Built by Doosan Robotics for industrial collaboration
➝ Known for strong cobot arms and clean design
QUADRUPED ROBOTS
• 🇪🇸 Keybotics
➝ Keyper
➝ Built by Keybotics for industrial inspection
➝ Designed to move through facilities where wheels struggle
• 🇨🇳 Unitree
➝ B2
➝ Built by Unitree for larger quadruped tasks
➝ Built for payload, speed and outdoor mobility
• 🇺🇸 Boston Dynamics
➝ Spot
➝ Built by Boston Dynamics for inspection and mapping
➝ Famous for balance, terrain recovery and field use
• 🇨🇭 ANYbotics
➝ ANYmal
➝ Built by ANYbotics for industrial inspection
➝ Used in energy sites, plants and rough environments
• 🇨🇳 DeepRobotics
➝ X30
➝ Built by DeepRobotics for industrial patrol and inspection
➝ Designed for outdoor terrain and harsh sites
• 🇺🇸 Ghost Robotics
➝ Vision 60
➝ Built by Ghost Robotics for rugged field mobility
➝ Used for defense, security and perimeter work
• 🇨🇳 Unitree
➝ Go2
➝ Built by Unitree for consumer and developer robotics
➝ Smaller, cheaper and more accessible than industrial quadrupeds
• 🇨🇳 XPENG Robotics
➝ Robot Pony
➝ Built by XPENG Robotics as a smart mobility companion
➝ Blends quadruped movement with consumer robot design
• 🇨🇳 Xiaomi
➝ CyberDog 2
➝ Built by Xiaomi for consumer robotics research
➝ A compact robot dog focused on agility and interaction
• 🇨🇳 Pudu Robotics
➝ Pudu D1
➝ Built by Pudu Robotics for service robotics
➝ Shows how delivery robot companies are moving into legs
• 🇨🇳 OPPO
➝ Qric
➝ Built by OPPO as a robotic dog concept
➝ Interesting because a smartphone company explored legged robots
• 🇯🇵 Sony
➝ Aibo
➝ Built by Sony as a companion robot dog
➝ One of the clearest examples of emotional consumer robotics
A look at 40 robot designs from industrial arms to humanoids.
INDUSTRIAL ROBOT ARMS
• 🇨🇭 ABB
➝ IRB Series
➝ Built by ABB for factory automation
➝ Known for welding, handling and assembly lines
• 🇩🇪 KUKA
➝ KR CYBERTECH Series
➝ Built by KUKA for compact industrial workcells
➝ Used for handling, arc welding and machining tasks
• 🇨🇭 STÄUBLI
➝ TX2 Series
➝ Built by Stäubli for high-speed precision work
➝ Strong in electronics, pharma and clean production
• 🇯🇵 YASKAWA
➝ GP Series
➝ Built by Yaskawa Motoman for general handling
➝ Used where factories need speed and repeatability
• 🇯🇵 NACHI
➝ CM Series
➝ Built by NACHI for industrial automation
➝ Known for compact arms and production reliability
• 🇮🇹 COMAU
➝ Racer Series
➝ Built by Comau for fast industrial motion
➝ Used in automotive and high-volume manufacturing
• 🇯🇵 FANUC
➝ ARC Series
➝ Built by FANUC for arc welding
➝ Recognized for yellow factory robots and rugged uptime
• 🇯🇵 Mitsubishi Electric
➝ RV-FR Series
➝ Built by Mitsubishi Electric for flexible factory automation
➝ Used for assembly, inspection and machine tending
COBOTS
• 🇩🇰 Universal Robots
➝ UR10e Series
➝ Built by Universal Robots for human-side automation
➝ Popular because it is easy to deploy in small factories
• 🇩🇪 Agile Robots
➝ Diana Series
➝ Built by Agile Robots for collaborative manipulation
➝ Designed for precise arm motion near people
• 🇩🇪 NEURA Robotics
➝ Lara Series
➝ Built by NEURA Robotics for cognitive robotics
➝ Built for safer human robot collaboration
• 🇯🇵 DENSO
➝ COBOTTA Series
➝ Built by DENSO for compact workbench automation
➝ Useful for labs, small parts and repetitive tasks
• 🇯🇵 OMRON
➝ TM-RT Series
➝ Built by OMRON for collaborative factory work
➝ Focused on vision-guided handling and inspection
• 🇨🇦 Kinova
➝ Gen3
➝ Built by Kinova for lightweight robotic manipulation
➝ Used in research, assistive robotics and mobile platforms
• 🇨🇳 DOBOT
➝ CR Series
➝ Built by DOBOT for affordable collaborative automation
➝ Made for pick and place, packing and small production lines
• 🇰🇷 DOOSAN
➝ CRX Series
➝ Built by Doosan Robotics for industrial collaboration
➝ Known for strong cobot arms and clean design
QUADRUPED ROBOTS
• 🇪🇸 Keybotics
➝ Keyper
➝ Built by Keybotics for industrial inspection
➝ Designed to move through facilities where wheels struggle
• 🇨🇳 Unitree
➝ B2
➝ Built by Unitree for larger quadruped tasks
➝ Built for payload, speed and outdoor mobility
• 🇺🇸 Boston Dynamics
➝ Spot
➝ Built by Boston Dynamics for inspection and mapping
➝ Famous for balance, terrain recovery and field use
• 🇨🇭 ANYbotics
➝ ANYmal
➝ Built by ANYbotics for industrial inspection
➝ Used in energy sites, plants and rough environments
• 🇨🇳 DeepRobotics
➝ X30
➝ Built by DeepRobotics for industrial patrol and inspection
➝ Designed for outdoor terrain and harsh sites
• 🇺🇸 Ghost Robotics
➝ Vision 60
➝ Built by Ghost Robotics for rugged field mobility
➝ Used for defense, security and perimeter work
• 🇨🇳 Unitree
➝ Go2
➝ Built by Unitree for consumer and developer robotics
➝ Smaller, cheaper and more accessible than industrial quadrupeds
• 🇨🇳 XPENG Robotics
➝ Robot Pony
➝ Built by XPENG Robotics as a smart mobility companion
➝ Blends quadruped movement with consumer robot design
• 🇨🇳 Xiaomi
➝ CyberDog 2
➝ Built by Xiaomi for consumer robotics research
➝ A compact robot dog focused on agility and interaction
• 🇨🇳 Pudu Robotics
➝ Pudu D1
➝ Built by Pudu Robotics for service robotics
➝ Shows how delivery robot companies are moving into legs
• 🇨🇳 OPPO
➝ Qric
➝ Built by OPPO as a robotic dog concept
➝ Interesting because a smartphone company explored legged robots
• 🇯🇵 Sony
➝ Aibo
➝ Built by Sony as a companion robot dog
➝ One of the clearest examples of emotional consumer robotics