great point. What if the system knew the driver was refusing to stop and have a pee. Or worse, was about to road rage... Maybe the system will talk the driver down with some well chosen eckhart tolle quotes.
Concerns raised about new tech that uses AI, cameras to monitor workplace safety
AI that uses CCTV to identify health and safety hazards can be trained to identify breaches such as when a worker is not wearing gloves or a hard hat, or to identify hazards like spills. But privacy laws are lagging.www.abc.net.au
Interesting discussion.
Thinking about in cabin emotional surveillance. How would that affect any insurance or liability claim, if the AI had suggested a rest? How does it really know?
It’s coming…. and fast.
BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
Sprocket68
Emerged
Beat me to it, very quiet today
wilzy123
Founding Member
And at least 50%+ of the trades appear to be bot trades....
Bravo
If ARM was an arm, BRN would be its biceps💪!
This trial shows that neuromorphic computing is going to be a game-changer for people with disabilities. Whilst this research is being conducted with a robotic arm powered by Intel’s Loihi neuromorphic chip, it's important to rember that this is also 100 % applicable to us because Loihi is only a research chip only and AKIDA is commercially available now.
A clinical trial for a robotic arm based on neuromorphic computing could increase independence for spinal, neuromuscular injury patients, writes Caroline Hayes.
An early prototype of a robotic arm designed to assist patients with spinal injuries in performing daily tasks.
Patients with spinal cord or neuromuscular injuries resulting in limited mobility in their upper body could gain some independence if a trial being conducted at ALYN Hospital in Israel is successful. Small groups of patients at the paediatric and adolescent rehabilitation hospital will use a wheelchair fitted with a robotic arm powered by Intel’s Loihi neuromorphic chip. This uses adapted algorithms from Applied Brain Research.
The neuromorphic computing system can assess its immediate environment to understand where the robotic arm is in relation to an object, such as a cup, and calculate the trajectory and force needed for a specific movement. For example, such as to bring a cup of water to the wheelchair user’s mouth smoothly and replace it when finished.
The project uses a prototype robotic arm and neuromorphic computing to train machine-learning models in the same way the developing human brain learns; by seeing an image once and being able to recognise it from then on. Neuromorphic computing can automatically identify where the robotic arm is and calculate the movement required.
This differs from artificial intelligence, which is based on algorithms trained to perform specific tasks. Using neuromorphic computing eliminates many of the motors and controllers used in robotics to perform these tasks to ensure correct positioning and alignment, explains Mike Davies, director of Intel’s neuromorphic computing lab. This can reduce the bill of materials for specialist wheelchairs.
More benefits of neuromorphic computing are that less data is required to train machine-learning models and they consume less energy. Researchers expect that the real-time learning capability of the Loihi chip will allow them to implement adaptive control to enhance the arm’s functionality and the low power consumption will mean that the arm will need less frequent charging and is more practical for daily use over a longer period of time. Intel says that Loihi is up to 1,000 times more energy-efficient than general purpose processors.
Using the robotic arm, the research team built the neural network model that controls the arm using the recurrent error-driven adaptive control hierarchy algorithm developed by Applied Brain Research. The combination had already demonstrated movements of a simpler robotic arm through complex paths, including handwritten words and numbers, with fewer errors and improved energy efficiency compared with more traditional control methods. The team deployed the completed algorithm on Intel’s neuromorphic hardware and tested the capabilities of the arm in readiness for the clinical trials with around 25 patients. The first trial group of five patients took place between April and June 2021.
“Making these devices accessible, particularly to such young patients, can have a profound impact on their independence, improving the way they live,” observes Edy Liogosari, technology innovation growth and strategy lead and chief research scientist at Accenture.
“We believe that the development of a robotic arm based on neuromorphic computing can be a game-changer for people with disabilities,” adds Arie Melamed-Yekel, general manger of ALYNnnovation at ALYN Hospital. “It could make it easier for them to engage with the community, boost their independence and grant them new employment opportunities.”
The INRC neuromorphic robotic arm was given an honourable mention in Fast company magazine’s World Changing Ideas Awards 2021. These awards are for “Acknowledging concepts, prototypes and just launched ideas that… have the potential to change how we think about an issue.”
Neuromorphic architecture is characterised by high-speed processing at low power consumption. Unlike the von Neumann architecture, it has a continuous transition rather than highs and lows from binary encoding. It also integrates storage and processing, which eliminates the bus bottleneck between the CPU and memory.
The chips can be digital, analogue or mixed. According to analyst Mordor Intelligence, analogue chips are closer to biological neural networks and use fewer transistors to emulate neurons than digital versions. Theoretically, says the company, analogue neuromorphic chips consume less energy and can extend processing beyond the allocated time slot to accelerate the processing speeds beyond real-time speeds.
The architecture of analogue chips, however, leads to high noise levels, making digital neuromorphic chips more precise.
The digital architecture is optimal for on-chip programming of algorithms with low energy consumption compared to graphic processor units. Mixed chips combine analogue’s lower energy with precision.
With the potential to achieve massively parallel brain processing at a low power budget of 10s of Watts, neuromorphic chips use in-memory computing for a dynamic, self-programmable operation.
Neuromorphic chips are used in medical applications, for example to improve the accuracy of medical testing, and in the automotive industry to develop Level 5 Autonomy vehicles, that is, fully autonomous, with no need for any human attention to controls or driving conditions.
The neuromorphic chip market is expected to experience 47% CAGR between 2020 and 2026, said Mordor, increasing from a value of $22.5m to $333.6m in this period.
https://www.electronicsweekly.com/news/a-helping-hand-for-robotic-arms-2022-07/
A helping hand for robotic arms
Caroline Hayes 20th July 2022A clinical trial for a robotic arm based on neuromorphic computing could increase independence for spinal, neuromuscular injury patients, writes Caroline Hayes.
An early prototype of a robotic arm designed to assist patients with spinal injuries in performing daily tasks.
Patients with spinal cord or neuromuscular injuries resulting in limited mobility in their upper body could gain some independence if a trial being conducted at ALYN Hospital in Israel is successful. Small groups of patients at the paediatric and adolescent rehabilitation hospital will use a wheelchair fitted with a robotic arm powered by Intel’s Loihi neuromorphic chip. This uses adapted algorithms from Applied Brain Research.
The neuromorphic computing system can assess its immediate environment to understand where the robotic arm is in relation to an object, such as a cup, and calculate the trajectory and force needed for a specific movement. For example, such as to bring a cup of water to the wheelchair user’s mouth smoothly and replace it when finished.
The project uses a prototype robotic arm and neuromorphic computing to train machine-learning models in the same way the developing human brain learns; by seeing an image once and being able to recognise it from then on. Neuromorphic computing can automatically identify where the robotic arm is and calculate the movement required.
This differs from artificial intelligence, which is based on algorithms trained to perform specific tasks. Using neuromorphic computing eliminates many of the motors and controllers used in robotics to perform these tasks to ensure correct positioning and alignment, explains Mike Davies, director of Intel’s neuromorphic computing lab. This can reduce the bill of materials for specialist wheelchairs.
More benefits of neuromorphic computing are that less data is required to train machine-learning models and they consume less energy. Researchers expect that the real-time learning capability of the Loihi chip will allow them to implement adaptive control to enhance the arm’s functionality and the low power consumption will mean that the arm will need less frequent charging and is more practical for daily use over a longer period of time. Intel says that Loihi is up to 1,000 times more energy-efficient than general purpose processors.
Joystick operation
The wheelchair is equipped with a joystick that operates the robotic arm. In a year, the arm will be able to perform its own trajectory planning and be semi-autonomous through a 3D- camera mounted on the arm, says Dr Elishai Ezra Tsur, principal investigator of the neuro and biomorphic engineering lab at the Open University of Israel, which is leading the Intel Neuromorphic Research Community (INRC) project. The project is funded by Intel and Accenture Labs and conducted in collaboration with ALYN Hospital.Using the robotic arm, the research team built the neural network model that controls the arm using the recurrent error-driven adaptive control hierarchy algorithm developed by Applied Brain Research. The combination had already demonstrated movements of a simpler robotic arm through complex paths, including handwritten words and numbers, with fewer errors and improved energy efficiency compared with more traditional control methods. The team deployed the completed algorithm on Intel’s neuromorphic hardware and tested the capabilities of the arm in readiness for the clinical trials with around 25 patients. The first trial group of five patients took place between April and June 2021.
Increasing independence
Applying assistive robotics to patients can increase a sense of independence for wheelchair users and reduce the time needed by caregivers. The clinical trial hopes to pave the way for a commercially viable, affordable, low energy, intelligent robotic arm for wheelchair users.
“Making these devices accessible, particularly to such young patients, can have a profound impact on their independence, improving the way they live,” observes Edy Liogosari, technology innovation growth and strategy lead and chief research scientist at Accenture.
“We believe that the development of a robotic arm based on neuromorphic computing can be a game-changer for people with disabilities,” adds Arie Melamed-Yekel, general manger of ALYNnnovation at ALYN Hospital. “It could make it easier for them to engage with the community, boost their independence and grant them new employment opportunities.”
The INRC neuromorphic robotic arm was given an honourable mention in Fast company magazine’s World Changing Ideas Awards 2021. These awards are for “Acknowledging concepts, prototypes and just launched ideas that… have the potential to change how we think about an issue.”
What is neuromorphic computing?
Neuromorphic computing mimics the human brain’s ability to learn about its environment and adapt behaviour in real time, expending minimal energy. Artificial intelligence (AI), on the other hand, uses algorithms trained for specific tasks that are used by artificial neural networks. These algorithms are developed using large amounts of data. They are used by artificial neural networks for training and inference tasks. Generally, AI cannot adapt to changes in an environment in real time, whereas a neuromorphic chip, typically an asic, uses artificial neural networks called spiked neural networks, which are modelled on the human brain’s neural network, sending signals when a neuron has reached its electrical charge threshold, rather than firing a signal with each propagation cycle.Neuromorphic architecture is characterised by high-speed processing at low power consumption. Unlike the von Neumann architecture, it has a continuous transition rather than highs and lows from binary encoding. It also integrates storage and processing, which eliminates the bus bottleneck between the CPU and memory.
The chips can be digital, analogue or mixed. According to analyst Mordor Intelligence, analogue chips are closer to biological neural networks and use fewer transistors to emulate neurons than digital versions. Theoretically, says the company, analogue neuromorphic chips consume less energy and can extend processing beyond the allocated time slot to accelerate the processing speeds beyond real-time speeds.
The architecture of analogue chips, however, leads to high noise levels, making digital neuromorphic chips more precise.
The digital architecture is optimal for on-chip programming of algorithms with low energy consumption compared to graphic processor units. Mixed chips combine analogue’s lower energy with precision.
With the potential to achieve massively parallel brain processing at a low power budget of 10s of Watts, neuromorphic chips use in-memory computing for a dynamic, self-programmable operation.
Neuromorphic chips are used in medical applications, for example to improve the accuracy of medical testing, and in the automotive industry to develop Level 5 Autonomy vehicles, that is, fully autonomous, with no need for any human attention to controls or driving conditions.
The neuromorphic chip market is expected to experience 47% CAGR between 2020 and 2026, said Mordor, increasing from a value of $22.5m to $333.6m in this period.
https://www.electronicsweekly.com/news/a-helping-hand-for-robotic-arms-2022-07/
Frank Zappa
Regular
One would think that the quarterly is coming off the printing machine as we post . The more copies , the more opportunities to whisper to a close colleague.The market is indicating that everyone is set . I reckon the starters gun is in the air and cocked and shorters have they fingers primed above their iPads .Good luck Chippers.FF said around $ 1 million in revenue .I’ll be happy with that coupled with good news update .
F
Filobeddo
Guest
Looking at the same thing
Calcs on number of shares in individual trades up until 10.30ish for those interested
Last edited by a moderator:
Frank Zappa
Regular
CoolLooking at the same thing
Calcs on number of shares in individual trades up until 10.30ish fo those interested
View attachment 12445
F
Filobeddo
Guest
This trial shows that neuromorphic computing is going to be a game-changer for people with disabilities. Whilst this research is being conducted with a robotic arm powered by Intel’s Loihi neuromorphic chip, it's important to rember that this is also 100 % applicable to us because Loihi is only a research chip only and AKIDA is commercially available now.
A helping hand for robotic arms
Caroline Hayes 20th July 2022
A clinical trial for a robotic arm based on neuromorphic computing could increase independence for spinal, neuromuscular injury patients, writes Caroline Hayes.
An early prototype of a robotic arm designed to assist patients with spinal injuries in performing daily tasks.
Patients with spinal cord or neuromuscular injuries resulting in limited mobility in their upper body could gain some independence if a trial being conducted at ALYN Hospital in Israel is successful. Small groups of patients at the paediatric and adolescent rehabilitation hospital will use a wheelchair fitted with a robotic arm powered by Intel’s Loihi neuromorphic chip. This uses adapted algorithms from Applied Brain Research.
The neuromorphic computing system can assess its immediate environment to understand where the robotic arm is in relation to an object, such as a cup, and calculate the trajectory and force needed for a specific movement. For example, such as to bring a cup of water to the wheelchair user’s mouth smoothly and replace it when finished.
The project uses a prototype robotic arm and neuromorphic computing to train machine-learning models in the same way the developing human brain learns; by seeing an image once and being able to recognise it from then on. Neuromorphic computing can automatically identify where the robotic arm is and calculate the movement required.
This differs from artificial intelligence, which is based on algorithms trained to perform specific tasks. Using neuromorphic computing eliminates many of the motors and controllers used in robotics to perform these tasks to ensure correct positioning and alignment, explains Mike Davies, director of Intel’s neuromorphic computing lab. This can reduce the bill of materials for specialist wheelchairs.
More benefits of neuromorphic computing are that less data is required to train machine-learning models and they consume less energy. Researchers expect that the real-time learning capability of the Loihi chip will allow them to implement adaptive control to enhance the arm’s functionality and the low power consumption will mean that the arm will need less frequent charging and is more practical for daily use over a longer period of time. Intel says that Loihi is up to 1,000 times more energy-efficient than general purpose processors.
Joystick operation
The wheelchair is equipped with a joystick that operates the robotic arm. In a year, the arm will be able to perform its own trajectory planning and be semi-autonomous through a 3D- camera mounted on the arm, says Dr Elishai Ezra Tsur, principal investigator of the neuro and biomorphic engineering lab at the Open University of Israel, which is leading the Intel Neuromorphic Research Community (INRC) project. The project is funded by Intel and Accenture Labs and conducted in collaboration with ALYN Hospital.
Using the robotic arm, the research team built the neural network model that controls the arm using the recurrent error-driven adaptive control hierarchy algorithm developed by Applied Brain Research. The combination had already demonstrated movements of a simpler robotic arm through complex paths, including handwritten words and numbers, with fewer errors and improved energy efficiency compared with more traditional control methods. The team deployed the completed algorithm on Intel’s neuromorphic hardware and tested the capabilities of the arm in readiness for the clinical trials with around 25 patients. The first trial group of five patients took place between April and June 2021.
Increasing independence
Applying assistive robotics to patients can increase a sense of independence for wheelchair users and reduce the time needed by caregivers. The clinical trial hopes to pave the way for a commercially viable, affordable, low energy, intelligent robotic arm for wheelchair users.
“Making these devices accessible, particularly to such young patients, can have a profound impact on their independence, improving the way they live,” observes Edy Liogosari, technology innovation growth and strategy lead and chief research scientist at Accenture.
“We believe that the development of a robotic arm based on neuromorphic computing can be a game-changer for people with disabilities,” adds Arie Melamed-Yekel, general manger of ALYNnnovation at ALYN Hospital. “It could make it easier for them to engage with the community, boost their independence and grant them new employment opportunities.”
The INRC neuromorphic robotic arm was given an honourable mention in Fast company magazine’s World Changing Ideas Awards 2021. These awards are for “Acknowledging concepts, prototypes and just launched ideas that… have the potential to change how we think about an issue.”
What is neuromorphic computing?
Neuromorphic computing mimics the human brain’s ability to learn about its environment and adapt behaviour in real time, expending minimal energy. Artificial intelligence (AI), on the other hand, uses algorithms trained for specific tasks that are used by artificial neural networks. These algorithms are developed using large amounts of data. They are used by artificial neural networks for training and inference tasks. Generally, AI cannot adapt to changes in an environment in real time, whereas a neuromorphic chip, typically an asic, uses artificial neural networks called spiked neural networks, which are modelled on the human brain’s neural network, sending signals when a neuron has reached its electrical charge threshold, rather than firing a signal with each propagation cycle.
Neuromorphic architecture is characterised by high-speed processing at low power consumption. Unlike the von Neumann architecture, it has a continuous transition rather than highs and lows from binary encoding. It also integrates storage and processing, which eliminates the bus bottleneck between the CPU and memory.
The chips can be digital, analogue or mixed. According to analyst Mordor Intelligence, analogue chips are closer to biological neural networks and use fewer transistors to emulate neurons than digital versions. Theoretically, says the company, analogue neuromorphic chips consume less energy and can extend processing beyond the allocated time slot to accelerate the processing speeds beyond real-time speeds.
The architecture of analogue chips, however, leads to high noise levels, making digital neuromorphic chips more precise.
The digital architecture is optimal for on-chip programming of algorithms with low energy consumption compared to graphic processor units. Mixed chips combine analogue’s lower energy with precision.
With the potential to achieve massively parallel brain processing at a low power budget of 10s of Watts, neuromorphic chips use in-memory computing for a dynamic, self-programmable operation.
Neuromorphic chips are used in medical applications, for example to improve the accuracy of medical testing, and in the automotive industry to develop Level 5 Autonomy vehicles, that is, fully autonomous, with no need for any human attention to controls or driving conditions.
The neuromorphic chip market is expected to experience 47% CAGR between 2020 and 2026, said Mordor, increasing from a value of $22.5m to $333.6m in this period.
https://www.electronicsweekly.com/news/a-helping-hand-for-robotic-arms-2022-07/
Does the Lohi one play chess?
Shadow59
Regular
Could be into theatrics though, "break a leg"Does the Lohi one play chess?
alwaysgreen
Top 20
Market is extremely tentative. Likely waiting for Thursday night US economic data.
DingoBorat
Slim
Just a bit of feeble shorting action, possibly by a feeble company..
D
Deleted member 118
Guest
Did you lose any money on them by any chance
Thank you for all your words of both support for my idea (and it is only an idea!) and also those against it.
MD thanks for your post this morning and for now I am praying for a $40+ Mil 4C as I missed out on the Ken Shirts! Thanks but I believe you are reasonably safe for now.
I was waiting to see if anyone would have picked up on an interesting fact about PVDM chat to our forum member Crestman!
Quote - [ "I got the chance to speak to PVDM and I asked him about the ARM partnership. He told me that the agreement was that they will receive $1M upfront for every ARM customer who wants their device/chip to include Akida IP. And then will get ongoing royalties when that device/chip is manufactured on an ongoing basis"]
---------------------------------------------------------------------
Now that interesting fact I am talking about is this.
If Company xyz wants ARM Cortex with AKIDA IP included it must pay $1 Mil upfront fee plus later ongoing Royalty fees. Now forget the Royalty fees for now thats not in the box yet.
THINK about that $1 Mil upfront fee. To warrant paying that much upfront just for access to AKIDA on a ARM Cortex..................
YOU would need to make a substantial UNIT ORDER to make it viable.
HOW MANY units do you think would be the minimum needed?
10 Million units? Plus Royalties later? Sound feasible?
or MORE?100 million units?
10 Million units @ how much Royalties?
100 Million units @ how much Royalties?
By having that $1 Mil upfront fee it has automatically ensured ORDERS will be substantial in numbers!
So yeh, I would be very happy to see just (1) one single Upfront fee via ARM included in this next 4C.
Not to say there will not be "other" upfront fees from a different direction as they are on the cards as well just we have not become aware could exist yet. Plus Engineering fees & AKIDA Boards are still for sale out of Singapore! (note: the only place to get a single AKIDA Chip now)
--------------------------
SP being supported by a BoT with buying against that selling BoT.
The SP is just being played with really as they wait for the 4C to be released. BUT so far the "Shorters" have failed to create a DUMP.
IF we get confirmation of any upfront fees now, years end will get very interesting.
Yak52. GLTAH
MD thanks for your post this morning and for now I am praying for a $40+ Mil 4C as I missed out on the Ken Shirts! Thanks but I believe you are reasonably safe for now.
I was waiting to see if anyone would have picked up on an interesting fact about PVDM chat to our forum member Crestman!
Quote - [ "I got the chance to speak to PVDM and I asked him about the ARM partnership. He told me that the agreement was that they will receive $1M upfront for every ARM customer who wants their device/chip to include Akida IP. And then will get ongoing royalties when that device/chip is manufactured on an ongoing basis"]
---------------------------------------------------------------------
Now that interesting fact I am talking about is this.
If Company xyz wants ARM Cortex with AKIDA IP included it must pay $1 Mil upfront fee plus later ongoing Royalty fees. Now forget the Royalty fees for now thats not in the box yet.
THINK about that $1 Mil upfront fee. To warrant paying that much upfront just for access to AKIDA on a ARM Cortex..................
YOU would need to make a substantial UNIT ORDER to make it viable.
HOW MANY units do you think would be the minimum needed?
10 Million units? Plus Royalties later? Sound feasible?
or MORE?100 million units?
10 Million units @ how much Royalties?
100 Million units @ how much Royalties?
By having that $1 Mil upfront fee it has automatically ensured ORDERS will be substantial in numbers!
So yeh, I would be very happy to see just (1) one single Upfront fee via ARM included in this next 4C.
Not to say there will not be "other" upfront fees from a different direction as they are on the cards as well just we have not become aware could exist yet. Plus Engineering fees & AKIDA Boards are still for sale out of Singapore! (note: the only place to get a single AKIDA Chip now)
--------------------------
SP being supported by a BoT with buying against that selling BoT.
The SP is just being played with really as they wait for the 4C to be released. BUT so far the "Shorters" have failed to create a DUMP.
IF we get confirmation of any upfront fees now, years end will get very interesting.
Yak52.
GLTAH
robsmark
Regular
Id say that’s already priced in.
alwaysgreen
Top 20
I was just trying to sound intelligent
alwaysgreen
Top 20
Does anyone here actually loan out their shares to shorters? Or is that just an insto thing? What's the amount you get for loaning them and is there any risk that the borrower goes bust and you never get your shares back?
I've actually thought that I am not selling my holdings for years so why not make some extra money on them? I couldn't care less about the shorting because long term, I know our SP will be multiples higher than we are now. Short term manipulation doesn't really bother me (well, a little).
I've actually thought that I am not selling my holdings for years so why not make some extra money on them? I couldn't care less about the shorting because long term, I know our SP will be multiples higher than we are now. Short term manipulation doesn't really bother me (well, a little).
DingoBorat
Slim
I may have in the past
..
Fox151
Regular
Not entirely true Yak. There's a single Akida chip available at my house.Thank you for all your words of both support for my idea (and it is only an idea!) and also those against it.
MD thanks for your post this morning and for now I am praying for a $40+ Mil 4C as I missed out on the Ken Shirts! Thanks but I believe you are reasonably safe for now.
I was waiting to see if anyone would have picked up on an interesting fact about PVDM chat to our forum member Crestman!
Quote - [ "I got the chance to speak to PVDM and I asked him about the ARM partnership. He told me that the agreement was that they will receive $1M upfront for every ARM customer who wants their device/chip to include Akida IP. And then will get ongoing royalties when that device/chip is manufactured on an ongoing basis"]
---------------------------------------------------------------------
Now that interesting fact I am talking about is this.
If Company xyz wants ARM Cortex with AKIDA IP included it must pay $1 Mil upfront fee plus later ongoing Royalty fees. Now forget the Royalty fees for now thats not in the box yet.
THINK about that $1 Mil upfront fee. To warrant paying that much upfront just for access to AKIDA on a ARM Cortex..................
YOU would need to make a substantial UNIT ORDER to make it viable.
HOW MANY units do you think would be the minimum needed?
10 Million units? Plus Royalties later? Sound feasible?
or MORE?100 million units?
10 Million units @ how much Royalties?
100 Million units @ how much Royalties?
By having that $1 Mil upfront fee it has automatically ensured ORDERS will be substantial in numbers!
So yeh, I would be very happy to see just (1) one single Upfront fee via ARM included in this next 4C.
Not to say there will not be "other" upfront fees from a different direction as they are on the cards as well just we have not become aware could exist yet. Plus Engineering fees & AKIDA Boards are still for sale out of Singapore! (note: the only place to get a single AKIDA Chip now)
--------------------------
SP being supported by a BoT with buying against that selling BoT.
The SP is just being played with really as they wait for the 4C to be released. BUT so far the "Shorters" have failed to create a DUMP.
IF we get confirmation of any upfront fees now, years end will get very interesting.
Yak52.
Included with my framed XL Robot Ken Tshirt.
I haven't decided on a reasonable price yet.
TheUnfairAdvantage
Regular
“Does anyone here actually loan out their shares to shorters? Or is that just an insto thing? What's the amount you get for loaning them and is there any risk that the borrower goes bust and you never get your shares back?”
I’m sorry……..but that does not sound an intelligent thing to do let alone say
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