FlipDollar
Never dog the boys
Great post hop!
BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
Frangipani
Regular
That'ud be the dress code.
Yes you're right Tech. Many here, regardless of their entry price, would be suffering significant paper losses since the all time high - I certainly am. It's impossible to pick the best entry point with any share purchase and there is the option to average down if the price drops.Thanks Labsy, it seems a few weren't too happy with what I posted, and that's fine.
To buy Brainchip shares was and still is an individuals choice, to sell Brainchip shares was and still is an individuals choice.
I chose not to sell my shares North of $2.00 and that has in effect cost me over 2.5 million dollars, time to make further investments,
the opportunity to buy back into Brainchip and double my already solid holding, I could moan and whinge on this forum all day long,
feeling sorry for myself, but I choose not to vent and keep venting, it's all good and dandy to vent but it's not all good and dandy to
vent against the company because things don't appear on the surface to be tracking the way your cash position selfishly suggests it
should be.
Individuals have made their own choices, for goodness sake own them and stop bagging our company, that's my vent, please respect my
opinion, it's as valuable as yours.
Many on this forum and the past forum know that I have been one of the most positive, passionate supporters of Peter and Anil and the entire Brainchip team for close on 8 years, I'm hurting seeing our share price so low, but is this the place to be venting, I reserve my opinion.
Trust in your own decisions moving forward, I still see Brainchip crossing that finishing post in 1st place...
Regardless of the share price BRN is in a much better position with partners, ecosystem, product offerings etc than they have ever been. Of all of the partnerships and potential use cases for AKIDA it is difficult to imagine that not one more single IP agreement will be signed in the future.
I believe that we will sign many more contracts and the commercial engagements happening behind closed doors right now will materialise fairly close to one another. Even one of these announcements by a major company should be enough to change sentiment towards BRN. When this happens the reversal in share price will dwarf the current downtrend by multiples.
It helps not to look at the SP on a daily basis until then.
Hey Dio, there's heaps of secrecy surrounding our collaboration with Merc. I've tried to get some info from BRN but, understandably they're tight-lipped ATM, which I think is a good thing.
So, do you think we are still involved with Merc and to what extent?
Learning
Learning to the Top 🕵♂️
Thanks Steve for the question.
www.linkedin.com
Learning 🏖
AiLabs Inc | Ai Labs Inc on LinkedIn: #ml #dl #nlp #ailabs #minsky #ai #minskyengine #ailabsinc #minskyengine…
🔹 Need for an easy-to-use multi-purpose Ai Engine: Clients often wonder how they can maximize the value of their business using AiLabs Inc.'s cutting-edge…
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Good evening Chippers,
This coming week could be VERY enlightening on global markets....
RUSSIA.
The Wagner group ( Putins hired help ) have apparently turned on the hand that fed them .....
This shits about to get reel in down town St Petersberg.
Stay tuned for the fireworks.
* Big thankyou to all contributors, the good ,bad & ugly all adds to a well rounded , thought provoking experience.
Regards,
Esq.
This coming week could be VERY enlightening on global markets....
RUSSIA.
The Wagner group ( Putins hired help ) have apparently turned on the hand that fed them .....
This shits about to get reel in down town St Petersberg.
Stay tuned for the fireworks.
* Big thankyou to all contributors, the good ,bad & ugly all adds to a well rounded , thought provoking experience.
Regards,
Esq.
HopalongPetrovski
I'm Spartacus!
Yes, let's just hope if Puto does indeed go down he doesn't decide to take the rest of us with him.
Hopefully some calm heads and hands still in the nuclear fire chain command structure able to circumvent any short term thinking.
Also might be being tipped from the frying pan straight into the fire if the Wagner group gain control.
Potentially scary times.
GLTA
Tothemoon24
Top 20
This was released 2 months ago by the USA Air Force Laboratory.
Short little promo , gave me a thrill which isn’t too hard
Apologies if it’s old news
Short little promo , gave me a thrill which isn’t too hard
Apologies if it’s old news
Frangipani
Regular
How different industries benefit from edge AI | TechTarget
AI can operate on smaller devices and in remote environments, making it useful for many industries. Here's how various markets can use edge AI.
How different industries benefit from edge AI
From manufacturing to energy and healthcare, edge AI is promising to various industries. It brings data processing and analysis closer to data sources.
By George LawtonPublished: 22 Jun 2023
AI is known for eating up computing power, requiring massive data centers. But its impressive capabilities can exist on smaller and more portable devices when appropriate.
Edge AI is the practice of placing AI systems on decentralized hardware devices that operate closer to sources of data. This approach can reduce latency, improve privacy, cut down on data transfers from one device to another and improve the performance of local AI applications. However, it may also require more computing power than other common cloud computing workloads do.
Edge AI offers performance benefits in keeping computation close to a source of data, ensures security when privacy protection is a priority and provides logistical advantages where data is collected in difficult-to-reach locations. Use cases for edge AI that business leaders should know appear across various vertical markets. The main examples to explore are manufacturing and production, healthcare, energy, transportation and retail.
Edge AI vs. edge computing
Edge AI is about putting smart computing brainpower directly onto devices, such as smartphones, smart fridges and other IoT appliances. Devices make decisions without having to wait for information sent over the internet. Edge computing is about moving compute work close to where data is collected. In addition to AI-enabled decision-making, edge computing also covers tasks like data storage and simple processing."Edge AI is beginning to revolutionize the way that many industries collect and utilize data that is produced by their products and their operations," said Anand Rao, global AI lead at professional services firm PwC.
Edge computing runs many powerful systems, such as those for in-patient monitoring and predictive maintenance. Edge AI enhances the performance of these kinds of tasks. For example, it can use computer vision to detect important events, such as the slip and fall of a patient, from a local device and then send an alert to medical staff. Other examples of additional capabilities for edge devices include natural language processing and predictive analytics.
"Edge AI and edge computing are changing how we handle data and extract value out of data, but they do so in different ways," said Bharath Thota, partner in the advanced analytics practice of global strategy and management consulting firm Kearney.
Benefits of edge AI for businesses
Benefits for businesses include reduced costs associated with network load in instances of high data volumes, privacy protection for sensitive applications, and improved inference performance and accuracy. Edge AI also improves efficiency and reduces costs by pushing complex AI computations to local devices. This reduces reliance on large, centralized computer systems and servers for AI inferencing workloads. In cases where applications need to perform real-time analytics on data, the proximity to the data source reduces latency.Edge AI can also enhance data security. It localizes the data collection process, performs predictions at the source of the data and restricts external network traffic to only the AI model's outputs, thereby protecting potentially sensitive data inputs. Finally, it's a reliable solution for devices and operations in remote locations with inconsistent network connections.
"Edge AI enables a variety of new use cases by reducing latency or even the need for an internet connection," said Lucas Lau, senior director at global consulting firm Protiviti. Apps run more quickly in these scenarios than they could without the edge computing setup.
Industry-specific use cases for edge AI
Industry use cases include the following:- Manufacturing and production. Edge AI improves predictive maintenance on a fleet or set of production equipment. AI models predict when a piece of equipment is most likely to experience a failure. Locally running algorithms analyze factors like vibration, heat and acoustic data from machines. They do so at high resolutions and in real time. Insights gleaned from this analysis are the output.
Large-scale data collection efforts at manufacturing plants and field operations are improved by data cleansing and anomaly detection. Performing these tasks locally can reduce data overhead and improve response times. - Healthcare. Edge AI helps monitor patients in real time, improving care and safety. Wearable devices on the patient collect health data. When AI-based analysis of this information occurs locally, it reduces bandwidth consumption and enhances data privacy as compared to transmitting the data to be processed centrally.
- Energy. Edge AI can keep a real-time watch on equipment. This can help predict when energy equipment, like power plants and wind farms, might need fixing, just like in the manufacturing use case. In addition, it can improve tools that study energy use data to identify busy times, predict usage patterns and improve how plants distribute energy.
- Transportation. Edge AI processes data from sensorsattached to vehicles in real time, enabling a self-driving vehicle to understand the surroundings, make decisions and navigate quickly. It can also provide warnings when a car is leaving its lane and enhance driver assistance systems.
- Retail. Edge AI improves security event detection by processing video streams that support loss prevention.
Another connection to our friends at Carnegie Mellon…
Anand S. Rao - Digital Transformation and Innovation Center - Carnegie Mellon University
Global AI Leader, PwC
Digital Transformation and Innovation Center
Sponsored by PwC
Digital Transformation and Innovation Center › People › Anand S. Rao
Anand S. Rao
Global AI Leader, PwC
ContactBio
Dr. Anand S. Rao is the Global Artificial Intelligence Leader for PwC. He is also the leader of PwC’s AI and Emerging Technology practice. With over 35 years of industry and consulting experience, Anand leads a team of practitioners who advise C-level executives and implement advanced analytics and AI-based solutions on a variety of strategic, operational, and ethical use cases. With his PhD and research career in Artificial Intelligence and his subsequent experience in management consulting he brings business domain knowledge, software engineer expertise, and statistical expertise to generate unique insights into the practice of ‘data science’.Prior to joining management consulting, Anand was the Chief Research Scientist at the Australian Artificial Intelligence Institute. He received his PhD from University of Sydney (with a University Postgraduate Research Award-UPRA) in 1988 and an MBA (with Award of Distinction) from Melbourne Business School in 1997. Anand has also co-edited four books on Intelligent Agents and has published over fifty papers in Computer Science and Artificial Intelligence in major journals, conferences, and workshops.
He has received widespread recognition for his extraordinary contributions in the field of consulting and Artificial Intelligence Research. He has received the Most Influential Paper Award for the Decade in 2007 from the Autonomous Agents & Multi-Agent Systems organization for his contribution on the Belief-Desire-Intention Architecture; MBA Award of Distinction from Melbourne Business School, 1997 and University Postgraduate Research Award (UPRA) from University of Sydney, 1985; Distinguished Alumnus Award from Birla Institute of Technology and Science, Pilani, India; He was recognized as one of Top 50 Data & Analytics professionals in USA and Canada by Corinium; one of Top 50 professionals in InsureTech; one of Top 25 Technology Leaders in Consulting; and has won a number of awards for his academic and business papers.
Anand is an Adjunct Professor in BITS Pilani’s APPCAIR AI Center. He also serves on the Advisory Board of Oxford University’s Institute for Ethics in AI, World Economic Forum’s Global AI Council, OECD’s Network of Experts on AI (ONE), OECD’s AI Compute initiative, Advisory Board of Northwestern’s MBAi program, Responsible AI Institute, Nordic AI Institute, and International Congress for the Governance of AI.
Digital Transformation and Innovation Center
4615 Forbes Avenue, 4th Floor
Pittsburgh, PA 15213
For more information or inquiries please contact us at: RRSIC@andrew.cmu.edu
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- © 2023 Carnegie Mellon University
Makeme 2020
Regular
No that's not the duck whisperer ,That's the FAMOUS BURNING BIN BOY.Ahhh so you’re the duck whisperer everyone is talking about lol… relax. We’re all entitled to our own opinion.
Featuring innovative TMR technology, the BMM350 from Bosch Sensortec enables new applications such as eliminating motion sickness in VR headsets, while providing a huge reduction in power consumption compared to the previous generation device
In indoor navigation, the BMM350 can be used to improve positioning accuracy when no satellite signal is available. It also provides position and speed measurement in e-bikes and other vehicles.
Frangipani
Regular
Another article hot off the press extolling the virtues of Edge AI.
Although the author is CEO of Xperi, a company that has a competing (although apparently not truly neuromorphic) Edge AI processor (https://thestockexchange.com.au/threads/brn-discussion-ongoing.1/post-289368), it is nevertheless good publicity for the Edge AI market in general.
www.forbes.com
Jon Kirchner
Forbes Councils Member
Forbes Technology Council
COUNCIL POST| Membership (Fee-Based)
Jun 23, 2023,08:15am EDT
Jon Kirchner, CEO, Xperi.
GETTY
While consumers worldwide have largely ignored invitations to review lengthy data collection policy disclosures before accessing the services and experiences they want to enjoy, advocates for protecting personal digital information are wondering out loud if the real-world implications of cloud-based artificial intelligence (AI) will finally knock consumers out of their "privacy complacency."
Beyond taking legal boilerplates seriously, however, a meaningful conversation is emerging around the implications of applying AI and machine learning (ML) to gather, analyze and process information in the cloud compared to edge computing environments—in which processing and data storage takes place closer to where data is created or consumed. It turns out that integrating AI and edge computing opens the door to significant benefits for those interested in enhancing data-powered experiences while protecting their personal information.
Cloud-based AI/ML services have crossed an important line when it comes to personal digital information. The technology no longer just stores the data. It specifically gathers, optimizes, trains on and monetizes data from virtually every public online source—including cloud services and connected devices. The early use cases have demonstrated that this technology can—and will—indiscriminately access and absorb contextual information from any digital source to do its job.
This is especially concerning as elements in the most sensitive sectors of society—including healthcare—rush to integrate cloud-based AI tools into their offerings. Some online mental and emotional support services, for instance, have controversially integrated AI chatbot technology into therapy and counseling sessions. On at least one occasion, cloud-based AI was deployed without the informed consent of patients/clients.
Originally developed to prevent personal data breaches by incorporating privacy considerations into the architecture of digital offerings, privacy-by-design also seeks to ensure that consumers retain control over their information. It is an objective that is difficult to achieve if all data manipulated by AI technologies ends up in cloud environments.
There can be little doubt about the positive role that cloud computing has played in democratizing access to processing and storage capacity. At a business level, cloud computing has allowed small- and mid-sized organizations to take advantage of technology-enabled operations that were once the exclusive domain of the Global 2000.
It has also opened the door for corporate behemoths to become more agile, replicating the market responsiveness once associated with smaller entities. From a consumer point of view, cloud and mobile apps have introduced a wide array of new options that have greatly expanded the experiences available to individuals.
A good argument, however, is emerging for a more balanced approach to the future of the global digital economy. As a society, we should engage in a more robust discussion about how we can get the most out of AI/ML to improve end-users lives without aggregating every citizen's personal information into a handful of CSPs. Indeed, compelling technical benefits are associated with constructing a global information infrastructure that keeps the bulk of our information where most of it belongs—locally and in the control of those who truly own the data.
This challenge offers an excellent example of a use case in which data processing must occur at the edge because concepts like "latency" matter. It is difficult to see how drivers, passengers and pedestrians can be kept safe if data must be sent to a distant cloud resource for AI analysis.
There is also the issue of adoption. One can safely assume that many, if not most, consumers will be reluctant to enable functions that collect sensitive behavioral data if it is sent to the cloud for AI processing. (At a more practical level, it is probably not a good idea to deploy vitally important connected car solutions that only work when there is a cell signal—a requirement for remote access to cloud resources.)
There is simply no reason to move all information out of its local environment all of the time. There are growing use cases for edge computing technologies to be applied—and controlled—by consumers to improve accuracy and performance and protect privacy.
In short, consumers and enterprises interested in controlling the management of personal information should encourage providers of digital products and services to calibrate how and when data is used in cloud-based AI environments.
Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Follow me on LinkedIn. Check out my website.
Although the author is CEO of Xperi, a company that has a competing (although apparently not truly neuromorphic) Edge AI processor (https://thestockexchange.com.au/threads/brn-discussion-ongoing.1/post-289368), it is nevertheless good publicity for the Edge AI market in general.
Council Post: No Room For Privacy Complacency In The Era Of Cloud-Based AI
Beyond taking legal boilerplates seriously, however, a meaningful conversation is emerging around the implications of applying AI and machine learning.
www.forbes.com
No Room For Privacy Complacency In The Era Of Cloud-Based AI
Jon Kirchner
Forbes Councils Member
Forbes Technology Council
COUNCIL POST| Membership (Fee-Based)
Jun 23, 2023,08:15am EDT
Jon Kirchner, CEO, Xperi.
GETTY
While consumers worldwide have largely ignored invitations to review lengthy data collection policy disclosures before accessing the services and experiences they want to enjoy, advocates for protecting personal digital information are wondering out loud if the real-world implications of cloud-based artificial intelligence (AI) will finally knock consumers out of their "privacy complacency."
Beyond taking legal boilerplates seriously, however, a meaningful conversation is emerging around the implications of applying AI and machine learning (ML) to gather, analyze and process information in the cloud compared to edge computing environments—in which processing and data storage takes place closer to where data is created or consumed. It turns out that integrating AI and edge computing opens the door to significant benefits for those interested in enhancing data-powered experiences while protecting their personal information.
Cloud-based AI/ML services have crossed an important line when it comes to personal digital information. The technology no longer just stores the data. It specifically gathers, optimizes, trains on and monetizes data from virtually every public online source—including cloud services and connected devices. The early use cases have demonstrated that this technology can—and will—indiscriminately access and absorb contextual information from any digital source to do its job.
This is especially concerning as elements in the most sensitive sectors of society—including healthcare—rush to integrate cloud-based AI tools into their offerings. Some online mental and emotional support services, for instance, have controversially integrated AI chatbot technology into therapy and counseling sessions. On at least one occasion, cloud-based AI was deployed without the informed consent of patients/clients.
An Irrational Bias For Cloud Impedes Privacy-By-Design
In the meantime, terabytes of data are being "hoovered" into a small handful of cloud service providers (CSPs) as users engage cloud-based AI applications from mobile devices, smart homes, connected cars—and even biologically embedded technologies, such as connected pacemakers. It represents a colossal concentration of data that should raise serious alarms and prompt consumers—as well as business leaders across all industries—to develop robust privacy-by-design frameworks.Originally developed to prevent personal data breaches by incorporating privacy considerations into the architecture of digital offerings, privacy-by-design also seeks to ensure that consumers retain control over their information. It is an objective that is difficult to achieve if all data manipulated by AI technologies ends up in cloud environments.
There can be little doubt about the positive role that cloud computing has played in democratizing access to processing and storage capacity. At a business level, cloud computing has allowed small- and mid-sized organizations to take advantage of technology-enabled operations that were once the exclusive domain of the Global 2000.
It has also opened the door for corporate behemoths to become more agile, replicating the market responsiveness once associated with smaller entities. From a consumer point of view, cloud and mobile apps have introduced a wide array of new options that have greatly expanded the experiences available to individuals.
A good argument, however, is emerging for a more balanced approach to the future of the global digital economy. As a society, we should engage in a more robust discussion about how we can get the most out of AI/ML to improve end-users lives without aggregating every citizen's personal information into a handful of CSPs. Indeed, compelling technical benefits are associated with constructing a global information infrastructure that keeps the bulk of our information where most of it belongs—locally and in the control of those who truly own the data.
Integrating The Power of AI With Edge Computing
For instance, edge computing and AI can make our roadways safer by enabling connected car technologies—including in-cabin cameras and sensors—that notice when a driver is getting drowsy. According to the most recent Center for Disease Control (CDC) survey, approximately one in 25 adult drivers (18 years or older) reported falling asleep while driving. The CDC estimates this results in over 6,000 fatal crashes and 50,000 injuries yearly.This challenge offers an excellent example of a use case in which data processing must occur at the edge because concepts like "latency" matter. It is difficult to see how drivers, passengers and pedestrians can be kept safe if data must be sent to a distant cloud resource for AI analysis.
There is also the issue of adoption. One can safely assume that many, if not most, consumers will be reluctant to enable functions that collect sensitive behavioral data if it is sent to the cloud for AI processing. (At a more practical level, it is probably not a good idea to deploy vitally important connected car solutions that only work when there is a cell signal—a requirement for remote access to cloud resources.)
There is simply no reason to move all information out of its local environment all of the time. There are growing use cases for edge computing technologies to be applied—and controlled—by consumers to improve accuracy and performance and protect privacy.
How?
Cloud-based AI needs the brute force of big data analytics before arriving at a conclusion or result. Edge computing—done right—applies machine learning inference from the opposite direction. The most innovative edge-based computing technologies use a small amount of real-time information to derive an accurate result. It is like the old game "Name That Tune."In short, consumers and enterprises interested in controlling the management of personal information should encourage providers of digital products and services to calibrate how and when data is used in cloud-based AI environments.
Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Follow me on LinkedIn. Check out my website.
Getupthere
Regular
NHS to use 'cutting edge' AI to diagnose cancer in less than 30 seconds — The Sun
ARTIFICIAL intelligence will be rolled out more widely across the NHS to save lives and slash record waiting lists.
Labsy
Regular
Couldn't agree more... each to their own. I am in a similar position to you and standing by your wise words buddy....Let's see what the new financial year brings . Im not happy with sp but very happy with my investment...Thanks Labsy, it seems a few weren't too happy with what I posted, and that's fine.
To buy Brainchip shares was and still is an individuals choice, to sell Brainchip shares was and still is an individuals choice.
I chose not to sell my shares North of $2.00 and that has in effect cost me over 2.5 million dollars, time to make further investments,
the opportunity to buy back into Brainchip and double my already solid holding, I could moan and whinge on this forum all day long,
feeling sorry for myself, but I choose not to vent and keep venting, it's all good and dandy to vent but it's not all good and dandy to
vent against the company because things don't appear on the surface to be tracking the way your cash position selfishly suggests it
should be.
Individuals have made their own choices, for goodness sake own them and stop bagging our company, that's my vent, please respect my
opinion, it's as valuable as yours.
Many on this forum and the past forum know that I have been one of the most positive, passionate supporters of Peter and Anil and the entire Brainchip team for close on 8 years, I'm hurting seeing our share price so low, but is this the place to be venting, I reserve my opinion.
Trust in your own decisions moving forward, I still see Brainchip crossing that finishing post in 1st place...
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Frangipani
Regular
You gotta love this guy’s enthusiasm! But someone with a LinkedIn account should let him know in the comments that he is not up-to-date regarding the commercial availability of neuromorphic hardware and the early adoption timeline! 
www.linkedin.com
Neeraj Kumar
+ Folgen
Everyone is in awe of ChatGPT. It’s a great piece of tech. No doubt about it. But here’s something even more mind-blowing – Neuromorphic Computing.
Neuromorphic computing is like the lovechild of neuroscience (BTW, you should read A Thousand Brains) and computer science – it’s all about creating computer systems that mimic the structure and function of the human brain.
So, what’s the big deal? Well, imagine a world where machines can learn, adapt, and make decisions on their own. We’re not talking about your average Siri or Alexa here. Neuromorphic computing takes artificial intelligence to a whole new level. It’s like having a Silicon Valley version of Professor X from The X-Men, with computers that can understand and interact with the world in a human-like way.
One of the most significant impacts of neuromorphic computing is its potential to revolutionize the field of robotics. Picture this: robots that can learn and navigate their environment, interact with humans seamlessly, and perform complex tasks with ease. From healthcare to manufacturing to space exploration, the possibilities are endless. We could have robotic companions that truly understand us and assist us in our day-to-day lives. Say goodbye to menial tasks and hello to a world of robot helpers! Remember Kaylons from Star Trek Parody – Orville? Let’s hope it does not happen.
But it doesn’t stop there. Neuromorphic computing also holds the key to unlocking the mysteries of the human brain. By emulating its structure and function, we can gain insights into how our brains work, potentially leading to breakthroughs in understanding and treating neurological disorders. Imagine a world where we can find cures for Alzheimer’s, Parkinson’s, and other devastating conditions. It’s like having a superpower to heal our minds!
It is still in its early stages, and there are numerous challenges to overcome. Creating hardware that can replicate the complexity of the human brain is no easy task. Although, early adoption will happen after 5 years from now! We can expect to see some prototypes as soon as by the year-end.
But, let’s not forget the potential downsides. As with any disruptive technology, there are ethical and privacy concerns to address. We don’t want our robotic friends turning into Skynet, do we? Or do we? I am kind of conflicted here
. But I genuinely believe that AI will take over Humans someday. But that’s for another day!
We’re on the brink of a technological revolution that will redefine what it means to be human and push the boundaries of what we thought was possible. So, embrace the madness, and let’s ride this wave of innovation together!
Cheers!
Forget ChatGPT! Neuromorphic Computing is the next big thing
Everyone is in awe of ChatGPT. It’s a great piece of tech.
Forget ChatGPT! Neuromorphic Computing is the next big thing
Neeraj Kumar
Neeraj Kumar
Principal Consultant at Quick Brown Fox
Veröffentlicht: 20. Juni 2023+ Folgen
Everyone is in awe of ChatGPT. It’s a great piece of tech. No doubt about it. But here’s something even more mind-blowing – Neuromorphic Computing.
Neuromorphic computing is like the lovechild of neuroscience (BTW, you should read A Thousand Brains) and computer science – it’s all about creating computer systems that mimic the structure and function of the human brain.
So, what’s the big deal? Well, imagine a world where machines can learn, adapt, and make decisions on their own. We’re not talking about your average Siri or Alexa here. Neuromorphic computing takes artificial intelligence to a whole new level. It’s like having a Silicon Valley version of Professor X from The X-Men, with computers that can understand and interact with the world in a human-like way.
One of the most significant impacts of neuromorphic computing is its potential to revolutionize the field of robotics. Picture this: robots that can learn and navigate their environment, interact with humans seamlessly, and perform complex tasks with ease. From healthcare to manufacturing to space exploration, the possibilities are endless. We could have robotic companions that truly understand us and assist us in our day-to-day lives. Say goodbye to menial tasks and hello to a world of robot helpers! Remember Kaylons from Star Trek Parody – Orville? Let’s hope it does not happen.
But it doesn’t stop there. Neuromorphic computing also holds the key to unlocking the mysteries of the human brain. By emulating its structure and function, we can gain insights into how our brains work, potentially leading to breakthroughs in understanding and treating neurological disorders. Imagine a world where we can find cures for Alzheimer’s, Parkinson’s, and other devastating conditions. It’s like having a superpower to heal our minds!
It is still in its early stages, and there are numerous challenges to overcome. Creating hardware that can replicate the complexity of the human brain is no easy task. Although, early adoption will happen after 5 years from now! We can expect to see some prototypes as soon as by the year-end.
But, let’s not forget the potential downsides. As with any disruptive technology, there are ethical and privacy concerns to address. We don’t want our robotic friends turning into Skynet, do we? Or do we? I am kind of conflicted here
. But I genuinely believe that AI will take over Humans someday. But that’s for another day!We’re on the brink of a technological revolution that will redefine what it means to be human and push the boundaries of what we thought was possible. So, embrace the madness, and let’s ride this wave of innovation together!
Cheers!
Frangipani
Regular
Here is another post liked by Nandan Nayampally on LinkedIn, posted by a California internist, who is a specialist in pulmonary and critical care medicine:
I googled the hospital, which serves the Napa Valley area (excellent
region!) and discovered the following Spring/Sommer 2023 hospital newsletter with more info on the said lung nodule programme:
How probable is it that Nandan, who resides in Austin, Texas, would
this post about a newly launched “lung nodule programme” by an MD at a California hospital on a six-month demo trial with a state-of-the-art robotic-assisted bronchoscopy system, raising funds for “an Artificial Intelligence System to detect signs of cancerous lung nodules up to a year earlier than manual-only review of x-rays” without Brainchip being involved?!
I googled the hospital, which serves the Napa Valley area (excellent
region!) and discovered the following Spring/Sommer 2023 hospital newsletter with more info on the said lung nodule programme: How probable is it that Nandan, who resides in Austin, Texas, would
this post about a newly launched “lung nodule programme” by an MD at a California hospital on a six-month demo trial with a state-of-the-art robotic-assisted bronchoscopy system, raising funds for “an Artificial Intelligence System to detect signs of cancerous lung nodules up to a year earlier than manual-only review of x-rays” without Brainchip being involved?!
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It's worth noting that the use case in this article is one which has been specifically mentioned by the company.
Featuring innovative TMR technology, the BMM350 from Bosch Sensortec enables new applications such as eliminating motion sickness in VR headsets, while providing a huge reduction in power consumption compared to the previous generation device
In indoor navigation, the BMM350 can be used to improve positioning accuracy when no satellite signal is available. It also provides position and speed measurement in e-bikes and other vehicles.
Early Forest Fire Detection Using Sensors
Silvanet, an early forest fire detection system, uses small sensors to prevent forest fires and protect people, animals, and the environment. Read more!
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