MaxwellAnne
Regular
Aaaarrrggghhhh I still haven't worked out who it was!!! Am I the only one? The curiosity is killing me haha
BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
curlednoodles
Regular
theyre not. as you know. Was just adding to the hypothetical
Fact Finder
Top 20
I mentioned a few days ago that the government was running the change to superannuation tax rules up the flag pole despite promises to the contrary.
The present line is that it will only affect 80,000 superannuates however this is in its first year of operation.
Just like stamp duty on real estate in NSW it will not be indexed to adjust for inflation and so over time this number will greatly increase.
In the real world in which we all live someone today commencing work at the age of 20 years will have about 40+ years before they enter retirement. The implications for a ceiling of $3 million over 40 years can be evidenced by if you are an oldie like myself recalling what you paid for your first home about 45 years ago. In our case it was $38,000. It came on the market two or three years ago now and I noticed that the owners were then asking over $900,000.
Some here will not have given much thought to their retirement but the following graph using Monte Carlo calculations suggests that having $2 million in superannuation today and wanting to have an annual pension of $84,000 based on average returns will give you only a 30% chance of your $2 million lasting until your average life expectancy:
There are lots of these tables out there on the web but the reality is the younger you retire the more money you need to have tucked away because while $3 million might seem like a lot now in 40 + years it will be a bag of lollies.
Those retirees who retired last year would have sat down with their accountants or advisers and calculated what they needed to live a comfortable life in retirement based upon the known rules and government promises. Overnight those calculations became meaningless for 80,000 Australians.
Now before you decide that these 80,000 are all fat cats or filthy rich consider this Australia has almost 3 million small business owners providing approximately 97% of all jobs in our economy. Amongst this three million business owners are:
"Medium-scale enterprises are about 56,835 in number (employing about 20 to 199 people),"
Then ask yourself if you were one of these 56,835 medium scale business owners would you want the stress and responsibility this involves if you could not at least retire with a 100% certainty that your superannuation would see you out and give you a life style that made it all worthwhile.
On the above figures to guarantee this and have a good buffer against inflation and tax law changes you would want four or five million dollars in my opinion.
Anyway these changes will not be made until after the next election so you have plenty of time to take advice, do your numbers and complain to your local member if you feel that this proposed change might not be particularly fair or reasonable for you or your loved ones.
My opinion only DYOR
FF
AKIDA BALLISTA
A remarkable thing about these job ads is the expressed willingness to consider informal experience in lieu of formal qualifications:Employment certainly on the front foot.
Head of Customer Engineering
BrainChip Laguna Hills, CA Hybrid 6 hours ago 8 applicants
Full-time
- 11-50 employees
- See how you compare to 8 applicants. Try Premium for free
- Actively recruiting
- Job poster joined LinkedIn in 2008
Head of Customer Engineering
BrainChip Laguna Hills, CA Hybrid
About the job
**Please no agencies***
Come join the company leading the technological revolution in artificial intelligence. BrainChip is a global technology company producing a groundbreaking neuromorphic processor that brings artificial intelligence to the edge in a way that is beyond the capabilities of other products.
We are the world’s first commercial producer of ultra-low-power and high-performance artificial intelligence technology processors that enables a wide array of applications such as self-driving cars, hearing aids, drones, and agricultural equipment. The event-based neural network processor is inspired by the spiking nature of the human brain and is implemented in an industry-standard digital process.
Our company was recognized as one of the “Startups Worth Watching in 2021” in EE Times’ annual Silicon 100 list of global semiconductor technologies and our founder was named the winner of the AI Hardware 2021 Innovator Award. We have offices in Laguna Hills, California; Toulouse, France; Hyderabad, India; and Perth, Australia. We are also publicly traded on the Australian Stock Exchange (BRN:ASX) and the OTC Market (BRCHF).
Job Title: Head of Customer Engineering
Reports to: CEO
SUMMARY:
A principal goal for the Head of Customer Engineering is to bridge core engineering activities into commercialization efforts. This includes technical customer support policies, objectives, and initiatives. This is a hands-on position, managing a team as well as resolving higher level technical and customer relations issues. This position needs to be able to understand and maintain a working, technical knowledge of our client’s core technologies to provide full top level technical support.
ESSENTIAL JOB DUTIES AND RESPONSIBILITIES:
ENGINEERING
• Define deliverables, and program manage core developments from engineering to meet the Product Team specifications/requirements; Validate features and performance meet customer and market requirements
• Work closely with Product, Sales, Engineering and Advanced Research to optimize efficiency and effectiveness in technology handoff for commercialization
• Become the leader, and educator of fundamental knowledge related to machine learning functions and field deployments
• Working with the Product Team clearly define the hardware and s/w tool roadmap with critical milestones, dependencies, and staffing plans
MARKET
• Define strategy, and execute continuous benchmarking activities to ensure market competitiveness; identify strengths/weaknesses; feedback to organization for improvement
• Along with Sales, lead the definition, design and launch of customer centric evaluation boards//modules to highlight company value-add and differentiation
•Capable of basic application layer s/w coding, and debugging
SALES
•Take delivery of models from engineering and implement a real-life demonstration system to correlate assumptions related to ease of use, performance, and application
•Be the first to back up sales and system architects
• Handle basic level of application advice.
• In conjunction with Product deliver technical content for customer collateral (and consumption)
• Serve as a catalyst for growth in the marketplace by representing company at technical conferences/committees to stay up-to-date with the latest technologies, and trends impacting the AI Industry
• Formally document the design processes and methodology; (ie ISO, Automotive Qualification)
• Ensure all technical documentation is customer friendly
GENERAL
- Develops service level standards focused on response times, issue resolution, service quality, and customer satisfaction.
- Establishes policies and procedures that produce high quality customer support and that reflect industry best practices.
- Ensures that systems are in place and are utilized to capture and report on service metrics, including any customer feedback or trends in product or service issues.
- Manages resource decision-making, planning, and best practices.
- Aligns technical customer support activities and initiatives to support and enhance the objectives of the organization.
- Take ownership of unresolved technical issues, and bridge with Sales and Engineering teams to solve and/or develop solutions.
- Manage customer technical relationships as required and work with internal resources to ensure a high level of customer satisfaction.
- Ability to communicate orally with customers, management, and other co-workers, both individually and in front of a group is crucial.
QUALIFICATIONS:
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Education/Experience:
- B.S. in Computer Science, or EE; will consider experience in lieu of education
- Requires a very high technical acumen and understanding of machine learning and deep learning experience using Python, Tensorflow
- Firsthand experience with object classification, object detection, face recognition, keyword spotting a plus
- Experience with Git version control system
- Experience in CPUs, Tools and methodologies, machine learning, C++ programming
- PCB design, layout and bring-up experience a plus
- Has led small engineering teams
- Has been in front line customer support role
- Comfortable as a player coach—this is a very small team and the leader needs to spend 80% doing and 20% managing
Other Skills and Abilities:
- Strong verbal and written communication skills
- Ability to compose routine reports and correspondence
- Ability to effectively communicate with persons of various social, cultural, economic, and educational backgrounds
- Strong teamwork and interpersonal skills and analytical skills
- Desire to be involved in a diverse and creative work environment
- Must be a self-starter with mindset for growth and real passion for continuous learning
Compensation, Benefits, and Perks:
- Competitive Pay $175-$250K
- Restricted Stock Units
- Bonus Pay
- 401K with matching - Fully Vested from Day one
- Free Lunch Daily and Snacks
- Paid Time Off
- Holiday Pay
- Company-paid Medical HMO, Dental PPO, and Vision Insurance
- Company-paid Life Insurance and AD&D
- Employee Assistance Program
BrainChip is an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.
Benefits found in job post
- 401(k)
- Vision insurance
About the company
BrainChip
8,577 followers
- B.S. in Computer Science, or EE; will consider experience in lieu of education
- B.S. in Computer Science, or EE; will consider experience in lieu of education
I guess one thing driving this is the fact that the internet makes all knowledge available.
Another thing is that there are lots of "amateur" software programmers without formal qualifications, and programming can be learnt on-line.
Mind you, I would think that an unqualified applicant would need exceptional experience to be considered for some of the BrainChip jobs that have been advertised.
Deadpool
Did someone say KFC
You're not the only one.
db1969oz
Regular
I think it was Blind Freddie, I haven’t seen him post for a while!
wilzy123
Founding Member
WBT has gone stratospheric @ $8.17 up 5.93% =53c today = the full price of one BRN share
Wags
Regular
Ha, no, your not the only one. I have no idea either. Surely we deserve some clue's?
Fact Finder
Top 20
Well let us all hope that those who identified it as a much better company than Brainchip way back sensibly sold out of Brainchip and maxed out on WBT otherwise it would be very sad if they were still here holding Brainchip shares.WBT has gone stratospheric @ $8.17 up 5.93% =53c today = the full price of one BRN share
My opinion only DYOR
FF
AKIDA BALLISTA
Damo4
Regular
With no revenue and a fast run up, I hope those here in the know can see a pattern forming.
If a genie told me I could sell BRN at $2 and still have time to buy in again for 50c before the journey continues I'd have made a different decision.
I hope everyone makes some cash dollars whichever way they bet on BRN or WBT!
curlednoodles
Regular
I agree completely. However, is it possible the record high of $2.34 was the result of a mini short squeeze? We know the shorters love BRN, and the Merc news came out of nowhere, catching shorters by surprise. Just a thought...
Rskiff
Regular
It would be a interesting comparison to see how many shorts there were back then to now. @Esq.111 are your skills up to this?I agree completely. However, is it possible the record high of $2.34 was the result of a mini short squeeze? We know the shorters love BRN, and the Merc news came out of nowhere, catching shorters by surprise. Just a thought...
Fact Finder
Top 20
There was certainly one high profile poster at HC who felt the need to communicate that the price of $2.34 was unsustainable and allegedly made a multi million dollar trade but now considers BRN the most over hyped under performing company on the ASX. If I had made millions out of a trade and not lost any money at all I would certainly love BRN but not so everyone it seems so perhaps short interest was at play back then.
My opinion only DYOR
FF
AKIDA BALLISTA
ndefries
Regular
At December 31 I believe we had 59m shorts which dropped to 29m mid Feb 2022. I think citi was doing a lot of buying to get to their 2nd spot.
Fullmoonfever
Top 20
Whilst I don't believe we are with Qualcomm as yet, in my personal layman opinion, if we are to be in Snapdragon at any point, I suspect it would be in the sensing hub.
This from their site for a start.
www.qualcomm.com
AI comes in different shapes and forms. For example, there’s AI that runs in the cloud — using large, deep neural networks — that lets you categorize your entire photo album in seconds. Then there’s AI that runs only on your smartphone, keeping all the calculation and personal data on the phone while making your social media posts and videos look great.
In this post, we are talking about another kind of AI. It is small and quiet, securely running in the background 24/7 to help you with everyday tasks. Last year at our annual Snapdragon Tech Summit we introduced our 2nd Generation Qualcomm Sensing Hub with a dedicated always-on, low-power AI processor that is uniquely designed to run some tiny, yet powerful AI use cases.
Thanks to this new, dedicated AI processor – now powerful enough to run small AI neural networks on your smartphone – we are seeing mind-blowing 5X AI performance improvement over our previous-generation Sensing Hub. Because of this performance gain, we took the neural networks that usually run on the Qualcomm Hexagon Processor and ported it to the Sensing Hub. Now we can offload up to 80 percent processing from our Hexagon Processor* — all at less than 1 milliamp (mA) of power consumption.
The sensing hub scope seems right up Akidas function alley & I presume where Prophesee will possibly link in too given the comments on camera function below.
www.qualcomm.com
I also read in some earlier papers about the Zeroth which we all know about.
Back in 2016 was the following article which, as we always know in hindsight, gives a good outline of where they were heading.
Neuromorphic was also the catch word back then for them and gotta wonder that if they can get their hands on something pretty much COTS and more advanced, that can readily slip into their product offering, then why wouldn't you look for a POC at least. Also coupled with the Prophesee relationship as we know.
SNN better than CNN RNN etc as we all believe & if AKD1500 has the CNN2SNN as indicated then the transition may be easier to slip into the sensing hub and run off the Hexagon processor?
rethinkresearch.biz
Machine learning is no longer a technology confined to supercomputers and massive AI engines – it is coming to the edge of the network and even to the handset, to power new user experiences and make complex decisions close to the user.
Google’s work with Movidius, and IBM’s TrueNorth ‘brain chips’ and device-based deployments of Watson, are examples, but perhaps the most ambitious effort comes from Qualcomm with its Zeroth machine learning platform, which can be embedded in the Snapdragon system-on-chip (SoC).
Initially, Qualcomm’s Zeroth/Snapdragon work focused on bringing AI algorithms and vision processing to cars, but many other applications are in its sights, as highlighted by its new deep learning software developers’ kit (SDK) for the Snapdragon 820 SoC.
Called the Snapdragon Neural Processing Engine, and unveiled at the recent Embedded Vision Summit, the SDK is an attempt by Qualcomm to expand beyond its core smartphone markets – by enticing automotive, industrial, and IoT developers to its Snapdragon platform. It also sees the chip supplier looking for broader market reach, and accelerated uptake, by enabling a great deal of its brain-like functionality in software.
Back in May 2014, when Qualcomm first introduced the Zeroth project, the goal was to build a neural processing unit (NPU) that would be a hardware module for its advanced SoCs. But dedicated hardware not only adds to cost and power consumption for mobile devices, but raises barriers to developer support.
So the new SDK for the neuromorphic Zeroth Machine Intelligence Platform – Qualcomm’s equivalent of IBM’s TrueNorth – aims to bring the hardware-specific functions of these brain chips to a more general purpose Snapdragon platform. This will help mobile devices to leverage the potential of silicon that acts in a manner somewhat akin to the human brain.
While IBM is planning on shipping its brain chips to end-customers, who will put them to use in servers, the Qualcomm approach relies on software to bring those capabilities to a far more adaptable chipset – one that can be used in mobile devices, industrial IoT endpoints and vehicles.
Machine learning is central to the evolution of the IoT. There simply aren’t enough engineers to monitor and manage the billions of devices that are expected to be deployed. There aren’t enough developer resources to teach image recognition to camera systems, or collision avoidance to autonomous cars, and so the machines have to be able to evolve from a base-level intelligence installed in the factory, and adapt to the dynamic world around them.
If a connected traffic camera had to poll a real human being every time it spotted a car licence plate it didn’t recognize, entire systems would crawl to a halt. From the edge devices to the centralized data center deployments, machine learning enables vast libraries of data to be independently analyzed at speeds far in excess of what a human could manage – in theory, creating value from data that is just lying around, waiting to be used.
Qualcomm says that the SDK will allow OEMs to run their neural network models on the Snapdragon 820, which will allow devices like smartphones, drones, and automobiles, to carry out image recognition, object tracking, gesture and facial recognition, and natural language processing.
The new SDK’s flagship features include an accelerated runtime for the on-device execution of the convolutional and recurrent neural networks, configured in software to get the most out of the 820’s cores – the 64-bit Kyro quad-core CPU, Adreno 530 GPU, and the Hexagon 680 DSP.
A core part of the offering is the Snapdragon’s ability to move its workloads between the different cores, in order to achieve an optimal load or efficiency. This heterogeneous compute power should allow for more capable end devices, and support for Caffe and CudaConvNet is also included, which will be appreciated by developers who have used those familiar environments.
“The demand for untethered, mobile learning-driven user experiences is increasing rapidly and Qualcomm Technologies’ customers have been clamoring for tools to help them realize their product visions,” said Gary Brotman, director of product management at Qualcomm Technologies. “With the introduction of the new Snapdragon Neural Processing Engine SDK, we are making it possible for myriad sectors, including mobile, IoT and automotive to harnesses the power of Qualcomm Snapdragon 820 and make high-performance, power efficient on-device deep learning a reality.”
The Zeroth software package is currently used in Qualcomm’s Snapdragon Scene Detect, for spotting objects or faces in a camera view and adjusting the settings accordingly, and its Smart Protect malware detection, which looks for anomalous behavior in the phone that might be a sign of a security compromise.
Qualcomm has referred to this offering as one of the first examples of the emerging age of “conscious computing”. Last fall, Raj Talluri, SVP of product management in mobile computing, said in an interview: “We’ve done a lot of work getting cameras and computer vision optimized in the phone space. Now we’re bringing that technology into this space where the application is a little different, but the technology we built applies perfectly.” The result, he said, is “a camera conscious of what’s happening in the scene”.
That consciousness is achieved with software to perform on-camera video analytics such as object detection, facial detection and recognition and multi-object tracking, harnessing Zeroth to classify different objects.
By bringing the intelligence to the local site, Qualcomm believes the cameras will be able to go a step further than current cloud-based systems – for instance, not just distinguishing residents of the home from strangers, but being able to ignore ‘safe’ incidents, like a car driving past outside, and not waste time and processing power by uploading images of them.
This reveals the Qualcomm agenda – to shift the edge of the network into the device, and to make the mobile gadgets, in which its chips are so strong, the seat of artificial intelligence, rather than the centralized machine learning platforms where Intel is the dominant silicon provider and the smarts are controlled by IBM or Google. Zeroth is key to this agenda, but the Snapdragon camera indicates the same directions.
More prosaically, it also opens up new addressable markets for Qualcomm processors, amid intense pressures in the smartphone market. Talluri said: “We’re tapping into our immense portfolio to build custom platforms for key segments within the IoT, and connected cameras are one of these areas that can benefit.”
This from their site for a start.
A brand-new AI runs on 2nd gen Qualcomm Sensing Hub [video]
In this post, we are talking about another kind of AI. It is small and quiet, securely running in the background 24/7 to help you with everyday tasks.
AI comes in different shapes and forms. For example, there’s AI that runs in the cloud — using large, deep neural networks — that lets you categorize your entire photo album in seconds. Then there’s AI that runs only on your smartphone, keeping all the calculation and personal data on the phone while making your social media posts and videos look great.
In this post, we are talking about another kind of AI. It is small and quiet, securely running in the background 24/7 to help you with everyday tasks. Last year at our annual Snapdragon Tech Summit we introduced our 2nd Generation Qualcomm Sensing Hub with a dedicated always-on, low-power AI processor that is uniquely designed to run some tiny, yet powerful AI use cases.
Thanks to this new, dedicated AI processor – now powerful enough to run small AI neural networks on your smartphone – we are seeing mind-blowing 5X AI performance improvement over our previous-generation Sensing Hub. Because of this performance gain, we took the neural networks that usually run on the Qualcomm Hexagon Processor and ported it to the Sensing Hub. Now we can offload up to 80 percent processing from our Hexagon Processor* — all at less than 1 milliamp (mA) of power consumption.
The sensing hub scope seems right up Akidas function alley & I presume where Prophesee will possibly link in too given the comments on camera function below.
Mobile AI | On-Device AI | Qualcomm®
Learn about the advantages of AI on-device, such as improved user privacy and enhanced application performance. Unlock the power of mobile AI today.
Qualcomm Sensing Hub
The latest generation of Sensing hub has more horsepower with an additional dedicated AI processor to support audio, sensing and camera-based experiences, becoming the most powerful ultra-low-power AI architecture in the industry.I also read in some earlier papers about the Zeroth which we all know about.
Back in 2016 was the following article which, as we always know in hindsight, gives a good outline of where they were heading.
Neuromorphic was also the catch word back then for them and gotta wonder that if they can get their hands on something pretty much COTS and more advanced, that can readily slip into their product offering, then why wouldn't you look for a POC at least. Also coupled with the Prophesee relationship as we know.
SNN better than CNN RNN etc as we all believe & if AKD1500 has the CNN2SNN as indicated then the transition may be easier to slip into the sensing hub and run off the Hexagon processor?
Qualcomm’s latest SDK brings deep learning to humble devices - Rethink
Machine learning is no longer a technology confined to supercomputers and massive AI engines – it is coming to the edge of the network and even to the handset, to power new user experiences and make complex decisions close to the user. Google’s work with Movidius, and IBM’s TrueNorth ‘brain...
Machine learning is no longer a technology confined to supercomputers and massive AI engines – it is coming to the edge of the network and even to the handset, to power new user experiences and make complex decisions close to the user.
Google’s work with Movidius, and IBM’s TrueNorth ‘brain chips’ and device-based deployments of Watson, are examples, but perhaps the most ambitious effort comes from Qualcomm with its Zeroth machine learning platform, which can be embedded in the Snapdragon system-on-chip (SoC).
Initially, Qualcomm’s Zeroth/Snapdragon work focused on bringing AI algorithms and vision processing to cars, but many other applications are in its sights, as highlighted by its new deep learning software developers’ kit (SDK) for the Snapdragon 820 SoC.
Called the Snapdragon Neural Processing Engine, and unveiled at the recent Embedded Vision Summit, the SDK is an attempt by Qualcomm to expand beyond its core smartphone markets – by enticing automotive, industrial, and IoT developers to its Snapdragon platform. It also sees the chip supplier looking for broader market reach, and accelerated uptake, by enabling a great deal of its brain-like functionality in software.
Back in May 2014, when Qualcomm first introduced the Zeroth project, the goal was to build a neural processing unit (NPU) that would be a hardware module for its advanced SoCs. But dedicated hardware not only adds to cost and power consumption for mobile devices, but raises barriers to developer support.
So the new SDK for the neuromorphic Zeroth Machine Intelligence Platform – Qualcomm’s equivalent of IBM’s TrueNorth – aims to bring the hardware-specific functions of these brain chips to a more general purpose Snapdragon platform. This will help mobile devices to leverage the potential of silicon that acts in a manner somewhat akin to the human brain.
While IBM is planning on shipping its brain chips to end-customers, who will put them to use in servers, the Qualcomm approach relies on software to bring those capabilities to a far more adaptable chipset – one that can be used in mobile devices, industrial IoT endpoints and vehicles.
Machine learning is central to the evolution of the IoT. There simply aren’t enough engineers to monitor and manage the billions of devices that are expected to be deployed. There aren’t enough developer resources to teach image recognition to camera systems, or collision avoidance to autonomous cars, and so the machines have to be able to evolve from a base-level intelligence installed in the factory, and adapt to the dynamic world around them.
If a connected traffic camera had to poll a real human being every time it spotted a car licence plate it didn’t recognize, entire systems would crawl to a halt. From the edge devices to the centralized data center deployments, machine learning enables vast libraries of data to be independently analyzed at speeds far in excess of what a human could manage – in theory, creating value from data that is just lying around, waiting to be used.
Qualcomm says that the SDK will allow OEMs to run their neural network models on the Snapdragon 820, which will allow devices like smartphones, drones, and automobiles, to carry out image recognition, object tracking, gesture and facial recognition, and natural language processing.
The new SDK’s flagship features include an accelerated runtime for the on-device execution of the convolutional and recurrent neural networks, configured in software to get the most out of the 820’s cores – the 64-bit Kyro quad-core CPU, Adreno 530 GPU, and the Hexagon 680 DSP.
A core part of the offering is the Snapdragon’s ability to move its workloads between the different cores, in order to achieve an optimal load or efficiency. This heterogeneous compute power should allow for more capable end devices, and support for Caffe and CudaConvNet is also included, which will be appreciated by developers who have used those familiar environments.
“The demand for untethered, mobile learning-driven user experiences is increasing rapidly and Qualcomm Technologies’ customers have been clamoring for tools to help them realize their product visions,” said Gary Brotman, director of product management at Qualcomm Technologies. “With the introduction of the new Snapdragon Neural Processing Engine SDK, we are making it possible for myriad sectors, including mobile, IoT and automotive to harnesses the power of Qualcomm Snapdragon 820 and make high-performance, power efficient on-device deep learning a reality.”
The Zeroth software package is currently used in Qualcomm’s Snapdragon Scene Detect, for spotting objects or faces in a camera view and adjusting the settings accordingly, and its Smart Protect malware detection, which looks for anomalous behavior in the phone that might be a sign of a security compromise.
Qualcomm has referred to this offering as one of the first examples of the emerging age of “conscious computing”. Last fall, Raj Talluri, SVP of product management in mobile computing, said in an interview: “We’ve done a lot of work getting cameras and computer vision optimized in the phone space. Now we’re bringing that technology into this space where the application is a little different, but the technology we built applies perfectly.” The result, he said, is “a camera conscious of what’s happening in the scene”.
That consciousness is achieved with software to perform on-camera video analytics such as object detection, facial detection and recognition and multi-object tracking, harnessing Zeroth to classify different objects.
By bringing the intelligence to the local site, Qualcomm believes the cameras will be able to go a step further than current cloud-based systems – for instance, not just distinguishing residents of the home from strangers, but being able to ignore ‘safe’ incidents, like a car driving past outside, and not waste time and processing power by uploading images of them.
This reveals the Qualcomm agenda – to shift the edge of the network into the device, and to make the mobile gadgets, in which its chips are so strong, the seat of artificial intelligence, rather than the centralized machine learning platforms where Intel is the dominant silicon provider and the smarts are controlled by IBM or Google. Zeroth is key to this agenda, but the Snapdragon camera indicates the same directions.
More prosaically, it also opens up new addressable markets for Qualcomm processors, amid intense pressures in the smartphone market. Talluri said: “We’re tapping into our immense portfolio to build custom platforms for key segments within the IoT, and connected cameras are one of these areas that can benefit.”
wilzy123
Founding Member
Hiring is not what it was 10, 20, 30+ years ago. Degrees are not essential, especially in this field of work. If anything, I think the absence of consideration given to 'experience in lieu of education' is a big red flag for a lot of people.
White Horse
Regular
Hi all.
Question of new employment location resolved.
On 1/03/2023 3:37 pm, Tony Dawe wrote:
Question of new employment location resolved.
On 1/03/2023 3:37 pm, Tony Dawe wrote:
Fullmoonfever
Top 20
Dang Son
Regular
Sad is that the market has completely lost interest in BRN after our massive P&D ( not to say that wont change if we can make a go of Akd1.5 and actually sell it as they're threatening to)
I don't hold WBT and haven't followed their tech but seems they Managed to avoid the pitfall that constrains BRN investors at present.
(Not to say WBT won't retrace some but certainly looks to be out of the woods)
Congratulations WBT holders.
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