BRN Discussion Ongoing
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Intel Loihi2 .. not BrainChip AkidaOne of Ericsson’s Stockholm-based neuromorphic researchers, Ahsan Javed Awan, who describes himself on LinkedIn as “Technology Specialist - Emerging Compute Algorithms” is looking for 3 Master students to work on “Brain-Inspired Algorithms for Telecom Networks” relating to RAN (Radio Access Network) workloads:
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As per my June 2024 post above, Ahsan Javed Awan had been very enamoured with Loihi over the past few years, but may possibly be open to evaluate other neuromorphic processors as well.
The job ad posted on LinkedIn doesn’t specify what specific neuromorphic hardware the algorithms would be implemented on:
Ericsson hiring Master Thesis: Brain-Inspired Algorithms for Telecom Networks in Stockholm, Stockholm County, Sweden | LinkedIn
Posted 7:17:52 PM. Join our TeamAbout this opportunity:With the rapid adoption of machine learning in…See this and similar jobs on LinkedIn.www.linkedin.com
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Master Thesis: Brain-Inspired Algorithms for Telecom Networks
Stockholm, Stockholm County, Sweden · 19 hours ago · 4 people clicked apply
Promoted by hirer · Responses managed off LinkedIn
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Master Thesis: Brain-Inspired Algorithms for Telecom Networks at Ericsson
About the job
Join our Team
About this opportunity:
With the rapid adoption of machine learning in telecommunication networks, the energy consumption associated with the training of cognitive algorithms and inference engines is of increased concern. Bio-inspired computing architectures such as Neuromorphic systems could process cognitive tasks in an energy-efficient manner, thereby yielding the networks sustainable. A variety of tasks such as deep learning inference, dynamic programming, quadratic unconstrained binary optimization etc... can exploit the neuromorphic hardware by reformulating the problem to the brain-inspired neural network architecture. To harness the potential of neuromorphic hardware in the telco networks, it is imperative to understand how brain-inspired neural networks can solve relevant computational problems in energy efficient manner.
This master thesis aims at developing brain-inspire neural networks (SNN, BCPNN, etc..) for certain telco use cases and demonstrating the potential energy efficiency gains.
What you will do:
The skills you bring:
- Understand Radio Access Network workloads that need to be energy efficient.
- Reformulate the RAN workloads into customized brain-inspired neural network architecture and validate the functionality using neuromorphic simulator.
- Devise technique to estimate the energy efficiency gains of the brain-inspired neural network for the RAN workloads.
- Documentation of the solution and evaluation.
Application:
- MSc Student in Physics/Computer Science/Mathematics/Embedded Systems or other related fields
- Proficient in Probability Theory, Deep Neural Networks, Spiking Neural Networks.
- Understanding of Neuromorphic Computing hardware and software stacks
- Good programing skills are required, knowledge of C++, Python, Linux.
Your application should include: CV, Cover letter, Transcripts of studies (both B.Sc. and up-to-date M.Sc.).
Why join Ericsson?
At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.
What happens once you apply?
Click Here to find all you need to know about what our typical hiring process looks like.
Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more.
Primary country and city: Sweden (SE) || Stockholm
Req ID: 773239
I’m of course aware of the December 2023 paper “Towards 6G Zero-Energy Internet of Things: Standards, Trends and Recent Results” paper, in which six Ericsson researchers had experimented with Akida for a ZE-IoT device…(https://d197for5662m48.cloudfront.n...rint_pdf/dfcbe2c260b5426434db681b0f637243.pdf)
…but this is a different area of research, in which Ericsson has been collaborating with Intel for years:
https://thestockexchange.com.au/threads/brn-discussion-ongoing.1/post-446092
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smoothsailing18
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Here’s the link for Chips
#brainchip #akida #ecg #edgeai #healthcareinnovation #medicaldevices #remotemonitoring #wearabletech #artificialintelligence #healthtech #smarthealthcare #aihealthcare #neuromorphicai #preventivecare | BrainChip
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supersonic001
Regular
#brainchip #akida #ecg #edgeai #healthcareinnovation #medicaldevices #remotemonitoring #wearabletech #artificialintelligence #healthtech #smarthealthcare #aihealthcare #neuromorphicai #preventivecare | BrainChip
What if detecting dangerous heart rhythms could happen instantly, privately, and without draining your device’s battery? With BrainChip’s Akida™ technology, ECG Anomaly Detection is bringing healthcare to the edge. By learning the unique patterns of normal heartbeats, Akida can identify...
A Chat with GPT: Brainchip Akida versus GPU / TPU technology | Justin Wearne
I argued the case with ChatGPT exploring why the world is persisting with GPU technology (developed for video games) to process AI workloads when breakthrough developments like Brainchip's Akida™ neuromorphic technology seem to offer a potentially better solution. During the conversation, it...
I argued the case with ChatGPT exploring why the world is persisting with GPU technology (developed for video games) to process AI workloads when breakthrough developments like Brainchip's Akida™ neuromorphic technology seem to offer a potentially better solution.
During the conversation, it became apparent that ChatGPT was parroting the world of AI hardware and software as it exists now and was initially blind to the future possibilities.
And this is not surprising because Large Language Model engines like ChatGPT get their information from readily available sources - they are therefore prone to tapping into the dominant information, dominant opinions, and reflect industry best practices. Sometimes (not always) you have to push them hard to consider disruption.
I wanted to peer into the future.
I didn't get the answer I was hoping for - I got something better...
hashtag#Brainchip hashtag#Akida hashtag#Neuromorphic hashtag#AI
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