wilzy123
Founding Member
cheers rocket. good job
it's ok buddy... just make better life choices.
cheers rocket. good job
I concur. I was also present at the AGM.Good evening All,
My thoughts on this mornings AGM.
On-time...
Sean spoke well, clearly felt that he needed to yet again reinforce what the companies objectives are, are we on track ?...oh yes we are !
Has he the backing of the Board ?...oh yes he has, despite getting crap from the Board !!
Sean could not have worded things clearer, I'm extremely comfortable, are you ?
As I and a few others have mentioned over the last 12/24 months, the progress has been a lot slower with regards uptake of IP Licenses,
customers products flooding the market and so on, which the company have honestly acknowledged is frustrating to them, from the
office staff to the top.
As I have personally mentioned and now been confirmed by Antonio, the engineers, scientists and everyone working within our company
are working their backsides off to achieve excellence, we ALL WISH TO SEE BRAINCHIP SUCCEED ! and we will.
I love Antonio, he is a calm, professional executive, speaks very precisely, clearly thinks before he comments and covered very
diplomatically for Sean on more than one occasion, if you listen carefully what he said, he's basically telling us that Sean is meeting with
CEO's, CTO's of "major world technology companies"...we are talking multibillion dollar companies, think about that comment carefully.
Then we have Sean, doing his utmost not to breach any NDA's, stating he can't name a date, but the quarter (3 month) timeline when
some of these big players may decide that, having reduced the field from 8 or so, down to 2 or 3 go ahead and choose us, but I'm open
to the fact that some companies may decide to punt a little and give those 2 or 3 all a go, depending on their future plans, which we,
Brainchip, may never be privy to.
The shareholder who persistently went on about IP Licenses, well, I felt Antonio showed real professional skill in attempting to answer
this persons questions, in fact, I'll go as far as to say, that's the best explanation of IP protocol I've heard.
It was great that Dr. Tony flew down under, he spoke great as he did on his recent podcast, clear, no mucking around, a straight shooter,
that I really like in an individuals personality, he is an excellent replacement for Peter, if that's the right wording ?
Finally, I'd like to thank Peter for attending, it shows the flock of Peter's love and belief in his own company, still the number one stake
holder, and he is clearly unwell, which shows shareholders that the founder 'still' puts others before his own self, I love his spirit, don't you ?
Thanks Peter and the entire team, I still believe that the dream is red hot to succeed.
Love Akida Tech (Perth)
A reminder that Sean will be leaving Australia soon as he is "off to another country to make more sales calls" (13:36 mark Episode 5 – BrainChip Investor Podcast Q1 2024)
Having a surf and wonder if this young mans education experience at CMU in 21 / 22 gets asked about at his current employer
Andrew Siemer
Engineering @ NVIDIA | CMU
NVIDIA Carnegie Mellon University
San Francisco Bay Area
GPU Firmware Engineer
NVIDIA
Jan 2023 - Present 1 year 5 months
Santa Clara, California, United StatesGPU Firmware Intern
NVIDIA
May 2022 - Aug 2022 4 months
Santa Clara, California, United StatesEmbedded Engineer Intern
Edge Impulse
May 2021 - Aug 2021 4 months
San Jose, California, United States
Built Sensor Fusion framework & firmware driver, enabling real-time data multiplexing from diverse hardware sensors. Core feature in company's SDK, favored in industrial applications for multi-sensor ML models. Led product launch with Silicon Solutions team & Harvard University, developing image processing firmware & custom hardware for TinyML course.
Carnegie Mellon University
Master of Science - MS Electrical and Computer Engineering
2021 - 2022
Studied embedded kernel design, fast code, and modern computer architecture. Conducted research in neuromorphic processor design, focusing on edge learning applications for artificial general intelligence using BrainChip's Akida SoC.
I guess he must just like the spicy noodles and kimchi.After leaving Melbourne on Thursday Sean is going to Korea
He forked my repo years ago:
GitHub - andrewsiemer/akida-camera: Learning how to use Akida with a Camera Feed
Learning how to use Akida with a Camera Feed. Contribute to andrewsiemer/akida-camera development by creating an account on GitHub.github.com
We are on a mission to make edge AI even lighter and better.
Rudy Pei - ML Research Engineer Brainchip
Rudy Pei on LinkedIn: #tenns
Still remember learning about polynomials from highschool? It turns out they are all you need to make highly performant neural networks. One novelty (among…www.linkedin.com
Still remember learning about polynomials from highschool? It turns out they are all you need to make highly performant neural networks. One novelty (among many) of the TENNs model of BrainChip is we build temporal kernels with orthogonal polynomials. Check out our latest work here:
By applying only the concept of polynomial parameterization, we crushed event-based dataset with very few parameters. Notably, we get 100% test accuracy on DVS128 hand gesture recognition benchmark.
Papers with Code - DVS128 Gesture Benchmark (Gesture Recognition)
The current state-of-the-art on DVS128 Gesture is TENNs-PLEIADES. See a full comparison of 13 papers with code.paperswithcode.com
We are on a mission to make edge AI even lighter and better.
She must be leaving and recruiting for her replacement. No way we need another hr person at this senior level for a head count under 100. If the role grew you would start with a more junior burger to assist.
Could be wrong but time will tell.
Hi @Diogenese
I note from the attached post akida uses quantisation. What is your opinion of this please. I also note in full moons post akida claims a 3.67 x gains using this method, Qualcomm claims 4 x so similar.
Liked by Nikunj from Brainchip. Does it mean something? Or nothing. Tyia
Introduction to On-Device AI - DeepLearning.AI
Learn to deploy AI models on edge devices like smartphones, using their local compute power for faster and more secure inference.www.deeplearning.ai
@Fullmoonfever
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