Morning FF
Thought you might like a Sunday read.
Hi Rocket
Nice read.
There are three takeaways for me:
1. The speed of change is going to require flexibility. The authors see that flexibility being a driver of software solutions as hardware cannot be easily updated or retrained. The authors clearly have not heard of AKIDA technology and it’s on chip learning. (The audience goes quiet absorbing the enormity of this technology breakthrough then thunderous applause.)
2. The following extract regarding ARM opens up the prospects for some very close relationship with Brainchip. In what form is the billions and billions of dollars question???
“Arm Will be Forced to Change Its Business Model to Sustain Innovation
It was announced over a year ago that an agreement had been reached for NVIDIA to acquire Arm for US$40 billion, despite the takeover still needing approval from the European Union (EU) and several regulators around the world, as well as from Arm’s IP licensees. However, this development has uncovered numerous concerns about Arm’s future, and chief among them is the lack of synergy needed to transform itself and grow beyond just licensing its IP. Arm is in crucial need of expanding its engineering resources, while revamping its business model and technology offerings, if it wants to cope effectively with the phenomenal demand for technology innovation required to sustain the mobile and the computing ecosystems, and to become a key solution provider for the markets it serves.
With or without the NVIDIA acquisition, if Arm’s Research and Development (R&D) and engineering resources do not evolve in line with market demand for innovation, then the entire industry will be slowed because it is Arm’s Instruction Set Architectures (ISAs) and micro-architectures that are the foundation platforms for innovation in the mobile computing markets. Therefore, it will be incumbent on the industry to inject billions of dollars to expand Arm’s R&D and sustain innovation because the company cannot achieve this objective under the current status quo. If this is not addressed, then Arm will not be able to execute on its ambitious plans with the resources it has currently, which could become a major issue that will affect the entire industry.”
3. Further evidence that Brainchip is in the right place ahead of all the world with its COTs AKD1000 chip, IP and product pipeline and ongoing planned AKD2000, AKD500, AKD1500, AKD3000, AKD4000, AKD5000.
“The Proliferation of TinyML
TinyML is already showing massive potential and will be on the path to becoming the largest segment of the edge Machine Learning (ML) market by shipment volume. ABI Research forecasts total shipments of 1.2 billion devices with TinyML chipsets in 2022. This means more devices will be shipped with TinyML chipsets, as compared to those with edge ML chipsets. In addition, the proliferation of ultra-low-power ML applications means more brownfield devices will also be equipped with ML models for on-device anomaly detection, condition monitoring, and predictive maintenance.
The Commercialization of the Neuromorphic Chipset
With the recent release of Intel’s Loihi 2 neuromorphic chip, research in neuromorphic and Spiking Neural Networks (SNNs) will increasingly involve the industry and provide a hint about the sort of commercial Artificial Intelligence (AI) applications in which these networks can integrated. Other neuromorphic chipset vendors to take note of are BrainChip and GrAI Matter Labs. Neuromorphic chips can implement the currently popular Deep Neural Networks (DNNs) as well. However, the use of SNNs will provide the most significant benefits in the long term, with superior performance in latency response and energy efficiency.”
My opinion only DYOR
FF
AKIDA BALLISTA
www.graimatterlabs.ai
