BrainChip + Tata Consultancy Services

[Fact Finder]

It was almost 4 years ago we announced this joint demonstration with Tata, which in turn would mean BrainChip was working with TCS sometime before this announcement.

In other words, Tata & BrainChip have been working together for at least 5 years.

I suspect now that a commercial arrangement has been announced (ie. " partnership " ), commercial products will materialise relatively quickly, as the groundwork has already been done.

Hi Quiltman

We appear to agree with you that this relationship between Brainchip and Tata Group of companies could be at least of five years standing probably much longer.

Considering the length of time most research work takes and the fact that Douglas Fairbairn stated that it took Megachips about 18 months to get their engineers up to speed with AKIDA technology before they announced the agreement with Brainchip it is entirely possible that for Tata Consulting Services engineers to lead the demonstration of AKIDA technology doing a live demonstration of gesture recognition to control a robots movements on 14 December, 2019 it may well be that the relationship commenced way back in 2018.

If so this then allows for the feedback from early access customers that Peter van der Made referenced which caused them to go back to the drawing board on AKD1000 and delay its taping out by 12 months to have come in part from Tata Consulting Services.

Now assuming this to be correct about how long standing this relationship has been then I will share with you what I consider the missing piece of the medical applications puzzle:

“Tata Elxsi opens a dedicated Global Engineering Center for Aesculap as part of the strategic multi-year engagement​

Bangalore, Oct 28, 2020– Tata Elxsi, a global design and technology services company, announces the opening of a Global Engineering Center (GEC) with Aesculap AG, a subsidiary of B. Braun, one of the world´s leading manufacturers of medical devices and pharmaceutical products and services. Tata Elxsi has been selected as the global engineering services partner by Aesculap. The GEC is part of a strategic multi-year engagement in the field of engineering services.

The GEC serves as a platform of talent and expertise for product design & engineering, regulatory support and clinical evaluation services. This center will be essential to accelerate innovation, drive the transformation and growth for Aesculap‘s medical business.

Martin Schaeuble, Vice President Abdominal and Cardio-Thoracic Surgery, Aesculap commented on this announcement” Tata Elxsi has proven to be the right partner, bringing the right mix of technical expertise and program management skills. Together with Tata Elxsi we are in the position to continue our innovation activities as well as adherence across Aesculap ‘s product portfolio."

"We are elated to be selected as a strategic partner of Aesculap. It is an absolute honor for us to be part of this journey in supporting Aesculap through our Global Engineering Center, bringing together integrated competencies in R&D and innovation, digital technologies, deep domain understanding of medical devices and ever-evolving regulatory standards. This further consolidates our position in the Medical Devices and Healthcare market in Europe, and strengthens our relationship with Aesculap and the B. Braun group," said Nitin Pai, Chief Strategy Officer and CMO, Tata Elxsi.

About Aesculap​

With over 64,000 employees in 64 countries, B. Braun is one of the world’s leading manufacturers of medical devices and pharmaceutical products and services. Through constructive dialog, B. Braun develops high quality product systems and services that are both evolving and progressive – and in turn improves people’s health around the world.

With 3,600 employees at the headquarters in Tuttlingen and 12,600 worldwide AESCULAP® belongs to the B. Braun Group. Since 1976, Aesculap is thus part of a family-run company. Aesculap is a reliable partner for all treatment concepts in surgery, orthopedics and interventional vascular medicine. With products like the Digital Surgical Microscope Platform Aesculap Aeos® the company strives for innovations, which result in medical advances“

As you know and have documented in many of the above posts Tata Consulting Services has been driving research into the use of wearable devices for monitoring health conditions particularly cardiac conditions and exploring every aspect of SNN technology with Arijit Mukherjee even confirming on LinkedIn the ongoing close relationship with Brainchip it makes sense at least to me, to believe that the early positive findings by Tata Consulting Services translated into interest and research by Tata Elxsi and Aesculap/Braun Group at their jointly developed Global Engineering Centre for the purpose of advancing the design of medical devices and pharmaceutical products and services.

This being the case some may well be taken by surprise as to the speed with which this Brainchip and Tata Elxsi partnership commences to bear fruit.

As they say time will tell but with the release of AKIDA 2.0, confirmation that AKD1000 is the stuff of science fiction and capable of supporting space missions and AKD1500 achieving perfect production first time through Global Foundries it seems reasonable to believe
AKIDA technology will be found fit for purpose, remembering that almost on the day of the announcement a senior sales executive at Tata Elxsi was calling out the over priced nature of Nvidia Jetson in comparison to AKIDA technology.

Now I admit he could have been talking through his hat but at his level of seniority the odds of him coming out with these comments without some deeper understanding of AKIDA technology born out of the posited long term relationship as opposed to a sales briefing on the day of the release seem fairly high particularly given the type of customers/clients he would be dealing with on behalf of Tata Elxsi noting they do not service the retail market and his target audience are not the type to line up in the street over night to buy the next big thing as a result of a
bit of marketing spin on LinkedIn.

My opinion only so DYOR
FF.

 

[Fact Finder]

Arijit Mukherjee’s Post​

Arijit Mukherjee
Principal Scientist, Embedded Devices & Intelligent Systems at TCS Research
4d

Vision-based AI is generally costly. But how can we utilise AI in Industrial and Infrastructural Inspection in a resource efficient manner? How does it benefit the industry? Hrishikesh Sharma, from Tata Consultancy Services - Research, will be talking practical applications of AI in such scenarios at the 1st International Workshop on Sustainable AI for Edge (SAI4E) as part of AI-ML Systems Conference 2023. Join us for this exciting talk at Bangalore... #SAI4E #AIMLSys2023 #TCSResearch #InventingForImpact #EdgeComputing #NeuromorphicComputing #SustainableAI Arpan Pal Jayavardhana Gubbi Prasant Misra, Ph.D. Sounak Dey Swarnava Dey Manan Suri

 

[Quiltman]

A couple of posts & "celebrates" on LinkedIn from Chetan, another member of the TCS Neuromorphic Research Group.
Supporting & working with Brainchip.

 

[Fact Finder]

The significance of Brainchip's engagement with TATA Group and its presence in India is clearly undervalued by Australian investors. It really is quite sad that the work done by Brainchip commencing from at least 2018 (most likely earlier) to foster and grow this relationship has not been properly recognised:

Ratan Tata receives the Order of Australia, country's highest civil honour​

SECTIONS
Ratan Tata receives the Order o ..

Read more at:
https://economictimes.indiatimes.co...ofinterest&utm_medium=text&utm_campaign=cppst

TATA Group employs over 17,000 Australians and is working in the high tech industry where Brainchip is set to dominate yet ignorance prevails in the financial press.

My opinion only DYOR
FF

 

[Quiltman]

This post was made by Arijit from TCS Research 5 months ago, seeking PhD and Masters candidates.
I'm unsure if it was posted on this forum at the time.

Two months after this post by Arijit, TCS announced a formal commercial partnership with BrainChip via Tata Elxsi, with a focus on healthcare and industrial ( robotics ).

Just think about what is being said here .... with knowledge it is being done utlising BrainChip IP.

At TCS Research, we specialise in embedding intelligence at the edge through Neuromorphic Computing and Spiking Neural Networks.
Our systems targeted for evolving neuromorphic hardware offer extreme low-power consumption, online learning, and real-time inferencing, ideal for IoT, edge analytics, healthcare, robotics, space-tech & more.

explore new topics, advance ongoing projects

If we can't be bullish about this ... well .... then I am lost for words !

 

[Quiltman]

Not sure if anyone posted the European patent application. The US was posted previously.

EPO - European publication server​

European publication server - the source of information on published patent applications and granted patents.

data.epo.org

"
The active power consumption of a neuromorphic hardware is mainly contributed by the spiking network’s total
number of synaptic operations (SOP). Following (7) and the method mentioned in Sorbaro et al.
This converted SNN can be implemented on neuromorphic platforms such as Brainchip Akida (e.g., refer "Brainchip
unveils the akidatm development environment.," https://www.brainchipinc.com/news-media/pressreleases/de￾tail/61/brainchip-unveils-the-akida-developmentenvironment, 2019"), Intel® Loihi (e.g., refer "Mike Davies.et.al, "Ad￾vancing neuromorphic computing with loihi: A survey of results and outlook," Proceedings of the IEEE, vol. 109, no. 5,
pp. 911-934, 2021."), etc. to achieve further power benefit (~100x). FIG. 9 shows the confusion matrix for converted
SNN for 8 gesture classes.

 

[Quiltman]

And from Tata Elxsi Q4 FY24 report from a few days ago.

Yes, we know about Tata Elxsi, but nice to see it in their market submitted earnings reports / presentations too

The opinions and research I share are my own and I am not licensed. External links are not recommended. To be safe, conduct your own research or seek advice from a licensed financial advisor.

Stock Disclosure:

 

[SharesForBrekky]

Even though from about 3 months ago, interesting read about a promising future of incorporating neuromorphic computing into the BFSI sector (banking, financial services, and insurance):

Sukriti Jalali on LinkedIn: Neuromorphic Computing in BFSI: The tech of the future

It’s a delight to share my insights on ‘Neuromorphic computing: Ushering in AI innovation in BFSI’. Neuromorphic computing is showing promise as the future of…

www.linkedin.com

Neuromorphic Computing in BFSI: The tech of the future

Spiking neural networks, when run on NC hardware, can help overcome issues in the existing AI and ML deployments and conceptualize new products and services.

www.tcs.com

 

[Fact Finder]

​

Malliswar T’s Post​

Malliswar T
Chief Data Scientist; Researcher - LLMs, AI & ML
1d Edited

On-device LLMs: The Next Big Race is On Large language models (LLMs) are one of the most exciting developments in artificial intelligence in recent days. LLMs can generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. However, LLMs are typically very large and complex models, which means that they can be computationally expensive to run. This has limited the widespread adoption of LLMs The open-source movement focused on small models capable of running on client devices is one of the industry's most discussed topics. Despite the impracticality of running GPT-4 or the full PaLM on laptops and smartphones, a thriving ecosystem exists for on-device inference model development On-device LLMs are a new generation of LLMs that are designed to run on devices such as smartphones, laptops, and IoT devices. On-device LLMs offer a number of advantages over traditional cloud-based LLMs. Here are some examples of how on-device LLMs could be used in the future: -A voice assistant that can understand and respond to complex questions, even in noisy environments. - A translation app that can translate text in real time, even without an internet connection. - A keyboard that can predict what you're going to type next, making it faster and easier to type messages and emails. - A personalized educational app that can adapt to your individual learning style and pace. - A virtual assistant that can help you with your daily tasks, such as scheduling appointments, booking travel, and managing your finances. The race for on-device Large Language Models (LLMs) is the next frontier in AI, and major tech giants like Google, Microsoft, Qualcomm, Apple, Meta and NVIDIA are making significant investments in both hardware and software research and development. -Google's Tensor G3 chip enables on-device generative AI, potentially featured in Pixel 8 Pro. -Apple's Ajax GPT with 200 billion parameters integrates into Apple products. -Qualcomm's Snapdragon Oryon with a dedicated AI engine revolutionizes mobile devices -Microsoft offers Orca, a 125-billion parameter model for mobile and edge devices, soon to be open-source -NVIDIA leads with Hopper GPUs for on-device LLMs; TensorRT-LLM software boosts efficiency. -Nautobot specializes in on-device LLMs for robotics, integrating with existing applications. -BrainChip optimizes on-device LLMs for Akida Neural Processor, focuses on neuromorphic computing. On-device LLMs represent a significant leap in AI and technology. They offer greater privacy, speed, and a host of real-world applications. The future is bright as these models make devices more powerful, versatile, and accessible

#OnDeviceLLMs,

#TechTrends,

#AIResearch


To the above add the following from Quora:

Tata Consultancy Services (TCS) has a strong relationship with the Indian Institutes of Technology (IIT) in India. The relationship between TCS and IIT dates back to the 1970s when TCS was established as the in-house software development division of Tata Sons, a large Indian conglomerate.
TCS has been a major recruiter of students from IITs, which are among the most prestigious engineering institutions in India. TCS recruits a large number of graduates from IITs every year and has a strong presence in their campus placement programs. In fact, TCS is one of the largest recruiters of IIT graduates, with a significant percentage of its workforce comprising IIT alumni.
Apart from recruitment, TCS also collaborates with IITs on research projects, sponsorships, and other initiatives. TCS has established research labs in collaboration with several IITs, including IIT Delhi, IIT Bombay, and IIT Madras. These labs work on cutting-edge technologies such as artificial intelligence, machine learning, and blockchain.
In summary, the relationship between TCS and IIT is a symbiotic one, with TCS benefiting from the high-quality engineering talent produced by IITs, and IITs benefiting from the exposure to industry and research opportunities provided by TCS.

Then read this link:

https://www.tataelxsi.com/news-and-...logy-guwahati-iit-g-to-foster-ev-technologies

TATA ELXSI & BRAINCHIP PARTNERSHIP IS BIGGER THAN THE US CENTRIC ASX MARKET UNDERSTANDS.

My opinion only DYOR
FF

 

[Fact Finder]

“SNN is one of the most powerful neural networks that can process temporal data in real-time” - TCS 2023

https://www.tcs.com/insights/topics/ai-ml-topic/article/spiking-neural-networks

 

[Fact Finder]

“SNN is one of the most powerful neural networks that can process temporal data in real-time” - TCS 2023

https://www.tcs.com/insights/topics/ai-ml-topic/article/spiking-neural-networks

Hi All
After much trial and error here is the main text of the document minus photos and links for those who do not like to open strange links. Those who follow Tata Consulting Services know that they appear to mainly play with AKIDA and Loihi. You will also probably know that Loihi does not do feedforward or on chip convolution and strangely AKIDA uses three layers. AKD1000 has 'near memory' but it is often described as 'in memory' compute. We also know that Loihi is not a commercially available chip nor does it come as IP and of course we know that TCS has faced off AKD1000 with Nvidia Jetson TX and AKIDA's performance blew TX away:

Spiking neural networks

www.tcs.com

"HIGHLIGHTS

• Evolving neuromorphic processors, which are designed to replicate the human brain, is critical for enabling intelligence at the edge and processing sparse events.
• With neuromorphic computing, low latency real-time operations can be performed with significant reduction in energy costs.
• Advances in neuromorphic computing promise to ease the energy concerns associated with Dennard Scaling, Moore’s Law, and von Neumann bottleneck.

WHAT IS AN SNN

Spiking Neural Network: The building block for innovation

The Spiking Neural Network (SNN) is the third generation of neural network models, built with specialized network topologies that redefine the entire computational process. The spiking makes it more intelligent and energy-efficient, which is crucial for small devices to perform.

With a three-layered feedforward specialized network topology, the SNN is one of the most powerful neural networks that can process temporal data in real-time. This high computational power and advanced topology make it suitable for robotics and computer vision applications that require real-time data processing.

SNN facilitates real-time sourcing and processing of the data and is a major improvement over other neural networks, which primarily rely on frequency rather than temporal data.

SNN is one of the most powerful neural networks that can process temporal data in real-time.

The SNN spikes are computationally more advanced, and the firing activity of the neuron in the SNN architecture is not tied to static inputs but to the notion of time.

CORE SNN ARCHITECTURE

How SNN's are all set to shape the future

The SNN is made of billions of very well-connected neurons through a three-layer mechanism. These three—input, hidden, and output layers—work in tandem to mimic the function of the human brain. In other words, there is no separation of data perception and processing.

Instead, the entire process happens at once because the input layer’s vectors are connected to that of the hidden, which is in turn connected to the output layer. This interconnectivity ensures the continuous transmission of signals between the neurons. Among these layers, the hidden layers (there can be multiple) are the most significant ones, as this is where the convolution process takes place.

Together, the convolutional capabilities and highly connected layers take image and video processing to the next level, particularly in medical image analysis and natural language processing. These critical applications require advanced classification and processing, often in real-time.



USE CASES FOR SNN

SNN's specialized network topology unleashes numerous possibilities in the world of robotics and computer vision

The SNN has created a lot of excitement in the AI community because of its specialized network topology that unleashes numerous possibilities in the world of robotics and computer vision. The biggest advantage is SNN’s in-memory computing using neuromorphic hardware.

The human brain’s efficiency comes from its ability to store and process information from the same organ. In the case of machines, the Von Neumann bottleneck creates inefficiency and latency because the memory and processing units are separate.

So, every time data is received, it is stored in the memory and then accessed by the processing unit, which creates a delay. The SNN eliminates this two-step process through in-memory computing. Since there is no passage of information from the memory to the processing unit, the latency is

reduced. Also, the energy consumption is much lower when neuromorphic hardware is used.



ABOUT THE HARDWARE

SNN to lower energy consumption

The SNN’s function closely emulates the human brain and therefore encodes temporal data, by which it introduces the concept of time along with other elements. This ensures lower energy consumption, particularly when neuromorphic hardware is used.

The neuromorphic hardware enables better performance because it simulates neurons, which is essential to stimulate differential equations to leverage the discreet and sparse behavior of the neurons. As regular hardware is not designed to handle this behavior, it can be less inefficient. Spiking Neural Networks and their classification capabilities have been tested. According to a study, the trained neurons can run the classification even when the stimuli and corresponding decision times are segregated while there is simultaneous neural activity. This has been tested on the Statlog Landsat and Iris datasets in various experiments.



Advancing edge computing capabilities with neuromorphic platforms

With neuromorphic computing, low latency real-time operations can be performed with significant reduction in energy costs.



CONCLUSION

SNN spells a breakthrough for the robotics sector

The SNN undoubtedly spells a breakthrough for the robotics sector because, unlike AI chips, the SNNs emulate the original language of human intelligence to interpret real-world data. This is precisely what robotics needs to perform tasks that are normally executed by human beings. Until now, they could only perform redundant tasks, but with SNN, that is bound to change.

Nevertheless, it cannot be denied that SNN only lays the foundation and is not perfectly aligned with human brain functions. That’s because the neurons in the various layers of the human brain adjust and auto-readjust themselves based on the situation. Although the SNN’s layering gives neurons a certain degree of individuality, it is far from becoming human-like."

My opinion only so DYOR
Fact Finder

 

[fukthechinesedrc]

Hi everyone how can I change the fact to be a observer?