BRN Discussion Ongoing

[buena suerte :-)]

Certainly going in the right direction ...(Data 1 week old!!)

 

[Tothemoon24]

This Indian Company Controls 1/3rd Of The World’s Internet​

-
November 26, 2023

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Ever wondered about the intricate web that brings the internet to your fingertips? Imagine a vast digital network, akin to a colossal spider web, connecting computers and networks globally, enabling seamless data flow across continents. Yet, buried beneath the ocean’s surface, there lies a crucial infrastructure—a network of cables spanning 1.2 million kilometers, binding nations together. But who holds the reins to this expansive digital domain? Enter the Tata Group, specifically its subsidiary, Tata Communications, orchestrating nearly 30% of the world’s internet traffic.

The Backbone of Connectivity​

This global digital infrastructure isn’t just a web of cables—it’s the lifeline of connectivity that spans six continents. With over 130,000 miles of undersea fiber optic cables and 400 global Points of Presence (PoPs), Tata Communications facilitates internet connections to a staggering 240 countries and territories. This intricate network is the unseen foundation supporting your virtual interactions—be it streaming, emailing, or video calling across the globe.

---

Also Read: ResearchED: Why Odisha Can Become The Sports Capital Of India​

---

The Tata Group’s dominance extends beyond internet connectivity. Managing a colossal 53 billion minutes of international voice traffic annually—equivalent to one in ten worldwide voice calls—their voice network becomes the conduit for over 100,000 ongoing international calls. This vast control over communication channels signifies Tata’s pivotal role in enabling global connectivity.

The Magnitude Of Data Control​

Beyond voice traffic, Tata Communications wields authority over an astonishing 7,600 petabytes of internet data each month. This staggering volume underscores their pivotal role in the digital ecosystem.
Yet, such unparalleled control comes with immense responsibility. A technical glitch within Tata’s network infrastructure could potentially disrupt internet and voice services across various parts of the world, highlighting the intricate dependency on their seamless operations.

Grasping The Marvel Behind The Scenes​

The next time you engage in routine online activities—sending emails, streaming movies, or connecting via video calls across continents—take a moment to acknowledge the behind-the-scenes marvel that is Tata Communications. Their unassuming yet integral role in global connectivity serves as a reminder of the intricate infrastructure supporting our daily digital interactions.
The internet’s vastness often conceals the intricate mechanisms and entities ensuring its seamless operation. Tata Communications, with its unparalleled global network and control, stands as a behemoth in enabling worldwide connectivity. So, the next time you engage in a digital interaction transcending borders, pause for a moment to appreciate the invisible yet indispensable role played by entities like Tata, shaping our connected world.

 

[Fullmoonfever]

Could be an interesting diary reminder to check in around Q3 2024 to see what the various authors thoughts are when the papers are published.

I'll take the call as a pretty much acceptance of neuromorphic going mainstream

IEEE Transactions on Consumer Electronics
Call for Papers
Special Section on “Neuromorphic Computing Technologies for Consumer Electronics”
Theme:

Recently, consumer electronics have moved toward data-centric applications due to the development of artificial intelligence (AI) technologies. With the growing demand for large memory capacity, fast processing speed, and complex data computation in consumer electronics, neuromorphic computing has been emerged as the next-generation technology to promote the revolution and development of consumer electronics.

Neuromorphic computing technologies offer tremendous potential for computing beyond Moore’s law, which have been
involved in all aspects of consumer electronics applications. Specifically, neuromorphic computing technologies with extreme energy efficiency will be indispensable for smart device applications such as intelligent monitoring system, unmanned aerial vehicle, service robotic, etc. In addition, neuromorphic computing technologies inspired by human brain can handle the avalanche of unstructured data, which are well poised to become the AI accelerators in personal computing devices such as smart phones, laptops, and desktops.

Furthermore, neuromorphic computing technologies promise a massively parallel, efficient, and scalable computational solution with large implications such as smart manufacturing, smart grids, smart home, and smart city on the daily lives of consumers.

To promote the development of neuromorphic computing and related fields in consumer electronics, this special section will provide a platform for researchers to exchange the latest research and practitioner findings. The special section will focus on the hot topics of neuromorphic computing, the latest progress of emerging devices and hardware implementations for consumer electronics, brain-inspired computing structures and learning methods in consumer electronics, the interdisciplinary applications of neuromorphic computing in consumer electronics, etc. This special
section aims to achieve the deep integration of advanced materials science, computer science, and electronic science and technology, which is expected to accelerate the development of neuromorphic computing systems and the adoption for consumer electronics applications.

Topics of interest in this Special Section include (but are not limited to):
 Evolving consumer materials, attributes, and functionality in neuromorphic computing systems
 Emerging neuromorphic computing devices, circuits, and algorithms for consumer electronics applications
 Integration of sensing, storage, and processing in consumer electronics
 Consumer behavior analysis with neuromorphic computing systems
 Brain-inspired neuromorphic computing architecture in consumer electronics
 Hardware and software interaction and codesign in consumer electronics
 Emerging neuromorphic computing applications and their cases studies in consumer electronics
Important dates:
 End of submission of Manuscripts: September 30, 2023
 Expected publication date (tentative): Third Quarter, 2024
Guest Editors:
 Dr Zhekang Dong (Lead Guest Editor), Hangzhou Dianzi University, Hangzhou, China, englishp@hdu.edu.cn
 Dr Ping Lu, University of Oxford, UK, ping.lu@eng.ox.ac.uk
 Dr Chun Sing Lai, Brunel University London, UK, chunsing.lai@brunel.ac.uk
 Dr Zhongrui Wang, The University of Hong Kong, Hong Kong, China, zrwang@eee.hku.hk

 

[DaBenjamins]

Exciting news from one of our partners

 

[7für7]

Aaaww that's nice of Rob

View attachment 50675

OMG can you imagine Samsung brings out a robo with akida inside? I’m sure it’s a hint

 

[Tothemoon24]

What are the key technologies and tools that content creators use to implement AI-driven personalization in their content?

There are several AI-driven technologies and tools to implement personalization in content. This could be machine learning frameworks like TensorFlow, PyTorch, and scikit-learn.

These are used to develop and deploy machine learning models for tasks such as natural language processing (NLP), recommendation systems, and image recognition. NLP libraries are also used by content creators who work with text data. These tools can aid with sentiment analysis, language translation, and content generation. More com-monly, AI-based recommendation engines offer algorithms to personalize content recommendations based on user behavior and preferences.

Tata Elxsi AI Innovations Driving New Trends in Personalisation​

Critical Role of AI Algorithms in Shaping the Landscape: From Tailoring Personalized Recommendations to Analyzing User Behavior​

Can you provide an overview of how AI innovations are currently being utilized to create interactive and personalized content experiences?
The ongoing trend in content delivery is centered on interaction and personalization, with AI technology taking the forefront as a pivotal player in the media and broadcasting sector. AI algorithms play a vital role in this landscape, extending from tailoring personalized recommendations to scrutinizing user behavior. Their application significantly augments the overall viewing experience while concurrently aiding businesses in making data-informed decisions.
Below are some of the ways in which AI is being used for personalized and interactive content –
Personalized recommendations: AI-driven recommendation systems are widely used in streaming services and OTTs. These analyze data gathered from user behavior, likes, and prefer ences to suggest content such as movies, music, and other content.
Content curation: AI tools are not just limited to personalized recommendations. Rather, they are being used to curate content by categorizing, tagging, sorting, and so on. This helps users discover content that aligns with their interests, especially in the vast sea of content available today.
Virtual assistants and chatbots: Recommendations aside, AI is a key player in interactive media. For one, AI tools are used for chatbots and virtual assistants that provide personalized interactions with users. They can answer questions, provide recommendations, and offer customer support, that enhances the overall user experience.
AI for advertising: Advertising and marketing have come a long way and we have personalized and curated ads today. Based on user data, demographics, and other factors, AI is being utilized to create advertisements and deliver them more effectively. In AdTech, we are working on automated ad insertion and Virtual Ad placement.
Generating content: Content recommendation and curation aside, AI tools are also deployed to create content as well. Be it articles, reports, art, or music, Generative AI tools are being actively deployed in the modern broadcasting industry. For the Media industry, we are using GenAI for content discovery and meta data enrichment.
AR/VR for personalization: The new trend is diving into AR and VR experiences, blurring the line between digital and reality. AI is playing a crucial role here, providing personalized virtual environments and interactions for users. This makes the immersive experience even more engaging and relevant to the viewer.
What are some specific examples or use cases where AI-driven technologies have successfully fostered deeper connections through personalized content experiences?
Today, we are at times of hyper-personalization and AI is at the forefront to be able to achieve this. With the increased amount of video content in the market, it has become challenging for users to search for the content that they want to watch. A recent survey indicates that 83% of viewers look for something new to watch a few times per month and 42% of viewers spend their time searching for the right content to view. Some examples of how AI-driven technologies have successfully fostered deeper connections through personalized content experiences are mentioned below –

1. Curated social media feeds – Social media platforms have also come a long way. The platforms are upgraded with AI tools that analyze behavior and interests to deliver content that is more likely to resonate with individual users.
2. E-commerce/shopping recommendations – Online shopping platforms have also been upped the ante when it comes to personalization. AI tools have been picking up data on previous buying behavior. E-commerce platforms are now delivering more personalized product recommendations, which has further increased the chances of buying and better sales for brands.
3. Music streaming platforms – Broadcasting streaming platforms now extend to music and podcast streaming apps. AI tools are being deployed to better understand the kind of music/podcasts that a user is interested in to provide similar playlists and shows.
4. Content streaming recommendations - Operators are continually enhancing traditional content discovery methods by integrating powerful recommendation engines, and interactive UI for the near term and adopting AI for long-term success.

Tata Elxsi’s Center of Excellence (CoE) has developed a platform designed to expedite deployments with a focus on achieving heightened levels of personalization and swifter content discovery. This AI-driven intelligent video analytics solution centers around image tagging as its core feature. Its primary objective is to provide insights that enhance the customer experience through immersive and targeted advertising, closed caption generation for individuals with hearing impairments, interactive gaming analytics, and content performance analysis, among other notable features aimed at improving the overall user experience. The presence of a platform utilizing AI technology to empower viewers in searching, discovering, and promptly accessing highly personalized content is poised to be a determining factor for the success of OTT (Over-The-Top) operators.
How does AI impact user engagement and interactivity in content creation?
User engagement is crucial for customer retention today, especially for the broadcasting industry and OTT platforms. It boils down to personalization and content curation to enhance user engagement. AI-driven user data analysis also plays a key role in understanding the latest trends and preferences. Understanding user engagement will in turn help in improving the quality and quantity of the content, which in turn impacts the overall user engagement.
What are the key technologies and tools that content creators use to implement AI-driven personalization in their content?
There are several AI-driven technologies and tools to implement personalization in content. This could be machine learning frameworks like TensorFlow, PyTorch, and scikit-learn.
These are used to develop and deploy machine learning models for tasks such as natural language processing (NLP), recommendation systems, and image recognition. NLP libraries are also used by content creators who work with text data. These tools can aid with sentiment analysis, language translation, and content generation. More com-monly, AI-based recommendation engines offer algorithms to personalize content recommendations based on user behavior and preferences.
In what ways can AI adapt content to suit the preferences and needs of individual users or target audiences?
This is where the core of the AI algorithm comes at its best. Every data point or features about the content, usage history is stratified in high dimensional space, which we call embedding space. This is a complex representation of information in human unreadable matrix format, which is used to search and collocate the information needed for an identified user or target audience. The trick is in the design of this embedding space, which places all similar items in a close neighbourhood. AI algorithms deployed for the task of adapting the content to the target audience is constantly optimizing the search space for better co-location and faster retrieval.
How does AI enable content creators to collect and analyze user data for more effective personalization?
AI is the key driver behind the feasibility of both personalization and hyper-personalization today. AI-powered tools and algorithms play a pivotal role in automating data processing, recognizing patterns, and extracting valuable insights. These insights are instrumental in delivering personalized content and recommendations within the realm of the broadcast and media industry.
AI for data collection – AI systems integrate data from various sources like websites, mobile apps, social media, and more to create a unified user profile. It’s also possible to capture user data in real-time, enabling content creators to respond quickly to user behavior and preferences. The massive volumes of data are further identified and cleaned by AI tools, which further help in personalization of the highest quality.
AI for data analysis – AI tools further assist in analyzing the data collected. For one, AI algorithms are applied for user profiling, behavioral tracking, and so on. Moreover, AI employs machine learning algorithms to build predictive models that can forecast user behavior and preferences. For instance, predicting which products a user is likely to purchase or which content they will engage with. AI-powered recommendation systems also analyze user data and generate personalized content suggestions based on behavior trends.
Ultimately, AI streamlines the collection and analysis of user data, making it more efficient and accurate. This enables content creators to implement highly effective personalization strategies, resulting in more engaging and relevant content for their target audiences.
What are the ethical considerations and challenges associated with AI-driven personalization in content, such as privacy concerns or potential biases?
The implementation of AI-driven personalization raises numerous ethical concerns and challenges that demand the attention of broadcasters and content creators. These encompass issues like privacy, data protection, user manipulation, user autonomy, and various related matters.
Spokesperson: Biswajit Biswas - Chief Data Scientist, Tata Elxsi

 

[IloveLamp]

OMG can you imagine Samsung brings out a robo with akida inside? I’m sure it’s a hint

 

[IloveLamp]

https://www.mediatek.com/products/smartphones-2/mediatek-dimensity-9300

Looks like an impressive chip, not neuromorphic though..

They won't advertise neuromorphic necessarily. But mediatek are partnered largely with ARM, so i would not be surprised if our ip ended up in a MEDIATEK chip in the 9300 or later.

Pure guess work based on my own research. We are a big threat to companies like MediaTek. Imo a lot of these companies will have no choice but to jump on the akida train or get left behind.

I'm sure a few big companies will disappear into the history books in the next few years if they can't keep pace.

Interesting times

Imo dyor

 

[Tothemoon24]

Welcome to the Chip Wars, Microsoft​

By Forrester analysts on November 27, 2023

It was inevitable and expected, but we now have a new power player in the ever-expanding semiconductor landscape: Microsoft. Recently, it announced its Cobalt 100 CPU and Maia AI accelerator at its Ignite conference. In simpler times, we had Intel and AMD playing leapfrog with their competing x86 CPUs. It wasn't a very exciting time. All that changed — almost stealthily, until the silence grew into a cacophony of chipmakers, architecture variants, and geopolitical tensions over the past few years. It's boring no more.
Recent developments saw other tech giants deciding that they could design their own chips. The tectonic event was the 2020 introduction of Apple’s M1 processor. Apple proved that it could replace Intel CPUs with its own, a move that demonstrated superior performance per watt. The floodgates were now open.
Cloud giants such as Google and AWS followed, designing their own processors. Meanwhile, NVIDIA took the world by storm with expanded demand for its GPUs to perform machine learning and other AI tasks. A little-known U.K. firm called Arm emerged as a powerhouse because its ARM architecture lent itself well to the new generation of CPUs, including Apple's M-series. Previously the choice for smartphones and other low-power devices, ARM (the architecture from "Arm," the company) became a viable contender for high-end CPUs in data centers and PCs. It was only a matter of time before Microsoft jumped in … and now it has.

RELATED​

• Sentient LLMs: Must Generative AI Attain Human Consciousness?​

• Google Turns To AI to Design Its Next AI Chips​

Microsoft's move erodes lucrative business for Intel, AMD, and NVIDIA, all of whom are key suppliers to Azure. All three will remain part of Azure's menu of customer options, but the main growth for Azure will come on its own chips. This is especially impactful for NVIDIA since Microsoft focuses so much of its Azure services on generative AI, which currently depends on huge quantities of NVIDIA GPUs.
Democratized Processor Design Presents Broad Choice
The new Cobalt 100 instances will offer superior price performance for some workloads. Maia will make Microsoft's Copilot services more powerful (maybe cheaper, but that's TBD). We advise enterprise application developers and cloud decision-makers to evaluate these new offerings for new applications or migrating existing applications. After years of force-fitting workloads into one or two instance types, cloud providers can now tailor instances to workload type and/or cost efficiency when that's a higher priority than sheer power.
Custom processors are inevitable. As great as Intel's and AMD's x86 processors continue to be, they are general-purpose devices—a jack of all trades and master of a few. Although superior for AI needs, even GPUs like NVIDIA's are also general-purpose chips. Don't even think of kissing x86 goodbye. It is here to stay for a long time, and it keeps getting better as AMD and Intel add new capabilities and significantly improve power efficiency. We expect ARM to gain even more momentum, though. Although ARM is also fundamentally general-purpose, the building blocks that Arm provides allow its partners great flexibility in customizing their designs.
Arm is making it easier to build chips on the ARM architecture. Qualcomm, NVIDIA, Samsung, and plenty of other chipmakers already provide ARM-based processors, and they’re starting to work their way into hardware for corporate data centers, end users, and consumers. NVIDIA’s much-hyped Grace Hopper processor teams an ARM-based CPU with its GPU into a formidable choice for AI applications. Dell now offers a Windows PC based on Qualcomm’s Snapdragon CPU. We expect it to be popular, as its power consumption (and resulting heat dissipation) and pricing make it an attractive alternative to Chromebooks.
Democratized Silicon Brings Power To The People
All of this means that tech buyers have more choices even beyond the cloud. In fact, today's options come from the tech giants, but the trend will extend to enterprises that don't currently identify as tech companies. Chip design will get easier as chipmakers and software companies evolve design automation in a manner similar to low-code application development. Low-code empowers a far richer community for creating digital business value. Our friend Diego Lo Giudice introduced TuringBots, extending this concept whereby generative AI can assist in code development. The ideas and much of the same technology will allow you to software-define custom processors even if you don't have a Ph.D. in electrical engineering.
“Power to the people” is taking on a profound new meaning in tech. John Lennon would be proud. Microsoft’s silicon announcements represent one more step forward in that democratization pursuit. Embrace the power and enjoy the ride!
Caution: Weigh The Advantages And Risks
Today’s hyperscalers are no longer just cloud providers—they are tech juggernauts. You see clear signs of vertical integration from chips to software to artificial intelligence. While it makes technology choices easier for many, it rings alarm bells for many others, whether that is lock-in, being too big to fail, or concentration risk. Weigh your risks and advantages before you enthusiastically embrace one hyperscaler and put all your eggs in one basket.

 

[IloveLamp]

How Hitachi Rail is Using Metaverse and AI to Transform the Railway Industry | Hitachi Rail

www.hitachirail.com

 

[Diogenese]

Does anyone know anything about Dimensity 9300 chip?? From Bloomberg - “Dimensity 9300 is the most powerful mobile system-on-chip" 2nd half of the story

AI Chip Boom Fuels Taiwan Firm’s 40% Rally, Beating Qualcomm and Peers​

• Company’s Dimensity 9300 chip is viewed as a game changer
• Valuation relative to growth prospect is attractive, GAM says

By Charlotte Yang
27 November 2023 at 11:40 am AEST


A five-month rally in MediaTek Inc. looks set to extend as booming demand for smartphones and a promising new AI chip brighten the outlook.
The Taiwanese tech firm’s stock has soared almost 40% since end-June, outperforming a 2% advance in the Philadelphia Stock Exchange Semiconductor Index and a 7% rise in its US-based rival Qualcomm Inc. The gains have been fueled by robust appetite for mobile devices that utilize the company’s chips, especially in China.
The buzz surrounding MediaTek casts the spotlight on the growing competition between semiconductor firms that are exploiting the use of AI to grab a larger share of the smartphone business. Investors see the Taiwanese firm’s Dimensity 9300 chip as a game-changer that will help it to steal a march over Qualcomm, the current leader in the high-end mobile market.

The bullishness surrounding MediaTek’s shares is growing. Analysts have boosted estimates for the company’s earnings per share by 13% since the end of July while short interest on the stock has fallen from a June peak. They have also lifted its estimated price target by 27% since a July low.
MediaTek’s “valuation relative to its growth prospect into next year still looks attractive,” said Robert Mumford, an investment manager at GAM Hong Kong Ltd. “The handset cyclical recovery and MediaTek’s new system-on-chip — a cutting edge product released at the right time — plus potential AI product rollout, are all tailwinds.”

A lot of the optimism is centered around the Dimensity 9300 chip, which is a direct competitor of Qualcomm’s Snapdragon 8 Gen 3. Both firms are racing to unleash AI technology on devices, part of the so-called “edge AI” phenomenon that multiple Wall Street banks say will be a key investing theme heading into 2024.
“Dimensity 9300 is the most powerful mobile system-on-chip and has started to gain traction with Vivo’s new phone,” Morgan Stanley analysts including Charlie Chan and Daisy Dai wrote in a note. The bank expects MediaTek’s market share in the flagship smartphone segment to increase from 20% in 2023 to 30%-35% in 2024, or up from 13 million units to around 20 million.

The Dimensity 9300 chip is designed to address more complex workloads of new generative AI and gaming applications and its launch follows several earlier designs which failed to excite investors. Chinese smartphone Vivo X100, which was released this month, is the first model to use the chip, and this will be followed by the OPPO Find X7 series.
The stock is trading at about 17 times forward estimated earnings, roughly in line with its five-year average. With a market capitalization of over $47 billion, MediaTek ranks as the the island’s second-largest listed company, after only Taiwan Semiconductor Manufacturing Co Ltd.

Smartphone Boom​

The company’s sales are expected to grow 14% this quarter from last year, snapping four straight quarters of year-on-year decline, according to data compiled by Bloomberg.
MediaTek said in its earnings call that its inventory has fallen for five straight quarters and the days of inventory reached a healthy level of 90 at the end of the third quarter. Mobile phone sales, which contributed about half of the firm’s revenue in the three months through September, gained 19% on quarter, thanks to restocking demand and new 4G and 5G launches, management said.
The rally in MediaTek’s shares also reflects the recovery in China’s smartphone industry, which registered double-digit growth in October. Phone sales in the world’s biggest mobile market were up 11% in the first four weeks of last month compared to the same period a year ago, according to Counterpoint Research data.

MediaTek, you don't know nutthin':


US2021334586A1 EDGE LEARNING DISPLAY DEVICE AND METHOD

An image processing circuit stores a training database and models in memory. The image processing circuit includes an attribute identification engine to identify an attribute from an input image according to a model stored in the memory. By enhancing the input image based on the identified attribute, a picture quality (PQ) engine in the image processing circuit generates an output image for display. The image processing circuit further includes a data collection module to generate a labeled image based on the input image labeled with the identified attribute, and to add the labeled image to the training database. A training engine in the image processing circuit then re-trains the model using the training database.

mediaTek uses MACs, not SNNs:

[0038] The CNN accelerator 612 includes hardware components specialized for accelerating neural network operations by convolutional operations, fully-connected operations, activation, pooling, normalization, element-wise mathematical computations, etc. In some embodiments, the CNN accelerator 612 includes multiple compute units and memory (e.g., Static Random Access Memory (SRAM)), where each compute unit further includes multipliers and adder circuits, among others, for performing mathematical operations such as multiply-and-accumulate (MAC) operations to accelerate the convolution, activation, pooling, normalization, and other neural network operations. The CNN accelerator 612 may perform fixed and floating-point neural network operations. In connection with the picture quality enhancement described herein, the CNN accelerator 612 may perform training and inference operations described in connection with FIG. 1.

Well they can do training:

An image processing circuit stores a training database and models in memory. The image processing circuit includes an attribute identification engine to identify an attribute from an input image according to a model stored in the memory. By enhancing the input image based on the identified attribute, a picture quality (PQ) engine in the image processing circuit generates an output image for display. The image processing circuit further includes a data collection module to generate a labeled image based on the input image labeled with the identified attribute, and to add the labeled image to the training database. A training engine in the image processing circuit then re-trains the model using the training database.

... but it will cut your milage in half.

 

[CrabmansFriend]

Although way over my paygrade,
it seems like there is some serious effort made in improving devlopment for neuromorphic systems cross hardware platform/software (easier to port between and compare). Allthough Brainchip is mentioned in the PDF (linked below), they are currently not part of the 7 listed hardware platforms.

Neuromorphic Intermediate Representation: A Unified Instruction Set for Interoperable Brain-Inspired Computing

In a joint effort between academia and industry, we present the Neuromorphic Intermediate Repre-
sentation (NIR): an abstraction layer that bridges neuromorphic software and hardware platforms

sources:

https://arxiv.org/pdf/2311.14641.pdf

GitHub - neuromorphs/NIR: Neuromorphic Intermediate Representation reference implementation

Neuromorphic Intermediate Representation reference implementation - neuromorphs/NIR

github.com

 

[Fullmoonfever]

Get the feeling MB still working out their blends of tech innovations to meet overall processing requirements, cloud connections as necessary, latency and retaining the data cybersecurity.

Given the ChatGPT use in the Hey Merc function is driven by LLM, I suspect the need for us to bed down the LLM processing ability too for ease of integration.

Re-engineering tomorrow's hyperconnected autonomous world

Re-engineering tomorrow's hyperconnected autonomous world Author: Rajaganapathy Rajendran, Vice President - Cloud and Connected Services, MBRDI Let’s begin with what a future exchange with Mercedes’ voice assistant ‘Hey Mercedes’ would look like. You: Hey Mercedes! Hey Mercedes: Hello...

community.nasscom.in

RE-ENGINEERING TOMORROW'S HYPERCONNECTED AUTONOMOUS WORLD​

Mercedes-Benz Research and Development India​

@MBRDI
November 17, 2023

Re-engineering tomorrow's hyperconnected autonomous world
Author: Rajaganapathy Rajendran, Vice President - Cloud and Connected Services, MBRDI

Let’s begin with what a future exchange with Mercedes’ voice assistant ‘Hey Mercedes’ would look like.

You: Hey Mercedes!

Hey Mercedes: Hello! Good morning! You have an upcoming appointment at 9 AM and I have mapped the fastest route to your destination. You should arrive by 8:50 AM. Your favourite playlist is being brought up for you to enjoy the ride. Enjoy your ride!
….
Hey Mercedes: Due to traffic congestion, there is going to be a delay and as per the new estimate, your arrival time has been updated to 9:10 AM. Other participants in the meeting have been notified of your delay.
…
Hey Mercedes: Would you like me to connect you to your meeting via voice call?
Please be mindful of your driving.

This is a glimpse of what the hyperconnected future offers but before we understand the nuances, let’s take a short walk down memory lane.

Since the advent of the Internet of Things (IoT), the automotive industry has revolutionised and moulded vehicles to operate as more than just a means of transportation. We have taken it a step further by marrying IoT and Autonomous Vehicles to redefine mobility and luxury.

Advancing with ADAS
To decipher the mercurial trajectory of the automotive industry, we must go back to the start. When the concept of an Advanced Driver Assistance System (ADAS) first seeped into the industry in the 1970s, it was about diminishing road fatalities through systems that attempted to negate human error. What started with Anti-lock Braking Systems (ABS) has today evolved to using Radar and LiDAR to evaluate optimal deceleration, even without human intervention.

A changing paradigm
While the intention is to remain uncompromising with safety, enhancing the driving and passenger experience is what the future firmly points towards. IoT, cloud connectivity and data sharing are all growing trends, and increasing the capabilities of the connected car is a collective vision all manufacturers share.

The first step towards achieving this has been transitioning from Electronic Control Units (ECU) to High-Performance Computers (HPC). HPCs are crucial in order to handle the advanced architecture modern vehicles possess.

5G at the core
Trends are increasingly moving towards making vehicles more autonomous. The connected car and 5G will undeniably have a crucial play in this transformation.

But we aren’t quite there yet. For autonomous vehicles to boast better reliability, connectivity and safety, extensive data from numerous sensors must be processed. Thus, the need for 5G, considering 4G hasn’t been able to handle the load and efficiently process the data.

5G is further essential with cloud computing, simplifying processing times and latency. This paves the path for effortless vehicle-to-everything (V2X) communications. V2X remains a vital cog in car-to-car and car-to-infrastructure exchanges.

Implications of data collection
Extensive data exchange necessitates extensive security measures. The future of mobility is powered by data collection and its efficient and intelligent non-intrusive use.

The strive towards positive impact isn’t bereft of its share of risks. Opening a communication channel with cloud devices exposes the ever-prevalent risk of cyber breaches. The more we innovate towards advanced autonomous levels of driving, the greater the risks of hackers introducing harmful elements into the vehicle architecture and inducing catastrophic consequences.

Now more than ever before, there is a need to fortify our cybersecurity infrastructure. This is where circling back to the start of this piece will give us a better understanding. Mercedes-Benz’s recent integration of ChatGPT and Hey Mercedes reaffirmed the necessity of having a watertight system to safeguard the privacy of our customers while allowing them the benefits of a truly delightful in-cabin experience.

The industry remains focused on navigating towards a hyperconnected, and hyper-personalised space.

Essentially, safety, convenience and luxury must be at the core of this journey. Innovating responsibly and using technology sensibly is the way forward, as we enter a new dawn with a ‘third living space’.
Rajaganapathy Rajendran

 

[AARONASX]

 

[Esq.111]

Morning AARONASX ,

Not getting any joy from link provided for some reason.
May be at my end ?

Regards,
Esq.

 

[AARONASX]

Morning AARONASX ,

Not getting any joy from link provided for some reason.
May be at my end ?

Regards,
Esq.

I think it was on my end on the computer, tried again on mobile and fixed it, i thinkg

 

[buena suerte :-)]

Morning AARONASX ,

Not getting any joy from link provided for some reason.
May be at my end ?

Regards,
Esq.

 

[Frangipani]

Stumbled across this short video just now and honestly don’t know why I even bothered to watch it, as I actually suspected it to be another one of those boring AI-generated clips mushrooming everywhere these days… Much to my surprise, though, this slide came up right at the beginning:

… and even though the rest of the video doesn’t live up to the expectations this intro raises (delving into PVDM’s insights in less than three minutes sounded massively overpromising anyway ), as it covers very little except for some basic statements about the future of AI, the importance for companies to embrace it and a brief explanation of what neuromorphic processing is about (however, without once referring to Akida)…

… it is still free publicity for Brainchip! And many a mickle makes a muckle. Right, James?! It cuts both ways, you know…

The person behind this YouTube channel is a Japan-based Pakistani lady called Hinza Asif (https://nftstudio24.com/hinza-asif/) who had recently been nominated for a Women in Tech APAC Award. I’d imagine that at least some of her 3000 plus followers would now google “Peter van der Made” as well as “neuromorphic” to find out more about The Future of AI…

 

[Bravo]

Can someone please call Rob Telson ASAP to get him to speak to someone at Phillips Medical Systems?

I just stumbled upon this Power Point Preso which shows Phillips are working with IMEC on the denoising of medical XRAYs using SNN's (SENECA) and they're hoping to apply this same technology can be applied in WIDE RANGE OF CLINICAL APPLICATION AREAS.

I believe that SENECA is still only at research stage which could leave the door wide open for us to say hello to Phillips. It says in this research paper below, published 23 June 23 that " The SENECA platform and the tools used in this project are available for academic research upon request."

Then there's also this Linkedin response from 5 months ago where the researcher at IMEC says they can't compare SENECA with BrainChip which he differentiates as being "commercial neuromorphic architecture".

SENECA: building a fully digital neuromorphic processor, design trade-offs and challenges

Neuromorphic processors aim to emulate the biological principles of the brain to achieve high efficiency with low power consumption. However, the lack of flexibility in most neuromorphic architecture designs results in significant performance loss and ...

www.ncbi.nlm.nih.gov

https://tempo-ecsel.eu/wp-content/uploads/2022/03/TEMPO-poster-demo-image_denoising.pdf

 

[MDhere]

Got a couple hours up my sleeve today and boy brn movement is tight this morning.