Jio Platforms Teams with NVIDIA to Bring State-of-the-Art AI Cloud Infrastructure to India

Jio Platforms Limited today announced plans to build a state-of-the-art cloud-based AI compute infrastructure to accelerate India’s position as a growing force in artificial intelligence, in collaboration with NVIDIA.

The new AI cloud infrastructure will enable researchers, developers, startups, scientists, AI practitioners and others across India to access accelerated computing and high-speed, secure cloud networking to run workloads safely and with extreme energy efficiency.

The new infrastructure will greatly speed up a wide range of India’s key initiatives and AI projects, including AI chatbots, drug discovery, climate research and more.

As part of the collaboration, NVIDIA will provide Jio with end-to-end AI supercomputer technologies including CPU, GPU, networking, and AI operating systems and frameworks for building the most advanced AI models. Jio will manage and maintain the AI cloud infrastructure and oversee customer engagement and access.

Mukesh Ambani, Chairman & Managing Director, Reliance Industries Limited, said on the partnership, “As India advances from a country of data proliferation to creating technology infrastructure for widespread and accelerated growth, computing and technology super centres like the one we envisage with NVIDIA will provide the catalytic growth just like Jio did to our nation’s digital march. I am delighted with the partnership with NVIDIA and looking forward to a purposeful journey together.”

Akash Ambani, Chairman of Reliance Jio Infocomm Limited, said, “At Jio, we are committed to fuelling India’s technological renaissance by democratizing access to cutting-edge technologies. Our collaboration with NVIDIA is a significant step in this direction. Together, we will develop an advanced AI cloud infrastructure that is secure, sustainable, and are deeply relevant to India’s unique opportunities. This state-of-the-art platform will be a catalyst in accelerating AI-driven innovations across sectors, from healthcare and education to enterprise solutions. Our vision is to make AI accessible to researchers, start-ups, and enterprises across the nation, thereby accelerating India’s journey towards becoming an AI powerhouse.”

“We are delighted to partner with Reliance to build state-of-the-art AI supercomputers in India,” said Jensen Huang, founder and CEO of NVIDIA. “India has scale, data and talent. With the most advanced AI computing infrastructure, Reliance can build its own large language models that power generative AI applications made in India, for the people of India.”

The Top Large Language Models (LLMs) Revolutionizing Technology in 2023

Language is a powerful tool that enables us to communicate and understand the world around us. With advancements in technology, large language models (LLMs) have emerged as game-changers, revolutionizing various fields. In this article, we will delve into the top LLMs that are shaping the way we interact with technology.

  1. OpenAI’s GPT-3.5:

OpenAI’s GPT-3.5, one of the most remarkable LLMs, has captivated the tech world. It stands as a testament to the impressive strides made in natural language processing (NLP). GPT-3.5 boasts an astounding 175 billion parameters, making it capable of generating highly coherent and contextually relevant responses.

  1. Google’s Switch Transformer:

Google’s Switch Transformer is another groundbreaking LLM that has garnered significant attention. Designed to handle vast amounts of data efficiently, it stands out for its versatility and scalability. Switch Transformer excels in a wide range of tasks, including translation, image captioning, and even playing video games.

  1. Microsoft’s Turing NLG:

Microsoft’s Turing Natural Language Generation (NLG) model showcases the company’s dedication to pushing the boundaries of AI. With 17 billion parameters, Turing NLG offers impressive text generation capabilities. It demonstrates exceptional performance in various language tasks, such as summarization, translation, and sentiment analysis.

  1. Hugging Face’s Megatron:

Megatron, developed by Hugging Face, has made waves in the NLP community. This LLM shines when it comes to parallel training on multiple GPUs. Megatron’s architecture allows for efficient distribution of computation across these GPUs, resulting in faster training times and enhanced performance.

  1. Salesforce’s CTRL:

CTRL, developed by Salesforce, focuses on generating coherent and controlled language. This LLM enables users to prompt it with specific instructions, allowing for more targeted and precise responses. CTRL’s fine-tuning capabilities make it a valuable asset for content generation and human-like conversational experiences.

  1. EleutherAI’s GPT-Neo:

EleutherAI’s GPT-Neo is an open-source LLM that emphasizes accessibility and democratization of AI technology. It offers models with varying sizes, ranging from small to extra-large, accommodating diverse use cases and computational resources. GPT-Neo is built on the GPT-3 architecture, making it a versatile and resourceful tool.

  1. NVIDIA’s Megatron-Turing:

NVIDIA’s Megatron-Turing is a fusion of Hugging Face’s Megatron and Microsoft’s Turing NLG. This collaboration brings together the strengths of both models, offering enhanced performance and capabilities. Megatron-Turing excels in various NLP tasks, including language generation, summarization, and understanding.

  1. Google’s T5:

Google’s Text-To-Text Transfer Transformer (T5) is a highly flexible and versatile LLM. With 11 billion parameters, T5 is capable of performing a wide range of language-related tasks, such as translation, summarization, question answering, and more. Its adaptability makes it a powerful tool for developers and researchers.

The world of LLMs is rapidly evolving, empowering us with advanced AI capabilities. As these models continue to develop and refine, they hold the potential to reshape how we interact with technology, enabling more natural and human-like experiences.

Google Bard: More global, more visual, more integrated

Artificial intelligence (AI) has grown in importance in modern society, with an increasing number of organisations implementing AI into their daily operations. AI technologies are being utilised to automate routine processes, improve decision-making, and improve user experiences in areas such as healthcare, banking, retail, and transportation. 

At the beginning of 2023, OpenAI released a language-based AI model called ChatGPT that took the digital world by storm. A few months later, search engine giant Google announced that it would also launch its very own language model soon, and now it is finally here. The AI model has finally been made publicly available in 180 countries, including India. 

What is Google Bard?

Google Bard is a conversational AI developed by Google and powered by LaMDA (Language Model for Dialogue Applications). With the AI chatbot Bard, Google aims to combine the depth of human knowledge with the strength, wit, and inventiveness of its massive language models. Bard will use the plethora of data available on the internet to deliver original and accurate answers.

How to use Bard AI? A step-by-step guide

Bard AI is finally available for the public to use. Here is a step-by-step guide on how to use Google Bard:

  • Click on the “Try Bard” button, which can be found at the bottom right of your screen.
  • Sign up for Bard with your Google account. 
  • Agree to the terms and conditions and privacy policy of the AI model.
  • And you are good to go!

You can use Google Bard for a variety of things, like writing poems, searching the web for anything, finding entertainment, and so much more. 

Is Google Bard better than ChatGPT?

OpenAI’s ChatGPT was launched earlier this year. It is also a language-based model that generates human-speech-like prompts. However, GPT has been known to produce factual errors and make stuff up. Its information is also limited to events until 2021. Google Bard, on the other hand, has access to the latest data and is believed to provide more accurate information. Additionally, Bard AI has an advantage over other AI platforms in terms of the depth and range of information it can access thanks to Google’s enormous data collection. 

AI models are slowly taking over the digital world. From language-based AI models like Bard and GPT to AI art generators like DALL-E and Midjourney, these models are becoming increasingly sophisticated and are being integrated into various industries, from healthcare to finance, to improve efficiency and accuracy. As technology continues to advance, we can expect even more advanced models to emerge and revolutionise the way we interact with the digital world.

ChatGPT : Breaking down the language barrier!

ChatGPT is a language model developed by OpenAI, one of the world’s leading artificial intelligence research organizations. As a language model, ChatGPT uses machine learning algorithms to understand and generate natural language responses to a wide range of questions and prompts.

The technology behind ChatGPT is based on a deep learning model known as a transformer, which is trained on vast amounts of data to learn the patterns and structures of human language. This allows ChatGPT to generate natural and coherent responses to a wide range of prompts, from simple questions to complex conversations.

To use ChatGPT, users can simply input a question or prompt into the system, and ChatGPT will generate a response based on its training and understanding of natural language. The system is designed to learn and improve over time, as it is fed more data and experiences a wider range of prompts and questions.

Potential Use Cases

ChatGPT is used in a variety of applications, from customer service chatbots to virtual assistants and language translation systems. Its ability to understand and generate natural language responses has made it a valuable tool for businesses and organizations looking to improve their communication with customers and users.

  • Customer Service: ChatGPT can be used to provide customer service through chatbots, which can help businesses automate routine interactions with customers and improve response times.
  • Education: ChatGPT can be used to create personalized learning experiences for students, providing feedback and guidance on assignments and coursework.
  • Healthcare: ChatGPT can be used to provide virtual healthcare services, such as symptom triage or mental health counseling.
  • Content Creation: ChatGPT can be used to generate content for websites, social media, and other digital channels, such as news articles or product descriptions.
  • Translation: ChatGPT can be used for language translation, allowing users to communicate with people who speak different languages.
  • Research: ChatGPT can be used for research purposes, such as language modeling and information retrieval.
  • Entertainment: ChatGPT can be used to create interactive games and storytelling experiences, allowing users to engage with virtual characters and narratives.

Limitations

While ChatGPT is an impressive achievement in natural language processing and machine learning, there are still some limitations to the technology that are important to consider. Here are some of the key limitations of ChatGPT:

  • Contextual Understanding: ChatGPT is trained on a vast amount of data, but it still has limitations in terms of its ability to understand the context of a conversation or prompt. It can struggle with understanding nuances or sarcasm, which can lead to incorrect or inappropriate responses.
  • Biases: Like any machine learning model, ChatGPT can also be prone to biases in the data it is trained on. This can lead to responses that may unintentionally reinforce harmful stereotypes or prejudices.
  • Generating Original Content: While ChatGPT is capable of generating text, it’s important to remember that it’s doing so based on patterns and structures it has learned from existing data. It may not always be capable of generating truly original content that is entirely unique or creative.
  • Limited World Knowledge: While ChatGPT can learn from a large amount of data, it may not have the same breadth of knowledge and experience as a human. It may struggle with tasks that require a deep understanding of the world and the ability to reason and make connections between different ideas.

While ChatGPT is a powerful tool, it’s important to understand its limitations and use it appropriately. As with any technology, it’s not a perfect replacement for human interaction or decision-making.

5G Connected Ambulance : Jio’s ‘True 5G’ to revolutionise remote healthcare!

• A robotic arm that will perform ultrasound
• The robot will deliver medicine and food to the patient’s bed

Reliance Jio has introduced a 5G connected ambulance at the Indian Mobile Congress. This is such an ambulance which will digitally deliver all the important information of the patient to the hospital in real time and that too before the patient reaches the hospital. In the event of a medical emergency, the doctor present at the hospital can make all necessary medical arrangements before the patient arrives. You can guess how much the medical industry will change in the future by looking at this ambulance.

The Jio Pavilion will also feature a robotic arm that specializes in X-rays and ultrasounds. In fact, a radiologist or sonographer sitting hundreds of miles away can easily run it through Jio True 5G. This robotic arm will directly connect city-based radiologists with rural patients. For basic medical needs like X-ray and ultrasound, villagers will no longer have to go around the city and the report will also be available at home.

Reliance is launching 5G service on Diwali. Relying on the high speed and low-latency of its True 5G network, Reliance Jio is also working on many technical solutions that will come in handy in everyday life. One of them is Jio 5G Healthcare Automation. Many frontline workers lost their lives in isolation wards of hospitals during the Kovid epidemic. Reliance Jio is working on the technology of 5G controlled robots which will be able to deliver medicines and food to isolation wards as well as other patients.

Due to the use of cloud based 5G controlled robots the margin of error will be zero. With a robot fleet management system, their maintenance and sanitization will also be easier than humans and most importantly, the lives of thousands of frontline workers and patients can be saved.

5G and Digital Way of Life

After years of hype and a bumpy first year of launches, carrier 5G networks are almost here. The technology is supposed to change your life with its revolutionary speed and responsiveness. But before we get into that, it’s important to understand what the technology is, when and how it will affect you, and how to distinguish between (the still growing) hype and reality.

Just like with everything else, you must give 5G some time to mature.

Things are certainly getting better — carriers continue to expand 5G coverage into more cities, and new devices compatible with multiple networks are coming out. But just how quickly that life-changing aspect of 5G will arrive remains up in the air. That’s exacerbated by the novel coronavirus, which has locked down millions around the world, potentially slowing the 5G rollout and dampening consumer enthusiasm for pricey new devices, even with those stimulus checks.

All this means 5G is slowly inching from years of promises — ever since Verizon talked about moving into the area four and a half years ago to AT&T kicking off the first official mobile network at the end of 2018 and T-Mobile going nationwide in December — to becoming reality for more than a handful of early adopters. Beyond a big speed boost, 5G has been referred to as foundational tech that’ll supercharge areas like self-driving cars, virtual and augmented reality and telemedicine services such as remote surgery. It will eventually connect everything from farming equipment to security cameras and, of course, your smartphone.

But what exactly is 5G? Why are people so excited? This CNET Report is a breakdown of why the next generation of wireless technology is more than just a boost in speed. (If you’re really interested, check out our glossary of 5G terms.)

What is 5G?

It’s the next (fifth) generation of cellular technology, and it promises to greatly enhance the speed, coverage and responsiveness of wireless networks. How fast are we talking? Carriers like Verizon and AT&T have shown speeds surging past 1 gigabit per second.

That’s 10 to 100 times speedier than your typical cellular connection, and even faster than anything you can get with a physical fiber-optic cable going into your house. (In optimal conditions, you’ll be able to download a season’s worth of Stranger Things in seconds.)

Is it just about speed?

No! One of the key benefits is something called low latency. You’ll hear this term a lot. Latency is the response time between when you click on a link or start streaming a video on your phone, which sends the request up to the network, and when the network responds, delivering you the website or playing your video.

That lag time can last around 20 milliseconds with current networks. It doesn’t seem like much, but with 5G, that latency gets reduced to as little as 1 millisecond, or about the time it takes for a flash on a normal camera.

That responsiveness is critical for things like playing an intense video game in virtual reality or for a surgeon in New York to control a pair of robotic arms performing a procedure in San Francisco. You know that little lag when you’re on a Zoom video conference call? 5G will help eliminate some of those awkward, “Sorry, you go ahead” moments after people talk over each other. That lag time won’t completely go away, especially if you’re communicating with someone halfway around the world. The distance matters, since that info still has to travel there and back.

But a virtually lag-free connection means self-driving cars have a way to communicate with each other in real time — assuming there’s enough 5G coverage to connect those vehicles.

Are there other benefits?

The 5G network is designed to connect a far greater number of devices than a traditional cellular network does. That internet of things trend you keep hearing about? 5G can power multiple devices around you, whether it’s a dog collar or a refrigerator.

The 5G network was also specifically built to handle gear used by businesses, such as farm equipment or ATMs, and can adjust for differing needs. For example, some products like sensors for farming equipment don’t need a constant connection. Those kinds of low-power scanners are intended to work on the same battery for 10 years and still be able to periodically send data.

How does it work?

5G initially used super high-frequency spectrum, which has shorter range but higher capacity, to deliver a massive pipe for online access. Think of it as a glorified Wi-Fi hotspot.

But given the range and interference issues, the carriers are also using lower-frequency spectrum — the type used in today’s networks — to help ferry 5G across greater distances and through walls and other obstructions.

Last year, Sprint (now part of T-Mobile) claimed it has the biggest 5G network because it’s using its 2.5 gigahertz band of spectrum, which offers wider coverage. But T-Mobile in December launched a nationwide network using even lower-frequency spectrum, which can spread further. T-Mobile intends to use Sprint’s 2.5 GHz spectrum to add more speed to its network. AT&T also launched 5G with lower bands at the end of last year, and says it plans to have nationwide coverage by the end of summer.

The result is that the insane speeds companies first promised won’t always be there, but we’ll still see a boost from what we get today with 4G LTE.

Health Care: Covid-19 Accelerates AI Use

Courtesy: Getty Images

From predicting outbreaks to devising treatments, doctors are turning to AI in an effort to combat the COVID-19 pandemic.

While machine learning algorithms were already becoming a part of health care, COVID-19 is likely to accelerate their adoption. But lack of data and testing time could hinder their effectiveness — for this pandemic, at least.

With millions of cases and outbreaks in every corner of the world, speed is of the essence when it comes to diagnosing and treating COVID-19. So it’s no surprise doctors were quick to employ AI tools in an effort to get ahead of what could be the worst pandemic in a century.

  • HealthMap, a web service run by Boston Children’s Hospital that uses AI to scan social media and other reports for signals of disease outbreaks, spotted some of the first signs of what would become the COVID-19 outbreak. This was days before the WHO formally alerted the rest of the world.
  • Early in the outbreak the Chinese tech company Alibaba released an AI algorithm that uses CT scans of possible coronavirus patients and can diagnose cases automatically in a matter of seconds.
  • In New York, Mount Sinai Health System and NYU Langone Health have developed AI algorithms that can predict whether a COVID-19 patient is likely to suffer adverse events in the near future and determine when patients will be ready to be discharged. Such systems can help overburdened hospitals better manage the flow of supplies and personnel during a medical crisis.

Even before COVID-19, AI was already becoming a bigger part of modern health care. Nearly $2 billion was invested in companies involved in health care AI in 2019, and in the first quarter of 2020, investments hit $635 million — more than four times the amount seen in the same period of 2019, according to digital health technology funder Rock Health.

  • The advance of AI is partially a result of the rapid increase in data, the lifeblood of any machine learning system. The amount of medical data in the world is estimated to double every two months.
  • Engineer and entrepreneur Peter Diamandis told Wired an estimated 200 million physicians, scientists and technologists are now working on COVID-19, generating and sharing data “with a transparency and at speeds we’ve never seen before.”
  • “We understand who is at risk and how they’re at risk, and then we can get the right treatment to them,” says Zeeshan Syed, the CEO of Health[at]Scale, an AI health care startup.

In trials, at least, AI has demonstrated a decent record of success, especially when it comes to rapidly diagnosing COVID-19 by interpreting medical scans.

  • A study published in Nature Medicine this month found an AI system was more accurate than a radiologist in diagnosing COVID-19 patients using CT scans — X-ray images of lungs — combined with clinical symptoms.
  • A systematic review of preprint and published studies of AI diagnostic systems for COVID-19 published in the British Medical Journal in April noted the models reported “good to excellent predictive performance,” but cautioned the data was still limited for real-world applications and at high risk for bias.

That’s the perennial challenge for AI systems in any field. Experts worry models that perform well in an experiment may not be able to replicate that success in a hospital under stress.

  • “There is a lot of promise in using algorithms, but the data in the biomedical space can be really difficult to deal with,” says Gabe Musso, the chief science officer at BioSymetrics, a biomedical AI company that uses machine learning for simulation-based drug discovery. Genetic data, imaging data and data from electronic health records are often unstructured and rarely share a common format, complicating efforts to feed the information into an algorithm.
  • Many of the AI diagnostic systems being rushed into the fight against COVID-19 were developed before the pandemic and thus were trained on other respiratory diseases like tuberculosis. That reduces their accuracy — especially if their training datasets don’t match the gender or age of typical COVID-19 patients.
  • As a result, pioneering computer scientist Kai-fu Lee wrote recently, “I would give [AI] a B-minus at best” for its performance during the pandemic.

 As both the size and quality of medical data on COVID-19 improves, so should the AI systems that draw from it. But that will take time.

  • “AI will not be as useful for COVID as it is for the next pandemic,” Rozita Dara, a computer scientist at the University of Guelph, told Science recently. (Source: Axios)