Built to meet the growing needs of today’s digital consumer, Airtel Assist provides round the clock full-service experience that allows customers to check balances, buy airtime or data, make secure payments, troubleshoot issues, and access personalised assistance all from the convenience of WhatsApp.

At the core of this innovation is Airtel Nigeria’s commitment to putting people first, ensuring customer experiences are faster, more intuitive, and deeply personalised.

Speaking on the launch, Dinesh Balsingh, Airtel Nigeria CEO, said,

“This is Airtel meeting Nigerians exactly where they are, on platforms they trust and use every day. With Airtel Assist, we are adapting technology at the personal level. It’s fast, secure, and always available, designed to serve real people with real needs, in real time. As a company with a constant focus on customer satisfaction, this is one of the ways we make customer care more accessible.”

The new chatbot highlights Airtel’s continued integration of AI-powered tools to scale service delivery, reduce wait times, and maintain secure customer interactions, solidifying its position as a customer-first, innovation-led brand in Nigeria’s telecom landscape.

It also demonstrates the company’s clear ambition to lead innovation in Nigeria’s telecom sector by adopting tools that are secure, scalable, and inclusive.

To emphasize this perspective, Ismail Adeshina, Director of Marketing at Airtel Nigeria, noted that Airtel Assist was developed with both convenience and empathy in mind.

Ismail said,

“Everything about Airtel Assist is designed to simplify and enhance the way our customers engage with us. Whether it’s to check data balance in the middle of a conversation, buying data while commuting, or resolving issues after hours, Airtel Assist is always available, right there on their phones.”

Meanwhile, the product’s intuitive design and ease of use is a demonstration of adaptive technology, adapted for the nuances of local consumers, added Oyebowale Akideinde, Head of Digital Products & Innovation.

“With Airtel Assist, we’re unlocking a human way to connect on one of Nigeria’s favourite digital platforms: WhatsApp! You can now recharge, check balances, and get help instantly,” he said.

He also noted that all Airtel subscribers may activate Airtel Assist by sending a WhatsApp message to +2348028800000 or clicking https://wa.me/2348028800000.

By bridging the gap between digital sophistication and everyday convenience, Airtel Nigeria is setting a new benchmark in customer care, one that puts the power of self-service, choice, and real-time resolution into the hands of every user.

While the current AI boom is only just getting started, an early winner is Nvidia, who – on Tuesday, May 30th – saw the company’s market capitalization exceed US$1 trillion for the first time. For a chip designer with no fabrication capabilities of its own, this is a significant moment.

Hovering at around US$970 billion as of 1st June, the momentary increase in share price saw Nvidia join an elite club occupied by only five other companies currently: Apple, Microsoft, Alphabet, Amazon, and Saudi Aramco.

Previously, only three other companies (Tesla, Meta and PetroChina) have also crossed the US$1 trillion threshold.

Nvidia’s share price has increased roughly 170% since the beginning of the year, growth that has outpaced other members of the S&P 500 index.

That growth is directly correlated to the increasing awareness and use of AI tools, and the potential for impact on business and consumers alike.

ChatGPT has been discussed in boardrooms and at the water cooler since it was released in November 2022. As of January 2023, just three months after its release, ChatGPT had registered 100 million users.

The chatbot – which is built on a large language model consisting of 175 billion parameters – was trained using approximately 10,000 Nvidia A100 Graphics Processing Units (GPUs).

Nvidia currently accounts for around 80% of all GPUs globally, where the use of these GPUs has been bolstered by AI and data mining (the parallel processing benefits of GPUs making them as useful for the training of AI algorithms as for cryptocurrency mining).

Market research company IDTechEx recently published a report that forecasts Nvidia’s continued dominance not just on the GPU stage but more specifically as AI hardware leaders, with the company taking a considerable percentage of the forecast US$257 billion AI chip revenue as of 2033.

Presently, Nvidia generates more revenue from their data center and networking market segment (which includes data centre platforms as well as autonomous vehicle solutions and cryptocurrency mining processors) than from their graphics reporting segment. In FY2023, Nvidia generated US$15.01 billion in Data Center revenue, which accounted for 55.6% of the total revenue generated for the year.

This presents an increase in Data Center revenue of 41% from 2022, where Nvidia has shown year-on-year growth in Data Center revenues of over 40% since 2020. Contrast this to other AI chip designers – such as AMD (who recently acquired Xilinx) and Qualcomm – and it is clear that Nvidia are establishing early dominance in the data center AI space.

The company is not resting on its laurels either. While the A100 is presently the most commonly used chip for AI purposes within data centers, Nvidia announced early this year the H100 GPU, based on their new Hopper architecture.

The Hopper architecture is built in TSMC’s 4N process (an enhanced version of the 5 nm node), incorporating 80 billion transistors (the A100 has 54.2 billion transistors, made in a 7 nm process). With speedups ranging from 7X to 30X across training and inference when compared with the A100 – as well as a comparable thermal design power in the PCIe form factor – Nvidia will be supplying the key hardware necessary to run the increasingly complex AI algorithms of tomorrow.

And yet, while Nvidia acquires more of the data center processing market, there is still significant opportunity for chip designers at the edge, which is forecast to grow at a greater compound annual growth rate than for cloud AI over the next ten years, according to IDTechEx’s latest report on AI chips.

AI at the edge has different requirements than in the cloud, chief among them the power consumption of chips due to the thermal capabilities of the devices in which they are embedded. As chips at the edge can typically consume no more than a few Watts, the complexity of the models that they run must be greatly simplified.

A chip such as the A100, with its large footprint and transistor density, would be a waste; instead, companies need not design at the cutting-edge in terms of node processes and can instead opt to manufacture at more mature nodes, which have a lower price point (and therefore barrier to entry) than leading-edge nodes.

It is difficult to determine the precise location of the AI inflection point and how far in the future it is. While opinions may differ, there is no questioning that the AI boom is happening and that AI tools have the capacity to transform workflows across industry verticals.

To learn more about the global AI chips market, including the technology developments, key players, and market prospects for AI-capable hardware, please refer to IDTechEx’s “AI Chips 2023-2033” report.

Google and Microsoft are aware of AI’s potential to transform many industries. And what has been glaring recently is the commitment to openly and collaboratively develop the technology to maximize its potential for everyone.

The truth is that the web search paradigm hasn’t changed in a long time, but AI can deliver information more fluidly and quickly than traditional methods. With AI, everything is drastically changing. 

The companies are determined to reinvent internet search engines such as Google Search and Microsoft Bing, talking digital assistants such as Alexa and Siri, and email programs such as Gmail and Outlook.

For instance, Google believes its users increasingly want to access information in a more natural, intuitive way using tools such as Google Lens, which allows people to search using images and text.

Bing AI & Google Chatbot

Bing AI is a new version of Bing’s search engine that is powered by an improved version of the same AI technology that powers chatbots. This AI conversationally browses the web. Users will be able to chat with Bing similarly to ChatGPT, asking questions and receiving responses in natural language.

In a blog post, Google said Bard seeks to combine the breadth of the world’s knowledge with the power, intelligence, and creativity of our large language models. It draws on information from the web to provide fresh, high-quality responses. 

“It’s a really exciting time to be working on these technologies as we translate deep research and breakthroughs into products that truly help people. 

That’s the journey we’ve been on with large language models. Two years ago we unveiled next-generation language and conversation capabilities powered by our Language Model for Dialogue Applications (or LaMDA for short).”

The bottom line is that individual users’ specific needs and preferences will ultimately determine which of these services they use.

Further, Bing AI includes various features such as visual search, intelligent recommendations, and natural language understanding. It offers a chatbot interface, known as Bing Chatbot, that can assist users with various tasks, such as booking flights, making restaurant reservations, and finding local businesses.

Emphatically, Google Chatbot and Bing AI offer similar functionalities but have different strengths and weaknesses. It also has a wide range of integrations with other Google services, such as Google Maps and Google Calendar, which allow it to provide personalized recommendations based on the user’s previous interactions with those services.

Concerns

Technology has flaws. Because chatbots learn their skills by analyzing massive amounts of text posted on the internet, they can’t tell the difference between fact and fiction and can generate text that is biased against women and people of color.

Google was hesitant to make this type of technology available to the public because executives were concerned that the company’s reputation would suffer if the A.I. generated biased or toxic statements.

According to experts, AI tools are “vast autocomplete systems, trained to predict which word follows the next in any given sentence.” As such, they have no hard-coded database of “facts” to draw on—just the ability to write plausible-sounding statements. 

This means they tend to present false information as truth since whether a given sentence sounds plausible does not guarantee its factuality.

Chatbots learn their skills by analyzing massive amounts of text posted on the internet; they can’t tell the difference between fact and fiction and can generate text that is biased against women and people of color.

For the time being, Google has been hesitant to make this type of technology available to the public because executives are concerned that the company’s reputation will suffer if the A.I. generates biased or toxic statements.

Conclusion

In conclusion, while Google Chatbot and Bing AI are both competitors in the AI space, they are not necessarily competing head-to-head. Each tool has advantages and disadvantages, and users may prefer one based on their specific requirements and preferences.

Arguably, it is fair to mention that Google Chatbot and Bing AI are scrambling for the attention of users. However, it is important to note that these two technologies take different approaches to AI, and thus they may not necessarily compete.