Naresh Chouhan, GSMA (00:09):
Hi everyone. Can everyone hear me okay? Good. Hi. So I'm Naresh Chouhan. I'm part of the GSMA. I work in the AI Technology and Strategy team, and AI is across the whole of the GSMA in lots of different ways - everything from regulatory and policy all the way through to frameworks that we have for responsibility, and then how AI is going to be utilised within the networks in both 5G and 6G environments or 6G futures. And then other strands that we're working on around building telco-grade AI, building inclusive AI, as well as looking at monetisation frameworks and agents in action - or AI in action - as well. So just concentrating on a couple of those things. The first is around building telco-grade AI. So for a few years now, we've been monitoring how AI is handling and coping with telco-specific data.

Naresh Chouhan, GSMA (01:11):
Why is that important? Well, what we've heard over the past couple of days is how the operators and the community in general are trying to look at network operations and how to optimise those and automate those, building towards fully autonomous networks as well. So as you can see, this is a model from Stanford and their AI Index. The past 12 years have seen vast improvements in terms of AI capability - the ability to handle mathematical equations, complex constructs within AI, as well as looking at particular Q&A responses as well.

Naresh Chouhan, GSMA (01:52):
And so some vast strides have been made, and even in this last year alone we've seen a huge amount of progress within AI overall. However, AI systems still don't properly speak telco, so they still don't really help operators in the way they need to. And what we have been seeing is operators looking more in depth at how to utilise AI, as we've all heard. But again, we're still seeing a lack of accuracy, and that's one of the things that we want to try and improve. Why is that important? Well, from a recent GSMA Intelligence research report earlier this year, it's not rocket science to say that a huge percentage - around a third - of all operational costs that network operators are spending has been on network operations, yet their spend in AI doesn't match that. It's only at 16%, whereas they're focusing on things like customer experience and other uses of AI within their environment. So there's an opportunity there, and when we're talking about an industry that spends billions, that opportunity is actually large monetarily as well.

Naresh Chouhan, GSMA (03:12):
So what are we doing about this? Well, earlier this year at Mobile World Congress in Barcelona, GSMA launched the OpenTelco AI platform, and this is a community resource. So it's important to state that this is community - it's not just the telco industry. It is academia, it is operators, it is the frontier LLM companies, as well as innovative start-ups that focus on different things. And what we're doing is making available large datasets. So you all know the 3GPP specifications, but those have all been contributed to the OpenTelco platform as well as what we call the PRDs - these are all the documents that go into building the actual standards themselves. So there's a vast amount of data that has been encoded and made available open source for people to utilise.

Naresh Chouhan, GSMA (04:13):
So when we see the leaderboards, what we're also doing is benchmarking LLMs that people are building - everything from the frontier model companies as well as models that are being built by operators. So that is where we really start to see some of the real insights and benefits as to how and why operators are using LLMs. And if you look at the leaderboard now, which I can show you outside, what you'll see is that AT&T are topping the charts, and they've just recently released the OTEL 2 model, which is now performing - in certain categories - at 96% accuracy. So this has helped them to understand how to adopt, modify and utilise AI within the networks. But predominantly, they're now looking at specific use cases across different areas of the network, everything from configuration through to management, through to root cause analysis, and then onwards to self-healing as they build towards their autonomous network as well.

Naresh Chouhan, GSMA (05:31):
So this was actually built using the largest corpus of data that we released just about six weeks ago, which is based on 400 billion parameters, and that is available for the whole community to use. So moving on from that. This is about building telco-grade AI. The other really useful thing, and one of the key themes coming through in this forum, is that voice is important, and AI and voice is going to play a major part. So last year we launched a pilot project with the African Union, concentrating on building languages for Africa. So there are 2,000 dialects in Africa under major groupings of languages such as Swahili, Yoruba, Kikuyu, Xhosa - all of these things. So what we're building is another community around African languages and building that at scale. So ATLAS is African Tongues and Languages at Scale. Umoja is unity in Swahili.

Naresh Chouhan, GSMA (06:41):
And what this aims to do is to encode all the different languages from an inclusive point of view. So in the last series of revolutions that we've seen on the internet and over mobile, a lot of the African population and many populations around the world have been left out because they don't have access to smartphones or to full services. So what ATLAS Umoja is aiming to do is make those languages available to people via voice, via smartphones, or whatever mechanisms are possible, and bring them into the fold. So the idea is to build out these languages over a period of time and involve governments as well as broadcasters, linguists, culturalists and historians to amass all the data in each country, encode that into an LLM, and make those LLMs available nationally for others to lay their services on top of. So what we are now starting to see is some very clever and inclusive services - everything from a farmer in rural Uganda being able to describe a symptom on his farm with his crop and receive a response back in his natural language and natural dialect as to what to do with that crop.

Naresh Chouhan, GSMA (08:10):
So why am I telling you all this? Well, it's really simple. We need more and more people involved in the community. We need more and more contributions from everyone here, and all of these resources are available. We have a lot of interaction mechanisms - we launch campaigns around challenges, and at Shanghai this year we recently launched an agentic evaluation. So this is something that Philippe and Serge were talking about: how to evaluate agents, what guardrails and controls are in place, and what impact they're having on the network directly. So those challenges are means of engagement, and that's where we engage academia, students, and other companies as well. And then ATLAS Umoja again - the demonstration shown by Sanas earlier on today is a good example of how language is playing a major part. To a certain extent, we could almost say that this is signalling the death of the app economy, because voice is predominant and everyone knows how to use voice. So it's an alternative view. But with that, I thank you.