This video explores the dynamic field of artificial intelligence (AI), highlighting its pervasive impact on various industries and job roles. It delves into the everyday tasks of tech professionals working with AI at companies like MasterCard and Amazon Web Services. Through examples such as simulated security environments and language models for varied linguistic contexts, the video demonstrates AI's utility in combating cyber fraud, developing innovative technology solutions, and fostering inclusivity in tech development.

The featured professionals use AI to preemptively address security risks, design large language models (LLMs) that understand multiple languages, and create personalized experiences with generative ai models. A case in point is the creation of immersive experiences in Singapore's libraries, showcasing AI's role in fostering creativity. The video also touches on the burgeoning career opportunities in AI, emphasizing prompt engineering as a skill that does not require a deep technical background.

Main takeaways from the video:

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Key Vocabularies and Common Phrases:

1. synthetic [sɪnˈθɛtɪk] - (adjective) - Made by chemical synthesis, especially to imitate a natural product. - Synonyms: (artificial, fake, imitation)

These are synthetic IDs. As good as a genuine ID.

2. cyber [ˈsaɪbər] - (adjective) - Relating to or characteristic of the culture of computers, information technology, and virtual reality. - Synonyms: (computerized, digital, virtual)

Rajat Maheshwari is part of the cyber and Intelligence Solutions team at Mastercard.

3. scams [skæmz] - (noun) - Dishonest schemes or frauds. - Synonyms: (fraud, scheme, deception)

From fighting scams and fraud, developing large language models from scratch, to designing chatbots, they're all working with one technology, AI.

4. generative ai [ˈʤɛnərətɪv aɪ ˈaɪ] - (noun) - AI systems that can generate text, images, or other media in response to prompts. - Synonyms: (creative AI, growth AI, production AI)

The generative ai market is expected to grow over a trillion dollars in the next decade.

5. inclusive [ɪnˈkluːsɪv] - (adjective) - Including all the services or items that are normally expected or required. - Synonyms: (comprehensive, all-embracing, all-inclusive)

The rest of Weiqi's team, hailing from all over Southeast Asia, are working on making Sea Lion more inclusive.

6. parsing [ˈpɑːsɪŋ] - (verb) - Analyzing a string of symbols, either in natural language or in computer languages. - Synonyms: (analyzing, deconstructing, examining)

parsing refers to the process of breaking down a user's input into smaller pieces.

7. mid-career switch [mɪd kəˈrɪr swɪʧ] - (noun) - A significant change in career path during middle age or mid-point of one's career life. - Synonyms: (career change, job shift, career transition)

AI is one of those industries where you can make a mid-career switch.

8. apprenticeship [əˈprɛntɪsʃɪp] - (noun) - A system of training a new generation of practitioners of a trade or profession. - Synonyms: (training, internship, mentorship)

AI Singapore's apprenticeship program aims to grow the pool locally.

9. intelligent ai systems [ɪnˈtɛləʤənt aɪ ˈaɪ ˈsɪstəmz] - (noun) - Advanced AI systems capable of learning, adapting, and performing complex tasks. - Synonyms: (smart AI, advanced AI, adaptive AI)

Rajat's work at MasterCard includes working with banks and governments to apply intelligent ai systems to predict whether scams are taking place.

10. deep fakes [diːp feɪks] - (noun) - synthetic media in which a person in an existing image or video is replaced with someone else's likeness, using AI techniques. - Synonyms: (synthetic media, manipulated media, digital forgery)

We have seen that the world has evolved from these masks and now the deep fakes are coming in.

AI engineers are in high demand – but what is the job really like?

These are some of the world's most in-demand tech jobs. These are synthetic IDs. As good as a genuine ID. Didn't understand the phrase. It took it literally. Oh, it even read my handwriting. Is this what people mean when they say that AI is going to take our job? But what does a day in one of these roles actually look like? From fighting scams and fraud, developing large language models from scratch, to designing chatbots, they're all working with one technology, AI.

Rajat Maheshwari is part of the cyber and Intelligence Solutions team at Mastercard. In his role, his team develops tools to manage customer risk and prevent scams. Part of his role involves getting in the mind of potential fraudsters by creating fake identities. So these are synthetic IDs. As good as a genuine ID. You can have these identities, you can have the face mask, you can have the fingerprint, and then you are essentially replicating someone else. That person can do anything with these. This was done by a Japanese artist who did the mask for James Cameron movie Avatar. Sometimes we have to think like bad actors to come up with the solution which can stop these things. We have seen that the world has evolved from these masks and now the deep fakes are coming in. The intent was not to break the technology, but the intent was to help the solution providers to enhance the level so that they can stand against these kind of attacks as well.

Over at Amazon Web Services, Joe Garcia and his team have made a game out of simulating real world security conditions as well, which they hope will help clients improve their incident response processes. What we have here is a project called Chaos Kitty. Why Kitty? Well, I have cats at home who always destroy my furniture. Oh yes, agents of chaos for sure. What exactly is Chaos Engineering? We're going to intentionally inject some failure so that we can learn. You can see that there's many colorful lights and all these bricks that we use to kind of represent what we have in our AWS cloud. When it's red, something is wrong with the security configuration. And when it's green, it's all good or compliant. What we added on a Genai assistant here, what we have here is a typical company security policy. Typically without a Genai assistant, they will have to look through, study this policy document very deeply we have fed this document along with the Genai assistant, so it knows all this information. I could go in there and ask questions. It's going to give me some best practices. Alexa fix Chaos Kitty, remediating Chaos Kitty environment. You'd be able to leverage AI and Genai to actually help fix the challenges, and then they'd be more focused on the other areas that could be improved.

To be able to converse naturally with an AI chatbot, a large language model or LLM is needed. LLMs are AI models pre-trained on vast amounts of data which can understand and generate human language responses. Popular models include ChatGPT4 and Gemini. The generative ai market is expected to grow over a trillion dollars in the next decade. The team in Singapore is developing a large language model that's catering to Southeast Asian languages. Leong Weiti speaks 14 languages fluently, and he's an AI engineer and linguist involved in developing the Sea lion model.

We're going to look at an example about informal Indonesian. We're essentially asking the model. Our friend is sort of, because of his work, he's sort of panicking, you know, and he's working really hard every day. How can we help him best manage his work? Yeah, but in that context, they're saying they're using an idiom, right? Exactly. And they're saying that his beard is always on fire. Exactly. So that idiom might not be so understandable to certain models. So let's see how they deal with this. For this demo, we have four panels, and each of them corresponds to one language model. So on the left we have Sea lion, our model, and we have three other models on the right. We can see that it didn't understand the phrase. It took it literally, like it's thinking about setting someone on fire. Oh, no. It's also in the same tone. Exactly. It's casual, informal, it's still colloquial. Whereas this one, it's still sticking to, like a more formal kind of respect. Exactly. And that's really what we want to achieve as well.

Now we are seeing that some of these models out there, they are not able to sort of, handle multicultural contexts. And that's sort of understandable because they're building those models for a particular audience. Right. For us in Southeast Asia, we need to operate within this region, handling our languages and cultures. So this is why we decided to build Sea Lion. Vincent Oh works as a senior specialist solutions architect at Amazon Web Services, and his projects involve leveraging generative ai based on human prompts to create personalized experiences.

Storygen was a project that we did with the National Library Board of the entire Singapore where we wanted to reinvent the future of the libraries. We use generative ai and AWS technology to create an experience whereby young children and adults, they can put in a series of inputs selection and a brand new book will be created on the spot for them. What you call the prompts, right, that you're actually sending back to the large language model. This is just the very beginning of the art of the possible. And it's going to be amazing how people will leverage Genai to unleash their extended level of creativity. Part of those new jobs that are created as part of AI is a role or a skill set which is actually prompt engineering which didn't exist before. And when you look at prompt engineering, you don't need to be technical, you just need to understand how to put those prompts as you would, for example, like a detailed search to maximize and leverage the power of a large language model.

There is a growing demand for AI specialists and here at AI Singapore, the rest of Weiqi's team, hailing from all over Southeast Asia, including Vietnam, the Philippines and Thailand, are working on making Sea Lion more inclusive. My dream is eventually we have everybody from all the countries in Southeast Asia being represented here. AI Singapore's apprenticeship program aims to grow the pool locally, even those considering mid-career switches. In fact, some of the Sea Lion team graduated as AI apprentices after switching disciplines, such as Tai who studied finance and Weiqi who was previously a pharmacist. We're not really alone in trying to tackle low resource languages. Ultimately all the stuff that we do is fully open source as well, and it's really shared with the public in general so that everyone can benefit.

Everyone is working on different aspects of the large language model. We get to learn about it with each other. It does feel a bit like Mini asean. There is so much to do in this field. Yeah. And AI, you know, is one of those industries where you can make a mid-career switch. Absolutely, absolutely. And I'm a good example. Nessa Rajat started his career in the mobile and semiconductor industry and made the switch over to AI in 2014. I have seen that journey in past 20 years or so where AI has really flourished and it's becoming an inherent part of our lives.

When you ask people to use digital ecosystem, there are side effects. According to the Global Anti Scam Alliance, more than $1 trillion are lost to scams every year affecting 2 billion victims. Rajat's work at MasterCard includes working with banks and governments to apply intelligent ai systems to predict whether scams are taking place. Let's take the example that you giving me hundred dollars Nessa looks a perfectly legitimate transaction. But thousand more people giving me hundred dollars in a. In a day something is suspicious. Exactly. We train the models to detect the behavior, to detect the patterns and then do the risk assessment. And save you sending money to me.

Welcome to the MasterCard Experience Center. Whenever a person taps the card, our AI models kicks in. Then we give a risk assessment to the issuing institution that what do we feel about this transaction? You can see the screen here showing that the transactions are getting declined. Where do you see the state of AI in the next couple of years? The integration with the LLMs. So that's LLM is essentially the large language models. Large language models form a big part of the user experience solutions that Joel works on for AWS.

Take reading invoices for example. If you want to introduce something else into your business, a new form, a new process, then you'll have to reevaluate the technology or refactor that in with Genai, you know, because of the large language model, it can actually parse these. parsing refers to the process of breaking down a user's input into smaller pieces and analyzing each piece to determine its meaning. I'd like to know if there is a proper signatory. Oh, it even read my handwriting. So it knows that it's my terrible handwriting, that it's Michael Garcia. Did you see yourself ending up where you are today? Even at a young age, I knew that in some form, way or that I was going to be involved with technology. What did you start out studying? I graduated computer science. I went through a variety of jobs. I even founded a company before startups were fashionable.

Today with AI, when you're thinking about redefining experiences, you're not going to get to it on the first. This is like super long shot ambition, right? You know that Southeast Asia is not 10 languages only. There are like hundreds of dialects. Balinese, Javanese, Visayan. So we hope to get those represented as well eventually. How soon can we get there? Our hope is that it will trigger similar movements across the region. Outside of Southeast Asia, the interest is also very strong, right? We have similar situation in India, we have similar situation in Africa where there's a bit of underrepresentation.

If I am able to save someone's lifelong savings, I mean, it itself that makes my day. Is this what people mean when they say that AI is going to take our jobs? It's going to make something more efficient so that people can actually concentrate on what matters more, either for the business or for customers.

Artificial Intelligence, Technology, Innovation, Ai Careers, Cyber Security, Southeast Asia, Cnbc International