Can you hear me? Yes, yes, fantastic. Thank you, thank you. Thanks a lot for the introductions. The news is that Rahul found my questions too controversial. So possibly that's the reason why he's not here. No, no, he's joining us. His flight got delayed slightly. So he will be here. And that's why I've left the chair. Nothing to do with that I'm allergic to Suresh or anything like that. But so I think the topic is fairly clear. First of all, welcome to the first panel discussion of the day. It is about gen AI impact on creativity. A fantastic discussion to start the day with almost. A small caveat, there is no use of gen AI that we have done in our conversations. We will keep it very real, very honest, and that's the promise I've got from all of them. You know, when we were discussing this when I was thinking about it, I said if we were having this discussion two years back, I would have said, what AI? Nothing's going to impact creativity. It will remain the same. But two years down the line, I think AI or gen AI is reality. It is impacting creativity in many ways. Good or bad, we'll figure out in the next 45 minutes. But let me begin the discussion, possibly with you, Suresh. So I'll start with you.  When you disrupt something, not all would be good and not all would be bad. Your point of view on what you feel is the good and the bad of generative AI. And like I said, Suresh, honest. Hello. Yeah, thanks, Amit. I think first of all, I'll start with the disclaimer that I'm not really a big expert in terms of AI and probably cannot, you know, I wouldn't say that I can make a comprehensive view that I can share on this. In fact, what consoles me is that even the developers of these AI tools themselves often find themselves surprised with what comes out of their tools and what the capabilities and this emerging qualities and capabilities of those creations themselves. So what is, I think, at this stage people feel is about the unpredictability itself of the AI and the gen AI that we talk about. And hence, I think, you know, as we go forward, there'll be definitely a lot more of developments and a lot more of applications across various areas of not just marketing and creativity, but across various operations. And we've been seeing, you know, such developments. Good and bad, yeah, I think there are, already we can see in terms of, in marketing, we can see the use of AI in various tools which is leading or which could lead even more towards building efficiencies, personalization, personalization at scale, or even the overall effectiveness of the communication and so on. And not just in marketing, but like I said, healthcare and other areas we're seeing that this tremendous amount of developments which are actually good and enabling. Bad, of course, we've also seen the bad in the last few weeks and months where those deep fakes and those images and I think we'll have to get over quite a bit of those bads as well and how those are regulated, I think will be very critical as we move forward. Yeah, I know, and I would tend to agree with you. It's super exciting to see where we are heading. It's also scary in some ways. Kathleen, would you want to put your thoughts on it when we were discussing just before this? You had an interesting view on the good and the bad. Is there anything that you would want to share? Yeah, I think, thanks, Amit, and thank you for having us and LinkedIn thrilled to be sponsoring the digital report this year. I'm really happy to be here. I'm an optimist, so part of that optimism is driven by the data, which everything points to AI being a massive boost for growth, for economies, for industries, all of that. So I'll start there, which is where much of my optimism comes from, for sure it's disruption when it comes to creativity and content. Every aspect of the value chain is getting disrupted, but when I think about the industry that I've always been a part of, marketing and advertising, we are the best in the world at taking disruption and technological disruption and turning it into creativity and innovation and making it good for the world. So most of what I'll say today starts from that optimism. On LinkedIn, what we see when it comes to what our members have been doing over the last year, conversations around AI, we all know this, they've exploded around our dinner tables and in our workplaces, but they've exploded on LinkedIn, so 70% increase here over a year on conversations around AI on our platform, 80% plus increase in learning courses, so I'm sure many of you in the room, I certainly have been, we're taking advantage of LinkedIn learning courses around AI and gen AI, and that's just really, again, it makes me so optimistic to see that people are upskilling, they're not letting fear hold them back. The bad, there's always a bad side to disruption. I think much of my sort of concerns around AI are in the area of ethics, we'll get onto that I think a bit later, something very close to my heart and that we see coming through in some research. We recently did with the World Economic Forum, is that AI, if we're not careful, has the potential to widen the gender gap that already exists, so we have to make sure, as we are on the cusp of this becoming really mainstream, that we make sure that the models and the algorithms don't widen that gap, and also that women and men have equal access and equal opportunity to the careers that will open up an AI, so the bad for me, if we assume everybody will do what they're supposed to do, lies more in that space, but I think we're gonna chat a bit more later. It's fantastically put, Catherine, it's a balanced view, and yes, we should be, I know there are reasons to be scared of, but there are more reasons to be excited about clearly there, so yeah, I think that's a good view, and thank you for this. Okay, now let's get a little more specifics, since we're talking about marketing and digital, and we have some of the best minds in marketing and digital in this country, and even from Singapore here, so of course I'll have to ask, AI is making its presence felt in on the creative side of things, it is impacting the world, and especially from where I see, it is a huge impact, so would love to hear, say, Pierre, from your point of view, how is it impacting creativity? Good afternoon, everyone, for you to agree on you, especially because you're going through my profile on LinkedIn. It's a pretty big question, actually, that you raised. We can talk hours about that. I think the first thing we saw, and I don't talk only for India, I talk about all the initiatives we took in the 52 countries, so one is the learning process, before anything else, nothing is definitive. At that stage, we are at the beginning of the learning curve about what AI can bring around creativity. The first thing that is very obvious to us is the capability of personalization. We have been extremely, extremely impressed by that, because we are doing pilot that became very strong campaign. So we are trying on small samples, and the small samples became a campaign by the, it became viral. The first initiatives we took became viral by itself. So actually, we are trying to go under the radar and it became very visible. The capability of personalization is amazing, because we just talk about that. We don't talk to a consumption pool anymore. We talk to individuals, literally to individuals. First of all, because we embark them in the experience itself. They are engaged in the experience of the brand. They participate to something. It's not passive, it's not just a push, it becomes a pool. So that's the beauty of it. It's extremely, extremely impressive. I would like to highlight, very quickly, I don't want to talk too much, but three main things that impacted the creativity at that stage. One is the scalability. What we've been able to do for one brand has been applicable to all brands. We don't have to, but it's definitely possible. The scalability. So all of us, all of you, by the way, we all manage a range of products. We manage different sectors on different industries. One technology is applicable to the entire portfolio. Scalability. The second one is the doability. At the beginning, it's not easy to address AI because we don't know the tools. We need to learn them. We need to study them. We need to pay for them. Some are free, some are paid. But it has to stay doable. We don't have the luxury to build a nuclear plant to tick the box about my CMO added some AI initiative and I shine. No. It needs to stay doable. The doability is very important. And the last one is the return on investment. Does it bring really value to the company? Is the campaign really, and I'm looking to you straight in the eyes of it, I don't love your concern too. Does it really bring an impact on the consumer? And it's a yes at that stage. All the KPIs, we all monitor in this room, the classical digital KPIs, very classical. The engagement rate, the views, the time spent and all of this. What we saw, the trend is we double the numbers. We double the numbers on everything. So AI brings real value on the classical way to read. But that's not enough because actually that's a very basic way to assess and evaluate the impact on creativity. The next one, that's the impact on the consumer. But we should also analyze the impacts on our industry here. The time we spend to build a campaign, the cost of the agency, the cost of the creativity, the time we save to get this personalization, the impact is massive as well. So it's not only an impact on the consumer, it's as well an impact in terms of creativity, I mean. The impact in the internal process to make it happen. So actually, both of it are for the moment positive. I just don't want to talk right now about the bad side. So we are extremely excited about it, but we are very cautious about it as well. We have very strong guidelines at the group level about how can we use AI on creatives because we don't know where it could bring your brands. It could create an impact on the brands, the brand itself, which is the core of what we sell. So we have a lot of caveat and a lot of precaution now in place. Fantastic. I'll use that in my next talk. Scalability, durability, return on investment. It's not patented as yet. Since you need voice. So Catherine, and then I can come to Apurva to you on this. I would love to get your views on how AI is impacting creativity or would impact creativity. So love your views on that. Apurva, would you like to kick us off? Hi, good evening. I'm Apurva Maheshwari. I head Marketing at Best Seller India. Best Seller is a fashion retailer and we retail some of the largest men's wear as well as women's wear and kids wear fashion brands in the country, like Jack and Jones, Veromoda, Selected and Only. So you may know us by these brand names and not so much by Best Seller. In terms of how the marketing team at Best Seller as well as our agency partners have been adopting AI and JNAI specifically over the last and these terms started floating around in the marketing circles only in the last 12 to say 18 months, right? But they've scaled very quickly and so has the adoption as Catherine was saying. I think marketers are one of the most creative people in any boardroom, right? So the adoption of it has really been across the marketing delivery per se, right? Whether it is driving faster consumer insights or doing better insight mining or whether, you know, from a marketing point of view, sharpening off brief creation from the agency point of view, generating more options or directions on campaigns from a media planning point of view, you know, driving advertising efficiencies, making sure that we are able to place these campaigns in front of audiences or in front of users or, you know, individuals as Pierre was saying because eventually everything is now boiling down to a segment of one. Placing these creatives or these ads in front of audiences that are the most likely to transact as well as leveraging AI and JNAI in experiential marketing. So we've seen adoption by bestseller as well as our agency partners as well as, you know, a lot of brands and companies across different sectors in the last 12 to 16, 18 months. Fantastic. The bell outside is a, you know, it's like a like button. It's really like your comment. That's why the bell outside. Catherine, your view on this. JNAI could not come up with that. That's a nice way to make the bell enhancing of our... Now wait for the bell now. If the bell doesn't go off while I'm speaking now, I'll be very disappointed. I think the, you know, there's naturally a lot of fear around, you know, I would say in the marketing creative industry is AI going to do copywriters or creative directors or even all of us as marketers out of a job. And I think I hope everybody in this room feels differently to that because, you know, another reason for my optimism is that, you know, I think finally we have a situation where that New Year's resolution we've all had for the last 10, 20 years to be more creative or find more time in our day to day lives for creative pursuits or thinking creatively at work, we finally have the chance to do that. You know, the excuse can be removed where we can now delegate so many of our admin tasks or the things that can be automated or the things that can be done just good enough to AI, to JNAI, whether you are a fan of JNAI writing your emails or your LinkedIn postsite, I'm not so much, but I think it's amazing for getting a thought on paper, getting you started, and then really speeding up the creative process. So I think about creativity in this new age as human-led and AI-powered. I think if you think that AI might take a copywriter's job, you've never tried to put a prompt that you've badly written into chat GPT, because you'll see what you get out at the end and it's not fit for purpose. So there is still so much room for craft and creativity and human-led strategy, just hopefully a lot less time for us all to spend on the stuff we have been trying to get off our desks for many years. I love that view. So what you're saying is actually it will get us to spend more time on creativity and the basics possibly out of the window, which is a fantastic view. And yeah, it's music to my ears too. Fantastic. Thanks, Catherine. Again, okay, let's think about examples, which possibly that you would have done or you would have heard about or read about somewhere which would have excited you. Suresh, we'll start with you. Are there any examples that you think on AI, on the creativity side of it that are exciting for you? Yeah, so before we get there, you know, basically AI, as I understand the tools, it's the ability to manipulate and generate language, whether it be in the form of words, images or sound, right? At the moment, what we see is the AI is working or playing the role of a collaborator rather than a comparator. And of course, there are several use cases and examples that I can think of, especially what has been mentioned in the past about personalizing, reaching out to the last customer based on the preferences of that consumer. In terms of reading a lot of data and then making, you know, based on the customer preferences, making some decisions, so making it more efficient and reaching out and so on. We have AI-powered chatbots, conversational bots which are getting there in terms of replying or responding to consumer queries and so on. In fact, we tried just a couple of months back, in terms of looking at various messages in the same month, but based on the consumer response, which creative to serve to whom, you know, based on the individual consumer's response. So I think there are examples of what we've been doing. But going forward, there is this whole discussion and this whole debate over creativity and whether, you know, the AI would be able to deliver on that and so on. But I think creativity is all about reading a pattern and then breaking it in to find new way of coming, you know, putting it across. And I'm sure we'll get to a stage where even in terms of creative work, there will be definitely some progress and probably AI tools will only help us, like you were saying, you know, spare more time and make it more effective. And also, personalization scale. For example, we've seen some examples of hyperlocal, you know, one creative reaching out to many different geographies, actually talking to those geographies with a message which was relevant to them. So similar is the case with, I mean, that's about geography and hyperlocal. But there could be other examples of personalized communication. And I'm sure that, you know, there will be a lot more of effectiveness and efficiency and personalization which will come up going forward. That's fantastic. So what I hear you say is that there are some exciting things that are happening which you are happy about. There are lots on the horizon. And before I move to you, welcome, Rahul. Thank you. The news on the floor is that you got... Hello, Rahul. The news on the floor is that you got worried with the questions being very controversial, so you decided to skip, but no, you have some. No, no, but welcome. I know you've had a delayed flight. Yes. You want some water? I'm good, I'm good. Thank you. So we'll carry on. On your... any examples that we would love to hear from you? The Koch masterpiece campaign that was released at the end of last year was, to me, a really good example of human-powered creativity which was supercharged by AI. It was essentially what a good creative is, right? It was succinct, effective, and clutter-breaking. So... and there are a lot more such examples, but that's one that immediately comes at the top of my mind. I'm really hoping to see more and more creative work in India and from India that leverages gen AI specifically that is, you know, is effective as a creative and a campaign. Fantastic. The Koch example, I'd just love to add a few that have inspired me and us even at LinkedIn. And the Koch example is a great... I think it's a great example of something that is available now for us all as marketers and brands to do and to use which is involve consumers. So consumers are out there creating using gen AI faster than most brands can do it. So the opportunity to co-create with them as Koch did is a great one. I think also we've seen in LinkedIn campaigns, Salesforce and Adobe are examples of two brands who've sort of taken the first mover advantage to power their campaigns, so their campaigns about AI that show best practice in using AI. So if you've seen Salesforce using Matthew McConaughey or an AI-generated version of Matthew McConaughey just to really show they're all in on AI through their creatives as well as their product, I think that's an inspiring approach for many technology brands. Adobe have done something similar where their creatives are really, you know, a bit like the Densu Digital Report if I could say, really created using best in class visual AI tools to show that Adobe are at the forefront of this. There are also lots of brands having a bit of fun with the limitations of AI. So there was a great campaign by Mint Mobile which is Ryan Reynolds' telecom brand, one of his many companies where they use chat GPT to create the script, and Ryan Reynolds is reading out this very clumsy script generated by chat GPT. So I think there's still an advantage for brands and marketers to, I guess, play on the novelty of the technology as well. Those are some inspiring examples that I've seen in the last few months. Fantastic. That's a lot of examples on... I think, would you, Rahul, have any example on any brand using AI that you've been fascinated with or possibly your brand, whichever... So, not a specific... I think most of the best examples have already been talked about, but I see today how media companies are leveraging it because they know that, you know, optimization of a campaign, of a media campaign can give you diminishing returns after a certain while. So how they are using generative AI to ensure that they have the right kind of content strategy which is powered by a dynamic content optimization backed up with the media to ensure that they get different versions of the creative for different people for different time so that they can get the right optimization of the money that they're spending, the dollar that they're spending for each media campaign. So I think the utilization is happening both at the end of optimizing the media in terms of the dollars that you're spending and also creating different kinds of creatives to ensure that it peaks up after just the media optimization kind of flattens out. It's brilliant, right? We're talking about... We've spoken about different examples. We've spoken about examples which have been fascinating because it's heightened creativity.  We're also talking about examples where it is heightened effectiveness. So, you know, it's working on both the spectrum. It's fantastic. I guess not so much to worry about AI, I guess. It's all good. I mean, I think you point to something really important there, Amit, which is you can experiment and you can find out what works maybe quicker than you could before and then you can turbocharge it. You know, most of the digital platforms now are offering AI-powered campaign planning tools. We have one at LinkedIn called Accelerate. You know, you can discover what works and then you can put, you know, a lot of power behind that and move on to your next brief, your next campaign, your next experiment, which is really exciting. That's fantastic. Yeah, I completely agree. Okay, let's spice things up a little bit, okay? We're talking about simple, straightforward stuff. Let's talk about ethics, the rights and the wrongs. Okay, Rahul, since you've come in late, let me start with you. Your view on the ethics of AI and, you know, you're working Microsoft, so I'm sure there is a deeper dwell that you've had on this. So, love to hear your view on it. Yeah, I think ethics is a very fundamental part of the AI model that we work on right now in Microsoft, but eventually I've seen all big tech companies have this model of responsible AI where ethics is an important pillar. So, transparency, fairness, trust are some of the others, but ethics is a very important part of the way that we kind of work on. Now, there are two parts to the ethics that we work on. One is that anything that you create using the AI, we don't hold any copyright content on that. It's something that you use the technology to create for and it's something that you kind of work on. Also, we make sure that the sources from which we've kind of worked on are all, the data that's been sourced, the data leaks that's been worked on are all trusted sources, are being ethically aligned and, you know, worked on to a level where we also say that, okay, if there is, while using Microsoft products in a way that we've kind of agreed on as per the agreement, if there is any incident that happened where there is a controversy or there is a debate on some things, we will be there with our customers to help them have that problem solved. So, it's very, very important that when you talk about ethics, the ethics falls at three level. The user, the service provider, and the end customer. And I think that's how the whole balance will come into the ecosystem. Fantastic. I think what I hear you say is that there is so much of background and backend work which has already gone into it to make sure that we are as right as possible. We are continuously working on that, everyone. All big tech companies. And I see that right now, the effort, the consciousness, because that's there. Trust is a basic currency on which e-commerce work. And if that's broken, nothing will work out. Fantastic. Catherine, your view on it, and then I would love Pierre also to give his two cents there. But, yeah, Catherine, start with you. Yeah, I think the optimism that I keep referring to is felt, we've seen it with some research we've done at LinkedIn where you have overwhelming majorities of CEOs and C-level executives feeling optimistic about the potential of AI for their organization. So that's there. However, consumers who are also professionals, we're all consumers and professionals, only 30-something percent of us trust organizations to do the right thing with AI. So there's a gap there. And I think while we have to rely on the, you know, the Microsofts and the regulatory bodies of the world to do the right thing, I think there's a huge onus on us all as organizations, individuals, marketing teams, agencies to put our own responsible practices in from the start. And, you know, I really feel that in some ways we have an opportunity with AI to do that where with social media as an example, we were all late to the game. You know, social media came and then a number of years later, you know, there was a rush to regulate, there was a rush to put, you know, rules and best practices in place and I really think we have that opportunity to build it into AI from the beginning. And then I think, you know, the other one that is, you know, really, really important to me is that progress in AI does not set the DEI and progress back because we can see that women are more likely to be in the jobs that might be displaced by AI and men are more likely to be in the jobs that will be augmented and made more powerful by AI. So India is one of the largest AI talent pools in the world, so I hope that in this country at least that can be a balanced opportunity and certainly that we all do everything we can to make sure that's the case. Fantastic. Any view on this? Yes. I think in terms of ethics, everything is about using AI to convince versus using AI to manipulate. If I can summarize it in one sentence, it's exactly that. Do we intend to use AI to really increase consideration and convince our consumers or manipulate the data we have from them to convince them? And I think that's very the resource hedge we are currently working on. And I fully agree, regulation should come very soon. We should really all contribute to regulate this because otherwise I think we could easily go to the dark side of it. You started to mention it, there is a dark side of it. So we started with very clear guardrails in the company. Many companies have started to put really rules and the common points in the conversation I can have with my counterparts. Where is the data? Where is the data? Who is really using the data? And that's the risk we are facing now is that when we subscribe to an AI tool, we give the data as a company, as a brand. We share the data from the consumer but from the brand itself, from the company itself. When we share a TG, social demo and passion points and very basic things, we are sourcing the data. We are sourcing the AI. So, and I will conclude on this. We have a very strict rule in the company. Do not put the name of the brand on chat GPT. Do not put any data, market share, pricing, whatever. Because the moment you do that, you make your information public. You don't know where the information you give on chat GPT to understand I said I am fighting with a market share of 35 and my competitor, you source the system and it becomes public. So, for instance, don't put your first name, last name. You never know where your name will land. In Australia, in grown lands, you don't know. So that's the limit of the data. Fantastic. Absolutely. I am saying it's a great example of what you are saying. It's super crucial for organizations to not put internal data on chat GPT and how we are working on it. We are working very closely with the enterprise to create something which is called the Bing Enterprise. You can give, you know, guardrails to the model in terms of making sure that none of the internal data goes outside. And how it kind of becomes intelligent on your own data and then that shouldn't go out in any way. That's one part of it. The second thing where I think we talked about how ethics have been not only put in by the governments, by the companies, but by the users as well. And I came across this recent example of Taylor Swift where all the Swifties came together and really defended her and the way that they've kind of put up the right pictures down there and really kind of put awareness about it. I think that was just a great example of how the companies, the governments and regulators and users are right now being conscious about this and are working towards it. That's fantastic. So basically what I'm hearing everyone say is whether it's a platform, whether it's the marketers, everyone is conscious of it and working towards it. But at the same time, this is one to embrace wholeheartedly which is fantastic and there's great news there. Quickly, we'll probably go with 30-second views on, and this is a selfish question, my point of view, which is what do you expect from your agency when it comes to AI? And I'll put that to Apoorva, Peer and Suresh, you there. So very quickly to our agency partners and to agencies, it is very tempting to plug in AI solutions and gen AI solutions in campaigns, in media planning, etc. Especially in creative campaigns, it's also very... So as I said, it's tempting, but it's also a lot of sameness and ideas that as a marketer you end up seeing. The moment a brief goes out from the company, the intent is for the agency partners to be able to come back with creative solutions. And every idea cannot be an AI-powered idea because then it's not creative. It may be creative, but it's not clutter-breaking enough. So given to the temptation sometimes, but also sometimes resist on charging a campaign with AI solutions, that's one. And to the marketing teams as well. And there it will be that it is not just the marketing department in an organization which is experimenting with AI. It is every single department, whether it's HR, whether it's IT, whether it is your sales teams, whether it is...in our case, we have a huge product development team, which is the brand team, right? They design clothes. So you're seeing AI being integrated across various business functions, right? So to be able to approach it not from a lens of fear or from, you know, being defensive about it, but to really embrace it and see how can it drive efficiencies and help you work better with other departments. Fantastic. I've taken a few cues. Pierre, you? Very quickly, 30 seconds. It's ongoing, Alvindor. We are currently building a project of AI with you right now. I cannot disclose, but it's ongoing. It's to push the clients to clarify the breach. Because AI, we think that everything is possible, that we can go everywhere in every direction and everything is doable. It's to push us more, to go potentially in a brief way more precise than what we used to share with an agency. Otherwise, it can go in so many different directions that we can lose our time and our energy and our money to look after the right solution on AI. Fantastic. Suresh, we'd love to get your view on it too. Yeah, quickly, three things. Quite optimistic that there will be extensive usage of AI and AI tools across various functions. And eventually, like I said, building on efficiencies, personalization at scale, hyperlocal land, and also overall effectiveness. Not just in marketing, but across various industries. I think there is a lot of potential. I'm sure there will be a lot more rapidly, a lot of developments rapidly coming up. At the same time, I think there's been a discussion around the ethics. So it's any technology comes with its set of the goods and of course the issues. It all depends on who's using it, how and with what intent. I'm sure we'll also see, I think a very good example there about the social media and how the regulations got up. So I think we'll also, we also look forward and we'll probably see a lot more of these regulations and other such safeguards being built by both organizations and the governments and whatever going forward. I'm sure, quite optimistic that it will definitely be quite effective. Yes, fantastic. So last question, a quick point of view from everyone. We're sitting in 2025. Expectations from AI and we can start from Catherine. I'm always very wary of predictions, especially when an event is being re-recorded. We're recording this one. It's being recorded. So I'll keep it relatively safe and they're linked because this is such a fast-moving area. Firstly, we'll just, in a year's time, we'll be talking about it less and doing it a lot more. And I think it's okay if you're not there yet, if you're not individually or as a brand trying out AI or generative AI in your marketing yet. That's okay. And we all need to have the growth mindset. So my new one this week is Perplexity, which is an AI-powered search engine that I'm trying out. Maybe it'll be around in a year. Maybe it won't. But I think just that experimentation is really important for all of us. And the second is something we see at LinkedIn, which is that the talent gap is just going to continue to widen between people who are gaining skills in gen AI and AI and those who are not. So I think employers are going to increasingly look for these skills and that gap will be more pronounced in a year than it is right now. Fantastic. Apurva, your take on it. I'm hoping by 2025 we're using AI more responsibly. We are making sure that we're reading out the biases that we have as humans and the output that goes through AI is sans-cos biases. Sorry? Come again? It's sans-cos. It's without those biases. Fantastic. Pierre? I still don't have the answer. No, mostly. It's just to get a better world that AI is here to help and not to play against us. That's it, because it's a little bit scary, to be honest. Just wish that the AI will bring value instead of destroying value from a consumer perspective, but as well from a career perspective, from an employment perspective. It's a wish. Good wish, I guess. Suresh, anything to add on that from your side since you touched on it?  But on the language processing that AI works on, whether it is words, images or sounds, I think we still have to do a little more on the words, probably somewhere there, but then the images and the sounds. 2025, look forward to getting somewhere. There? Yeah. Fantastic. Rahul, closing remarks from you since you came late. I would love to see this community using AI as a co-pilot and solving real human problems with creative, you know, with creativity going into it, with a lot of innovation going into it. So I think that's what I'm hoping for. And that's what the best combination is, when most creative brains in the country use AI as a co-pilot and solve some of the basic human problems that we're facing today. Fantastic. Thank you. I think a huge round of applause for all five of them. I am far more positive, excited about AI and creativity now. I hope all of us are. Are there any questions that we want to put across to these fantastic panel members? Are they? I know, time's over. It says two minutes over time. No? Going one, going two, going three. Okay, thank you guys. Thank you so much, everyone.


In the previous lesson, we saw how we could use a known plaintext attack in order to reverse engineer the keys for a particular cipher. In those examples, we assumed that maybe we knew a letter or maybe even a word from the plaintext that matched up with the ciphertext that we had. And now, how does that happen? Maybe we can identify some patterns in the way that messages are structured. Maybe we've got some good spies that can give us some information, but a lot of times we're going to be left to our own devices on having to make good guess. And one of the tools that we can use in order to start making good guesses about which letters in the ciphertext map back to which letters in the plaintext is a mathematical and statistical technique called frequency analysis. Let's take a look at the selection of texts from the book Pride and Prejudice. We might be able to look at this and pick up on some key patterns, maybe some letters show up more than other letters. And we can actually use this information about the way that the text shows, and we're going to do this for the entire book, but not just this one passage, and start constructing what's called a frequency bar chart, which will summarize the proportion of the entire text comprised by each of the characters. So we can start looking at, like, how many a's are there in the whole book and how many b's and c's and d's and so on. This would be a pretty tedious task to do by hand, but Python allows us to do this very easily and very quickly, and that's what we're going to learn how to do in the next few lessons. If we were to do this for the book Pride and Prejudice, we'd get the following bar chart. Now, what is a bar chart? We'll see in just a moment, but we're going to have a vertical bar, one for each of the characters in the English alphabet, so just a through z, and the height of that bar will represent the proportion of the text in the book that that character represents. So when we make the bars, we can see here. So we can see that about just under 8% of the book is the letter a, maybe about 2% of the book is the character b, e jumps up, maybe about 13% or so, and then letters like q, j, z, and x, fairly low proportion of the overall text. And you might think, well, this is the bar chart for this book. How does that compare to other books? So let's take a look. Here we've got a bar chart for Alice in Wonderland. Here's one for Frankenstein. And here's one for little women. And you'll see these bar charts don't really change that much from book to book, which may be that surprising because they're about different characters. They're in different places. You would imagine a lot of the words being used would be very different in these books. However, this underlying pattern remains. And that's actually the case for all of the English language. If you were to take the entire corpus or body of works are written in English and run a similar analysis, we get a histogram or a bar chart, rather, that looks just like this. Now, this is from Wikipedia. And depending on which books you use and the size of your analysis, these frequencies or percentages are going to change a little bit from analysis to analysis. But they're all approximately going to be about the same. And we can see that even for a relatively small passage of text, just a paragraph or two, these patterns will emerge. Now, if you had just one or two words, of course, we're not going to see the exact same distribution. But that law of large numbers will really start to weigh in once we get past just a few sentences of text. Now, some things to recognize in this histogram is that E is by far the most frequently used letter in the English language, weighing in at around 12.7% of all characters written in the English use that character E. So this could be a telltale sign if we were to look at an analysis of an encrypted message where the distribution might look a little bit different, that the most frequent letter of the ciphertext might go back to this letter E in the plain text. This kind of pattern here with A and E with the double spike spread out five across is a pretty common one to recognize, followed by the H I kind of together a higher frequency pair, and O is a higher frequency pair, and the RST is a high frequency triple. So if we're to start shifting around this alphabet, just like we do with Caesar, we would expect to recognize these kind of signatures or fingerprint of the distribution, maybe just in a different location on the encrypted message. Let's see how that might take a look. So here on the left is that same distribution of our English language that we would expect to see based off of our previous analysis. And on the right is a distribution of a Caesar text, a Caesar ciphertext that was created using a value of K or the key of three. And we can see that the letter E is most likely shifted three spots to the right in our ciphertext because the character H in the ciphertext is the most frequent letter. So there's our A, E, five apart, a double spike. There's our H I double spike now shifted over to KL. There's our N O double spike now shifted over to QR. And then there's the RST shifted over to UVW. Now notice the heights aren't exactly the same because our ciphertext uses different words and different letters to make up the message. However, they're roughly the same proportion. That's the law of large numbers weighing in again that we're going to get roughly the same shape even if it's not the exact same values. So we can definitely have a lot of different reasons to believe that K is K equals three is in fact the key for this message. We do the same thing for K equals seven. We can see L is the most frequent letter highlighted in red, which makes sense. That's seven shifted over from E. And then you can look for your AE double spikes, H, I, N, O, and RST spikes all shifted as well. Here's one for K equals 22. Probably easiest to recognize that E got shifted four spots to the left, which is the same thing as 22 to the right. Always trying to remember to put our key into a positive value. You try. Here's a distribution of a cipher text that was created using the Caesar cipher. Just pause the video and see if you can figure out what the key that was used. And we'll show you the answer in three, two and one. Here we can see that the most frequent letter in the cipher text was O, which is 10 spots to the right from the character E. So you might guess that the cipher text was created using a Caesar cipher with key of 10 and it was. So I think we've got a good handle on how the frequencies of this bar chart can help us make some educated guesses about the key that was used when creating cipher text using the Caesar cipher. However, we've seen a couple other ciphers, so let's see if these patterns remain and can be extended to other different encryption algorithms. Let's take a look at this cipher text that was created using a multiplicative cipher with key of three. Notice we can still tell that the letter M in the cipher text was the most frequently used character. So it's a pretty good guess that that came from the plain text character of E. However, you'll notice that the shape of the remainder of the distribution doesn't really match up with the English language distribution just shifted like we saw with Caesar. Consecutive plain text letters no longer get mapped to consecutive cipher text letters with a multiplicative base cipher. So we can't rely on those kind of AE double spikes or HI, NO, RST spikes to kind of correspond or corroborate the guess that we're making about the fact that E went to the letter M. We're just going to have to take a risk with our guests and hope that it plays out all right. All right, you take a try on this one. Here's a different cipher text also created using the multiplicative cipher with an unknown key. Pause the video and see if you can guess what the key might have been here. We're going to go over the answer and I'll find it in just a moment. We'll show you the answer in three, two, one. So again, it'd be a good guess here that the plain text letter E got mapped to the cipher text letter I. We can't use any of the other patterns to try and back up that guess. So let's just take that guess and run with it. So let's remember back to our previous lessons about how we could use this mapping to help us solve for the unknown key value. If our guess were correct and the multiplicative cipher then E, which remember has a numerical value of 4, was mapped to the cipher text value of I, which is 8. So we know that 4 times the k value modded by 26 should be congruent to the number 8. And a little bit of guess and check here. There's not a real easy way to solve this congruency. But a little bit of guess and check would determine that the k value could have been 2. 4 times 2 is in fact 8. And 4 times 15 would be 60. And 60 mod 26 is also 8. So these are the only two k values between 0 and 25 that would make this congruency true. Remember, we are working in a multiplicative cipher. So k equals 2 is not a valid key. It does not have a multiplicative inverse. So we can eliminate that as one of our two possibilities, meaning that k equals 15 is in fact the correct key that was used to generate the cipher text. Let's take this again to a new cipher, this time the affine cipher. So recall the affine cipher has two keys that get used in order to generate the cipher text. We take our English language or our plain text letter, convert that to a number. We're going to multiply it by the multiplicative key, k sub n, and then add on our additive key, k sub a. The distribution to the right was created using the affine cipher with the multiplicative key of 7 and an additive key of 2. Just like before, just like before, we can see that those patterns that remain in the English language in terms of the consecutive letters don't show up in the cipher text with the affine cipher. That's from the multiplicative component. But we can still see and make some good guesses about which plain text letter e went to the, which cipher text letter. In this case, they happen to be the same. It looks like the most frequent letter in the cipher text was e itself. So somehow, whatever combination of k sub a and k sub n that was used here, mapped e back onto itself. And that's okay. A lot of times plain text letters do get mapped onto themselves. And as long as they all don't do that, we're going to be okay with our encrypted message. All right, one more time for you to practice. Let's see if you could make a guess here about which values for k sub a and k sub m were used to generate this cipher text based on the distribution. Now remember, we need two keys here. So this is going to be a little bit trickier than the multiplicative one that we just did. Refer back to our previous lessons about how if we did know two correct mappings, how we could solve that system of equations to determine the key values. And I already gave you a little bit of a hint here. You're going to have to get two letters correct in order to make this possible. But you pause the video, take a look at these distributions and see what you can work out. We'll go over the answer in three, two, one. So looking at this, you probably guessed that letter m, the most frequent letter in the cipher text, came from e in the plain text. Here it got a little bit trickier though. Maybe the cipher text letter p was the letter t, our most kind of second most frequent letter in the English language. But due to the slight nuance in the actual text that we created versus this English language standard, maybe letter g was also a t. And we just had a weird selection of texts in this one where they flip flopped. These frequencies are all kind of close. And in fact, letter O, S, and t in the cipher text are all possible candidates for this letter t. It's going to get a little bit tricky. But let's go with the most likely guesses that we can tell from this bar chart. And that's that the plain text letter e was mapped to the cipher text letter m and at the plain text letter t, the second most frequent letter, was mapped from the plain text t to p. And assuming that those things are right, we can set up the following system of equations to solve for the two keys, which we'll call a and b here just to simplify the work. So if our guesses are correct, we can set up these two equations. If the plain text letter e, which has a numerical value of four, gets mapped to the cipher text letter m, which has a numerical value of 12, we can set up that second equation in our system, that four times the numerical key a, plus the additive key b, is congruent to 12, mod 26. And if our second guess is correct, that t, which has a numerical value of 19, is mapped to the cipher text letter p, which has a numerical value of 15, we can set up that first equation, that 19a plus b is congruent to 15 and mod 26. And as we've learned in our previous lesson, we can solve this system by subtracting the second equation from the first to eliminate the variable b and the new congruency that's set up, that three is congruent to 15a, mod 26. And we can solve this by multiplying both sides by the multiplicative inverse of 15, which if you remember is seven. So we can determine that a, the multiplicative key must be equal to 27. And now we can substitute that in to one of the two equations. Here I've chosen the second one, slightly smaller numbers to work with. To get the congruency that 12 is congruent to four times 21 plus b or 12 is congruent to 84 plus b or negative 72 is congruent to b. And then we mod that by 26 to find that b is equal to six. And now we've got both the multiplicative and additive key figured out for our cipher text. We should be able to use those to recover the entire plain text, not just the two letters that we've guessed. So there's our setup for frequency analysis. It helps us make some better guesses about some of the mappings between plain text, the cipher text. And while that might always get it right, it is gonna be a useful tool to have up our sleeve. In the upcoming lessons, we're gonna look at other ways that we can actually create these bar charts to kick off this analysis. And then also find another way to automate this process so we don't need to keep guessing these individual letters.


Land is a precious and increasingly limited resource. We use it to build houses and grow our food, to connect with nature and experience the outdoors, to tackle climate change and loss of biodiversity. But the demands we put on land are going up year on year, so if we don't change how we use our land soon, we might just run out. Judy Ling Wong is the honorary president of the Black Environment Network. She's agreed to meet me here at Kew Gardens in London to tell me more about Britain's land challenge. So Judy, what are the challenges we're facing with our land? You know as me, land is about life itself. Eighty percent of the population lives in urban areas, but everything's linked to land and land is now so limited. The pressure of population, climate change and the challenges of biodiversity. We must think about how we efficiently use land in order to move into a sustainable future. So how can we use land more efficiently and sustainably? In order to inform our action, science plays a great role. Some places are much more suitable for a particular aspect of land use. Others can accommodate a mixture of them. The choices have to be informed by sound science. Agroforestry is a great example where we actually introduce trees in a landscape that would otherwise be covered just in crops or just for growing animals. By introducing trees gives us better water quality, biodiversity and carbon storage. I think we must think about science as spanning both social and natural sciences. It is about getting all stakeholders on board, informing them of a whole range of scientific analysis so that they can really make good choices. It's clear that science is crucial in helping us to solve our land use issues. So I'm off to the Otter Valley in Devon to speak with Dr Sam Bridgewater about how they're already using science and working with nature to transform the landscape. What informs your decisions about how to use land for the future? Everybody wants something different from the landscape. So if you're trying to deliver a lot of landscape scale change you need to involve lots of different parties. A good example of that for us would be the Lower Otter Restoration Project. It's trying to adapt the Lower Otter Valley to climate change and restore about 55 hectares of salt marsh and mudflat which was the natural original habitat for the valley. These kind of habitats are important for many species of fish, wading birds, storing carbon. There are multiple things that landscape can be delivering depending on how you manage it. The flood embankment was built several hundred years ago that essentially drained salt marsh and mudflat for agriculture. Now with sea level rise that flood embankment is starting to fail and it's better to manage the process preemptively. The sea is coming back up that valley whether we like it or not and there's all sorts of things that shouldn't really be there. We have already relocated the cricket club to a new site. We are protecting an old municipal tip which is environmental liability and the fields that are there now, the kind of pastoral landscape will change to salt marsh and mudflat over a five-year period. One of the things that took quite a lot of time was having that discussion with the existing farmers and they negotiate the release of land elsewhere so they can still have their business. It can be challenging to reconcile these different demands and of course it's very place-specific. Food production where we are now is not incompatible with having a nature-rich landscape. We have some fairly new beaver habitats here and the dams are now increased. That beaver wetland happens to be upstream of a village that is historically flooded on a regular basis and water comes down through that wetland it's storing like a sponge and the peak flows are reduced. The benefits of those beavers there far outweigh the loss of agriculture which is pretty small. When things like this happen it's a kind of opportunity. Should we as society be more interested in land? Absolutely because land affects all of us and I think it's absolutely critical. I feel I've gained a new appreciation for land and why we need science to use it well. If you'd like to have a go at creating your own landscape that works for both people and nature check out our multifunctional landscapes interactive. Go to rawsociety.org.


Hello and welcome to the Monday market update with me at David Madden. Today's date is Monday the 25th of March 2019 the time has just gone at 935 GMT We've had a bit of a negative start to the European session We had a major sell-off in Asia overnight That's a lot of ground in the decade to do five in Japan and the Hank saying in sing it in Hong Kong rather Basically the the mood of the last couple training sessions has been quite negative given They're very disappointing Manufacturing numbers you've seen out of France Germany and the US. We had very disappointing Manufacturing number manufacturing numbers out of Germany on Friday. It was the lowest level since July 2012 That has really been the catalyst for the sell-off in global equity markets Paceo over the last two days This they're kind of renewed concerns about the state of the global economy And that essentially be the kind of the major theme of this particular session We did we did have some positive news out of Germany this morning at the German IFO places climate Index came in at 96 90 99 point six Head of expectations Of 98.5 so some positive news, but nonetheless our traders are still a bit on the nervous side So take a look now at some of the major major markets. See if they've been forming excuse me Starting off with the FTSE 100 So back back on Thursday last week FTSE 100 hit a level not seen since October So give you the indication for bullish mark the market originally was and this large red candle here It's a major sell-off that we saw on Friday. It was the largest the FTSE endured its largest daily loss in 2019 So sentiment is still about the negative side. We're firmly we're still below this red line here at the 200-day move average and while we remain below the 200-day moving average which comes into play at 7235 it's likely we could see further move to the downside and if we do see further pressure to the downside on the FTSE 100 support might be found from this region down here in late February which comes to play at 7,040 But keeping in mind There's been a wide upper train in place in late December So obviously if we if we don't take out the that the lows of late February And if you just maybe say drifting around here down towards 50 moving average this blue line here at the south of 7,100 if the wider upward trend does continue We could be looking at retest the recent highs of 7,000 370 and looking beyond that we could be likely heading up towards the kind of psychology important 7,400 and if you go beyond that we then we'd be kind of creating new multi-month highs And we could be looking at our getting this area up here at 7,558 Take a look now what's going on over in Germany the germarket attacks similar situation whereby we endured a very large sell-off. Excuse me. We endured a very large sell-off On Friday, but keep in mind that your markets last Wednesday. Once again hit a level not seen since mid-October So a multi-month high was reached last last Last week, but this red candle here was the on the Friday the 22nd Signify the major loss that we saw on Friday on the back of those very disappointing manufacturing numbers, so similar situation whereby The market has been under tense pressure in the last couple of sessions If you do continue to drift lower in the near term Support might be found from this in the other line here that the water demovie average Which comes to play just above 11,200 we can see that at the water demovie average actually has both resistance and also support here In February and well in early February and mid-February, so the metric has been Acting as support and no resistance recently it makes it more likely it would do so again in the future And if you draw a trend line from the highs of June through the highs of July through the highs of September We get this trend line along here And if that the previous trend line resistance might eat again act as trend line support So if you do manage to push on lower from here Support we support by commit to play in on the trend line, which would be in around 11,100 It is worth pointing out That the the tax is back below a very significant level here Of 11,611 690 or 11 hours to shy of 11,700 this area here was very significant and the market did manage to It didn't manage to act at resistance in early March when I finally broke above it That was a that was a positive side, but the market has probably moved back below And ultimately while we remain below that level it's likely we could see further losses So we really would need to get a take back the 11,700 to 11,690 mark If you do have any chance of retesting the mid-march March eyes of 11,823 and if you go beyond that then the next year to keep an eye for will be the big kind of psychology important 12,000 Excuse me. I'll take a look now. What's going on over in the US? With the S&P 500 So the S&P 500 speaking of important levels Last week the S&P 500 also racked up a multi-month high which is pretty significant in itself But if you just if you keep an eye on this area here in around 2870-2820 The S&P 500 finally broke above that that area So then it went regardless active as a bit bit of support But now we're actually traded back below that and ultimately while we hold below that level and in fact We're currently it's just at the S&P 500 will open below 11 11 but below 2,800 while we hold below the 2,817-820 mark it's likely we could see further losses on the S&P 500 and It moves if you're looking off for areas of potential support Support might be found for this red line here, which is the tourty moving average which comes to play at 2,754 and if you drop below that support might be found from this trend line here And if you draw a trend line between the lows Well, February 2016 with the lows of November 2016 you get this trend line along here And we can see how it was well respected and support back in October and November and then active resistance on a couple of occasions in 2019 and this trend line here my act might act as support yet again If does that support it might be support might be found in around the 2,720 mark But keeping in mind This people have under has been a solid upward trend for with three months now since late December If the market does continue to push on higher from here, and if you can take out 2,820 we could be looking heading up towards 2,866 this area around here and then beyond that The next next area to keep an eye out for Well next area beyond that will be the kind of the big cycle action number of 2,900 take a look now on the gold market and Gold has been in a fairly decent upward trend since mid-November So a nice series of higher highs and higher lows as classic upward trend Now granted that the sell-off that we saw in February didn't manage to take out the Didn't manage to create a lower low so the lows of March check out the lows of mid-February But we are pushing back higher again So it would appear that the wider upward trend is still intact And if you continue to press on higher from here We could be looking at targeting a 3,020 and if you go beyond that We could be like we had up towards again a 1350 region and a move beyond that could take us up to the levels of 266 that I never have not seen since the first quarter of 2018 any move to the downside in The gold market support might be might be found from the cycle actually port 1,300 and I move below that might take us back down towards the 1,280 Marker to 1,276 in around here take a look now on the oil market So see the fairly decent bounce back in a break crude oil Since late December and in fact last week we have levels not seen since mid-November So we have four month highs on the oil market. So give you indication if I'll abolish things are Like I said given that there's an uncertainty of a global growth on Friday because of disappointing Manufacturing numbers from France Germany and the US the better concerns about what the demand be for oil If manufacturing figures are weak, so we have seen the oil market trip to bit lower There's been a slight increase in negative momentum So if you do manage to drift a bit lower on bread We could be head back down towards $65 a barrel or support by people from this blue line here and the fifth in a moving average Which comes to play at 64 spot 37 If the wider upward trend comes to play the one that's been in place now for about four but for a since late December And that does come into play We could be like you heading back and forward this red line here the tour they move the average Which comes to play at 69 spot 74 and we'll be on that with every the psychology important 70 bucks per barrel into play Lucky now WTI Similar picture similar picture will buy a WTI as you pushing higher since late December and we've racked up a four month high Only last week, but of course we did see a bit of a sell-off on Friday And if the market does manage you drips a bit lower from here We could be like you heading back down towards fifty seven dollars a barrel We can see in the fifty seven dollar area has access resistance on a location So all resistance might become new support And if you drift below that we could be lucky any back down towards this blue line here the fifth in a movie average Which comes to play at 55 spot 13? We notice that we saw medical solidation from the 50 movie average Back in early January. So if I ever was significant the past it makes it more likely that that will be in the future If WTI can get above the psychology board at sixty dollars a barrel We could be like you heading up towards the Trinity will be average this red line here Which comes to play at sixty one spot 78 Take a look now Euro versus the US dollar your dollar. So you have your dollars been in a solid for the obvious downward trend since this is January in January my series of higher highs and higher lows Granted the highs of March to measure take out the highs of late February, but as you can see here We've matured another sell-off and if the if the If they get a downward trend that's been a play in the last couple last couple this continues We could see the market head back down towards the early March the early March lows of 111 spot 76 in around here and a break below that my previous back down towards one spot 1110 We really would need to be taken out of the recent high of one spot 1448 Before you can actually consider maybe you know shaking off the recent downward trend And if you go beyond that the next year to keep an eye forward to the upside would be the early January high of one spot 1570 Take a close go of the pound So the pound has been a fairly solid upper trend for three months My series of higher highs and higher lows and ultimately while we hold above this red line here I wonder where we average which comes to play just under one spot 30 if you hold above that We could maintain in the wider upward trend So we could be looking heading up towards the one spot 33 61 region I think I'll be on that. We could be looking at heading up towards the 11 that scene. This is June 2018 in at one spot 3472 It's only if you have a size of break below the kind of 130 turning we have an average which could play at one spot 2980 It's only if you have a size of break below that because then we've been looking at any back down towards it one spot 2775 area in or out here In terms of one of the major events of the week well we are Week ahead article can be found on a website if you're going to see if see markets calm And that take a look one of the news and analysis section. You saw the week ahead article So later today we have a lot of launching launching their new video streaming service It's going to be a rival of Amazon Prime and also Netflix. So keep an eye out for that Tomorrow fever fever fever three have full-year figures out the British drinks company AG bar also have fun your numbers out From the UK tomorrow on Wednesday lean our group have first quarter numbers on Thursday lift or have their IPO They are floating on the Nasdaq On Thursday, we also have fourth quarter GDP from the US and also in relation to the mission of brexit So the European Union have granted Theresa May their Require the extension that she requested but depending on which we're depending on whether whether whether MPs back Theresa May's withdrawal agreement it depends When the exit date will actually be it might be mid-April it might be late May depending on how things go and also on Friday, we have the UK fourth quarter GDP and we have the European Union CPI numbers so keep an eye out for that If you've any comment to make on this video or any of the other videos we've made here at CMC markets Please feel free to leave review of the news. Thank you very much


I have some few quick comments on how important it is to look now differently about how to respond to different sorts of emergencies, crises, and how the humanitarian response system now starts to engage in this discussion about chronic diseases. One comment that I want to raise is about all that interventions from, you know, heat instability for insulin or MI intervention, motivation interviews among Syrian refugees for. Mostly all that interventions are not functioning in a vacuum. There's a lot in the new crises of political determinants. There's a lot of social determinants. There's sort of tension sometimes between, you know, refugees and hosting communities. There's a lot of sometimes having like a parallel system, you know, with the national system. A lot of, let's say, overlapping research, you know, or fragmented research, and sometimes without any evaluation component when coming to, you know, big organizations and U.N. agencies. So there's a sort of complex factors that sometimes need to be considered while thinking about long-term interventions or long-term health access when we have such a sort of protracted crisis. I would like to open the discussion now for, you know, so the lady here and then you'll be after that. So my question leads on almost from your comment there, so Emma King in MSF UK. So how do you address questions about sustainability of that level of intervention? So say MSF's not going to be there forever and handing over safely of a project that gives quite a lot of intervention. How do you address those issues? So let's start from Beatrice if you want. No, no problem. So yeah, I can start by that. So of course that's an issue, but I think that's been, if you decide to take the decision of going into non-communal disease care, as MSF did 15 years ago when it comes to HIV, there was a big controversial debate. Are we supposed to do this? But now we're doing HIV projects when we only, when in the very unstable settings where we can only guarantee maybe being there for six months and we're, we can look at, we're filling into a gap of a health need. And even if it's a one-year or two-year gap, we're still affecting mobility and mortality in terms of, yeah, do you want to fill in? Sure, no. I mean, I'll speak particularly for the Lebanon context, I guess, because it's a very interesting context.  So it's really quite an overwhelmed country in terms of the burden of refugees that it's facing. And we're really implementing a model of care that's very different to the existing system. So of course there are going to be significant questions on how to hand over that model of care. Yet the way in which we're doing it is really to try and do something that is more cost-effective and rationalised, utilising a GP-based model, so that we could hope that by demonstrating a model that works, it's something that we could work with the existing system to see if that could be handed over to be something that is more sustainable in the long run and in this particular context. Just a quick addedness. We're working together with the Minister of Health with their NCD advisors and hoping to together develop a new model. Lady, please here. Hi, Ruby from MSFUK. My question is for Beatrice. Thank you for a very exciting talk. It could be a real game changer for our management of diabetes in the field. I wanted to ask how the pharmaceutical companies have reacted to your findings and if they're planning their own investigations? I don't think the pharmaceutical companies are already aware of our findings. So this is a close meeting. It's quite new. So the last experiment ran this week. And we are currently writing a scientific paper to be published in a peer-reviewed journal, but it's very early in the process. But at the moment of the study, we asked the pharmaceutical companies if they already conducted stability studies on insulin. And it was a total blocus. We could not obtain any information from them. So that's why we had to perform a literature survey and to do the whole stability study by ourselves because they were not able to give us any results. If I can intervene here. Also, I've heard a while ago I read something about heat instability for measles vaccines. So there's a lot of discussion sometimes about all that conditions that need it now in a different setting. So yeah, maybe all that will be raised in the... Any other comments? No, it's a different context now. Yes, please there. I'm encouraging people in the back. Just to follow up on that discussion, I think it's good to have the data, but then we have to move to the regulatory issue regarding this to allow us to use the outcomes of this study of stability out of cold chain as we have seen for vaccines. We need to have that to be authorized to use it on a large case in country where we work. That's one thing. The other thing is there is a need to standardize the condition on which either pharmaceutical company or MSF or every other person look at the stability study so we can have clear and unified recommendation for the field implementation. Okay, thank you. So, Kiran, please here. No. I hear you, but not there in the back. Yeah, thank you. So thanks very much for those presentations. I think just to pick up on something that Ford was saying and maybe it's a question mainly for John and Philippa.  There are broader social determinants of health that play here in terms of, well, which represent to some extent barriers to change for the patients you're seeing. I notice that you made mention of sort of stress and mental health issues and also isolation, vulnerability. I just wonder, already you have a sort of multidisciplinary model with counsellors, dieticians and so forth. Are you thinking about more involvement of social workers, for example, mental health officers? What would be your optimal team for managing these patients? Do you want to start? Sure. So, in fact, I only presented a small component of what we do and, in fact, my mental health advisor is going to kill me because I left out a key part which is that we do have integrated mental health care and social workers. In fact, the project initially, the initial emergency intervention had mental health as one of the key components and as time went on and other actors came in, we were able to hand over some components of that but then really our team started to say to us again and it's a very good point, Kieran. I mean, we're seeing this amongst our patients. They're not always able to access the care even though other providers exist and we want to be able to provide it in-house in a comprehensive way. So, in fact, we do have within our team social workers and they do things like follow up the patients who we think need home care or who need referrals. A big component of that is referrals to hospital which is quite problematic there and our social workers are involved in that and then we have some psychologists but also particularly just use of counsellors to support our patients. So, it is very much a multidisciplinary team. We have the community health care workers, counsellors and then nurses, doctors and the patient support education counselling nurses as well. John and Ian, yeah? Yeah, we have a similar right now. We're implementing, we're starting, we're proposing to add mental health to our project and also a mobile home visit unit because many of our patients are not able to come to us and then we come to them. So, we're in the same process of adding those activities. And definitely, I mean, in our refugee context in general, we're certainly more and more having mental health as a key component of the very initial interventions and when you're looking at patients with these complex medical problems that require a lot of self-management to enable that self-management, it's very difficult if you don't take care of their mental and psychosocial concerns that they have as well. It actually has an effect on how they remember the information that comes into them. A patient with depression do not remember the information that you provide them the same rate as... So, we all offer a patient coming back and saying, I don't remember what we talked about last time. That's enough.  So, question? Yeah, my question is a bit in line with that. It's about the limits that we face and some of the limitations that the projects may experience. And then, in particular, in terms of lifestyle changes, you know, can we imagine an MSF gym at some point? About it. Or in terms of referrals, you know, oncology, heart operations, you know, where do you stop and what... Where do you think this will lead us as MSF? Yeah, yeah. I mean, I think this is the core... I think the question that everybody is talking about, should MSF do this? Is this MSF? Is it emergency healthcare? I would say that. Yes, but the big question is, it has to be an operational decision. Where does our responsibility end? Are we doing bypass surgery for our patients? There's a need for our MSF doing it. Or should we advocate for other actors stepping in? There always has to be the link with advocacy. No, I mean, I agree. I think this is a discussion we've started to have and it's certainly something that our teams face and every context is a little bit different and certainly a lot of the times we won't provide some of the more complicated or high level care ourselves, but at least we can facilitate the referral and the access to that care where possible. And that's what we try in Lebanon. We use our social workers in our team to try and see what other access is available for things like dialysis, which is one of the big issues there, and certainly admission to hospital and more complex care. But I think this is a discussion we'll continue to have in MSF and as the sort of changes in terms of the global burden of disease and the places in which we intervene come, we're going to have to evolve in that discussion and see where our limits take us. We're now looking at cancer management in terms of cervical cancer treatment and some of the HIV cohorts. We're looking at things perhaps we never thought we would look at before and I think we'll continue to evolve with that. I have a story here, a quick story, about two years ago I was like a newly arrival to Beirut, Lebanon and I had a meeting with MSF staff, you know, was a leader at that time and now he's ex-MSF. So I presented on NCDs in an emergency, on a chronic emergency and in the discussion actually he was so nice person because he said that okay that's very good but it's not MSF so you can say that somewhere else. So I'm happy now that we are here in MSF and we are talking the same issue. At least now we are raising that very important issue. So we have some time for some questions. Yes please there. Hi I'm Ben Holt, the head of the UK digital team. My question is about how MSF shares innovation and technology around the movement. So for example I've worked on an SMS patient system in Zimbabwe which alerts patients to upcoming appointments and reminds them if they've missed them help them reschedule it. It's led to the highest ever treatment adherence in that project and we're now working on the next iteration. The problem I have is then distributing it to other MSF projects where it could be useful and I'm sure there are other similar trials going on. So the question is how can MSF improve the way it shares its innovation and reduces duplication of efforts? Do you want to link on to that? I think we have someone who wants to link on to that question. Yeah yeah. Someone will answer from the audience. Just to help you answer that question we started last year co-organized with OCB a sort of innovation fair where we got the different operational sections together. The five operational sections together and we had a cross-cutting participation from operational directors, logistics directors, middle-managed medical innovation people and we shared the innovation projects that are going on within the operational centers as much as we could. We are trying to keep that momentum going. There's today as you can see I think some of the projects are coming out presented here today and we hope okay this is a publicity plug but we hope we are going to hold another of one of these innovation fairs this year again and and I think that's the space to share these kind of projects because as you say there is a lot going on in the movement and we need to be able to share what's going on and to help disseminate this throughout the movement. And to just add on on that we are actually implementing in a reminder system so we already been doing it manually on a daily basis repining our patients with SMS's before the day before and we're contacting the same day if the missed appointments if they come back so it's a very quick to falter tracing but next week we are implementing an SMS reminder system in our project next week. So the lady there? Yeah hi I'm Inma Gonzalez from OCBA and also from the information systems management platform it's quite a new platform in the movement and also working cooperating with Maya in innovation and also from our perspective we are starting to see and try to how to identify common projects and common initiatives and try to see how we can start sharing because actually that's the weakest point that we see we are doing a lot of enormous efforts and small ones that are very successful but not very good at sharing and sometimes even competing internally instead of cooperating so we need to continue working on that thanks. Yeah thank you thank you so we have online question. Hi there sorry I have a question from MSF Zimbabwe this is for Emily how would you envisage adapting Mac to mobile communities? Have you heard the question? Okay thanks Zimbabwe for the question. It's a good question I honestly don't know I think you can factor migration and mobile communities into models of care by thinking about the timing of the sessions so in southern Africa there's a lot of migration kind of before December so you could make sure that patients have this bigger three-month supply of drugs to see them over the holiday period and I think again it's also linked to gender as well so that might be where the previous question came in earlier and thinking about different strategies for maybe male migrants at different times of year compared to female ones. Okay thank you. Is it far back? Hi thank you very much for all the presentations it's a bit following on from Emily's presentation it's a common question so the common is that I guess introducing new health programming it's always easier in some senses to have a very vertical approach right but then the limitations to that is you already have an overburdened primary health care system and so I like Emily's presentation I like the fact that we're thinking of integrating these new health programming into other existing health programs and looking through a broader lens of chronic disease so my question is twofold one is there other parts of that care model that you have already thought about that could be integrated and also in a wider sense is there also models that we could look at which you have a fully integrated system of various not only just chronic diseases but also other health programming aspects within a primary health care system. If we think about the experience in Kibera I mean it's only the very first year of implementation so I think yeah it's been a good way of integrating the two together I'm honestly not sure what else we could integrate into that model in general I think we just need to see how the next year goes and then think further about it. We have time for one more question before closing Kyanna again. Okay thank you I know I've already had my one question so thanks for the second it was to pick up on what Ariane said that you know where are we going to put the limits in in terms of NCD programming and I think it's it's sort of a remark that I think that here we see we've heard about three very different models of looking at how we can deliver NCD care and already we can see that delivering NCD care is very intensive requires a lot of treatment support and potentially could be expensive so it's just a remark that I think how are we going to set the limits it's through conducting these well controlled pilots in very specific settings and it's through it's not applying this these models absolutely everywhere now because we really need to learn from these sort of flagship projects and so it's really just a request also to the panel who've been involved in these projects to rigorously evaluate these projects and really draw all the lessons we can learn from this because this is going to help us in limit setting and this is going to help us define where we can have added value at a cost that we can accept. Yeah, any comment for the person? No, I completely agree. I think that that is the key thing is we need to really be maximising what we can capitalise from these and then we need more examples as well so these are very specific contexts and we need to learn we have the very different context of sort of Middle East refugee setting and then the stable African slum setting we're starting to look in other settings but I agree it needs to be done very systematically and really trying from the beginning to make sure we set it up in a way we can learn the lessons. The emergency context is the big one that I see at the moment and in Ukraine we're being faced with this with a high burden of NCDs but we're running mobile clinics so again it's a very different setting to the stable clinics that we have in the Middle East where we don't have access to we have very limited access to investigative capacity and so we need to see how we can do it even in a much simpler manner again with mobile clinics and perhaps disruption to care because of conflict there were we are looking at things like telephone follow-up of patients and we're doing that in Iraq as well with our mobile clinics so really trying to innovate in many different ways to bring the care to these settings and can I just add on quickly and I think your point about being systematic is a good one but also I'd stress the flexibility and as much as you can have a model such as the MAC or a support club for people with HIV in South Africa I think being able to kind of pick and mix in a way and take the bits that work for your own project is definitely the way to do it and not feel scared that oh no I don't want to do this because you've only done it with over 25s or something I think being flexible is definitely beneficial I think that you know turn us back to the first presentation the keynote speaking you know about the big data and that's how we need more in terms of you know better and new which is not always you know that we have data now start building this data but still we need to know more about that how we can do the best and useful intervention the last word all the presenters and I thought it was interesting that we had a you know the innovation can sometimes exist in doing in not doing something so not cold chaining an item rather than inventing new and applying new techniques but I think there was a very interesting it's going to be a very interesting field for myself but what I'm proud of is that we're engaging and we're finding out about our limits rather than being stopped by questions about the limitations that we will inevitably face so thank you very much for that and particularly thank you Dr. Fouat for chairing this session in a very interesting manner an announcement here about the conflict and health journal they released call for paper about NCDs in emergency so please if you want to have a look here and you have the pressure outside so thank you very much


Hey psych2goers, welcome back to our channel. Thank you all so much for the love that you've given us. Your ongoing support is helped us make psychology and mental health more accessible to everyone. So, thank you. Now, let's continue. Have you been through a traumatic event in your life? Are you possibly struggling to heal from this event? An estimated 70% of adults in the US have experienced at least one traumatic event during their lifetime. Traumatic events include any form of abuse. Road accidents, medical emergencies, invasive medical procedures, natural disasters, social unrest, loss, grief, and cultural, intergenerational, and historical trauma. The lasting effects of trauma include negative self-talk and low self-esteem. To help you become more aware of yourself, here are six harmful beliefs about trauma that can hurt your mental health. As a quick disclaimer, we wanted to let you know that this video is for informative purposes only and is not meant to diagnose PTSD. If you think you need help, reaching out to a mental health professional is important. Okay, let's begin. Number one, you're defined by your past. It's easy to compare your current self to the person you were before the traumatic event happened. If a traumatic event happened over a long period of time, like in an abusive relationship, it can be hard to separate your personality from the things you did to adapt during the traumatic event. But while this traumatic event will always be a part of your story, you're not wholly defined by what happened to you. Spending too much time reliving your past is what limits your ability to heal, grow, and work towards building your future. Number two, your trauma makes you think you're damaged. Another common harmful belief is that your trauma makes you damaged. This mentality is toxic because it devalues the parts of your identity outside of your trauma and equates trauma with brokenness, when it's really a normal reaction to an extremely stressful situation. Although you will never be the person you were before you experienced the traumatic event, that doesn't mean you'll never heal. It's important to remember that you don't have to go through your healing journey alone. You can seek help from friends and family support groups or a licensed therapist. Number three, you think you have to carry with you the shame of your mistakes. After a traumatic event, it's easy to replay your actions in your mind and blame the negative outcomes of a complex situation on your mistakes. And while taking accountability for your actions so you can better learn from them is good. Worrying and obsessing over your mistakes can lead to a fear of failure, avoidance behaviors, and even slower recovery from PTSD or other traumatic effects. So while guilt is a normal part of the trauma response, it's vital to remember that you can't change the past no matter how much you want to. Beating yourself up over common mistakes can take a toll on your mental health. Everyone makes mistakes. It's how you learn from them and act on them in the future that matters. Number four, you think your trauma or mistakes are what keeps others from loving you. Healing from trauma is emotionally exhausting. Things may trigger you unexpectedly. You may get frustrated with yourself or you may feel worthless and struggle with self-confidence. The healing process isn't a straight line and it's normal to have setbacks and bad days where it feels like you haven't made any progress. All these experiences can make you feel like you're difficult to love or like your significant other deserves someone who's unbroken by trauma. This mentality is harmful because it puts unattainable expectations on yourself that you think you need to meet before you're able to accept love. This can lead to trust issues and self-sabotaging your relationships. Number five, you think what happened to you has to dictate your future. There's no denying that events from your past influence your present opportunities. Some paths may be closed off to you because of traumatic events that you've lived through. For example, if you were cheated on by a lover, you may never be able to fully trust them again. Morning the future you could have had is part of the grieving process and it's also part of the healing process from trauma. But if you find yourself thinking that you can't achieve your goals because of your trauma and the effects of a traumatic event, you may be self-sabotaging your chances in the future you want. And number six, you think your trauma makes you less worthy. Finally, thinking that your past makes you less worthy can also harm your mental health. Living through traumatic experiences might leave you feeling like there's something wrong with you or that the trauma was somehow your fault. During the healing process, it sometimes feels like you'll never be whole again and it can be easy to fall into unhealthy comparisons between yourself and other trauma survivors or even people who have never experienced trauma. These thoughts are harmful because they base your self-worth on your past experiences and not your personal progress and intrinsic worth. Just because you're dealing with the effects of trauma does not mean you're undeserving of opportunities or have less to contribute than those who have never had a traumatic experience. Traumatic experiences shape your life and the lives of the people around you. If you've been through a traumatic event or are currently processing your emotions and trauma responses, know that you are not alone. Seeking help from a licensed mental health professional, support group, or other communities are great options if you need support on your healing journey. Do you relate to any of these beliefs mentioned in this video? I did. Let us know in the comments below and don't forget to like and share this video if it helped you and you think it could help someone else too. The studies and references used are listed in the description below. Don't forget to hit the subscribe button and notification bell icon for more Psych2Go videos. Thank you for watching and we'll see you next time.


I'm Mike Renzlo. I teach the LIDAR class for the Penn State University online geospatial education program. LIDAR has been a technology that has been commercialized for about the last 15 years, and in that time it has become pretty much the technology of choice. It has shown to be very, very effective on mapping the terrain and also the features on the surface of the Earth. It also has revolutionized the way that we're able to use remote sensing technology and applications in GIS. Keeping in mind that LIDAR is natively collected in 3D. So this class I think is very exciting. It begins with an overview of current platforms and the type of sensors that are used in this technology with a little bit of history. It also quickly moves into what are the characteristics of LIDAR and what makes it different than other types of technology that we've used in the past and analysis of not just a few points but point clouds of billions of points. And all of these are in 3D. The course moves forward with looking at the accuracy of this point cloud and some of the features that can be identified and also an overview and application of standards that are acceptable for evaluating the qualitative and the quantitative aspects of LIDAR. The class then moves into applications focusing on first digital elevation models and all the different types of elevation models and enhancements to the elevation models that can be very valuable for identifying features for all kinds of very, very useful applications and decision making. There's also a module on forestry applications and another module on corridor mapping looking at transmission line corridors and also transportation corridors. The class ends on a final project where the students have an opportunity to apply all of what they've learned in an organized method and they find it to be very, very rewarding. We've had great feedback from all of our students that we've taught this class for in the last four years. Thank you.