Podcasts about NLG

Military Decruitment, Trump 2.0 and Resisting New Empire (with Fig of About Face) This week, we're featuring an interview with Fig, an anarchist and member of the anti-Imperialist US veterans organization About Face to talk about decruitment, the work of About Face and an assessment of shifts in military priority under the lead of Hegseth towards the southern US border and the Trump administration 2.0's multi-polar spin. There's a lot here and we'll have a transcript in the near future. About Face: https://aboutfaceveterans.org/ GI Rights Hotline: https://girightshotline.org/ Military Law Task Force of the NLG: https://nlgmltf.org/ a recent Politico article considering some military focus shifts discussed in this chat Past veteran interviews on TFSR: Graham Clumpner pt 1 & pt 2 (2020) Eddie Falcon (2013)

Bætum upp fyrir þáttaleysið í vikunni með þessum hérna!Arnór Steinn ferðaðist í Next Level Gaming í Egilshöllinni og spjallaði við Þóri og Adam.Mario Con 2025 verður haldið í NLG vikuna 10.-16. mars og er þétt pökkuð dagskrá. Adam segir okkur meira frá því.Spjöllum líka um hvernig gengur í NLG og fleira skemmtilegt! Þátturinn er í boði Elko Gaming.

Bio   Bala has rich experience in retail technology and process transformation. Most recently, he worked as a Principal Architect for Intelligent Automation, Innovation & Supply Chain in a global Fortune 100 retail corporation. Currently he works for a luxury brand as Principal Architect for Intelligent Automation providing technology advice for the responsible use of technology (Low Code, RPA, Chatbots, and AI). He is passionate about technology and spends his free time reading, writing technical blogs and co-chairing a special interest group with The OR Society.   Interview Highlights 02:00 Mentors and peers 04:00 Community bus 07:10 Defining AI 08:20 Contextual awareness 11:45 GenAI 14:30 The human loop 17:30 Natural Language Processing 20:45 Sentiment analysis 24:00 Implementing AI solutions 26:30 Ethics and AI 27:30 Biased algorithms 32:00 EU AI Act  33:00 Responsible use of technology   Connect   Bala Madhusoodhanan on LinkedIn     Books and references   ·       https://nymag.com/intelligencer/article/ai-artificial-intelligence-chatbots-emily-m-bender.html  - NLP   ·       https://www.theregister.com/2021/05/27/clearview_europe/  - Facial Technology Issue   ·       https://www.designnews.com/electronics-test/apple-card-most-high-profile-case-ai-bias-yet  - Apple Card story   ·       https://www.ft.com/content/2d6fc319-2165-42fb-8de1-0edf1d765be3  - Data Centre growth   ·       https://www.technologyreview.com/2024/02/06/1087793/what-babies-can-teach-ai/   ·       Independent Audit of AI Systems -   ·       Home | The Alan Turing Institute   ·       Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World, Marco Iansiti & Karim R. Lakhani   ·       AI Superpowers: China, Silicon Valley, and the New World, Kai-Fu Lee   ·       The Algorithmic Leader: How to Be Smart When Machines Are Smarter Than You, Mike Walsh   ·       Human+Machine: Reimagining Work in the Age of AI, Paul R Daugherty, H. James Wilson   ·       Superintelligence: Paths, Dangers, Strategies, Nick Bostrom   ·       The Alignment Problem: How Can Artificial Intelligence Learn Human Values, Brian Christian   ·       Ethical Machines: Your Concise Guide to Totally Unbiased, Transparent, and Respectful AI, Reid Blackman   ·       Wanted: Human-AI Translators: Artificial Intelligence Demystified, Geertrui Mieke De Ketelaere   ·       The Future of Humanity: Terraforming Mars, Interstellar Travel, Immortality, and Our Destiny Beyond, Michio Kaku, Feodor Chin et al  Episode Transcript Intro: Hello and welcome to the Agile Innovation Leaders podcast. I'm Ula Ojiaku. On this podcast I speak with world-class leaders and doers about themselves and a variety of topics spanning Agile, Lean Innovation, Business, Leadership and much more – with actionable takeaways for you the listener. Ula Ojiaku So I have with me here, Bala Madhusoodhanan, who is a principal architect with a global luxury brand, and he looks after their RPA and AI transformation. So it's a pleasure to have you on the Agile Innovation Leaders podcast, Bala, thank you for making the time. Bala Madhusoodhanan It's a pleasure to have a conversation with the podcast and the podcast audience, Ula. I follow the podcast and there have been fantastic speakers in the past. So I feel privileged to join you on this conversation. Ula Ojiaku Well, the privilege is mine. So could you start off with telling us about yourself Bala, what have been the key points or the highlights of your life that have led to you being the Bala we know now? Bala Madhusoodhanan It's putting self into uncharted territory. So my background is mechanical engineering, and when I got the job, it was either you go into the mechanical engineering manufacturing side or the software side, which was slightly booming at that point of time, and obviously it was paying more then decided to take the software route, but eventually somewhere the path kind of overlapped. So from a mainframe background, started working on supply chain, and then came back to optimisation, tied back to manufacturing industry. Somewhere there is an overlap, but yeah, that was the first decision that probably got me here. The second decision was to work in a UK geography, rather than a US geography, which is again very strange in a lot of my peers. They generally go to Silicon Valley or East Coast, but I just took a choice to stay here for personal reasons. And then the third was like the mindset. I mean, I had over the last 15, 20 years, I had really good mentors, really good peers, so I always had their help to soundboard my crazy ideas, and I always try to keep a relationship ongoing. Ula Ojiaku What I'm hearing is, based on what you said, lots of relationships have been key to getting you to where you are today, both from mentors, peers. Could you expand on that? In what way? Bala Madhusoodhanan The technology is changing quite a lot, at least in the last 10 years. So if you look into pre-2010, there was no machine learning or it was statistics. People were just saying everything is statistics and accessibility to information was not that much, but post 2010, 2011, people started getting accessibility. Then there was a data buzz, big data came in, so there were a lot of opportunities where I could have taken a different career path, but every time I was in a dilemma which route to take, I had someone with whom either I have worked or who was my team lead or manager to guide me to tell me, like, take emotion out of the decision making and think in a calm mind, because you might jump into something and you might like it, you might not like it, you should not regret it. So again, over the course of so many such decisions, my cognitive mind has also started thinking about it. So those conversations really help. And again, collective experience. If you look into the decision making, it's not just my decision, I'm going through conversations that I had with people where they have applied their experience, so it's not just me or just not one situation, and to understand the why behind that, and that actually helps. In short, it's like a collection of conversations that I had with peers. A few of them are visionary leaders, they are good readers. So they always had a good insight on where I should focus, where I shouldn't focus, and of late recently, there has been a community bus. So a lot of things are moving to open source, there is a lot of community exchange of conversation, the blogging has picked up a lot. So, connecting to those parts also gives you a different dimension to think about. Ula Ojiaku So you said community bus, some of the listeners or people who are watching the video might not understand what you mean by the community bus. Are you talking about like meetups or communities that come around to discuss shared interests? Bala Madhusoodhanan If you are very much specifically interested in AI, or you are specifically interested in, power platform or a low code platform, there are a lot of content creators on those topics. You can go to YouTube, LinkedIn, and you get a lot of information about what's happening. They do a lot of hackathons, again, you need to invest time in all these things. If you don't, then you are basically missing the boat, but there are various channels like hackathon or meetup groups, or, I mean, it could be us like a virtual conversation like you and me, we both have some passionate topics, that's why we resonate and we are talking about it. So it's all about you taking an initiative, you finding time for it, and then you have tons and tons of information available through community or through conferences or through meetup groups. Ula Ojiaku Thanks for clarifying. So, you said as well, you had a collection of conversations that helped you whenever you were at a crossroad, some new technology or something emerges or there's a decision you had to make and checking in with your mentors, your peers and your personal Board of Directors almost, that they give you guidance. Now, looking back, would you say there were some turns you took that knowing what you know now, you would have done differently? Bala Madhusoodhanan I would have liked to study more. That is the only thing, because sometimes the educational degree, even though without a practical knowledge has a bigger advantage in certain conversation, otherwise your experience and your content should speak for you and it takes a little bit of effort and time to get that trust among leaders or peers just to, even them to trust saying like, okay, this person knows what he's talking about. I should probably trust rather than, someone has done a PhD and it's just finding the right balance of when I should have invested time in continuing my education, if I had time, I would have gone back two years and did everything that I had done, like minus two years off-set it by two years earlier. It would have given me different pathways. That is what I would think, but again, it's all constraints. I did the best at that point in time with whatever constraints I had. So I don't have any regret per se, but yeah, if there is a magic wand, I would do that. Ula Ojiaku So you are a LinkedIn top voice from AI. How would you define AI, artificial intelligence? Bala Madhusoodhanan I am a bit reluctant to give a term Artificial Intelligence. It's in my mind, it is Artificial Narrow Intelligence, it's slightly different. So let me start with a building block, which is machine learning. So machine learning is like a data labeller. You go to a Tesco store, you read the label, you know it is a can of soup because you have read the label, your brain is not only processing that image, it understands the surrounding. It does a lot of things when you pick that can of soup. You can't expect that by just feeding one model to a robot. So that's why I'm saying like it's AI is a bit over glorified in my mind. It is artificial narrow intelligence. What you do to automate certain specific tasks using a data set which is legal, ethical, and drives business value is what I would call machine learning, but yeah, it's just overhyped and heavily utilised term AI. Ula Ojiaku You said, there's a hype around artificial intelligence. So what do you mean by that? And where do you see it going? Bala Madhusoodhanan Going back to the machine learning definition that I said, it's basically predicting an output based on some input. That's as simple as what we would say machine learning. The word algorithm is basically something like a pattern finder. What you're doing is you are giving a lot of data, which is properly labelled, which has proper diversity of information, and there are multiple algorithms that can find patterns. The cleverness or engineering mind that you bring in is to select which pattern or which algorithm you would like to do for your use case. Now you're channelling the whole machine learning into one use case. That's why I'm going with the term narrow intelligence. Computers can do brilliant jobs. So you ask computers to do like a Rubik's cubes solving. It will do it very quickly because the task is very simple and it is just doing a lot of calculation. You give a Rubik's cube to a kid. It has to apply it. The brain is not trained enough, so it has to cognitively learn. Maybe it will be faster. So anything which is just pure calculation, pure computing, if the data is labelled properly, you want to predict an outcome, yes, you can use computers. One of the interesting videos that I showed in one of my previous talks was a robot trying to walk across the street. This is in 2018 or 19. The first video was basically talking about a robot crossing a street and there were vehicles coming across and the robot just had a headbutt and it just fell off. Now a four year old kid was asked to walk and it knew that I have to press a red signal. So it went to the signal stop. It knew, or the baby knew that I can only walk when it is green. And then it looks around and then walks so you can see the difference – a four year old kid has a contextual awareness of what is happening, whereas the robot, which is supposed to be called as artificial intelligence couldn't see that. So again, if you look, our human brains have been evolved over millions of years. There are like 10 billion neurons or something, and it is highly optimised. So when I sleep, there are different set of neurons which are running. When I speak to you, my eyes and ears are running, my motion sensor neurons are running, but these are all highly optimised. So the mother control knows how much energy should be sent on which neuron, right, whereas all these large language models, there is only one task. You ask it, it's just going to do that. It doesn't have that intelligence to optimise. When I sleep, maybe 90 percent of my neurons are sleeping. It's getting recharged. Only the dream neurons are working. Whereas once you put a model live, it doesn't matter, all the hundred thousand neurons would run. So, yeah, it's in very infancy state, maybe with quantum computing, maybe with more power and better chips things might change, but I don't see that happening in the next five to 10 years. Ula Ojiaku Now, what do you say about Gen AI? Would you also classify generative AI as purely artificial neural intelligence? Bala Madhusoodhanan The thing with generative AI is you're trying to generalise a lot of use cases, say ChatGPT, you can throw in a PDF, you can ask something, or you can say, hey, can you create a content for my blog or things like that, right? Again, all it is trying to do is it has some historical content with which it is trying to come up with a response. So the thing that I would say is humans are really good with creativity. If a problem is thrown at a person, he will find creative ways to solve it. The tool with which we are going to solve might be a GenAI tool, I don't know, because I don't know the problem, but because GenAI is in a hype cycle, every problem doesn't need GenAI, that's my view. So there was an interesting research which was done by someone in Montreal University. It talks about 10 of the basic tasks like converting text to text or text to speech and with a generative AI model or multiple models, because you have a lot of vendors providing different GenAI models, and then they went with task specific models and the thing that they found was the task specific models were cheap to run, very, very scalable and robust and highly accurate, right. Whereas GenAI, if, when you try to use it and when it goes into a production ready or enterprise ready and if it is used by customers or third party, which are not part of your ecosystem, you are putting yourself in some kind of risk category. There could be a risk of copyright issues. There could be a risk of IP issues. There could be risk of not getting the right consent from someone. I can say, can you create an image of a podcaster named Ula? You never know because you don't remember that one of your photos on Google or Twitter or somewhere is not set as private. No one has come and asked you saying, I'm using this image. And yeah, it's finding the right balance. So even before taking the technology, I think people should think about what problem are they trying to solve? In my mind, AI or artificial intelligence, or narrow intelligence can have two buckets, right. The first bucket is to do with how can I optimise the existing process? Like there are a lot of things that I'm doing, is there a better way to do it? Is there an efficient way to do it? Can I save time? Can I save money? Stuff like that. So that is an optimisation or driving efficiency lever. Other one could be, I know what to do. I have a lot of data, but I don't have infrastructure or people to do it, like workforce augmentation. Say, I have 10 data entry persons who are graduate level. Their only job is to review the receipts or invoices. I work in FCA. I have to manually look at it, approve it, and file it, right? Now it is a very tedious job. So all you are doing is you are augmenting the whole process with an OCR engine. So OCR is Optical Character Recognition. So there are models, which again, it's a beautiful term for what our eyes do. When we travel somewhere, we get an invoice, we exactly know where to look, right? What is the total amount? What is the currency I have paid? Have they taken the correct credit card? Is my address right? All those things, unconsciously, your brain does it. Whereas our models given by different software vendors, which have trained to capture these specific entities which are universal language, to just pass, on data set, you just pass the image on it. It just picks and maps that information. Someone else will do that job. But as part of your process design, what you would do is I will do the heavy lifting of identifying the points. And I'll give it to someone because I want someone to validate it. It's human at the end. Someone is approving it. So they basically put a human in loop and, human centric design to a problem solving situation. That's your efficiency lever, right? Then you have something called innovation level - I need to do something radical, I have not done this product or service. Yeah, that's a space where you can use AI, again, to do small proof of concepts. One example could be, I'm opening a new store, it's in a new country, I don't know how the store layout should look like. These are my products. This is the store square footage. Can you recommend me the best way so that I can sell through a lot? Now, a visual merchandising team will have some ideas on where the things should be, they might give that prompt. Those texts can be converted into image. Once you get the base image, then it's human. It's us. So it will be a starting point rather than someone implementing everything. It could be a starting point. But can you trust it? I don't know. Ula Ojiaku And that's why you said the importance of having a human in the loop. Bala Madhusoodhanan Yeah. So the human loop again, it's because we humans bring contextual awareness to the situation, which machine doesn't know. So I'll tie back this to the NLP. So Natural Language Processing, it has two components, so you have natural language understanding and then you have natural language generation. When you create a machine learning model, all it is doing is, it is understanding the structure of language. It's called form. I'm giving you 10,000 PDFs, or you're reading a Harry Potter book. There is a difference between you reading a Harry Potter book and the machine interpreting that Harry Potter book. You would have imagination. You will have context of, oh, in the last chapter, we were in the hilly region or in a valley, I think it will be like this, the words like mist, cold, wood. You started already forming images and visualising stuff. The machine doesn't do that. Machine works on this is the word, this is a pronoun, this is the noun, this is the structure of language, so the next one should be this, right? So, coming back to the natural language understanding, that is where the context and the form comes into play. Just think of some alphabets put in front of you. You have no idea, but these are the alphabet. You recognise A, you recognise B, you recognise the word, but you don't understand the context. One example is I'm swimming against the current. Now, current here is the motion of water, right? My current code base is version 01. I'm using the same current, right? The context is different. So interpreting the structure of language is one thing. So, in natural language understanding, what we try to do is we try to understand the context. NLG, Natural Language Generation, is basically how can I respond in a way where I'm giving you an answer to your query. And this combined is NLP. It's a big field, there was a research done, the professor is Emily Bender, and she one of the leading professors in the NLP space. So the experiment was very funny. It was about a parrot in an island talking to someone, and there was a shark in between, or some sea creature, which basically broke the connection and was listening to what this person was saying and mimicking. Again, this is the problem with NLP, right? You don't have understanding of the context. You don't put empathy to it. You don't understand the voice modulation. Like when I'm talking to you, you can judge what my emotion cues are, you can put empathy, you can tailor the conversation. If I'm feeling sad, you can put a different spin, whereas if I'm chatting to a robot, it's just going to give a standard response. So again, you have to be very careful in which situation you're going to use it, whether it is for a small team, whether it is going to be in public, stuff like that. Ula Ojiaku So that's interesting because sometimes I join the Masters of Scale strategy sessions and at the last one there was someone whose organisational startup was featured and apparently what their startup is doing is to build AI solutions that are able to do sentiment analysis. And I think some of these, again, in their early stages, but some of these things are already available to try to understand the tone of voice, the words they say, and match it with maybe the expression and actually can transcribe virtual meetings and say, okay, this person said this, they looked perplexed or they looked slightly happy. So what do you think about that? I understand you're saying that machines can't do that, but it seems like there are already organisations trying to push the envelope towards that direction. Bala Madhusoodhanan So the example that you gave, sentiment of the conversation, again, it is going by the structure or the words that I'm using. I am feeling good. So good, here is positive sentiment. Again, for me the capability is slightly overhyped, the reason being is it might do 20 percent or 30 percent of what a human might do, but the human is any day better than that particular use case, right? So the sentiment analysis typically works on the sentiment data set, which would say, these are the certain proverbs, these are the certain types of words, this generally referred to positive sentiment or a good sentiment or feel good factor, but the model is only good as good as the data is, right? So no one is going and constantly updating that dictionary. No one is thinking about it, like Gen Z have a different lingo, millennials had a different lingo. So, again, you have to treat it use case by use case, Ula. Ula Ojiaku At the end of the day, the way things currently are is that machines aren't at the place where they are as good as humans. Humans are still good at doing what humans do, and that's the key thing. Bala Madhusoodhanan Interesting use case that I recently read probably after COVID was immersive reading. So people with dyslexia. So again, AI is used for good as well, I'm not saying it is completely bad. So AI is used for good, like, teaching kids who are dyslexic, right? Speech to text can talk, or can translate a paragraph, the kid can hear it, and on the screen, I think one note has an immersive reader, it actually highlights which word it is, uttering into the ears and research study showed that kids who were part of the study group with this immersive reading audio textbook, they had a better grasp of the context and they performed well and they were able to manage dyslexia better. Now, again, we are using the technology, but again, kudos to the research team, they identified a real problem, they formulated how the problem could be solved, they were successful. So, again, technology is being used again. Cancer research, they invest heavily, in image clustering, brain tumours, I mean, there are a lot of use cases where it's used for good, but then again, when you're using it, you just need to think about biases. You need to understand the risk, I mean, everything is risk and reward. If your reward is out-paying the minimum risk that you're taking, then it's acceptable. Ula Ojiaku What would you advise leaders of organisations who are considering implementing AI solutions? What are the things we need to consider? Bala Madhusoodhanan Okay. So going back to the business strategy and growth. So that is something that the enterprises or big organisations would have in mind. Always have your AI goals aligned to what they want. So as I said, there are two buckets. One is your efficiency driver, operational efficiency bucket. The other one is your innovation bucket. Just have a sense check of where the business wants to invest in. Just because AI is there doesn't mean you have to use it right. Look into opportunities where you can drive more values. So that would be my first line of thought. The second would be more to do with educating leaders about AI literacy, like what each models are, what do they do? What are the pitfalls, the ethical awareness about use of AI, data privacy is big. So again, that education is just like high level, with some examples on the same business domain where it has been successful, where it has been not so successful, what are the challenges that they face? That's something that I would urge everyone to invest time in. I think I did mention about security again, over the years, the practice has been security is always kept as last. So again, I was fortunate enough to work in organisations where security first mindset was put in place, because once you have a proof of value, once you show that to people, people get excited, and it's about messaging it and making sure it is very secured, protecting the end users. So the third one would be talking about having secure first design policies or principles. Machine learning or AI is of no good if your data quality is not there. So have a data strategy is something that I would definitely recommend. Start small. I mean, just like agile, you take a value, you start small, you realise whether your hypothesis was correct or not, you monitor how you performed and then you think about scale just by hello world doesn't mean that you have mastered that. So have that mindset, start small, monitor, have constant feedback, and then you think about scaling. Ula Ojiaku What are the key things about ethics and AI, do you think leaders should be aware of at this point in time? Bala Madhusoodhanan So again, ethical is very subjective. So it's about having different stakeholders to give their honest opinion of whether your solution is the right thing to do against the value of the enterprise. And it's not your view or my view, it's a consent view and certain things where people are involved, you might need to get HR, you might need to get legal, you might need to get brand reputation team to come and assist you because you don't understand the why behind certain policies were put in place. So one is, is the solution or is the AI ethical to the core value of the enterprise? So that's the first sense check that you need to do. If you pass that sense check, then comes about a lot of other threats, I would say like, is the model that I'm using, did it have a fair representation of all data set? There's a classic case study on one of a big cloud computing giant using an AI algorithm to filter resumes and they had to stop it immediately because the data set was all Ivy League, male, white, dominant, it didn't have the right representation. Over the 10 years, if I'm just hiring certain type of people, my data is inherently biased, no matter how good my algorithm is, if I don't have that data set. The other example is clarify AI. They got into trouble on using very biased data to give an outcome on some decision making to immigration, which has a bigger ramification. Then you talk about fairness, whether the AI system is fair to give you an output. So there was a funny story about a man and a woman in California living together, and I think the woman wasn't provided a credit card, even though everything, the postcode is the same, both of them work in the same company, and it was, I think it has to do with Apple Pay. Apple Pay wanted to bring in a silver credit card, Apple card or whatever it is, but then it is so unfair that the women who was equally qualified was not given the right credit limit, and the bank clearly said the algorithm said so. Then you have privacy concern, right? So all these generic models that you have that is available, even ChatGPT for that matter. Now you can chat with ChatGPT multiple times. You can talk about someone like Trevor Noah and you can say hey, can you create a joke? Now it has been trained with the jokes that he has done, it might be available publicly. But has the creator of model got a consent saying, hey Trevor, I'm going to use your content so that I can give better, and how many such consent, even Wikipedia, if you look into Wikipedia, about 80 percent of the information is public, but it is not diversified. What I mean by that is you can search for a lot of information. If the person is from America or from UK or from Europe, maybe from India to some extent, but what is the quality of data, if you think about countries in Africa, what do you think about South America? I mean, it is not representing the total diversity of data, and we have this large language model, which has been just trained on that data, right? So there is a bias and because of that bias, your outcome might not be fair. So these two are the main things, and of course the privacy concern. So if someone goes and says, hey, you have used my data, you didn't even ask me, then you're into lawsuit. Without getting a proper consent, again, it's a bad world, it's very fast moving and people don't even, including me, I don't even read every terms and condition, I just scroll down, tick, confirm, but those things are the things where I think education should come into play. Think about it, because people don't understand what could go wrong, not to them, but someone like them. Then there is a big fear of job displacement, like if I put this AI system, what will I do with my workforce? Say I had ten people, you need to think about, you need to reimagine your workplace. These are the ten jobs my ten people are doing. If I augment six of those jobs, how can I use my ten resources effectively to do something different or that piece of puzzle is always, again, it goes back to the core values of the company, what they think about their people, how everything is back, but it's just that needs a lot of inputs from multiple stakeholders. Ula Ojiaku It ties back to the enterprise strategy, there is the values, but with technology as it has evolved over the years, things will be made obsolete, but there are new opportunities that are created, so moving from when people travelled with horses and buggies and then the automotive came up. Yes, there wasn't as much demand for horseshoes and horses and buggies, but there was a new industry, the people who would mechanics or garages and things like that. So I think it's really about that. Like, going back to what you're saying, how can you redeploy people? And that might involve, again, training, reskilling, and investing in education of the workforce so that they're able to harness AI and to do those creative things that you've emphasised over this conversation about human beings, that creative aspect, that ability to understand context and nuance and apply it to the situation. Bala Madhusoodhanan So I was fortunate to work with ForHumanity, an NGO which basically is trying to certify people to look into auditing AI systems. So EU AI Act is now in place, it will be enforced soon. So you need people to have controls on all these AI systems to protect - it's done to protect people, it's done to protect the enterprise. So I was fortunate enough to be part of that community. I'm still working closely with the Operation Research Society. Again, you should be passionate enough, you should find time to do it, and if you do it, then the universe will find a way to give you something interesting to work with. And our society, The Alan Turing Institute, the ForHumanity Society, I had a few ICO workshops, which was quite interesting because when you hear perspectives from people from different facets of life, like lawyers and solicitors, you would think, ah, this statement, I wouldn't interpret in this way. It was a good learning experience and I'm sure if I have time, I would still continue to do that and invest time in ethical AI. As technology, it's not only AI, it's ethical use of technology, so sustainability is also part of ethical bucket if you look into it. So there was an interesting paper it talks about how many data centres have been opened between 2018 to 2024, which is like six years and the power consumption has gone from X to three times X or two times X, so we have opened a lot. We have already caused damage to the environment with all these technology, and just because the technology is there, it doesn't mean you have to use it, but again, it's that educational bit, what is the right thing to do? And even the ESG awareness, people are not aware. Like now, if you go to the current TikTok trenders, they know I need to look into certified B Corp when I am buying something. The reason is because they know, and they're more passionate about saving the world. Maybe we are not, I don't know, but again, once you start educating and, telling those stories, humans are really good, so you will have a change of heart. Ula Ojiaku What I'm hearing you say is that education is key to help us to make informed choices. There is a time and place where you would need to use AI, but not everything requires it, and if we're more thoughtful in how we approach, these, because these are tools at the end of the day, then we can at least try to be more balanced in the risks and taking advantage of opportunities versus the risks around it and the impact these decisions and the tools that we choose to use make on the environment. Now, what books have you found yourself recommending most to people, and why? Bala Madhusoodhanan Because we have been talking on AI, AI Superpower is one book which was written by Kai-Fu Lee. There is this book by Brian Christian, The Alignment Problem: Machine Learning and Human Values alignment of human values and machine it was basically talking about what are the human values? Where do you want to use machine learning? How do you basically come up with a decision making, that's a really interesting read. Then there is a book called Ethical Machines by Reid Blackman. So it talks about all the ethical facets of AI, like biases, fairnesses, like data privacy, transparency, explainability, and he gives quite a detail, example and walkthrough of what that means. Another interesting book was Wanted: Human-AI Translators: Artificial Intelligence Demystified by a Dutch professor, again, really, really lovely narration of what algorithms are, what AI is, where, and all you should think about, what controls and stuff like that. So that is an interesting book. Harvard Professor Kahrim Lakhani, he wrote something called, Competing in the Age of AI, that's a good book. The Algorithmic Leader: How to Be Smart When Machines Are Smarter Than You by Mike Walsh is another good book, which I finished a couple of months back. Ula Ojiaku And if the audience wants to find you, how can they reach out to you? Bala Madhusoodhanan They can always reach out to me at LinkedIn, I would be happy to touch base through LinkedIn. Ula Ojiaku Awesome. And do you have any final words and or ask of the audience? Bala Madhusoodhanan The final word is, again, responsible use of technology. Think about not just the use case, think about the environmental impact, think about the future generation, because I think the damage is already done. So, at least not in this lifetime, maybe three or four lifetimes down the line, it might not be the beautiful earth that we have. Ula Ojiaku It's been a pleasure, as always, speaking with you, Bala, and thank you so much for sharing your insights and wisdom, and thank you for being a guest on the Agile Innovation Leaders Podcast. Bala Madhusoodhanan Thank you, lovely conversation, and yeah, looking forward to connecting with more like minded LinkedIn colleagues. Ula Ojiaku That's all we have for now. Thanks for listening. If you liked this show, do subscribe at www.agileinnovationleaders.com or your favourite podcast provider. Also share with friends and do leave a review on iTunes. This would help others find this show. I'd also love to hear from you, so please drop me an email at ula@agileinnovationleaders.com Take care and God bless!   

Join Chris Norris from Integrity Advisory Solutions and Rush Wilbanks from NLG as they dive deep into annuity products. In this episode, they discuss National Life Group's innovative offerings, highlighting the unique features of the Retire Max Secure 5, Growth Driver 10, and Income Driver 10. Discover the benefits of multi-year guaranteed annuities (MIGAs), fixed indexed annuities (FIAs), and flexible premium indexed annuities. Learn about the updated green sheet process, sales techniques, and potential market opportunities. Stay tuned for insights into customer profiles, the importance of income riders, and strategies for maximizing retirement savings. This episode is a must-watch for financial advisors looking to boost their annuity business.

Stephen Solka, CTO and co-founder of Standd.io, joins Elixir Wizards Owen and Charles to share the journey of building an AI-native deal intelligence and due diligence platform. Designed to streamline document analysis and text generation for venture capital firms, Standd.io leverages large language models and AI tools to address key customer pain points in document workflows. Stephen explains how Elixir and Phoenix LiveView enabled rapid UI iteration and seamless integration between the front-end and back-end. The conversation also explores the human side of startup life. Stephen reflects on balancing tech debt with customer demands, the value of accelerators in building networks and securing funding, and the challenges of pricing in early-stage startups. He emphasizes the importance of validating ideas with potential customers and learning from the hurdles of growing a business. Tune in for insights on leveraging AI in Elixir, solving real-world problems, and navigating the journey from concept to company. Topics discussed in this episode: The journey from self-taught programmer to CTO The perks of Phoenix LiveView for rapid UI development Integrating front-end and back-end technologies AI tools for code generation How early adopters balance functionality with product polish Validating ideas and understanding customer needs The impact of accelerators on networking and fundraising Approaches to managing pricing strategies for startups Balancing technical debt with feature development The role of telemetry and error reporting in product development Creating collaborative and supportive tech communities Educating users on AI's capabilities and limitations The broader implications of AI tools across industries Links Mentioned Contact Stephen & Julie at Standd: founders@standd.io https://www.standd.io/ https://www.digitalocean.com/community/tutorials/gangs-of-four-gof-design-patterns https://www.thriftbooks.com/w/code-completesteve-mcconnell/248753/item/15057346/ https://aws.amazon.com/sagemaker/ https://www.anthropic.com/ https://getoban.pro/ https://kubernetes.io/ https://www.apollographql.com/ https://aws.amazon.com/startups/accelerators https://accelerate.techstars.com/ https://aider.chat/ https://github.com/Aider-AI/aider https://neovim.io/ https://ui.shadcn.com/ https://tailwindui.com/ https://www.ycombinator.com/ https://www.thriftbooks.com/w/close-to-the-machine-technophilia-and-its-discontentsellen-ullman/392556 Special Guest: Stephen Solka.

- Theo Quy hoạch Điện VIII, đến năm 2030, tổng công suất các nhà máy điện chạy bằng nhiên liệu khí LNG có thể đạt 22.400 MW (chiếm ~ 26.5% so với công suất đặt thời điểm hiện tại của hệ thống điện); Công suất nguồn điện gió ngoài khơi đạt 6.000 MW (chiếm ~ 4% công suất đặt của hệ thống điện). Tuy nhiên, hiện tại vẫn chưa có các cơ chế (về sản lượng điện huy động, giá điện) để phát triển điện khí thiên nhiên trong nước, điện khí LNG hay điện gió ngoài khơi (ĐGNK). Điều này sẽ tạo ra rào cản, không thu hút được các nhà đầu tư và có nguy cơ làm chậm tiến độ các nguồn điện theo Quy hoạch Điện VIII. Thông tin được đưa ra tại toạ đàm “Luật điện lực sửa đổi: Các khoảng trống pháp lý cần được lấp đầy và bổ sung” (theo tinh thần Nghị quyết 55-NQ/TW, Kết luận 76-KL/TW của Bộ chính trị) do Hội dầu khí Việt Nam (VPA) tổ chức hôm nay (16/10/2024). Tác giả : Nguyên Long Chủ đề : Luật Điện lực (sửa đổi), PVN, Điện gió ngoài khơi, Điện khí NLG, ĐGNK --- Support this podcast: https://podcasters.spotify.com/pod/show/vov1sukien/support

The potential effectiveness of counterspeech as a hate speech mitigation strategy is attracting increasing interest in the NLG research community, particularly towards the task of automatically producing it. However, automatically generated responses often lack the argumentative richness which characterises expert-produced counterspeech. In this work, we focus on two aspects of counterspeech generation to produce more cogent responses. First, by investigating the tension between helpfulness and harmlessness of LLMs, we test whether the presence of safety guardrails hinders the quality of the generations. Secondly, we assess whether attacking a specific component of the hate speech results in a more effective argumentative strategy to fight online hate. By conducting an extensive human and automatic evaluation, we show how the presence of safety guardrails can be detrimental also to a task that inherently aims at fostering positive social interactions. Moreover, our results show that attacking a specific component of the hate speech, and in particular its implicit negative stereotype and its hateful parts, leads to higher-quality generations. 2024: Helena Bonaldi, Greta Damo, Nicolás Benjamín Ocampo, Elena Cabrio, S. Villata, Marco Guerini https://arxiv.org/pdf/2410.03466v1

As Chicago gears up for the 2024 Democratic National Convention, we get in tune with movement lawyer and professor Sheila Bedi, who breaks down some of the changes in CPD policy that Chicagoans engaging in direct action should know about. We also talk about the beautiful, challenging, and important ways Sheila has provided care and protection for both organizers facing state repression and the family members of those who have been murdered by the police. Plus, some laughs through it all! SHOW NOTES NLG HOTLINE for DNC protest legal support - (872) 465 4244 Thread of support materials from NLG - https://x.com/NLGChicago/status/1823723532783886702 Get in tune with Sheila -https://www.law.northwestern.edu/faculty/profiles/sheilabedi/ Follow AirGo - instagram.com/airgoradio Find One Million Experiments on tour! - www.respairmedia.com/events Bring us to your community by hitting us up - contact@respairmedia.com CREDITS Hosts & Exec. Producers - Damon Williams and Daniel Kisslinger Associate Producer - Rocío Santos Engagement Producer - Rivka Yeker Digital Media Producer - Troi Valles

Ralph welcomes Dr. Feroze Sidhwa, an American trauma surgeon who worked at the European Hospital in Khan Younis. They'll discuss Dr. Sidhwa's experience on the ground in Gaza, as well as his letter (co-signed by 45 other American medical practitioners) to President Biden, VP Harris, and First Lady Dr. Jill Biden. Then, Ralph is joined by University of Chicago Booth School of Business Professor Luigi Zingales to look at why business schools are setting capitalism up to fail.Dr. Feroze Sidhwa is a trauma and critical care surgeon as well as a Northern California Veterans Affairs general surgeon, and he is Associate Professor of Surgery at the California Northstate University College of Medicine. Dr. Sidhwa served at the European Hospital in Khan Younis in March and April of this year, and he has done prior humanitarian work in Haiti, the West Bank, Ukraine, and Zimbabwe. Dr. Sidhwa and 45 other American doctors and nurses who have served in Gaza recently sent a letter exhorting President Biden, VP Harris, and First Lady Dr. Jill Biden to effect an immediate ceasefire. Gaza is definitely unique compared to anywhere else that I've been—the level of violence, the level of displacement, the level of deprivation of normal things that society provides.Dr. Feroze SidhwaThere's so much in this letter, listeners, that you need to know about because it's such heartfelt and professionally documented close observation. This short interview cannot do justice to the horrors that Dr. Sidhwa and others observed—and they were just there for a few weeks. Ralph NaderOne of the things that we tried to emphasize in the letter is that we don't have anything to say about the politics of the Israel-Palestine conflict…We, as physicians, that's not what we're talking about.  We're talking about our own participation in a massive unprecedented assault on a civilian population. By a military that we fund—we supply, literally every day. We provide the training. We provide all the diplomatic cover. The economic support. Everything is coming from the United States. And in the end, the Israelis have already decided what they're going to do. They have decided to destroy Gaza. If half the people there die, oh well, if all of the people there die, oh well. But we don't have to be involved in it.Dr. Feroze SidhwaI think the situation in Gaza has reached such a level, the political moment in the U.S. with Biden not running again, has reached a certain level, and then with Netanyahu's bonker address to Congress—when Nancy Pelosi is openly criticizing the Prime Minister of Israel, he's really screwed up.Dr. Feroze SidhwaLuigi Zingales is the Robert C. McCormack Distinguished Service Professor of Entrepreneurship and Finance at the University of Chicago Booth School of Business. He co-developed the Financial Trust Index, which is designed to monitor the level of trust that Americans have toward their financial system. He is currently a faculty research fellow for the National Bureau of Economic Research, a research fellow for the Center for Economic Policy Research, a fellow of the European Governance Institute, and the director of Chicago Booth's Stigler Center for the Study of the Economy and the State. Professor Zingales is the co-host (with Bethany McLean) of the podcast Capitalisn't, and co-author (with Raghuram G. Rajan) of the book Saving Capitalism from Capitalists. These days, there is a lot of attention in business school about the environment, about so-called social responsibility, about all these aspects…but business schools like to keep separate the social aspects from the business aspects. So, in many places now there are classes on social entrepreneurship—which is something very interesting where people try to use their entrepreneurial skills to promote an initiative that is good for society at large, even if it's not necessarily profitable. But then if you are not a social enterprise, then you have to be the most capital, profit-maximizing firms on the face of the earth. There is nothing in between.Professor Luigi ZingalesOne year there was a management conference, and I organized a session on corporate fraud. And I expected a lot of people to show up and listen to the panel. In fact, it was a fiasco. Almost nobody showed up, because they don't want to confront their own limitations and problems. They want to see the more glitzy and shiny aspects of success. And that's what attracts them to business school, and that's what we end up selling to them. So I think that we are in part responsible because we cater too much to their own demand. Professor Luigi ZingalesIn Case You Haven't Heard with Francesco DeSantisNews 7/31/241. On Monday, nine Israeli soldiers were arrested on suspicion of raping a Palestinian prisoner at the Sde Teiman detention facility. In response, the Middle East Eye reports “Dozens of people…including members of parliament and Heritage Minister Amichai Eliyahu, gathered outside Sde Teiman and stormed the…facility…[and] Hours later, some 1,200 rioters gathered outside the Beit Lid base, where the nine suspects were taken for questioning.” This piece quotes military chief of staff Herzi Halevi who described the riots as “bordering on anarchy” and said the rioters harmed the military. Yet, “Finance Minister Bezalel Smotrich described the suspects as as ‘heroic warriors'…[and] National Security Minister Itamar Ben Gvir, who oversees the prisons where Palestinians are detained, called [the suspects] the ‘best heroes' and described the arrests as ‘shameful'.” One of these soldiers has now been released, according to the Middle East Monitor.2. Israeli Prime Minister Netanyahu addressed Congress last week amid mass protests in Washington D.C. During his speech, Axios reports six spectators were arrested for “disrupting” the address. All six of these demonstrators are family members of the Israeli hostages. Capitol Police spokesperson Brianna Burch is quoted saying “demonstrating in the Congressional Buildings is against the law.”3. In the U.K., the new Labour government is sending mixed messages on their Middle East policy. Late last week, the government announced that they would drop the United Kingdom's opposition to the International Criminal Court's arrest warrant against Netanyahu, per CNN. Yet this week, Foreign Secretary David Lammy announced that despite campaign promises, “Labour will…delay recognition [of a Palestinian state] indefinitely, making it conditional on Israel feeling ‘safe and secure,'” as reported by British blog Stats for Lefties. Labour continues to face pressure from independent MPs like Jeremy Corbyn on this issue.4. This week, President Nicolas Maduro was reelected in Venezuela. Elon Musk was caught spreading misinformation implying that Maduro engaged in election fraud – sharing a video that he claimed showed ballot boxes being stolen, when in fact the ballot boxes in question were actually air conditioning units, per Mediaite. The National Lawyer's Guild International Committee however, which sent a delegation to monitor the election, “observed a transparent, fair voting process with scrupulous attention to legitimacy, access to the polls and pluralism.” The NLG statement went on to decry “Despite the soundness of the electoral process, the U.S. backed opposition, with support from an anti-Maduro western press has refused to accept the results, undermining the stability of Venezuela's democracy.”5. Forbes reports that Disney has reached a deal with the unionized workers at Disneyland, ratifying a three-year contract that includes “a $24 hourly minimum wage…wage increases, seniority increases, more flexible attendance and sick leave policies, and other benefits.” This deal thus averts the first strike at the Anaheim park in four decades. Last week, More Perfect Union reported that the 14,000 unionized Disneyland workers “authorized a strike by 99%.”6. Jacobin reports “SpaceX [has won] a First Battle in Its Assault on the NLRB.” In this piece, People's Policy Project founder Matt Bruenig lays out how “SpaceX...[winning] a preliminary injunction in a Texas federal district court against the National Labor Relations Board… moves us closer to a potential Supreme Court decision declaring the NLRB unconstitutional.” This is the latest installment in the corporatist war on administrative law, which has already scored major victories in the SEC v. Jarkesy and Loper Bright Enterprises v. Raimondo cases. Bruenig notes that “For now, the district court's decision simply prevents the NLRB from processing a fairly run-of-the-mill unfair labor practice charge against SpaceX. The real question is going to be what the Supreme Court does once this case makes it to their docket. But in the meantime…it is likely that other companies subject to NLRB proceedings will seek similar injunctions.”7. A storm is brewing within the Kamala Harris campaign over Federal Trade Commission Chair Lina Khan. Democracy Now! Reports “some of the Democratic Party's biggest donors, including LinkedIn co-founder Reid Hoffman, are openly pushing Harris to fire…Khan, who has led Biden's antitrust efforts.” NBC notes that Hoffman is a billionaire megadonor and that other megadonors like Barry Diller are also calling for Khan's removal, and adds that “Khan's pro-consumer, pro-worker, anti-monopoly agenda has attracted no small amount of hate from powerful and monied interests.” On the other side, Senators Bernie Sanders and Elizabeth Warren and the Service Employees International Union – a close labor ally of Harris – have defended Khan. This battle illustrates the cross-cutting interests Harris will have to navigate as the Democratic nominee, and possibly, as president. We urge the Vice President to back Khan, not the billionaire donor class.8. The Washington Post is out with a heartbreaking new report on the increase of homelessness among “Working Americans with decent-paying jobs who simply can't afford a place to live.” This report cites data showing that homelessness, already at record highs, is only getting worse – growing by 61% in Southeast Texas over the past year, 35% in Rhode Island, and 20% in northeast Tennessee. Throughout the country, rents have risen by over 32% in four years and overall homelessness by 12%.9. In another disturbing economic trend, a new academic working paper out of UCLA and USC analyzes how the “widespread legalization of sports gambling over the past five years has impacted consumer financial health.” The most-discussed findings of this paper have to do with debt, with a “roughly 28% increase in bankruptcies and an 8% increase in debt transferred to debt collectors,” along with substantial increases in auto loan delinquencies and use of debt consolidation loans. As the researchers put it “these results indicate that the ease of access to sports gambling is harming consumer financial health by increasing their level of debt.”10. Finally, for some good news, the White House issued a statement Monday celebrating that “As of today, over 600,000 Teamster workers and retirees have pensions protected from devastating cuts,” as part of Biden's signature American Rescue Plan. This announcement came after the administration acted to protect 70,000 worker pensions in New England, building on similar actions in Ohio, Michigan, Illinois, Missouri, Wisconsin, Minnesota, and Pennsylvania. As the Boston Globe explains “The [American Rescue Plan] set up a special financial assistance program that allows struggling multi-employer pension plans to apply for assistance from the Pension Benefit Guaranty Corporation, a federal agency that protects the retirement incomes of workers in defined benefit pension plans.” The administration is paying particular attention to the protection of Teamsters, as that union's leadership has been flirting with an embrace of the GOP. Not one Republican voted for the American Rescue Plan.This has been Francesco DeSantis, with In Case You Haven't Heard. Get full access to Ralph Nader Radio Hour at www.ralphnaderradiohour.com/subscribe

Make sure you support Desire and the young ladies over at the NLG.

In the latest episode of Bring the Pain, I continue my Hometown Series by highlighting Next Level Gaming that a friend of mine came up with. Jason, who is the mastermind behind the whole shebang, talks to us about his journey through life, which ultimately led to the creation of his gaming company. Jason actually outsources into many different avenues outside of E-Sports, like birthday parties, gaming/comic conventions, and weddings. Anywhere you think gaming can be a huge part of a party, Next Level Gaming is here to fill that void with amazing entertainment. In the end, Jason talks about his huge event he had coming up called the Rust Belt Showdown pt.2, which is coming up April 20th and 21st, which is going to be held at the Days Inn Hotel at 6101 Wattsburg Road, Erie, PA. This tournament is going to feature some of the best competition not only in the Rust Belt but also outside of the tri-state area. Some of the competitors going to this event are some of the best around so if you feel like you want to test your skills amongst the best, this will be your chance.This episode was a great way to catch up with Jason and showed why he is ready to bring the next level gaming to you plus your competition. Thank you for the support and contributions all of you make for my podcasts and articles each week. Y'all the real #Painbringers! Follow Jason and Next Level Gaming at... *Facebookhttps://www.facebook.com/bookN... *Website linkhttps://booknextlevelgaming.co... *Rust Belt Showdown Pt. 2 website & Infohttps://www.start.gg/tournamen... Follow me at.... *Facebookhttps://www.facebook.com/Bring... *Twitterhttps://twitter.com/HeatOverid... *Spreakerhttps://spreaker.page.link/VS5... *Dr Roto Sports Websitehttps://drroto.com/author/robe... *You Tubehttps://youtube.com/@Heat00veride05?si=cVb49FjQD-Y6fKjTBecome a supporter of this podcast: https://www.spreaker.com/podcast/bring-the-pain--3659369/support.

We welcome Fred Schonenberg to AI Uncovered. Fred is the founder and CEO of VentureFuel. He has created an innovation framework that bridges the VC, Angel, and Startup ecosystem with enterprises to deliver tangible technology solutions that drive growth. In his role at Venture Fuel, Fred has worked with over 100 companies from General Mills to Netflix.He is a frequent speaker at industry events such as SXSW, Ad Tech, and Advertising Week and is published in broad media publications including Huffington post, Creator Magazine and Ad Week. In this episode Tim and Fred discuss generative AI and the role and collaboration between venture capital firms, startups, and enterprises. Fred has worked with over 100 companies, from General Mills to Beam Suntory to Netflix. He has helped companies discover and implement new technologies and delivered breakthrough results including an 18.7% uptick in sales , $10m+ savings, and 5x increase in purchase intent. Welcome to AI Uncovered, a podcast for technology enthusiasts that explores the intersection of generative AI, machine learning, and innovation across regulated industries. With the AI software market projected to reach $14 trillion by 2030, each episode features compelling conversations with an innovator exploring the impact of generative AI, LLMs, and other rapidly evolving technologies across their organization. Hosted by Executive VP of Product at Yseop, Tim Martin leads a global team and uses his expertise to manage the wonderful world of product.

In this episode of Elixir Wizards, Katelynn Burns, software engineer at LaunchScout, and Alexis Carpenter, senior data scientist at cars.com, join Host Dan Ivovich to discuss machine learning with Elixir, Python, SQL, and MATLAB. They compare notes on available tools, preprocessing, working with pre-trained models, and training models for specific jobs. The discussion inspires collaboration and learning across communities while revealing the foundational aspects of ML, such as understanding data and asking the right questions to solve problems effectively. Topics discussed: Using pre-trained models in Bumblebee for Elixir projects Training models using Python and SQL The importance of data preprocessing before building models Popular tools used for machine learning in different languages Getting started with ML by picking a personal project topic of interest Resources for ML aspirants, such as online courses, tutorials, and books The potential for Elixir to train more customized models in the future Similarities between ML approaches in different languages Collaboration opportunities across programming communities Choosing the right ML approach for the problem you're trying to solve Productionalizing models like fine-tuned LLM's The need for hands-on practice for learning ML skills Continued maturation of tools like Bumblebee in Elixir Katelynn's upcoming CodeBeam talk on advanced motion tracking Links mentioned in this episode https://launchscout.com/ https://www.cars.com/ Genetic Algorithms in Elixir (https://pragprog.com/titles/smgaelixir/genetic-algorithms-in-elixir/) by Sean Moriarity Machine Learning in Elixir (https://pragprog.com/titles/smelixir/machine-learning-in-elixir/) by Sean Moriarity https://github.com/elixir-nx/bumblebee https://github.com/huggingface https://www.docker.com/products/docker-hub/ Programming with MATLAB (https://www.mathworks.com/products/matlab/programming-with-matlab.html) https://elixirforum.com/ https://pypi.org/project/pyspark/  Machine Learning Course (https://online.stanford.edu/courses/cs229-machine-learning) from Stanford School of Engineering Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/) by Aurélien Géron Data Science for Business (https://data-science-for-biz.com/) by Foster Provost & Tom Fawcett https://medium.com/@carscomtech  https://github.com/k-burns  Code Beam America (https://codebeamamerica.com/) March, 2024 Special Guests: Alexis Carpenter and Katelynn Burns.

Welcome Sarah Tilly to AI Uncovered. Sarah is the Founder and Director of Azur Health Science, a regulatory writing consultancy based in France.Guided by her expertise as a member of the European Medical Writers Association (EMWA), Tim and Sarah discuss what steps are being taken to better understand the benefits of AI for medical writing. Sarah has been involved in medical writing since 2006 for a variety of companies and is the EMWA president-elect. She mentors and provides training to new medical writers and conducts regular workshops at EMWA conferences. Sara holds a degree in Biology, a Postgraduate Certificate in International Health Technology Assessment, Pricing and Reimbursement, and is completing an executive MBA with a focus in Healthcare Management. Welcome to AI Uncovered, a podcast for technology enthusiasts that explores the intersection of generative AI, machine learning, and innovation across regulated industries. With the AI software market projected to reach $14 trillion by 2030, each episode features compelling conversations with an innovator exploring the impact of generative AI, LLMs, and other rapidly evolving technologies across their organization. Hosted by Executive VP of Product at Yseop, Tim Martin leads a global team and uses his expertise to manage the wonderful world of product.

We welcome Derek Kerton to AI Uncovered. Derek is the Founder and Chairman of the Autotech Council in Silicon Valley. His work brings global car companies together with startups to drive discussion around new technologies and their possible impact on the car industry. In this episode, Derek shares his expertise with Tim, offering valuable insights into the ever-evolving landscape of automotive tech. They discuss how cars are becoming safer and more efficient using innovation. They delve into groundbreaking breakthroughs across the automotive industry over the last decade, like connected cars, autonomous driving, and the impact of the sharing economy. They then look at what how AI is affecting the car experience, and what the future might hold.Along with his work, Derek has authored over 800 articles for news outlets including Techdirt, RCR Wireless, and GigaOm. He is also the co-author of the book Going Mobile: Building the real time enterprise with mobile applications. Derek has an MBA from Cornell University and an Economics degree from the University of Waterloo. Welcome to AI Uncovered, a podcast for technology enthusiasts that explores the intersection of generative AI, machine learning, and innovation across regulated industries. With the AI software market projected to reach $14 trillion by 2030, each episode features compelling conversations with an innovator exploring the impact of generative AI, LLMs, and other rapidly evolving technologies across their organization. Hosted by Executive VP of Product at Yseop, Tim Martin leads a global team and uses his expertise to manage the wonderful world of product.

We welcome Daniel O'Mahony to AI Uncovered. Daniel is a senior manager of sales and business consulting with Körber Pharma, a pharma manufacturing software company. Along with his work at Körber, Dan lectures with the national institute of bioprocessing research and training and at the Atlantic Technical University covering topics like BioPharma 4.0 and digital transformation. In this episode, Tim and Dan look at the impact of AI on the pharmaceutical manufacturing processes and the delicate balance between digital transformation, risk, and productivity gains in life sciences. They discuss why Ireland has been a hub for manufacturing and pharmaceutical growth over the last 60 years. Next, they dig into the digital transformation happening in drug manufacturing, the role of AI on the process, and the future of personalized drugs. Dan has a masters degrees in bioprocessing from Atlantic Technical University and in Pharmaceutical business and technology from Griffith College. He is based in Dublin, Ireland. Welcome to AI Uncovered, a podcast for technology enthusiasts that explores the intersection of generative AI, machine learning, and innovation across regulated industries. With the AI software market projected to reach $14 trillion by 2030, each episode features compelling conversations with an innovator exploring the impact of generative AI, LLMs, and other rapidly evolving technologies across their organization. Hosted by Executive VP of Product at Yseop, Tim Martin leads a global team and uses his expertise to manage the wonderful world of product.

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Cloud ML, On-Premise, Edge Device, Machine Learning -as-a-Service (MLaaS), explain how these terms relates to AI and why it's important to know about them. Show Notes: FREE Intro to CPMAI mini course CPMAI Training and Certification AI Glossary Glossary Series: Training Data, Epoch, Batch, Learning Curve Glossary Series: (Artificial) Neural Networks, Node (Neuron), Layer Glossary Series: Bias, Weight, Activation Function, Convergence, ReLU Glossary Series: Perceptron Glossary Series: Hidden Layer, Deep Learning Glossary Series: Loss Function, Cost Function & Gradient Descent Glossary Series: Backpropagation, Learning Rate, Optimizer Glossary Series: Feed-Forward Neural Network Glossary Series: OpenAI, GPT, DALL-E, Stable Diffusion Glossary Series: Natural Language Processing (NLP), NLU, NLG, Speech-to-Text, TTS, Speech Recognition AI Glossary Series – Machine Learning, Algorithm, Model AI Today Podcast: AI Glossary Series – Batch Prediction, Microservice, Real-time Prediction, Stream Learning, Cold-Path Analytics, Hot-Path Analytics This episode is sponsored by Algolia: Algolia Powers Discovery. Continue reading AI Today Podcast: AI Glossary Series – Cloud ML, On-Premise, Edge Device, Machine Learning -as-a-Service (MLaaS) at AI & Data Today.

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Batch Prediction, Microservice, Real-time Prediction, Stream Learning, Cold-Path Analytics, and Hot-Path Analytics, explain how these terms relate to AI and why it's important to know about them. Show Notes: FREE Intro to CPMAI mini course CPMAI Training and Certification AI Glossary Glossary Series: Training Data, Epoch, Batch, Learning Curve Glossary Series: (Artificial) Neural Networks, Node (Neuron), Layer Glossary Series: Bias, Weight, Activation Function, Convergence, ReLU Glossary Series: Perceptron Glossary Series: Hidden Layer, Deep Learning Glossary Series: Loss Function, Cost Function & Gradient Descent Glossary Series: Backpropagation, Learning Rate, Optimizer Glossary Series: Feed-Forward Neural Network Glossary Series: OpenAI, GPT, DALL-E, Stable Diffusion Glossary Series: Natural Language Processing (NLP), NLU, NLG, Speech-to-Text, TTS, Speech Recognition AI Glossary Series – Machine Learning, Algorithm, Model AI Glossary Series – Model Tuning and Hyperparameter AI Glossary Series: Overfitting, Underfitting, Bias, Variance, Bias/Variance Tradeoff AI Glossary Series: Operationalization Interview with Alex Measure, BLS This episode is sponsored by Algolia: Algolia Powers Discovery. Continue reading AI Today Podcast: AI Glossary Series – Batch Prediction, Microservice, Real-time Prediction, Stream Learning, Cold-Path Analytics, Hot-Path Analytics at AI & Data Today.

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Operationalization, explain how this term relates to AI and why it's important to know about them. Show Notes: FREE Intro to CPMAI mini course CPMAI Training and Certification AI Glossary Glossary Series: Training Data, Epoch, Batch, Learning Curve Glossary Series: (Artificial) Neural Networks, Node (Neuron), Layer Glossary Series: Bias, Weight, Activation Function, Convergence, ReLU Glossary Series: Perceptron Glossary Series: Hidden Layer, Deep Learning Glossary Series: Loss Function, Cost Function & Gradient Descent Glossary Series: Backpropagation, Learning Rate, Optimizer Glossary Series: Feed-Forward Neural Network Glossary Series: OpenAI, GPT, DALL-E, Stable Diffusion Glossary Series: Natural Language Processing (NLP), NLU, NLG, Speech-to-Text, TTS, Speech Recognition AI Glossary Series – Machine Learning, Algorithm, Model For more information on visit Algolia website FREE CPMAI Intro Course Glossary Series: Natural Language Processing (NLP), NLU, NLG, Speech-to-Text, TTS, Speech Recognition Glossary Series: Tokenization, Vectorization This episode is sponsored by Algolia: Algolia Powers Discovery. Continue reading AI Today Podcast: AI Glossary Series – Operationalization at AI & Data Today.

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Digital Transformation, Return on Investment (ROI), and Key Performance Indicator (KPI), explain how these terms relate to AI and why it's important to know about them. Show Notes: FREE Intro to CPMAI mini course CPMAI Training and Certification AI Glossary For more information on visit Algolia website Glossary Series: Natural Language Processing (NLP), NLU, NLG, Speech-to-Text, TTS, Speech Recognition Glossary Series: Tokenization, Vectorization This episode is sponsored by Algolia: Algolia Powers Discovery. Continue reading AI Today Podcast: AI Glossary – Digital Transformation, Return on Investment (ROI), Key Performance Indicator (KPI) at AI & Data Today.

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Confusion Matrix, Accuracy, Precision, F1, Recall, Sensitivity, Specificity, Receiver-Operating Characteristic (ROC) Curve, explain how these terms relate to AI and why it's important to know about them. Show Notes: FREE Intro to CPMAI mini course CPMAI Training and Certification AI Glossary Glossary Series: Training Data, Epoch, Batch, Learning Curve Glossary Series: (Artificial) Neural Networks, Node (Neuron), Layer Glossary Series: Bias, Weight, Activation Function, Convergence, ReLU Glossary Series: Perceptron Glossary Series: Hidden Layer, Deep Learning Glossary Series: Loss Function, Cost Function & Gradient Descent Glossary Series: Backpropagation, Learning Rate, Optimizer Glossary Series: Feed-Forward Neural Network Glossary Series: OpenAI, GPT, DALL-E, Stable Diffusion Glossary Series: Natural Language Processing (NLP), NLU, NLG, Speech-to-Text, TTS, Speech Recognition AI Glossary Series – Machine Learning, Algorithm, Model AI Glossary Series – Model Tuning and Hyperparameter AI Glossary Series: Overfitting, Underfitting, Bias, Variance, Bias/Variance Tradeoff Glossary Series: Classification & Classifier, Binary Classifier, Multiclass Classifier, Decision Boundary Continue reading AI Today Podcast: AI Glossary Series – Confusion Matrix, Accuracy, Precision, F1, Recall, Sensitivity, Specificity, Receiver-Operating Characteristic (ROC) Curve at AI & Data Today.

We welcome Gregor Mittersinker to AI Uncovered. Gregor is the founder and creative director at Loft. Loft focuses on product development and design with a specialty in building large product ecosystems.  In this episode, Tim and Gregor dive deep into UX and design. They discuss how LLMs, like ChatGPT, have impacted UI design, specifically around conversational UI and prompt interfaces. They evaluate how industry specific applications might use a variety of UI techniques to deal with the nuances of AI in the future.Gregor brings over 30 years of experience to product development and design. He holds over 100 patents and has worked with brands such as Bose, 3M, Dell, Square and Segate. Gregor has a BA and MA from the Technical University Vienna and University of Applied arts in Vienna. Gregor is currently an adjunct professor at the RISD (Rhode Island School of Design).Welcome to AI Uncovered, a podcast for technology enthusiasts that explores the intersection of generative AI, machine learning, and innovation across regulated industries. With the AI software market projected to reach $14 trillion by 2030, each episode features compelling conversations with an innovator exploring the impact of generative AI, LLMs, and other rapidly evolving technologies across their organization. Hosted by Executive VP of Product at Yseop, Tim Martin leads a global team and uses his expertise to manage the wonderful world of product.

It's time to end our seventh season and what better way than to answer some of your questions! We've had a wide variety come in and tackle a number of them in today's episode. Here are some of the questions we look at.I never legally adopted my spouse's kids from a previous marriage, but I love them like my own. Will I lose the right to see them?What happens if divorce is against my/my spouse's religion?My spouse is threatening suicide if I leave. What do I do?What if I can't be in the same room as my ex because of PTSD? How is this handled in court?I have a shady/questionable past but I've totally cleaned up my act, but my ex is threatening to use my past against me to get full custody of the kids. He has old videos, proof etc. Am I screwed?My ex is threatening to publicly post embarrassing photos/content about me if I divorce them. Is there a legal action I can take to prevent this?I found out my ex is a bigamist and has spouses in other states. Are we really married? How does the court handle this?Assuming most divorces are the same or fall into similar categories, what qualifies as an exceptional or unusual/unique divorce?My spouse took off and I can't find them to divorce them.Lots of great information in today's episode. We'll have a few rebroadcasts after this episode, followed by some conversations with other attorneys at NLG before we kick off season eight in August. In the meantime, keep those listener questions coming!Links & NotesSchedule a consult with SethGot a question you want to ask on the show? Click here! (00:00) - Welcome to How to Split a Toaster (03:02) - Mail Bag! (03:37) - Question 1 (05:47) - Question 2 (06:09) - Question 3 (08:04) - Question 4 (11:15) - Question 5 (12:30) - Question 6 (13:46) - Question 7 (18:00) - Question 8 (21:22) - Question 9 (24:56) - Wrap Up Establishing trust with Co-Parents can be difficult when alcohol abuse is involved. Use Soberlink as an opportunity to improve co-parenting arrangements. Visit their site to learn more and get a promo code for $50 off.

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms CPU, GPU, TPU, and Federated Learning, explain how these terms relate to AI and why it's important to know about them. Show Notes: FREE Intro to CPMAI mini course CPMAI Training and Certification AI Glossary Glossary Series: Artificial Intelligence AI Glossary Series – Machine Learning, Algorithm, Model Glossary Series: (Artificial) Neural Networks, Node (Neuron), Layer Glossary Series: Natural Language Processing (NLP), NLU, NLG, Speech-to-Text, TTS, Speech Recognition Continue reading AI Today Podcast: AI Glossary Series – CPU, GPU, TPU, and Federated Learning at AI & Data Today.

Join David Staley and Reid Wicoff in this episode of the Digible Dudes podcast as they sit down with Victor Dozal.  The trio dive deep into the world of AI, exploring the trend of generative AI and natural language processing, and discussing Digible's background in natural language generation (NLG). Victor shares his insights into the different applications and use cases that should be considered when using Chat-GPT. David, Reid, and Victor delve into the careful considerations businesses need to keep in mind when using Chat-GPT, and the accuracy and trustworthiness of AI platforms. They also touch upon whether the government should intervene in AI advancement, and whether Chat-GPT and Auto-GPT will change the world. The trio explores the impact of AI on the workforce and productivity, with a focus on the real estate and multifamily industries. Finally, the episode concludes with a discussion on how businesses can use AI to increase workforce productivity. If you enjoy this podcast, please leave a 5 star rating on Spotify and a review on Apple podcasts. Digible: https://digible.com/  Fiona: https://www.myfiona.com//  Leave a Spotify Review: https://spoti.fi/3LfoEdU  Leave an Apple Review: https://apple.co/3AA2zRj  (00:00) Preview (00:50) Learn about Victor Dozal's Background  (04:25) The Trend of Generative AI and Natural Language Processing: What You Need to Know (05:36) Discover Digible's Background in Natural Language Generation (NLG) (09:15) Applications and Use Cases: How to Leverage Chat-GPT's Potential (12:30) Careful Considerations When Using Chat-GPT: What You Should Know (16:50) Accuracy and Trustworthiness of Chat-GPT and Other AI Platforms: Insights to Know (18:55) Government Intervention with AI Advancement: Pros and Cons (21:00) Chat-GPT and Auto-GPT: Can They Change the World as We Know It? (24:17) The Impact of AI on the Workforce: Will it Reduce Jobs or Boost Productivity? (29:00) The Role of AI in Real Estate and Multifamily: Benefits and Opportunities (32:00) Enhancing Productivity with AI: How to Implement in Your Workforce

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Tokenization and Vectorization, explain how these terms relates to AI and why it's important to know about them. Show Notes: FREE Intro to CPMAI mini course CPMAI Training and Certification AI Glossary Glossary Series: Artificial Intelligence AI Glossary Series – Machine Learning, Algorithm, Model Glossary Series: (Artificial) Neural Networks, Node (Neuron), Layer Glossary Series: Natural Language Processing (NLP), NLU, NLG, Speech-to-Text, TTS, Speech Recognition Continue reading AI Today Podcast: AI Glossary Series – Tokenization and Vectorization at AI & Data Today.

We welcome Marjo Gazak to AI Uncovered. Marjo is a life sciences expert with over 22 years of experience in drug development, regulatory submissions, document development innovation and data mining systems. Tim and Marjo discuss a wide range of topics, from the emergence of automation in the drug delivery process to the future role of generative AI in helping this regulated industry get drugs to market faster.  Marjo has worked at Eli Lilly and more recently at FibroGen, where she is the Senior Director in Regulatory Affairs and Medical Writing. She has BS and MS degrees in Zoology from Clemson University and a PHD in Aquatic Toxicology from Louisville. Welcome to AI Uncovered, a podcast for technology enthusiasts that explores the intersection of generative AI, machine learning, and innovation across regulated industries. With the AI software market projected to reach $14 trillion by 2030, each episode features compelling conversations with an innovator exploring the impact of generative AI, LLMs, and other rapidly evolving technologies across their organization. Hosted by Executive VP of Product at Yseop, Tim Martin leads a global team and uses his expertise to manage the wonderful world of product.

Are you looking for ways to streamline your underwriting process? Look no further than this week's product call, hosted by Devon Martin from NLG. Devon will be introducing their new Business & Underwriting system, and providing valuable insights on how to communicate effectively to get your cases issued faster.

The second episode features a conversation with Emmanuel Walckenaer, CEO of Yseop. Yseop is reimagining the future of scientific writing through generative AI. The company's mission is to get medicine into the hands of those who need it, faster.Tim and Emmanuel shares insights on the state of natural language generation (NLG) today and the roots of the technology. They discuss how generative AI is automating parts of the clinical document landscape and why the tech is helping scientific writers be more productive. Welcome to AI Uncovered, a podcast for technology enthusiasts that explores the intersection of generative AI, machine learning, and innovation across regulated industries. With the AI software market projected to reach $14 trillion by 2030, each episode features compelling conversations with an innovator exploring the impact of generative AI, LLMs, and other rapidly evolving technologies across their organization. Hosted by Executive VP of Product at Yseop, Tim Martin leads a global team and uses his expertise to manage the wonderful world of product.

In episode 102, Jeff Coyle of MarketMuse stops by to discuss the past, present, and future of Natural Language Generation (NLG) content for SEO.Jeff shares his thoughts on how long it might be before we see consistency in the factual accuracy and quality of NLG outputs and how important content quality is within search rankings.We also chat about how Google can keep up with competitors in the AI space and if their current approach is the right one.(0:00) Intro(1:45) The History of NLG for Content Marketing(16:25) Content Quality(21:34) Can Google Keep Up?(30:08) The Present & Future of NLG for Content(34:45) How Far Away Are We From Reliable NLG Outputs?(40:15) How to Future Proof Your SEO Strategy & Content

What connects the disruptive protests against a conservative judge's speech to Stanford Law and the arrests of over two dozen demonstrators outside Atlanta? Both involved people aligned with the National Lawyers Guild, a radical-left association of attorneys, law students, legal workers, and jailhouse lawyers. Joining me to discuss the NLG is our colleague Robert Stilson, […]

What connects the disruptive protests against a conservative judge's speech to Stanford Law and the arrests of over two dozen demonstrators outside Atlanta? Both involved people aligned with the National Lawyers Guild, a radical-left association of attorneys, law students, legal workers, and jailhouse lawyers. Joining me to discuss the NLG is our colleague Robert Stilson, who has written and researched extensively on the history of the Guild. Links: https://capitalresearch.org/article/national-lawyers-guild-part-1/ https://www.influencewatch.org/non-profit/national-lawyers-guild/ https://www.influencewatch.org/non-profit/national-lawyers-guild-foundation/ https://www.wsj.com/articles/atlanta-cop-city-attacks-georgia-police-training-site-63c4cf40 https://www.wsj.com/articles/struggle-session-at-stanford-law-school-federalist-society-kyle-duncan-circuit-court-judge-steinbach-4f8da19e?mod=article_inline Follow us on our Socials: Twitter: @capitalresearch Instagram: @capitalresearchcenter Facebook: www.facebook.com/capitalresearchcenter YouTube: @capitalresearchcenter

Common Misconceptions in Divorce? Yeah, There Are Just a Few...Last week, we read a note from a listener asking to clear up some common misconceptions in the world of divorce. Today, we've invited Sterling Lovelady, one of the attorneys from the offices of NLG, to join Seth and Pete in a conversation clearing up some of these many misconceptions.Some of the misconceptions they address in today's episode include:The moms always get custodyLegal separation is always the first step to getting a divorceI had the job so I get the retirement moneyCheating spouses will be punishedMarital assets and debts are split 50/50You can withhold visitation rights if the other parent fails to pay child supportAnd more. Tune in for this response to one of our listeners who had some of these very questions. Likely, you may have some of the same!Links & NotesFollow Sterling on InstagramSchedule a consult with SethGot a question you want to ask on the show? Click here! (00:00) - Welcome to How to Split a Toaster (00:26) - Meet Sterling Lovelady (01:30) - Common Misconceptions (03:16) - if I buy a car in my name, then it's not marital property even if I'm married (04:51) - If I own my own business, I can just stop paying myself to avoid child support (06:32) - I'm easily going to be able to get sole custody of my kids (07:46) - mom always gets custody (09:23) - the parent who gets custody of the children will not be able to leave the state without the permission of the other parent (11:12) - I'm entitled to an attorney in my divorce just like in criminal law (13:25) - I don't need a lawyer (14:34) - I Can File for Divorce Whenever/Wherever I Like (16:29) - legal separation is the first step in getting a divorce (18:21) - No-Fault Divorce Is Faster and Cheaper (21:24) - Cheating Spouses Will Be Punished (21:46) - At the End of a Case, All Inequities Will Be Adjusted (24:12) - a common law marriage is the same thing is a regular marriage (26:57) - Sponsor: Soberlink (29:25) - I Can Always Reopen the Divorce Settlement at a Later Time (30:48) - YOU CAN WITHHOLD VISITATION IF THE OTHER PARENT FAILS TO PAY CHILD SUPPORT. (31:56) - YOU CANNOT GET A DIVORCE IF THE OTHER SPOUSE DOES NOT WANT THE DIVORCE. (34:55) - Dismissal vs. Annullment (37:50) - YOU CAN ONLY GET A DIVORCE IN THE STATE WHERE YOU GOT MARRIED. (38:37) - I had the job so I get the retirement money (39:20) - Only women get alimony (40:21) - Spouses Who Make Less Money or Who Were the Stay-at-Home Parent Are Entitled to Alimony (42:49) - you will not be able to get alimony because you are married less than ten years (44:18) - Is Mediation Mandatory or a Choice (45:44) - Is it Possible I Could Say the Wrong Thing in Mediation? (48:04) - if you leave the marital home, it is considered to be abandoned by you. (51:15) - If I just tell the judge my story... (52:39) - Grandparents' Rights (53:35) - Lawyers are the problems (55:17) - I have 50/50 custody, I shouldn't be paying child support. (57:07) - Sterling on Instagram (59:49) - Wrap Up

The first episode features a conversation with Craig Vachon, CEO of AI Redefined (AIR) and Head of US Operations at NextStage AM. Craig is an angel investor, author, TED speaker, and chairman of Yseop. Tim and Craig discuss the AI landscape as it exists today and then go into the benefits and limitations of ChatGPT and LLMs, especially for more regulated industries. They touch on some of the challenges involved with AI startups, advice for entrepreneurs, and practical considerations of rolling out AI technology to customers. Welcome to AI Uncovered, a podcast for technology enthusiasts that explores the intersection of generative AI, machine learning, and innovation across regulated industries. With the AI software market projected to reach $14 trillion by 2030, each episode features compelling conversations with an innovator exploring the impact of generative AI, LLMs, and other rapidly evolving technologies across their organization. Hosted by Executive VP of Product at Yseop, Tim Martin leads a global team and uses his expertise to manage the wonderful world of product.

Welcome to AI Uncovered, a podcast for technology enthusiasts that explores the intersection of generative AI, machine learning, and innovation across regulated industries. With the AI software market projected to reach $14 trillion by 2030, each episode features compelling conversations with an innovator exploring the impact of generative AI, LLMs, and other rapidly evolving technologies across their organization. Hosted by Executive VP of Product at Yseop, Tim Martin leads a global team and uses his expertise to manage the wonderful world of product.

Welcome back to How AI Built This, the show dedicated to data and entrepreneurial story telling. This episode I spoke to Ross Turner, The Chief Product Officer at Natural Language Generation specialists Arria. Ross is Berlin based, working remotely for a now global team at Arria, where they are at the cutting edge of NLG. We had a great chat about his journey, NLG, data in general and of course, some non-data related content, this time in the form of Mixed Martial Arts (MMA)! I hope you enjoy! As always, we're brought to you by the wonderful people at Cathcart Technology, recruitment experts & Infer who are building the next generation of analytics. Music by Noisyfilter from Fugue

No matter what Little Bird Momma and CEO, Priscilla McKinney, and Executive VP, Ashley Le Blanc do, they somehow end up writing. If you're working on writing posts on LinkedIn, blogs or books, get ready for four applicable tips from these seasoned veterans to make writing that much easier for you.  You know Priscilla is a straight shooter who doesn't shy away from tackling the big issues. In this episode, she delves into the world of ChatGPT, OpenAI, and the impact of NLP and NLG on business and branding. While she sees the potential for these tools to revolutionize the way we work, she also highlights some key concerns. For example, the lack of SEO integration in these systems can harm your online visibility, and using the same generated content as others can lead to plagiarism and a drop in page ranking. Additionally, the impersonal nature of these tools can detract from your brand's unique voice and style, and raises questions about the impact on thought leadership. Tune in to hear Priscilla's candid take on these cutting-edge technologies.  Enough about ChatGPT and AI already? On to the tips! Allow yourself the gift of the shitty first draft (SFD) as coined by Ann Lamott. Have you ever heard of the SFD? That shitty first draft is exactly what you need to write to beat procrastination and beat perfectionism. Perfectionism is the leading cause of writers' block and it's the enemy of writers! Don't keep waiting for inspiration. If you wait for the day that grand ol' magnificent and majestic inspiration pays a visit, you might be waiting for a long time. Waiting a long time means wasting a lot of time. Try to draw inspiration from your everyday experiences, from the mundane, from your drive to work and from your sock drawer! You make inspiration happen. Outwrite self-doubt. What if you just started calling yourself a writer? What if you started writing every day? Rather than basking in another self-doubt party, where it's just you and a blank page… write, write, and write some more. Don't be boring. Be creative. Be descriptive. See the world with new eyes. Try to describe things in such great staggering detail that your words come to life on the page. And then, after your first few drafts, we're sure you'll be cutting nearly half of all your descriptions, but still. It's worth spending time noodling over the descriptions and breathing life into your words. Marketing and content marketing is complicated. That's why you need a system. Have you heard about our SOAR system and even about our SOAR DIY offerings? Consider it the ultimate flight plan.  What's next for you? For business professionals, mastering social media is no longer a “nice to have” set of skills, but a fundamental need in order to advance your career. You need an effective and proven system to move from social selling all the way to digital dominance. Learn more here. Books discussed on the podcast: Bird by Bird by Anne Lamott The Obstacle is the Way by Ryan Holiday The Gifts of Imperfection by Brené Brown  On the Night You Were Born by Nancy Tillman Shoutout to our sponsor: Ag Access!  Uncovering insights in the agricultural industry can seem like looking for a needle in a haystack. Luckily, Ag Access has your back. From recruitment and survey design to planning and execution of custom full-service market research projects, you can count on Ag Access to deliver expertise and meaningful outcomes. Our 400,000+ member community covers the breadth of the agriculture chain, including technology, ag sales, crop growers, livestock producers, feed supply and more. With a full-time engagement center, research logistics team, and 400,000 member-strong insights community, Ag Access is an irreplaceable bridge between researchers and professionals in the agriculture industry. Visit ag-access.com to learn more. 

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define Natural Language Processing (NLP), Natural Language Understanding (NLU), Natural Language Generation (NLG), Speech-to-Text, Test-to-Speech, and (Automated) Speech Recognition. We share how these terms are related and how they fit into AI. Show Notes: FREE Intro to CPMAI mini course CPMAI Training and Certification AI Glossary AI Glossary Series – Content Summarization & Analysis, Sentiment Analysis AI Glossary Series – Conversational Systems, Chatbots, Voice Assistants, Machine Translation AI Today Podcast #104: Patterns of AI – Conversation / Human Interaction Continue reading AI Today Podcast: AI Glossary Series: Natural Language Processing (NLP), NLU, NLG, Speech-to-Text, TTS, Speech Recognition at Cognilytica.

Le président de la Fédération française de football Noël Le Graët a accordé un long entretien à RTL après la victoire de l'équipe de France face à l'Australie (4-1) pour son entrée dans la Coupe du monde au Qatar. "Vraiment heureux" pour Olivier Giroud, l'homme de 80 ans espère que l'attaquant de 36 ans "va en mettre un ou deux autres" et deviendra "le meilleur buteur de tout les temps" en équipe de France devant Thierry Henry. À propos de Kylian Mbappé, "NLG" relève que "dès qu'il a la balle, il se passe quelque chose. On sent un frisson dans les tribunes. C'est un surdoué (...) Il a vraiment envie de faire une grande coupe du monde". Concernant le forfait de Karim Benzema, "c'est une énorme déception parce qu'il avait dans la tête préparé cette compétition (...) Il sait que la Coupe du monde pour lui ça va être extrêmement difficile". Le Graët dresse aussi des éloges à Didier Deschamps, un "énorme entraîneur", "rassurant, régulier, loyal, honnête".

Meet Your ParalegalIn today's episode, Seth invited Stacy Recinella, one of the paralegals from his firm, to join the show. The conversation allows Seth and Pete to discuss the role of the paralegal with the intention of giving you insight into what the paralegal will do for you, how they're connected to your case, what sorts of things they take care of, and why your paralegal should be your new best friend on your own case.More About StacyWith over 11 years experience, Stacy has been working as a paralegal exclusively in the area of Family Law since 2013. She is naturally inquisitive and enjoys utilizing her analytical and critical thinking skills to provide detailed support to attorneys and clients. She has worked for firms in Missouri, Georgia, and now Florida. As a part of NLG, Stacy will support attorneys and clients through the gathering of information, facts and evidence, engage in client conversations, communicate with courts and other legal firms and provide the foundational support in preparing for a trial and/or hearing. Her ability to help clients navigate through an often times overwhelming process with compassion and understanding is one of the most rewarding aspects of her job. Stacy truly understands what the firm's clients are experiencing, as she went through a four-year, highly-contested divorce with minor children which ended in 2014. Two months ago, Stacy moved to Tampa with her husband, Kevin, and began working as a paralegal with NLG. In addition to having blended family of four children, a daughter-in-law, and one grandchild (with another due in early 2023), Stacy and Kevin have two dogs, one cat and a blue-and-gold Macaw. She loves the Florida weather, spending the day at the beach or by the pool, and having an active lifestyle.Links & NotesNelson Law GroupStacy on LinkedIn and FacebookSchedule a consult with SethGot a question you want to ask on the show? Click here! (00:00) - Welcome to How to Split a Toaster (00:26) - Meet Paralegal Stacy Recinella (02:19) - What Is a Paralegal? (05:08) - The Draw (07:16) - Things They Do (13:15) - Expectations and Roles (16:24) - Sponsor: Soberlink (18:48) - More Than a Junior Lawyer (24:35) - When They Get Involved (26:49) - Back End (27:48) - Ratio (30:57) - Last Thoughts (34:09) - Wrap Up

Episode Sponsor: --- This episode's Community Champion Sponsor is Salesforce. Salesforce believes the future of health is connected, do you? Learn more at https://www.salesforce.com/resources/healthcare-life-sciences/business-of-health/?d=7013y000002pgpNAAQ&nc=7013y000002pgpIAAQ&utm_source=direct-search&utm_medium=organic_social&utm_campaign=us_ihls&utm_content=business-of-health-hub_7013y000002pgpNAAQ&utm_term=&soc=us_direct-search (www.salesforce.com/businessofhealth) Hear from Kevin Riley, Salesforce's Chief Customer Officer, on this podcast: https://player.captivate.fm/episode/fefeb2b9-b848-4e52-8289-20a45ba4ae21 (CLICK HERE) --- Episode Overview:  In today's life sciences environment, developing and approving new drugs can take upwards of twelve to 15 years. One significant reason for these arduous processes and timelines is the lack of automation and artificial intelligence integration. Our next guest and his company are poised to change the game!  Emmanuel Walckenaer, CEO of Yseop, joins us to discuss his journey of becoming the CEO and how his company specializes in artificial intelligence and natural language processing to help pharmaceutical companies adopt modern technology solutions and bring their life-saving therapeutics to market faster.  Join us to learn how Emmanuel and Yseop team free time and money in the life sciences space with their company's intelligent automation. Let's go! Episode Highlights: Emmanuel's journey on becoming the CEO of Yseop How Yseop was pulled into the pharmaceutical industry with one phone call What is CSR, its importance to healthcare, and how Yseop is automating it   Emmanuales's vision of AI and automation in the years to come    About our Guest:  Emmanuel joined Yseop as CEO in 2017, leading the company's growth and vision to bring the benefits of automation and NLG to enterprise companies globally. He brings over 25 years of international experience in high-tech service and business development. Emmanuel joined Yseop in 2017 from Sierra Wireless, where he was General Manager and Senior Vice President of the Cloud & Connectivity Services business unit. He led the growth of this unit across Europe and North America through strategic acquisitions and the development of a bespoke cloud and connectivity offering for the expanding Internet of Things (IOT) market. Before joining Sierra Wireless, Emmanuel was Senior Vice President at Gemalto where he was responsible for the development of global Telecom business services. He had previously held various positions with Esso across IT and business development. Links Supporting This Episode: Yseop website: https://www.yseop.com/ (CLICK HERE) Emmanuel Walckenaer LinkedIn page: https://www.linkedin.com/in/emmanuelwalckenaer/ (CLICK HERE) Emmanuel Walckenaer Twitter page: https://twitter.com/EWalckenaer (CLICK HERE) Clubhouse handle: @mikebiselli Mike Biselli LinkedIn page: https://www.linkedin.com/in/mikebiselli (CLICK HERE) Mike Biselli Twitter page: https://twitter.com/mikebiselli (CLICK HERE) Visit our website: https://www.passionatepioneers.com/ (CLICK HERE) Subscribe to newsletter: https://forms.gle/PLdcj7ujAGEtunsj6 (CLICK HERE) Guest nomination form: https://docs.google.com/forms/d/e/1FAIpQLScqk_H_a79gCRsBLynkGp7JbdtFRWynTvPVV9ntOdEpExjQIQ/viewform (CLICK HERE)

In this week's episode, Florian and Esther discuss the language industry news of the week, with various natural language generation (NLG) startups gaining traction of late. Esther covers whether these NLG startups, which can help content creators write copy in multiple languages, are a threat or an opportunity for LSPs.Over in Europe, the strike at the European Parliament among interpreters continues, as they decline to interpret for those that dial-in remotely. Among the complaints, poor sound quality and a heavier workload. As negotiations between European Parliament staff interpreters and the administration collapse, efforts have been made to get European Parliament President, Roberta Mesilla, involved.In M&A news, Lionbridge is set to acquire Game Tester, a game-testing platform based in Australia and South Africa. This will be the third games-related acquisition for the Super Agency in three years and will allow them to add community-based testing capabilities to the Lionbridge Games division.Meanwhile, Airbnb becomes even more multilingual as it expands its machine translation capabilities to translate reviews. This move comes after the company successfully launched its messaging feature this summer. Airbnb currently runs on ModernMT, the Translated-led, open-source project, co-founded by Fondazione Bruno Kessler and the European Commission.

Who are the “Legal Observers” in green caps and vests who appear whenever the Left is engaged in a public demonstration? They are probably members of the National Lawyers Guild, a radical-left association of attorneys, law students, legal workers, and jailhouse lawyers. Joining me to discuss the NLG is my colleague Robert Stilson, who recently wrote an in-depth history of the group for InfluenceWatch and CapitalResearch.org. Links: https://www.influencewatch.org/non-profit/national-lawyers-guild/ https://www.influencewatch.org/non-profit/national-lawyers-guild-foundation/ Follow our socials: • Facebook: https://www.facebook.com/capitalresearchcenter • Twitter: https://twitter.com/capitalresearch • Instagram: https://www.instagram.com/capitalresearchcenter • YouTube: https://bit.ly/CRCYouTube • Rumble: https://rumble.com/capitalresearch • Gettr: https://gettr.com/user/capitalresearch

In episode 73, Cindy Krum of MobileMoxie explains her understanding of entities, entity-first indexing, and how it impacts search engine result pages.She provides insights into how organic results are showing up less in search due to Google's increase in search enhancement, rich features, advertisements, and context menus.[0:00] Intro[0:55] What is Entity First Indexing?[6:49] Why Entities are so important[9:45] Inclusivity in culture and language[11:14] Nuance in Entities[12:18] Thoughts on Zero Click[15:29] Can businesses depend on organic search?[18:15] NLG content[19:51] How to predict Google[21:21] MobileMoxie Chrome extensions[32:57] Moxie Scores[36:31] Rapid Fire Rankings

In this The Faces of Business Episode, our guest Andrew Lavoie talks about manufacturing hiring challenges. Andrew is the President of NLG as well as the President of East Coast Accounting Solutions in Charlottetown, Prince Edward Island, Canada. Next Level Group (NLG) helps SMB manufacturing companies increase productivity, profitability, & employee engagement by hiring “rockstars”.  ECA offers a wide range of professional accounting services to assist clients in building a strong financial future.      The conversation of this episode started with Andrew sharing how he got into the Manufacturing Industries. They talk about solving manufacturing hiring challenges.      Thanks for taking the time to listen today.   View our blog page for this episode here.   Find Damon Pistulka on LinkedIn talking about life & building businesses you can sell or succeed.    On Twitter as @dpistulka with inspiration and sharing thoughts.    Find out more about Damon when he's not working.  @dpistulka on Instagram, or Damon Pistulka on Facebook.      More information on building businesses you can sell or succeed and the Exit Your Way method on our website     Email us for more information info@exityourway.com

Card Grading | COMICS and MORE! | All C's Collector's Edition Ep 147 Guest Austin Adams COO of NLG. Bringing you the latest and hottest in collecting news, sports, and entertainment.   Connect with ALL C's Collectibles on Social Media: FB: https://www.facebook.com/AllCsCollectiblesInc TW: @allcscolorado IG: @allcscollectibles   #comics #podcast #wrestling #marvelcomics #diamondcomics #dccomics #collecting #toddmcfarland #spiderman300 #boxbreak #allcscollectibles #ksproductions #footballcards #cardbreaks #donruss #milehighsports #allcsgamingarena #podcastnation #wrestlingnews #comiccon #fanexpo #allcsfanexpo #coins #goldandsilver #markets

Wusstest du, dass im Jahr 2016 eine künstliche Intelligenz fast einen Literaturpreis in Japan gewonnen hat? Genau darum geht's heute: Synthetische Medien; Texte, die von Computern geschrieben werden. Wie groß ist die Business Opportunity?///Die besten Job-Angebote der ambitioniertesten Start-Ups: http://www.digitaleoptimisten.de/jobsAlle Gründergeschichten auf http://www.digitaleoptimisten.de/storiesFolge Digitale Optimisten auf Instagram: https://www.instagram.com/digitaleoptimisten//// Herzlich Willkommen bei Digitale Optimisten. Ich bin Alex, und wir sind in diesem Podcast auf der Suche nach den nächsten Elon Musks, die mit ihren Ideen die Welt verändern wollen. Damit sind sie aber noch ganz am Anfang, so dass Du urteilen kannst, ob es wirklich das next big thing ist.Wusstest du, dass im Jahr 2016 eine künstliche Intelligenz fast einen Literaturpreis in Japan gewonnen hat? Genau darum geht's heute: ein wirklich faszinierendes Thema mit einem sehr spannenden Gründer. Hast Du dich schon einmal gefragt, wer eigentlich diese ganzen Texte produziert, die du täglich liest? Artikel auf zeit.de, Produktbeschreibungen auf Amazon, eMail Newsletter, Werbetexte in Instagram-Werbung, und und und. Überall sind Texte, die produziert werden müssen um dann irgendwie gelesen zu werden. Einige Schätzungen sagen, dass jeden Tag über 8 Mrd. Euro an Wert nur durch Text geschaffen wird. Von daher ist es nicht verwunderlich, dass dieser Markt ein riesiger ist, es gibt massiv Agenturen, die tollen Content produzieren, Ghostwriter, die Abschlussarbeiten schreiben und so weiter. Und natürlich gibt es auch künstliche Intelligenz, die dabei helfen will. Das heißt Natural Language Generation, oder kurz NLG, und ist einer der Bereiche, in denen gerade wahnsinnig viel passiert.Deshalb muss ich das Thema besser verstehen, und spreche dazu mit Dominik Lambersy. Dominik hat mit TextCortex das Accelerator-Programm von Entrepreneur First entworfen, und glaubt massiv an die Chancen in diesem Bereich. Wir reden über die Größe des Marktes, vergangene und zukünftige Entwicklungen und natürlich, warum TextCortex das nächste große Dinge sein soll.Ich freue mich über 5 Sterne Reviews und dein Feedback an alexander@digitaleoptimisten.de. Bevor es mit dieser Folge losgeht: Bitte erzähle zwei Freundinnen oder Kollegen von diesem Podcast, wenn Dir diese Geschichten gefallen. Es hilft ungemein, neue Hörer zu finden und den Podcast weiter wachsen zu lassen. Wenn Du magst kannst Du mir auch einen Review auf Apple Podcasts oder Spotify geben.

Arria is a Natural Language Generation company that replicates the human process of expertly analyzing and communicating data insights. We caught up with their CTO, Neil Burnett, to learn more about how Arria's technology goes beyond the standard rules-based NLP approach, as well as how the technology develops and grows once it's placed in the hands of the consumer. Neil explains the huge opportunity within NLG, and how solving for seamless language based communication between humans and machines will result in increased trust and widespread adoption in AI/ML technologies.

V prvním letošním díle, který je velmi výživný, zrevidujeme naše předpovědi ze začátku loňského roku a pro rok 2022 už raději žádné neuděláme. Potom zrecenzujeme vánoční film Don't Look Up, který nastavuje zrcadlo zkorumpovaným politikům, autistickým technomagnátům a zmanipulovaným ovcím (tj. nám) a proto se nám dost líbil.Také si povíme, kdo schvaluje emojis, pomocí kterých miliardy lidí komunikují svoje emoce, že virální algoritmy Tik-Toku mohou způsobit nedostatek majonézy nebo sýru feta a že kongresmenka za QAnon Marjorie Taylor Greene dostala trvalý ban z Twitteru. Jo, a USA směřují buď k totalitě, nebo k občanské válce, nebo k obojímu.Tak šťastný nový rok 2022!Odkazy na dlouhé zimní večery:Loňská novoroční věštírna Microsoft Productivity ScoreBoj s Deepfakes je nekonečný závodČínský NLG model Wu DaoMegatron-Turing NLG 530B od Microsoftu a NVIDIASeznam EU politiků zkorumpovaných RuskemSebastian Kurz jde do PalantiruDon't Look Up na RottenTomatoesKdo povoluje EmojisVirální nedostatek majonézy a feta sýraAntivaxxerka Marjorie Taylor Greene vloni nakoupila akcie Big PharmaUSA směřují k totalitě a Kanada se bojí——Podcast pro Vás připravují Saša Alvarová (@alexalvarova) a Josef Holý (@holyj). Hudba a sound engineering: Psyek a deafmutedrecords.comTwitter Spaces moderuje @jiribulan .Najdete nás na www.kanarci.online !