Ludvig Strand

Finnish researchers have developed a technology that enables computers to understand human emotions to improve AI interactions, potentially allowing machines to adjust their behavior to enhance user experiences. Researchers at the University of Jyväskylä in Finland have created a model that allows computers to recognize and comprehend human emotions by employing mathematical psychology principles. This breakthrough could enhance the interaction between humans and smart technologies, such as artificial intelligence systems, by making them more attuned and reactive to users’ emotions. In everyday interactions with computers, users commonly experience emotions such as joy, irritation, and boredom. Despite the growing prevalence of artificial intelligence, current technologies often fail to acknowledge these user emotions. The model developed in Jyväskylä can currently predict if the user has feelings of happiness, boredom, irritation, rage, despair, and anxiety... #artificialintelligence #technology #machinelearning #breakthrough #innovation #computers #emotions #humans #research #psychology

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🎥 Meet our Associates 💫 Sanjan was a Headstart associate on a gamification project with Zoplo. Watch to learn more about his takeaways and how Headstart helped him secure a grad offer at Deloitte!

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PRACTICE MAKES PERFECT - PART TWO Hey guys, good morning and how’s your week going? I am grateful to all of you that celebrated my admission into the Svenska institutet’s Impact Pioneers ’24 program. At the appropriate time, I will share more info about it. Today, I would like us to examine the adage, “practice makes perfect” more deeply. Let’s understand the concept of #practice… “Practice" is the act of repeatedly performing a task or activity to improve one’s skills and gain proficiency. The idea behind it is that through intentional and focused repetition, an individual can hone his or her abilities, address his or her weaknesses, and ultimately achieve a level of excellence. Practice is not just about putting in hours of work; it's about the quality and intention behind those hours. According to the psychologist, Anders Ericsson, deliberate practice emphasizes that simply repeating a task is not enough but that the individuals must engage purposefully with specific goals in mind, seek feedback, and focus on challenging aspects of their crafts. Now, let’s understand the science behind #mastery… Several studies have shown that dedicated practice leads to expertise. Anders Ericsson's research suggests that it takes roughly 10,000 hours of deliberate practice to achieve mastery in any field. Even though, the number may vary depending on the complexity of the skill involved and the individual's starting point, the message remains clear: “proficiency can never be achieved overnight.” #Neuroscience has also shed light on how practice physically alters the brain. It says that repeated engagement in a skill strengthens the neural pathways, making actions more automatic and efficient. Hey guys, enough of too much grammar... To explain this further, I have decided to attach the video below for your viewing pleasure… TO BE CONTINUED… My name is Remy Chukwunyere. I am a personal development coach, startups mentor, leadership development coach, etc with 20+ years experiences working in both public and private establishments. For private consultations, DM me at [email protected] or via WhatsApp at +2348038702075. May the Lord bless your hustles, today and always! #Leadership #Mentorship #Startups #Education #BusinessCoach #CareerAdvice

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According to this fresh AI report, the use of AI is largely viewed positively, especially in Finland, but almost half of organisations do not yet use AI at all and only 15% have an AI strategy. 🤖 Finland is a leader in AI in the Nordics, with 61% of Finnish organisations using AI, compared to 52% in Norway, 48% in Denmark and 45% in Sweden. Currently, AI is used in organizations especially to boost productivity and optimize operations: 43% of organizations use AI to automate processes and 42% to improve the quality of products or services. Almost half (49%) of Nordic organisations, especially small companies, do not yet use AI at all. According to the study, the biggest obstacle to adoption is uncertainty or lack of information about the potential applications of artificial intelligence.

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We’re honoured to welcome Matthias Seeger, Principal Applied Scientist at Amazon AI, to the leading data science, ML, and AI event in the Nordics - NDSML Summit 2024, scheduled for the 23rd and 24th of October in Stockholm! On the Machine Learning + MLOps, Matthias will be presenting on "Challenges of Evaluating AI-Powered Troubleshooting Assistants". Matthias is a leading mind in machine learning and one of the scientists behind Amazon Q! With a Ph.D. from Edinburgh University, postdoc work at UC Berkeley, and a career spanning roles at the University of Saarbrueckens and EPF Lausanne, Matthias has made a huge impact in the AI and tech space. Since joining Amazon in 2014, he’s helped revolutionize how customers build, optimize, and operate applications on AWS. Oh, and did we mention he’s also an ICML Test of Time Award winner? Don’t miss this opportunity to meet Matthias and 400+ like-minded practitioners! Book your tickets at https://hubs.li/Q02RsQKs0 #NDSMLSummit #DataScience #AppliedDataScience #MachineLearning #ML #ArtificialIntelligence #AI #EnterpriseAI #DeepLearning #DataEngineering #MLEngineering #DataPipelines #BigData #Automisation #GenerativeAI #EthicalAI #TrustworthyAI #LLMs #DataOps #MLOps

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To transform an entire company we have to build understanding and new skills broadly in the organization. Listen to the great Eleni Rudman talking about the AI journey we are on from a learning perspective (in Swedish). #AItransformation #ICAgruppen https://lnkd.in/d_qxpJGa

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This course helps you finetune your AI prompting!

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#HumansOfExacaster: Meet Kornelija Janušytė Šilaikienė, our Data Analyst✨ Passionate about her role as a #dataanalyst, Kornelija shares insights about her team, learning bucket list, inspirations, and advice on how to kick-start a junior career in data analytics. 𝗪𝗵𝗮𝘁 𝗱𝗿𝗶𝘃𝗲𝘀 𝘆𝗼𝘂𝗿 𝗽𝗮𝘀𝘀𝗶𝗼𝗻 𝗳𝗼𝗿 𝘆𝗼𝘂𝗿 𝗿𝗼𝗹𝗲 𝗮𝘀 𝗮 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁? 💡 I would say non-monotonicity. Every project has different kinds of data, and it takes effort to analyze and develop a suitable solution. My daily tasks vary from simple descriptive business analysis to the application of ML/AI models. And it feels like I'm learning something new with every new project! 𝗛𝗼𝘄 𝘄𝗼𝘂𝗹𝗱 𝘆𝗼𝘂 𝗱𝗲𝘀𝗰𝗿𝗶𝗯𝗲 𝘄𝗵𝗮𝘁 𝘆𝗼𝘂 𝗱𝗼 𝗮𝘁 𝗘𝘅𝗮𝗰𝗮𝘀𝘁𝗲𝗿? 💡 Very simple and very hard question at the same time. My main responsibilities are related to customer value management solutions: NBOs configurations, user base segmentation, churn predictions. But at the same time, I take on more technical tasks when needed. So, my daily work varies from technical tasks to analytical tasks. 𝗪𝗵𝗮𝘁 𝗱𝗼 𝘆𝗼𝘂 𝗲𝗻𝗷𝗼𝘆 𝗺𝗼𝘀𝘁 𝗮𝗯𝗼𝘂𝘁 𝘆𝗼𝘂𝗿 𝘄𝗼𝗿𝗸 𝗮𝘁 𝗘𝘅𝗮𝗰𝗮𝘀𝘁𝗲𝗿? 💡 The ability to grow and learn from various projects. Exacaster is getting deeper and deeper into the latest ML/AI solutions and at the same time – so are we, analysts of Exacaster. I don't know any other place where a Data Analyst is able to cover the technical part of the project and apply data science at the same time. 𝗪𝗵𝗮𝘁'𝘀 𝘁𝗵𝗲 𝗻𝗲𝘅𝘁 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗮𝗿𝗲𝗮 𝘆𝗼𝘂'𝗿𝗲 𝗲𝘅𝗰𝗶𝘁𝗲𝗱 𝘁𝗼 𝗱𝗶𝘃𝗲 𝗶𝗻𝘁𝗼? 💡 I would like to grow in ML/AI applications in the CVM area. I believe that Exacaster is a great place for that as I can learn more about it from my colleagues and the various projects we deliver. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝘆𝗼𝘂𝗿 𝗴𝗿𝗲𝗮𝘁𝗲𝘀𝘁 𝘀𝗼𝘂𝗿𝗰𝗲 𝗼𝗳 𝗶𝗻𝘀𝗽𝗶𝗿𝗮𝘁𝗶𝗼𝗻? 💡 I would say my team. They always come up with amazing ideas and help each other. I don't feel any gap between junior and senior colleagues here at Exacaster. I think that is pretty much inspirational of how to be a great specialist, but at the same time, respect your junior colleagues' suggestions on solutions, work together in a team, and don't show any sight of arrogance. 𝗧𝗼 𝘄𝗿𝗮𝗽 𝘂𝗽, 𝗱𝗼 𝘆𝗼𝘂 𝗵𝗮𝘃𝗲 𝗮𝗻𝘆 𝗳𝗶𝗻𝗮𝗹 𝘄𝗼𝗿𝗱𝘀 𝗼𝗳 𝗮𝗱𝘃𝗶𝗰𝗲 𝗼𝗿 𝗽𝗲𝗿𝗵𝗮𝗽𝘀 𝗮 𝗺𝗲𝗺𝗼𝗿𝗮𝗯𝗹𝗲 𝗮𝗻𝗱 𝗳𝘂𝗻 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝘆𝗼𝘂'𝗱 𝗹𝗶𝗸𝗲 𝘁𝗼 𝘀𝗵𝗮𝗿𝗲? 💡 Don't be afraid to join a company with a lot of unknowns to you – in the long run, it will only bring you more knowledge and experience. Don't be afraid to learn new things, and don't hesitate to ask 'stupid 'questions. I came to Exacaster with very little knowledge of telco analytics and practically no knowledge of technical tools, but my Team allowed me to grow and learn from the best 😊

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Taking a product from ones 🧠 brain and into ✨ physical reality✨ is a scary process. For Maneuvering Monday we are currently living that scary process, as the first wave of readers make their way through the manuscript from start to finish 😬. And then when one gets feedback as the below 👇, it gives me the courage to keep on betting on the things in my brain. There will also be 👎 negative feedback and a thousand errors that need to be corrected. But right now, I am savoring these words. Especially the compliment about comic relief 😁. #feedback #create #innovate #publishing

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An incredible interactive project by Erik Nylund focuses on Carbon Emissions and the inequality behind this process! This project won the Data Art and Storytelling category in our Make Your Data Speak Award 2024! You can read all about how this project was created and the challenges the author faced in this fascinating article! Link in the comments! #Infographics #DataVisualization #CarbonEmissions #Inequality #Dataviz

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❄️ 𝗧𝗿𝗲𝗻𝗱𝘀 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗻𝗼𝗿𝘁𝗵 #2 🇸🇪 We feel alone, and here's some evidence from Sweden.   🔍 At Kairos Future, we have Sweden's longest-running survey on citizens' values and interests, dating back to the 1950s. Over time, we have added more questions that a representative panel of Swedes answers every single year. In 1995, we added a new question: 𝗪𝗵𝗮𝘁 𝗯𝗲𝘀𝘁 𝗱𝗲𝘀𝗰𝗿𝗶𝗯𝗲𝘀 𝘆𝗼𝘂𝗿 𝘀𝗶𝘁𝘂𝗮𝘁𝗶𝗼𝗻? (scale 1-7) - My life is rich with friends  - I feel alone  - Neither 📈 In 1995, 58% of Swedes reported that their life was rich with friends, while only 16% reported feeling alone.   📉 In 2024, the picture looks very different: Only 40% report having plenty of friends, and a staggering 36% report feeling alone.   "Richness in friends" has dropped by nearly a third, and "aloneness" has more than doubled in 29 years. This is serious stuff, and data I think a lot of us can feel in some way or another. This is evidence of a growing problem. What are the solutions? I don't think Sweden is the only one exposed to this shift.   💭 How can we expect to foster sustainable economic development if people feel alone? The physical health effects of loneliness have solid evidence of leading to depression and increased stress hormones, which in turn lead to higher risks of heart attacks, strokes, and dementia (according to Karolinska Institutet).   🌍 The data suggests to me at least that a major challenge for the public sector in the coming decade will have to center around finding incentives to decrease loneliness. Many are actively involved in building better cities, reducing screen time, and plenty of other initiatives that can help us feel less alone. But the long-term trend is not great.   ❓ Is it like this in other places? And what is the best way to reduce loneliness? #futureofwork #loneliness #mentalhealth #foresight

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View my verified achievement from Tableau.

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Simplify the evaluation & implementation of AI by being unapologetically practical & objective of how it can be beneficial to you. Read these wise words from Lasse Rindom below. My top 3 favorites are: 💡 How people and enterprises work with AI 💡 What AI can and cannot do 💡 How AI works when touching the real world #ai #genai #innovation

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What a great experience speaking at the Nordic Data Science and Machine Learning Summit 2024! 🙌 I had the opportunity to present on “Data Platforms - Generating Value from Analytical Data at Scale”, diving into how an opinionated data platform can help organizations build and operate data flywheels to unlock real business value. 🔄 The questions and discussions—both during the Q&A and later during the break—were insightful and showed how much we all care about tackling data engineering challenges together. 💡If you were there and didn’t get the chance to ask questions or discuss the topic, don’t hesitate to connect and DM. I also thoroughly enjoyed the session by the great storyteller Lars Albertsson on “Generative AI - the power to destroy democracy meets the security and reliability of MS-DOS”. What a thought-provoking talk! 🧠 Big thanks to the #NDSMLSummit team for putting together a well-organized event, and to everyone who attended and contributed to the lively discussions. 🙏 #DataEngineering #DataPlatforms #DataFlywheels #GenerativeAI #MachineLearning #NDSMLSummit

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Niclas got me thinking about knowledge sharing within the analytics context. The obvious angle is to organize some form of show and tell, (e.g. daily standup) where you can show how you did something, how to use a technology, or explain conclusions. Maybe the collective memory of the team will remember when this info becomes relevant, likely not. But I wonder - how does one convey the thought process that went into investigation, pattern recognition, applying business context to the data question at hand. After all, analytics is closer to detective work than anything else. Detectives string together many bits and pieces together, both newly dug up info as well as notes from old case files. Pretty sure in analytics we do something similar. - Talk to a stakeholder, find out there's another person to talk to - Stalk how current business processes are done in real life - Remember to exclude that data anomaly from 1.5 years where revenue got counted twice - Hunt down that one query you used few months ago that could repurposed Before the summer we spoke to a ton of analysts and a good majority cited that most time went into the context and investigation process. Mangling data close second, but the actual analysis part was quote - the easiest. So, if the majority of time is spent on the "WTF" phase, and every analyst goes through a personal, daily "WTF" phase, wouldn't it make sense to focus on the skills needed to get out of WTF faster? Less mistakes, more thorough work, faster turnaround time. Some of the brightest analysts I've met have a knack, natural or trained, for this. But - seems that currently the only real way to acquire this type of knowledge is with hands-on experience and time. -- #dataanalytics #analytics

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Many refer to artificial intelligence as supportive intelligence. Antell's ATSO demonstrates that artificial intelligence is rather, and more so, synergistic intelligence than supportive intelligence. In synergistic intelligence, artificial intelligence adds to human intelligence, making 1+1>2, rather than just supporting decision-making.

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