You can extract desired topics from large volumes of text using the applications of Natural Language Processing (NLP). The large text can include customer reviews of movies, restaurants, etc., feeds from social media, emails of customer complaints, user feedback, and so on.

The Department of Innovation & Technology (InnoTech) under Druk Holding & Investments (DHI), the commercial arm of the Royal Government of Bhutan, has partnered with Omdena, a global collaborative platform that makes AI for good accessible to all. This partnership is a step further in DHI InnoTech's mission to strategize technology and innovation pathways to enhance access and diffusion of emerging technologies, and build local capacity in the fields of science and technology. Omdena will assist InnoTech in hosting a global 2-week hackathon wherein InnoTech will identify key themes and issues that can be resolved using innovative AI/ML applications. Omdena will work with 50 AI engineers over an additional 8-week challenge to develop the idea or POC selected from the hackathon into a fully deployable algorithm. The pilot InnoTech-Omdena event will serve as a showcase for local institutions and the general public who are interested in AI/ML.

Artificial Intelligence (AI) is growing by leaps and bounds, with estimated market size of 7.35 billion US dollars. Machine learning (ML) is a field of AI that improves our daily living in various ways. ML involves a group of algorithms that allow software systems to become more accurate and precise in predicting outcomes. Machine learning has been at the forefront of recent years due to impressive advances in computer science, statistics, the development of neural networks, and the improved quality and quantity of datasets. Here we take a deep dive into machine learning examples to give you a better perspective.

Wildfires are more and more present in modern society, mainly caused by heat waves, lightning, droughts, climate change, or even human actions like car fires and cigarette butts. We've seen it everywhere recently Brazil, Australia, United States, Canada, etc., destroying plant, human, and animal life, property damage, and contributing to global warming through the high amount of CO2 produced. These countries all have walls of videos like the one below in the county's fire emergency to see if something is going on. The most common problem is that they are spotted too late and already widely spread out. This is because you cannot have somebody staring at that wall all day, waiting to spot smoke or fire.

Omdena collaborative AI projects run for two months and are a unique opportunity to work with AI practitioners from around the world whilst solving grand challenges. You augment both your soft and hard skills and get access to mentors, world-class tools, and courses. Add your name, email & interests here and we will get back to you when we find a project that aligns with your interests. The World Resources Institute (WRI) has been seeking to understand how regional and... In this Challenge 61 technology changemakers are building a machine learning solution for...

Nearly a decade ago, back in 2011, when I had just completed the 4th semester of my Computer Science & Engineering Degree course, I found that even though I had fared well in all my exams, my practical knowledge in this field was (in the words of Lord Kelvin -- the famous mathematical physicist)"of a meager and unsatisfactory kind". This was due to the fact that, aside from a handful of really great courses, the majority of my coursework relied on rote-learning and the competitive pursuit of grades instead of practical knowledge. I had joined the field of Computer Science to satisfy my childhood dream of working with computers, but I found I was still far from my dream of understanding and creating software with my computer. In this dismal state, I spent the beginning of my semester-break searching for a motivation in the online universe. After Googling for a short while, I stumbled upon Mehran Sahami's CS106A video lectures on Stanford's Youtube channel, and thus began my tryst with online education.

The power of wildfires to devastating has been tragically apparent across the world. Depending on terrain, they can stretch double in size every 10 minutes and every time that a fire burns makes it challenging to contain. With early detection and instant response, a fire may be quickly put out. In contrast, a fire can wipe out a massive amount of forest, killing and destroying as fast as it spreads. It is the job of a commercial agriculture technology company in Brazil, Sintecsys to surveil 8.7 million acres of forest and agricultural land around four biomes, including Amazon forest. Its system works around the clock to recognise fire and collect images from 360-degree cameras installed on towers distributed throughout the land.

We're only beginning to understand the full potential of AI, but here's what we do know: without doubt, it's foundational technology for IoT and the fourth industrial revolution. We also know that comp sci is just scratching the surface of what's possible well within the decade, with outcomes that not long ago would have caused more hilarity than knowing nods. "The fervor around state-of-the-art AI language models like Open AI's GPT-3 hasn't died down. Melanie Mitchell, a professor of computer science at Portland State University, found evidence that GPT-3 can make primitive analogies. Raphaël Millière, a philosopher of mind and cognitive science at Columbia University's Center for Science and Society, asked GPT-3 to compose a response to the philosophical essays written about it. Among other applications, the API providing access to the model has been used to create a recipe generator, an all-purpose Excel function, and a comedy sketch writer."

Throughout the rest of my high school, I learned about game development, advanced data structures and algorithms, but not much about AI. The only exposure I had to Machine Learning was this website here, which didn't make a whole lot of sense to me back then. Fast forward, I returned to India and was attending Eastern Public School, finishing up my 12th grade with an International Baccalaureate diploma. I started the Stanford University Machine Learning course taught by Dr. Andrew Ng, http://ml-class.org/. The best part is it does not use any high level libraries to teach the concepts to you, so you have to use MATLAB to answer all the programming assignments.

I had the opportunity to work with Spell on a challenge for Omdena to preprocessing our datasets. This was a great experience because on my laptop this process took many hours while on Spell it was much faster and my laptop didn't freeze. Additionally, Spell had logs where I can monitor my process, kill the run if it is necessary, and I can see how long the run is so I can monitor performance in my code.