Microsoft has announced plans to invest 1.7bn in artificial intelligence and cloud services in Indonesia. Under the plans unveiled by Microsoft CEO Satya Nadella, the tech giant will train 840,000 people in Indonesia in the use of AI and provide support for the country's growing ranks of tech developers. The announcement marks the biggest investment by Microsoft in its nearly three-decade history in the Southeast Asian country. Nadella on Tuesday held talks with President Joko Widodo, popularly known as Jokowi, at Jakarta's presidential palace before delivering a keynote speech about AI in the Indonesian capital. "This new generation of AI is reshaping how people live and work everywhere, including in Indonesia," Nadella said on the first stop of a tour of Southeast Asia.

Diabetes, especially T2DM, continues to be a significant health problem. One of the major concerns associated with diabetes is the development of its complications. Diabetic nephropathy, one of the chronic complication of diabetes, adversely affects the kidneys, leading to kidney damage. Diagnosing diabetic nephropathy involves considering various criteria, one of which is the presence of a pathologically significant quantity of albumin in urine, known as albuminuria. Thus, early prediction of albuminuria in diabetic patients holds the potential for timely preventive measures. This study aimed to develop a supervised learning model to predict the risk of developing albuminuria in T2DM patients. The selected supervised learning algorithms included Na\"ive Bayes, Support Vector Machine (SVM), decision tree, random forest, AdaBoost, XGBoost, and Multi-Layer Perceptron (MLP). Our private dataset, comprising 184 entries of diabetes complications risk factors, was used to train the algorithms. It consisted of 10 attributes as features and 1 attribute as the target (albuminuria). Upon conducting the experiments, the MLP demonstrated superior performance compared to the other algorithms. It achieved accuracy and f1-score values as high as 0.74 and 0.75, respectively, making it suitable for screening purposes in predicting albuminuria in T2DM. Nonetheless, further studies are warranted to enhance the model's performance.

We present publicly available COPAL-ID, a novel Indonesian language common sense reasoning dataset. Unlike the previous Indonesian COPA dataset (XCOPA-ID), COPAL-ID incorporates Indonesian local and cultural nuances, and therefore, provides a more natural portrayal of day-to-day causal reasoning within the Indonesian cultural sphere. Professionally written by natives from scratch, COPAL-ID is more fluent and free from awkward phrases, unlike the translated XCOPA-ID. In addition, we present COPAL-ID in both standard Indonesian and in Jakartan Indonesian--a dialect commonly used in daily conversation. COPAL-ID poses a greater challenge for existing open-sourced and closed state-of-the-art multilingual language models, yet is trivially easy for humans. Our findings suggest that even the current best open-source, multilingual model struggles to perform well, achieving 65.47% accuracy on COPAL-ID, significantly lower than on the culturally-devoid XCOPA-ID (79.40%). Despite GPT-4's impressive score, it suffers the same performance degradation compared to its XCOPA-ID score, and it still falls short of human performance. This shows that these language models are still way behind in comprehending the local nuances of Indonesian.

Find open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general, filtered by job title or popular skill, toolset and products used.

At Cadmus, we believe every student should have equal opportunity to achieve academic excellence; that's why we're changing how the world learns! Cadmus is a global EdTech company purposefully built for the higher education sector to break down global learning barriers by providing educators and diverse student cohorts with access to high-quality learning and assessment. Built on rich, student-centric values, Cadmus empowers individuals to achieve their highest potential and graduate with the critical skills and knowledge to profoundly impact our workforces, communities, and evolving world. At Cadmus, we're working hard in pursuit of an ambitious, world-shaping goal: to provide 1 billion students with access to high-quality education by 2050. That's why we need a Data Engineering superstar to join our team and help us maintain a high-quality experience for our users worldwide -- ensuring our cloud platform is reliable, performant and set up to scale.

On the side of a dusty Jakarta road, nestled in the corner of a gas station, might be the future of coffee. Driving home, you might preorder a cup as you plan to refill the car, even before pulling up to the gas station. Open the Kopi Kenangan app, click on "preorder," and choose one -- perhaps a mellow coffee with just a hint of acidity, creamy with milk. By the time you arrive at the station, the iced coffee, made by a human, will be sitting on the countertop, sweating in a plastic cup in the Jakarta humidity. Indonesian coffee chain Kopi Kenangan -- "coffee memories" in Bahasa Indonesia -- did not set out to be a tech-powered coffee chain.

An actual space laser is cruising 300 miles above your head right now. Launched in 2018, NASA's ICESat-2 satellite packs a lidar instrument, the same kind of technology that allows self-driving cars to see in three dimensions by spraying lasers around themselves as they roll down the street and analyzing the light that bounces back. But instead of mapping a road, ICESat-2 measures the elevation of Earth's surface with extreme accuracy. Although this space laser means you no harm, it does portend catastrophe. Today in the journal Nature Communications, scientists describe how they used ICESat-2's new lidar data to map the planet's land that's less than 2 meters above sea level, which makes it vulnerable to the creep of sea level rise.

This project presents the results of a partnership between the Data Science for Social Good fellowship, Jakarta Smart City and Pulse Lab Jakarta to create a video analysis pipeline for the purpose of improving traffic safety in Jakarta. The pipeline transforms raw traffic video footage into databases that are ready to be used for traffic analysis. By analyzing these patterns, the city of Jakarta will better understand how human behavior and built infrastructure contribute to traffic challenges and safety risks. The results of this work should also be broadly applicable to smart city initiatives around the globe as they improve urban planning and sustainability through data science approaches.

For a decade or so before the market for touchscreen smartphones took off around 2010, BlackBerry's hand-held communication devices were ubiquitous among thumb-jockeying executives trying to keep in touch with the office outside working hours. After several recent failed attempts to launch new phones and operating systems to compete against Apple, Google and Samsung Electronics products, the company that "made the modern cellphone," as BlackBerry's CEO John Chen puts it, is hoping to become the main supplier of secure applications and software for the next generation of internet-linked devices -- the much- touted "internet of things" -- from web-connected self-driving cars to "smart" domestic appliances that are expected to take off over the coming decade. "It's going to be very much driven by securing end-point communications," Chen told the Nikkei Asian Review. "We want to be the number one secure communications in IoT. We have signed a deal with Ford for seven years to help them build their next generation cars."