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How artificial intelligence helps firms stay relevant amid pandemic

#artificialintelligence

COVID-19 has put technology at the heart of many companies. Consumer behavior has shifted dramatically over the past few months, and ever more transactions are taking place online. While the pandemic has brought financial and operational challenges to all markets, technology, especially artificial intelligence (AI), proves that growth is still possible during times of crisis. Unfortunately, despite being around for quite some time, there are often misconceptions about what AI can and cannot do. Indonesia, with its large population and a deep smartphone penetration, presents a huge opportunity for data intensive technology.


Insight: How artificial intelligence helps firms stay relevant amid pandemic

#artificialintelligence

COVID-19 has put technology at the heart of many companies. Consumer behavior has shifted dramatically over the past few months, and ever more transactions are taking place online. While the pandemic has brought financial and operational challenges to all markets, technology, especially artificial intelligence (AI), proves that growth is still possible during times of crisis. Unfortunately, despite being around for quite some time, there are often misconceptions about what AI can and cannot do. Indonesia, with its large population and a deep smartphone penetration, presents a huge opportunity for data intensive technology.


Google Maps Keep Getting Better, Thanks To DeepMind's Machine Learning

#artificialintelligence

Google users contribute more than 20 million pieces of information on Maps every day – that's more than 200 contributions every second. The uncertainty of traffic can crash the algorithms predicting the best ETA. There is also a chance of new roads and buildings being built all the time. Though Google Maps gets its ETA right most of the time, there is still room for improvement. Researchers at Alphabet-owned DeepMind have partnered with the Google Maps team to improve the accuracy of the real-time ETAs by up to 50% in places like Berlin, Jakarta, São Paulo, Sydney, Tokyo, and Washington D.C.


Google Maps and DeepMind enhance AI capabilities to improve route calculations

ZDNet

It has been nearly 13 years since Google Maps started providing traffic data to help people navigate their way around, alongside providing detail about whether the traffic along the route is heavy or light, the estimated travel time, and the estimated time of arrival (ETAs). In a bid to further enhance those traffic prediction capabilities, Google and Alphabet's AI research lab DeepMind have improved real-time ETAs by up to 50% in places such as Sydney, Tokyo, Berlin, Jakarta, Sao Paulo, and Washington DC by using a machine learning technique known as graph neural networks. Google Maps product manager Johann Lau said Google Maps uses aggregate location data and historical traffic patterns to understand traffic conditions to determine current traffic estimates, but it previously did not account for what traffic may look like if a traffic jam were to occur while on the journey. "Our ETA predictions already have a very high accuracy bar -- in fact, we see that our predictions have been consistently accurate for over 97% of trips … this technique is what enables Google Maps to better predict whether or not you'll be affected by a slowdown that may not have even started yet," he said in a blog post. The researchers at DeepMind said by using graph neural networks, this allowed Google Maps to incorporate "relational learning biases to model the connectivity structure of real-world road networks."


Google Maps is improving travel ETAs with DeepMind AI

Engadget

Google Maps helps users navigate over one billion kilometers in more than 200 countries and territories daily, and Google says its estimated time of arrival (ETA) predictions have been consistently accurate for over 97 percent of trips. That's not good enough for Google, though, so the company partnered with DeepMind to use machine learning to make its ETAs even more accurate. Before partnering with DeepMind, an Alphabet AI research lab, Google Maps used a combination of historical traffic patterns and live traffic conditions to understand current traffic patterns. The partners wanted to be able to predict future traffic patterns, so DeepMind developed a graphic neural network, which also considers data on the time of year, road quality, speed limits, accidents and closures. Thanks to that machine learning approach, Google Maps has improved the accuracy of real-time ETAs by up to 50 percent in places like Berlin, Jakarta, São Paulo, Sydney, Tokyo, and Washington D.C. Now, Google Maps can warn users about traffic jams before they exist.


Artificial intelligence algorithm predicts slow earthquakes

#artificialintelligence

On August 21, Indonesia was struck by a 6.9-magnitude earthquake. Fortunately, it was a deep-focus temblor which did not result in loss of life or material damage. However, the country, which is located on the Pacific Ring of Fire, has an extensive record of highly dangerous seismic activity. As recently as 2018, the archipelago was struck by a 7.5 magnitude earthquake, which was part of a series of quakes and tsunamis that killed thousands in the country. Scientists are now wondering if devastation on this scale could be avoided using systems developed by artificial intelligence, among them a team of researchers from the French École Normale Supérieure (ENS), which recently announced the discovery of an AI algorithm to predict seismic events in the journal Nature Communications.


Artificial intelligence algorithm predicts slow earthquakes

#artificialintelligence

The Indonesian island of Lombok was hit by an earthquake in 2018. A team of researchers has succeeded in creating an artificial intelligence (AI) algorithm that can identify changes in the earth's crust that occur up to three months before an earthquake. On Aug. 21, Indonesia was struck by a 6.9-magnitude earthquake. Fortunately, it was a deep-focus temblor which did not result in loss of life or material damage. However, the country, which is located on the Pacific Ring of Fire, has an extensive record of highly dangerous seismic activity.


Asean firms stick to familiar security tools, with growing interest in newer options

ZDNet

When it comes to cybersecurity, most enterprises in Asean are opting to stick with the tried-and-tested and familiar. There is, however, growing interest in comparatively newer tools such as software-defined wide area network (SD-WAN) security systems. Antivirus or antimalware tools remained the most popular cybersecurity choice for enterprises in the region, with 71% deploying these applications, revealed a Palo Alto Networks study released Thursday. The online survey was conducted in February 2020 at the start of the COVID-19 outbreak, before safe distancing measures were rolled out, with 100 respondents each from four Asean markets: Singapore, Indonesia, Thailand, and the Philippines. With cybercriminals taking less and less time to break into corporate systems, enterprises will have to tap artificial intelligence and machine learning tools to bolster their ability to defend against attacks and beef up their network resilience.


Bank Central Asia, Cloudera partner for data and machine learning

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The banks hopes to streamline processes and protect clients from fraud. Indonesia's Bank Central Asia (BCA) will utilise data cloud firm Cloudera to boost operational efficiency and customer engagement, according to an announcement. The bank hopes that Cloudera will help them aggregate structured and unstructured data from emails, social media and call centres, as well as shorten the time taken for queries. Cloudera's data platform has also enabled BCA to implement machine learning processes for automation. As a result, the bank's business units have gained a holistic view of their customers and are using near real-time insights to provide personalised offerings based on customer profiles.


Eden deploys drone technology to help plant one tree at a time

ZDNet

Helping people to help the environment is the core mission at Eden Reforestation Projects, a non-profit that began its work in Ethiopia in 2004, according to the organisation's director of forest monitoring and evaluation Ezra Neale. "A lot of trees are being cut down without any alternatives and local communities are turning towards the land … [and] it creates this endless poverty cycle for the environment and communities; it's all interlinked," he said. "But there's this amazing ability to transform it through planting trees by directly employing and training people to plant trees, totally transforming their lives through a steady income … reinvesting in their community." These days the Los Angeles-based organisation has expanded operations to eight different countries -- Madagascar, Mozambique, Nepal, Haiti, Indonesia, Kenya, and Central America -- and has planted more than 330 million trees. This year alone, the company aims to plant over 120 million trees.