Google: Artificial Intelligence To Solve Complex, Real-world Problems

For over a decade, Google has been working on artificial intelligence to make more of the world’s information accessible and useful. Today, AI is an important part of many of Google’s products – helping you to snap the perfect selfie with Portrait Mode on Pixel, breaking down language barriers in Google Translate, and making it easier to respond to an email with Smart Reply in Gmail.

 

But so much more is at play such as using AI to help tackle conservation issues, preserve indigenous languages and improve third world health and Google is helping facilitate this in a big way, which is admirable.

The potential of AI to solve complex, real-world problems is huge.

To help more people tackle challenges with AI, Google has open-sourced machine learning tools like TensorFlow, and helped others innovate with Cloud AI – and collaborated with researchers around the globe. 

Dugongs are the gentle giants of the sea and despite their size, are hard to keep track of. This has presented a challenge for conservation researchers working to save this endangered species.

For decades, scientists had to spend days peering out of small planes to count populations, which was expensive, time consuming and often hazardous.

Researchers then analysed imagery manually, zooming in to count dugongs one-by-one.

Dr. Amanda Hodgson of Murdoch University and Dr. Frederic Maire of Queensland University of Technology knew there must be a better way.

In 2010, they began testing drones, which take aerial photography of the ocean and in 2014, they applied the magic of machine learning in their quest to make the processing of images from drones faster and cheaper, and therefore make drone surveys a realistic option.

Using TensorFlow, Google’s free open source machine learning platform, the team built a detector that could learn to find dugongs in these photos automatically.

So far, the team have processed 37k+ images, identifying 70% of the sea cows they’d found manually in images. This analysis took 18 hours to complete, compared to the 377 hours required for manual analysis. Hodgson and Frederic have now integrated this detection software with mapping software to plot all sightings, giving them richer data about the volume and locations of dugongs.

Preserving precious indigenous languages

Professor Janet Wiles talked about the challenges of preserving the indigenous languages in Australia of which there are many.

“We are in a race against time to support our indigenous languages,” said Professor Wiles.

There are 6,000+ languages in the world, and more than 50% of web content is in English. AI can help us make this content accessible, break down language barriers and even preserve endangered languages.

Since 2012, Google’s language technology teams have been using neural networks to make the world’s diverse language content universally accessible and useful.

Professor Wiles and Ben Foley, researchers with the ARC Centre of Excellence for the Dynamics of Language (CoEDL) are working to transcribe and preserve endangered languages. There are over 300 Indigenous languages in Australia which can be as distinct as Japanese is to German.

Indigenous languages are also inextricably connected to the land, imbued with history and sacred songlines––passed down through oral tradition.

With many indigenous languages endangered, research and transcription is both time sensitive and intensive. CoEDL has fieldworkers working with 130 languages, recording mountains of data (almost 50K hours of language audio in archives), which could take 1.9M hours to transcribe using traditional methods.

“The elephant in the room is a boring dull problem called transcription,” added Professor Foley. “We need speech detector systems.”

Recognising the importance and the sheer enormity of the work, Wiles and Foley realised AI could help provide a new solution to harness the contributions of community members and linguists, while protecting the integrity of this precious language data.

Another area for advancement thanks to AI is in healthcare and already Google is seeing hugely beneficial applications that could help billions of people. Working closely with clinicians and medical providers, Google is developing tools that will improve the availability and accuracy of medical services across a range of conditions, from diabetic eye disease, to cardiovascular health, and cancer.

In early 2017 Google partnered with Dr Elliot Smith, of Brisbane-based medical data specialist Maxwell Plus, to combine deep learning with medical imaging to diagnose prostate cancer in a faster, more affordable and accurate way.

Dr Smith, an expert in magnetic resonance imaging (MRI) systems with a Ph.D. in Electrical Engineering, was concerned that highly trained diagnostics are a scarce resource and poorly distributed in Australia. Moreover, prostate cancer diagnostic methods can take up to seven days to process results. He wanted to find a scalable solution and make this clinical brainpower available to all doctors, to offer patients better care.

He leveraged Google Cloud AI to ‘train’ a system to analyse hundreds of thousands of prostate cancer images using AI. This delivered results to clinicians in 10-15 minutes rather than 2-7 days by traditional diagnostic methods.

Maxwell Plus has since expanded to cover breast and lung cancer diagnostics – and has a goal to process 150,000 cases by the end of 2018.

With so many advancements being made to help the work of conservationists and medical teams taking place, the way is open for positive change on a scale we have never seen before.

So when someone bemoans the onset of the use of artificial intelligence leading to less jobs, remind them it is thanks to machine learning that complex, real-life problems are starting to be solved.

Watch this video for more info:

https://blog.google/technology/ai/fight-against-illegal-deforestation-tensorflow/