AI tu bukan semata²
Artificial Intelligence.
AI tu lebih penting lagi
* Akhlak Intelligence
* Adab Intelligence
Mana mungkin Artificial Intelligence itu menandingi "Adam" Intelligence.
#bilahudatulis
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Some old example of using artificial intelligence and machine learning in real life practice.
There are so many amazing ways artificial intelligence and machine learning are used behind the scenes to impact our everyday lives and inform business decisions and optimize operations for some of the world’s leading companies. Here are 27 amazing practical examples of AI and machine learning.
Consumer goods
Using natural language processing, machine learning and advanced
analytics, Hello Barbie listens
and responds to a child. A microphone on Barbie’s necklace records what is said
and transmits it to the servers at ToyTalk. There, the recording is analyzed to
determine the appropriate response from 8,000 lines of dialogue. Servers
transmit the correct response back to Barbie in under a second so she can
respond to the child. Answers to questions such as what their favorite food is
are stored so that it can be used in conversation later.
Coca-Cola’s global market and extensive
product list—more than 500 drink brands sold in more than 200 countries—make it
the largest beverage company in the world. Not only does the company create a
lot of data, it has embraced new technology and puts that data into practice to
support new product development, capitalize on artificial intelligence bots and
even trialing augmented reality in bottling plants.
Even though Dutch company Heineken has been a worldwide brewing
leader for the last 150 years, they are looking to catapult their success
specifically in the United States by leveraging the vast amount of data they
collect. From data-driven marketing to the Internet of Things to improving
operations through data analytics, Heineken looks to AI augmentation and data
to improve its operations, marketing, advertising and customer service.
Creative Arts
Culinary arts require the human touch, right? Yes and no.
AI-enabled Chef Watson from
IBM offers a glimpse of how artificial intelligence can become a sous-chef in
the kitchen to help develop recipes and advise their human counterparts on food
combinations to create completely unique flavors. Working together, AI and
humans can create more in the kitchen than working alone.
Another way AI and
big data can augment creativity is in the world of art and
design. In one example, IBM’s machine learning system, Watson, was
fed hundreds of images of artist Gaudi’s work along with other complementary
material to help the machine learn possible influences for his work including
Barcelona, its culture, biographies, historical articles and song lyrics.
Watson analyzed all the information and delivered inspiration to the human
artists who were charged with the creating a sculpture “informed” by Watson and
in the style of Gaudi.
Music-generating algorithms are now inspiring new songs.
Given enough input—millions of conversations, newspaper headlines and
speeches—insights are gleaned that can help create a theme for lyrics. There
are machines such as Watson BEAT that can come up with different musical
elements to inspire composers. AI helps musicians understand what their
audiences want and to help determine more accurately what songs might
ultimately be hits.
Energy
Global energy leader, BP is
at the forefront of realizing the opportunities big data and artificial
intelligence has for the energy industry. They use the technology to drive new
levels of performance, improve the use of resources and safety and reliability
of oil and gas production and refining. From sensors that relay the conditions
at each site to using AI technology to improve operations, BP puts data at the
fingertips of engineers, scientists and decision-makers to help drive high
performance.
In an attempt to deliver energy into the 21st century, GE Power uses
big data, machine learning and Internet of Things (IoT) technology to build an
“internet of energy.” Advanced analytics and machine learning enable predictive
maintenance and power, operations and business optimization to help GE Power
work toward its vision of a “digital power plant.”
Financial Services
With approximately 3.6 petabytes of data (and growing) about
individuals around the world, credit reference agency Experian gets
its extraordinary amount of data from marketing databases, transactional
records and public information records. They are actively embedding machine
learning into their products to allow for quicker and more effective
decision-making. Over time, the machines can learn to distinguish what data
points are important from those that aren’t. Insight extracted from the
machines will allow Experian to optimize its processes.
American Express processes
$1 trillion in transaction and has 110 million AmEx cards in operation. They
rely heavily on data analytics and machine learning algorithms to help detect
fraud in near real time, therefore saving millions in losses. Additionally,
AmEx is leveraging its data flows to develop apps that can connect a cardholder
with products or services and special offers. They are also giving merchants
online business trend analysis and industry peer benchmarking.
Healthcare
AI and deep learning is being put to use to save lives by Infervision.
In China, where there aren’t enough radiologists to keep up with the demand of
reviewing 1.4 billion CT scans each year to look for early signs of lung
cancer. Radiologists need to review hundreds of scans each day which is not
only tedious, but human fatigue can lead to errors. Infervision trained and
taught algorithms to augment the work of radiologists to allow them to diagnose
cancer more accurately and efficiently.
Neuroscience is the inspiration and foundation for Google’s DeepMind,
creating a machine that can mimic the thought processes of our own brains.
While DeepMind has successfully beaten humans at games, what’s really
intriguing are the possibilities for healthcare applications such as reducing
the time it takes to plan treatments and using machines to help diagnose
ailments.
Manufacturing
Cars are increasingly connected and generate data that can be
used in a number of ways. Volvo uses
data to help predict when parts would fail or when vehicles need servicing,
uphold its impressive safety record by monitoring vehicle performance during
hazardous situations and to improve driver and passenger convenience. Volvo is
also conducting its own research and development on autonomous vehicles.
BMW has
big data-related technology at the heart of its business model and data guides
decisions throughout the business from design and engineering to sales and
aftercare. The company is also a leader in driverless technology and plans for
its cars to deliver Level 5 autonomy—the vehicle can drive itself without any
human intervention—by 2021.
The AI tech revolution has hit farming as well, and John Deere is
getting data-driven analytical tools and automation into the hands of farmers.
They acquired Blue River Technology for its solution to use advanced machine
learning algorithms to allow robots to make decisions based on visual data
about whether or not a plan is a pest to treat it with a pesticide. The company
already offers automated farm vehicles to plough and sow with pinpoint-accurate
GPS systems and its Farmsight system is designed to help agricultural
decision-making.
Media
The BBC project, Talking with Machines is an audio drama that
allows listeners to join in and have a two-way conversation via their smart
speaker. Listeners get to be a part of the story as it prompts them to answer
questions and insert their own lines into the story. Created specifically for
smart speakers Amazon Echo and Google Home, the BBC expects to expand to other
voice-activated devices in the future.
UK news agency Press
Association (PA) is hoping robots and artificial intelligence might
be able to save local news. They partnered with news automation specialist Urbs
Media to have robots write 30,000 local news stories each month in a project
called RADAR (Reporters and Data and Robots). Fed with a variety of data from government,
public services and local authorities, the machine uses natural language
generation technology to write local news stories. These robots are filling a
gap in news coverage that wasn’t being filled by humans.
Big data analytics is helping Netflix predict
what its customers will enjoy watching. They are also increasingly a content
creator, not just a distributor, and use data to drive what content it will
invest in creating. Due to the confidence they have in the data findings, they
are willing to buck convention and commission multiple seasons of a new show
rather than just a pilot episode.
Retail
When you first think of Burberry,
you likely consider its luxury fashion and not first consider them a digital
business. However, they have been busy reinventing themselves and use big data
and AI to combat counterfeit products and improve sales and customer
relationships. The company’s strategy for increasing sales is to nurture deep,
personal connections with its customers. As part of that, they have reward and
loyalty programs that create data to help them personalize the shopping
experience for each customer. In fact, they are making the shopping experience
at their brick-and-mortar stores just as innovative as an online experience.
As the world’s second-largest retailer, Walmart is
on the cutting edge of finding ways to transform retail and provide better
service to its customers. They use big data, machine learning, AI and the IoT
to ensure a seamless experience between the online customer experience and the
in-store experience (with 11,000 brick-and-mortar stores, something rival
Amazon isn’t able to do. Enhancements include using the Scan and Go feature on
the app, Pick-up Towers and they are experimenting with facial recognition
technology to determine if customers are happy or sad.
Service
Central to everything Microsoft does
is leveraging smart machines. Microsoft has Cortana, a virtual assistant;
chatbots that run Skype and answer customer service queries or deliver info
such as weather or travel updates and the company has rolled out intelligent
features within its Office enterprise. Other companies can use the Microsoft AI
Platform to create their own intelligent tools. In the future, Microsoft wants
to see intelligent machines with generalized AI capabilities that allow them to
complete any task.
When you bring together cloud computing, geo-mapping and machine
learning, some really interesting things can happen. Google is using AI and
satellite data to prevent illegal
fishing. On any given day, 22 million data points are created that
show where ships are in the world’s waterways. Google engineers found that when
they applied machine learning to the data, they could identify why a vessel was
at sea. They ultimately created Global Fishing Watch that shows where fishing
is happening and could then identify when fishing was happening illegally.
Always at the top of delivery extraordinary service, Disney is
getting even better thanks to big data. Every visitor gets their own MagicBand
wristband that serves as ID, hotel room key, tickets, FastPasses and payment
system. While guest enough the convenience, Disney gets a lot of data that
helps them anticipate guests’ needs and deliver an amazing, personalized
experience. They can resolve traffic jams, give extra services to guests who
may have been inconvenienced by a closed attraction and data even allows the
company to schedule staff more efficiently.
Google is
one of the pioneers of deep learning from its initial foray with the Google
Brain project in 2011. Google first used deep learning for image recognition
and now is able to use it for image enhancement. Google has also applied deep
learning to language processing and to provide better video recommendations on
YouTube, because it studies viewers’ habits and preferences when they stream
content. Next up, Google’s self-driving car division also leverages deep
learning. Google also used machine learning to help it figure out the right
configuration of hardware and coolers in their data centers to reduce the
amount of energy expended to keep them operational. AI and machine learning has
helped Google unlock new ways of sustainability.
Social Media
From what tweets to recommend to fighting inappropriate or
racist content and enhancing the user experience, Twitter has
begun to use artificial intelligence behind the scenes to enhance their
product. They process lots of data through deep neural networks to learn over
time what users preferences are.
Deep learning is helping Facebook draw
value from a larger portion of its unstructured datasets created by almost 2
billion people updating their statuses 293,000 times per minute. Most of its
deep learning technology is built on the Torch platform that focuses on deep
learning technologies and neural networks.
Instagram also
uses big data and artificial intelligence to target advertising and fight
cyberbullying and delete offensive comments. As the amount of content grows in
the platform, artificial intelligence is critical to be able to show users of
the platform information they might like, fight spam and enhance the user
experience.
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