ARTIFICIAL INTELLIGENCE AT WORKCRIT February 1st 2017

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UPDATE YOUR TECHNOLOGY

Some companies lose their business because they keep on doing always the same thing and don’t realise that the world around them has changed.

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Sometimes is a matter of moving from one technology to another and re-inventing an old business.Yellow Pages for example, has been replaced by online search engines like Google

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BLOCKBUSTER failed to invest its capitals in the new web-based business model.Now it has been replaced by NETFLIX.

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Internet and the availability of cheap sensors and processors determined the end of KODAK and the rise

of INSTAGRAM.

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And remember that the Italian Yellow Pages, BLOCKBUSTER and Kodak were prosperous companies just then years ago.

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UNDERSTAND YOUR CUSTOMERS

Some other times the technology hasn’t been changed much, sometimes it’s a matter of adapting the product to the new customer demand or to pay attention to the market needs and to target new needs.

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Red Bull was the first to sell the “energy drink” concept:here the shift wasn’t related to the product’s technology, it was more about intuition and the discovery of a new business opportunity.Red Bull was the first to target this market and Coca Cola lagged behind.Just after realising it they tried to recover with burn.

In a while we’ll see an example on how Deep Learning and Artificial Intelligence can be used to discover new patterns in data to target new business opportunities.

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OPTIMISE PRODUCTION

Another application in which the Artificial Intelligence will have a huge impact is the optimisation of the manufacturing processes to achieve better quality, lower costs.The manufacturing systems are becoming more agile to adapt faster to the market requests.The same production line should be made to produce smaller products batches.The requirements are no more just about quality and speed but also on production agility.Here the new data analysis systems should be designed to rapidly adapt to the varying production environment.

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Amazon for example has been working on big numbers from it’s birth to be competitive on prices.PRESENTER NOTES

Now the advanced automation helps Amazon in keeping low the managing costs of its departments.At the same time the service is much faster and adaptable to the markets requests.

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THE 4TH INDUSTRIAL REVOLUTION

We are facing the 4th Industrial Revolution that will strongly modify our society.Most companies are adopting those technologies and the first to successfully implement it will be the next business leaders.

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The FIRST INDUSTRIAL REVOLUTION began when humans start to use FOSSIL ENERGY instead of MUSCLE POWER.The SECOND was about mass production and line assembly. It was about the standardisation or repetitive manual tasks.The THIRD was the first automation wave. It was in the 70’. Simple repetitive tasks were automated.Now we see the coming of the 4th and the biggest revolution.

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This is happening now: the companies listed in this slide provide the fundamental software components to create advanced Artificial Intelligence applications.

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And those other companies integrate that libraries to create vertical products on specific markets.Artificial Intelligence can perform tasks that since few years ago could be just performed by humans.The FIRST industrial revolution replaced the MUSCLE POWER, the coming FOURTH industrial revolution will replace the BRAIN POWER.As soon as the major companies will adopt these technologies, there will be an enormous impact on the job market.Repetitive tasks of progressively higher complexity will be automated as the technology evolves.

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This slide shows some results from a research made by the University of Oxford.In this case the telephone salespersons and the typists are two professions that will be impacted by machines that can understand the human spoken language and relative concepts.This will allow to automate call centres, customer care desks, automatic translation.

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Google Translate

This is not science fiction: you have a working example in your pocket: just check your Google Translate or your Apple Siri.

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Other jobs to be automated are those involving vision and handling.This is made possible by the Artificial Intelligence that can understand highly complex scenes in cluttered environments.Lets see two demo video that we made in Addfor.In the first one we will see how Artificial Intelligence recognise and classify objects in a complex situation.In the second video, the Artificial Intelligence describes a picture in plain english. Just try to image how can archives of million of images can be scanned and queried using plain written questions.

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See the related Videoon YouTube:

bit.ly/AI-Applications

IT IS NOT AN OPTION

Adopting the new Artificial Intelligence technologies wouldn’t be an option, it is the same as it was with the steam engine or the assembly line invented by Ford: those who do not adopt this technology will simply be excluded from the market.The development wouldn't stop: there is simply to much money involved.NVIDIA was the best-performing stock in 2016 S&P 500 delivering a 225% total return, it increased its market capitalisation by 11 BILLION dollar just in one day, in November 2016, the day of its Q3 earnings call.

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ALREADY HAVE SOME INTERNAL SKILL ?ASK FOR A CUSTOM TRAINING

ASK FOR ANALYSIS AND PROOF OF CONCEPTNO INTERNAL SKILLS ?

The adoption of a disruptive new technology can be risky and requires investments. You should take a safe path.There are many available software solutions on the market but just some of them will fit your needs.We are completely agnostic on hardware and software solutions, for this reason we can help our customers in making the best choices.Maybe the best start could be to share some ideas with us.Because the biggest risk for your company is just not being informed and not being ready.

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ARTIFICIAL INTELLIGENCE: SOME EXAMPLES

Now we will see some examples of Artificial intelligence algorithms that are readily available to be deployed on vertical solutions.This is just a partial list because those technologies can have a broad range of applications, nevertheless we think that those examples can be quite informative.

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UNDERSTAND THE MARKET

The first example is about finding Anomalies in the data streams. This class of algorithms can be applied to a wide range of problems to find glitches in production systems, unusual behaviours in supply chains, financial systems, energy and communication networks.Finding an Anomaly is important to trigger proper reactions, for example, it can be used for predictive maintenance or for discover some Latent Business Opportunities in market data.

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EXAMPLE: FIND ANOMALIES IN TAXI CALLSIn this case we analyse the NYC Taxi Calls Database: it contains the number of taxi calls hour by hour in the year 2014.

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ALGORITHM FINDS ANOMALIES

BY ANALYSING RAW DATAThe algorithm has been supplied with only the raw data. No other data (like holidays or special events has been provided).Here we see the algorithms that start to analyse the data and after a while understands that the data presents a normal seasonality and normal behaviours at peak hours.When the behaviour is different from what the algorithms predict the point is defined as an anomaly and is plotted in yellow or red depending of the anomaly strength.

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FIRST ANOMALY: XMAS + NEW YEAR

The first strongest anomalies detected have an easy explanation: on new year’s day there is a peak of taxi calls just after midnight and on December 25th there are few calls.Remember that the algorithms do not have any information about holidays, it sees Christmas just as a standard day, for this reasons it detects an abnormal pattern in the data.

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SECOND ANOMALY:SUNDAY AFTER HALLOWEEN

The second anomaly is detected for halloween and the night after when the people get back home.

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THIRD ANOMALY:

The third anomaly was about a strange low volume of calls the night after the thanksgiving day. It should be due to a bombing thread spread from the news

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LAST ANOMALY: WHAT’S APP ON DEC 6 2014 ?

What’s strange is this anomaly detected on December the 6th: it’s difficult to spot by eyes but the system detected here a strong glitch in data.Seemingly nothing special happened in NYC that day.

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Just after looking back in the NYC news we found this event that seemingly brought to NYC many unexpected visitors.Summarising, Artificial Intelligence can watch data streams 24/7 finding irregular behaviours, faults, and useful information to improve your systems and your businesses.

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OPTIMIZE PRODUCTIONThe second example is about production optimisation. In particular we will see how Artificial Intelligence can use the sensor’s data to predict system failures.

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EXAMPLE: ANALYSE MACHINERY DATA

The most common way to supervise machines is to create Dashboards for human operators. This approach has many limits: Time and human attention for example. Moreover humans cannot supervise hundreds of data streams at a time.

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ARTIFICIAL INTELLIGENCECAN WATCH 100’S OF VARIABLES

AND FIND USEFUL INFORMATIONS

FAILURE ORIGINAL

I this example our algorithm controls 100’s of variables together. Every single variable by itself is meaningless, nevertheless, we made a system based on a Deep Neural Network that combine all the variables to find the information we need. In this case the left graph shows the raw variables while the right graph shows the output our our system that predict a jet engine failure.

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ORIGINAL DATAFAILURE MODES

Here the Deep Learning algorithm finds three specific failure modes indicated by the three red circles on the right graphPRESENTER NOTES

OFFER NEW FEATURES

The last example is about using Artificial Intelligence to create new feature and set new market standards.In this image you can see a NEST thermostat that set new standards for home automation devices.

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EXAMPLE: ADVANCED TRACTION CONTROLSBut today I would like to bring you an Italian example that explains how Ferrari was the first carmaker to put an Artificial Intelligence system in its production Electronic Control Units. Nowadays this system is installed on every Ferrari model.To explain the system in detail I could like to give the floor to Marco Fainello

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See the related Videoon YouTube:

bit.ly/AI-Applications

We don’t know exactly how Intelligent Machines will evolveIt will be an Exponential Growth

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This mean that it will happen sooner than we expect

it.linkedin.com/in/ebusto

Thank You