Artificial IntelligenceEstimated Reading Time: just 2 min

Artificial Intelligence (AI) is the intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other living beings.

Therefore, AI research is defined as the study of devices that perceive environment and take actions that maximize their goals.

AI is associated with the machines that possess the same cognitive functions that are usually associated with the human mind, such as “learning” and “problem solving”.

Therefore, for a machine acting like a human means being able to perform 5 macro-functions:
- Perception (recognizing and interpreting reality)
- Reasoning (drawing new conclusions)
- Planning (detecting patterns and adapting to new environments)
- Knowledge Representation (extract and store knowledge)
- Natural Language Processing (communicate successfully in a human language)

To better understand what Artificial Intelligence really is and how it works, it is important to look at its history.

AI research started in 1956 after a workshop at Dartmouth College and its fathers where:
- Allen Newell and Herbert Simon from CMU
- John McCarthy and Marvin Minsky from MIT
- Arthur Samuel from IBM

Dartmouth College group focused on Restricted AI that solves only one of the 5 acting like a human macro-functions at a time.

The first project involving AI was funded by the US Government during the Cold War to have computers translating Russian.

The outcome was a disaster and it lead to an era called AI Winter where obtaining funding for AI projects was difficult.

But, suddenly, the situation got hot again with the birth of Expert Systems.

These were based of trees made of if-then rules that simulated the decision-making ability of a human and made machines able to solve more than one of the 5 acting like a human macro-functions at a time (the so called General AI).

These systems worked well in specific situations and the increasing computational power allowed them to be successful. The most famous achievement of Expert Systems is Deep Blue that became the first computer chess-playing system to beat a reigning world chess champion, Garry Kasparov on May 1997.

Still Deep Blue wasn’t acting like a human.

In fact, it was just a demonstration that the computational power of a machine can be greater than the one of human brain.

At this point, a huge breakthrough came with the birth of Machine Learning.

Machine Learning is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to learn from data, without being explicitly programmed.

This step ahead allowed systems to solve problems that involve:
- Supervised Learning
- Clustering
- Dimensionality Reduction
- Structured Prediction
- Anomaly Detection

Another breakthrough came with Deep Learning.

Deep Learning is a subset of Machine Learning that, using architectures based on Neural Networks, allows machines to learn a large variety of activities as humans do.

This step ahead allowed systems to solve problems that involve:
- Supervised/Semi-Supervised/Unsupervised Learning
- Image/Audio Recognition
- Natural Language Processing

The most famous achievement of Deep Learning is AlphaGo winning a three-game match of Go against Ke Jie, who at the time continuously held the world No. 1 Go Player ranking for the previous two years.

More than winning, AlphaGo surprised everyone by making moves that none had used before in thousands of years and that re-wrote the way Go is played.

This breakthrough was possible because of the accessibility of:
- Data Storage (today memory is roughly 2-300,000 times cheaper than in 1956)
- Computational Power (both in terms of space needed, energy consumption and costs)

The hype for AI is nowadays very high and involves industries such as:
- Advertising
- Audit
- Automotive
- Finance and Economics
- Healthcare
- Military
- Video Games

If you are interested in knowing more about AI applications and how they work, you can find a deep dive at the link AI APPLICATIONS.

Nicola Zaffonato Administrator

Business Strategy | Product Marketing | Executive Master eCommerce Management | Business Innovation Master | MSc

I am driven by my personal growth and of people/contexts that surround me.

I followed a professional path in Valentino Fashion Group and Luxottica during which, thanks to the ability to understand different businesses and interests, I was able to succeed in Operations, Merchandising and Retail.

These organizations have exploited my ability to mediate and translate needs/constraints into practice, assigning me to Project Management roles.

Luxottica relied on my ability to analyze, to anticipate things and to imagine/implement solutions by appointing me in Supply Chain Management department and assigning me to the Product Management of IoT solutions for Anti-counterfeiting and Retail digitalization.

During this professional path, I also developed my leadership by managing teams to build Processes, Organizations, Systems and Governance Tools.

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