A.I. Love You: what is Artificial Intelligence and how to change the relationship with companies
Artificial Intelligence (AI) over the last two years has catalyzed the attention and investments of leading companies around the world: from Amazon to Facebook, from Google to Microsoft, an investment value of over $16 billion is estimated in 2022 (a 62.9% growth since 2016).
The great promise of AI is a future where the ability to make complex predictions, data analysis and definitions of functional specifications will no longer be addressed to the programmer but to the program itself.
Today, the impression is that we are at an early stage, the tip of the iceberg so to speak: the potential is high and the idea that many people have is A.I. will be able to revolutionize the way we live and work.
The topic is fuelling the interest of companies, industries and governments (in October the Obama administration published a report on the future impact of Artificial Intelligence) and is increasingly the focus of media attention.
Studies on Artificial Intelligence began in the 1950s, but only in recent years have certain factors that derive from technological development led to increasing interest and rapid evolution:
- New algorithms: the evolution in recent years of deep learning algorithms has considerably increased the level of results achieved, exceeding human capabilities in terms of performance (as in the case of image or speech recognition);
2. More powerful Hardware: the increasingly sophisticated development of Graphical Processing Units (GPUs) has rapidly reduced the neural network training times used for deep learning;
2. Availability of data: instructing the neural networks used for deep learning also requires a large amount of data (from thousands to many millions). The availability and production of data has grown exponentially: in the era of Big Data, more than 2.2 exabytes of information are produced each day;
3. Cloud-based services: the availability of cost-effective cloud-based machine learning infrastructure and services by the leading cloud providers has quickly attracted the attention of companies and developers to the use of these technologies and applications in diversified contexts.
The combination of these technological evolutions has led to the rapid growth of AI, adopting an increasingly important role in almost all spheres and fields, in large companies as well as in small daily activities.
What is Artificial Intelligence
“Artificial intelligence is not about building a mind; it’s about the improvement of tools to solve problems.” — Gideon Lewis-Krause
The first to talk about Artificial Intelligence was John McCarthy in 1956, referring to hardware or software that assumed “intelligent” behaviors. In fact, it is still complicated today to give it a clear-cut definition. Within the macro category defined as “Artificial Intelligence” there are several types of A.I. which have different functions, specifications and complexities that, in turn, need different data, computing capabilities and hardware.
Strong vs. Weak A.I.
The main categorization that can be made concerns the distinction between two macro types of Artificial Intelligence, that are:
- The Strong (or general) A.I. is able to replicate human intelligence through machine learning and is therefore capable of perceiving, classifying, learning and reasoning, predicting and interacting;
- The Weak (or narrow) A.I. on the other hand is focused on specific cases of use. Some examples are Google search, recommendations, or chatbots, which can process a large amount of data to improve and optimize a variety of daily activities.
The landscape of Artificial Intelligence
The landscape of applications linked to Artificial Intelligence can also be defined by a classification based on two principal elements:
- the level of technological sophistication;
- the level of adoption and the scope of application.
Chatbots are an example of simple artificial intelligence: based on Natural Language Processing and applied in many areas. IBM Watson, on the other hand, is based on a much higher level of sophistication but is not yet accessible to a mass market.
The AI ecosystem therefore contains different systems, technologies and processes. The main macro categories that give you an overview are:
- Deep Learning;
- Recommendation engines;
- Predictive analytics;
- Natural Language Processing and text mining;
- Natural Language Generation;
- Prescriptive Analytics;
- Machine learning systems;
- Evidence based systems.
The value of Artificial Intelligence
Artificial Intelligence is relevant because it makes it possible to manage (and solve) a number of complex problems and finds application in most areas.
Research and technological evolution on the theme of A.I. focuses mainly on 5 areas of development:
· Reasoning: the ability to solve problems through logical deductions;
· Knowledge: the ability to possess knowledge of the world, that is, the understanding of entities, events and situations with the relative ability to categorize them;
· Planning: the ability to define and reach goals through a series of actions;
· Communication: the ability to understand language, written and spoken;
· Perception: the capacity of deduction through images, sounds and other sensory inputs.
The value of artificial intelligence comes from the opportunities generated by almost all sectors and markets through technological progress in these five areas.
The role of A.I. in organizations and companies
Increasingly simplified and growing access to a huge amount of data and the use of smart systems has accelerated the adoption of AI-powered technologies within companies and organizations.
Whether it’s predictive analytics, natural language generation, voice / image recognition, or machine learning, artificial intelligence is playing a major role in generating innovation and redefining the way companies operate.
From recommendation systems that suggest to users what to buy based on interests and tastes like Amazon, to IBM Watson, which is transforming diagnostics in the medical industry, and on to self-driving cars or intelligent bots, technological innovation is linked more and more often to the use of AI.
At present, the biggest gap for companies is poor knowledge of the issue, which implies a general difficulty in understanding the applications and uses of these technologies. According to the report “Outlook on Artificial Intelligence in the Enterprise” by NarrativeScience, 88% of companies use AI-related solutions and technologies, but only 38% of them are aware of this.
According to the same report, predictive analytics (i.e. data analysis, statistics and the use of machine learning to analyze current data with the aim of predicting future trends) are the most common application areas of AI diffused within companies (58%), followed by reporting and voice recognition (25%).
The main benefits perceived by companies concern:
- The ability to make forecasts of activities, consumers or business status (38%);
- The ability to automate manual and repetitive tasks (27%);
- The ability to monitor and evaluate the state of the business (14%).
According to Gartner, by 2020, 40% of new business investment in business intelligence and analytics will be dedicated to predictive analytics.
We are at the beginning of a new era no longer focussed on data collection and storage but aimed at creating more usable, more comprehensible, more impactful data.
According to research by the National Business Research Institute in 2016, 38% of companies used some form of A.I. and it is estimated that in 2018 it will be a good 62%.
Companies that give priority to innovation, creating a team and a dedicated budget will also be those that can generate greater value from the adoption of new technologies.
From sales to marketing, from development to customer service to internal management, the potential impact of A.I. in organizations extends to all departments and functions.
Artificial intelligence and related technologies are the next major enabler after mobile, social and cloud. Over the next few years, technologies will be increasingly AI-driven, especially as its major components will be made available in the form of libraries, frameworks, APIs and entire open source platforms, creating abstraction levels that will enable the creation of AI-native applications.
InsideIQUII
For the last Valentine’s Day in IQUII we looked for original ways to surprise our other half.
When it comes to engagement and emotions, whether it’s the relationship between two lovers or a brand and its fans, it’s important to create an experience that is not too obvious in order to win a special place in the heart and head of the right person.
For a new way to write and share emotions on our favorite messaging apps, on Valentine’s Day we created a set of stickers dedicated to all lovers thanks to our framework for the development of Sticker Keyboards for iOS and Android and personalized App iMessages.
Valentine Stickers are available free of charge for iOS and Android and you can find them here:
- The Keyboard for Sticker on Google Play;
- The Keyboard for Sticker on App Store;
- The iMessage App of stickers;
- The set of adhesives for Telegram.
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