Where are we really in Artificial Intelligence?

technology 3 scaled
technology 3 scaled

AI is a catch-all term that fuels fantasies but does not stick to reality, because what convinces scientists, for now, is only machine learning, a small part of what will make up the AI of tomorrow. Today, learning systems are becoming remarkable and allow us to achieve feats that we thought were impossible not so long ago, such as correctly translating languages, recognizing speech, or reading medical images.

In some areas, machine learning has taken precedence over humans. Take the game to go as an example. If it takes a lot of intelligence for a human to play it, 360digiTMG produced by DeepMind, You can automate your business process with artificial intelligence with the help of ai training in Bangalore . Memory, deduction, anticipation, self-learning, acting out, analysis of envisaged and lived situations and the correction of errors made to improve one’s performance is not intelligence but performance.

Is AI a threat or an opportunity for our societies?

Beyond the buzzword of the moment, the underlying technologies such as machine learning, more commonly known as Machine Learning, and its different versions represent a real technological breakthrough. Concrete applications will change our lives in the years to come, for example in the automobile with the autonomous car, in health with early detection, or finance for the fight against fraud. But today the frenzy of building systems integrating AI is very often without taking sufficient account of cyber risks.

Let us never forget: if a machine can detect the origin of a threat, the extent it could take, the flaws of a complex system, identify the weak points and bad reflexes of users, it is also capable of creating an attack and by passing the defense systems put in place to counter it.

On the one hand, AI can make cyberattacks (distributed denials of service, botnets1, ransomware…) more powerful and efficient. The first consequences of the automation of cyberattacks are already being felt, whether they attack critical infrastructure or seek to manipulate public opinion. In October 2016, a distributed denial-of-service attack on the Mirai malware transformed Internet-connected objects into botnets, remotely controlled bot networks, besieging the American DNS provider Dyn and the French host OVH and causing difficulties. access to a large number of websites. Social bots with political aims can also imitate human behavior on social networks to influence users at key political moments.

On the other hand, AI technologies can facilitate and improve the detection and mitigation of cyber threats. More and more applications integrate AI techniques and in particular Machine Learning to better identify threats and anomalies. Machine Learning allows machines to reproduce and recognize behaviors given from examples. The machines are thus able to process large amounts of data in a reduced time and to recognize the smallest changes in their environment, differentiating in real-time the normal behaviors from those which represent a threat.

Why is AI so worrying?

If their main concern is the impact that this technology will have on their professional life, the consequences of the digitalization of their environment in the personal sphere also worry them. The logic is implacable: the more the population will depend on the connected devices, the more they could be misused by hackers, the more the users will be vulnerable and exposed to cybersecurity problems.

According to the study The Global State of Information Security by PwC, the vast majority of people fear the piracy of the technologies around them: 36% fear an interruption in the operation of machines, the misuse of their sensitive data, an attack on property physical, 32% a threat to product quality and 25% risk to their lives.


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