1. In the Diagnosis, Monitoring, and Treatment of Diseases

Machine learning, a branch of artificial intelligence, stands out for its ability to analyze various data sources and detect complex patterns, as noted by Van der Schaar, who leads the eponymous lab at the University of Cambridge. This approach is crucial in fields like personalized medicine, where it can facilitate early diagnosis of diseases such as cancer.

In oncology, machine learning has found numerous applications in analyzing medical images and discovering patterns indicative of the disease. But its usefulness goes beyond that, as it can identify risk factors, whether genetic, lifestyle-related, or caused by environmental agents, before the disease manifests.

Moreover, this technology can intervene in the early stages of the disease by defining when and how preventive treatments should be administered. This is especially useful for personalizing medical care and optimizing outcomes for each patient.

A key aspect is artificial intelligence's ability to learn from a wide range of data, including different patients' responses to various treatments. This ability is difficult for doctors to achieve due to the complexity and diversity of available information.

Van der Schaar highlights a collaborative effort between his team and doctors from several countries, focusing on hospitalized patients who experienced sudden deterioration and needed to be transferred to intensive care units. This type of analysis demonstrates the potential of artificial intelligence to improve medical care and save lives by identifying critical situations early.

"Early identification of disease and patients who will require ICU access is important, and we demonstrated that artificial intelligence can identify up to 24 hours before doctors which patients will require ICU admission and what type of intervention they will need."

2. Data Collection to Help You Reach a Place or Understand What Clients in a Market Need

The artificial intelligence behind Google Maps uses data to provide updated traffic information and suggest alternative routes, sometimes even avoiding traffic jams altogether, as detailed in an article by the company titled "9 Ways We Use AI in Our Products."

This service helps drivers find the most efficient routes to their destination, whether by car or on foot. Google Maps uses a system that has learned to read street names and addresses from over a billion Street View images.

In addition to transportation, artificial intelligence is having a significant impact on the labor market, as explained by Rus. AI-based robotics and machine learning technologies enable routine tasks to be delegated to machines, increasing efficiency and productivity. This frees up time for people to focus on more cognitive aspects, such as critical thinking and creative analysis.

Artificial intelligence also provides data on customer needs and preferences on social media, as well as supply chain requirements. This data allows for forecasting demand and improving the efficiency of product and service delivery.

Additionally, this information helps to better understand how consumers use products and enables the offering of more personalized services based on individual needs.

3. Breaking Language Barriers by Enabling Automatic Translations

Google Translate uses a combination of optical character recognition and a translation system trained with millions of translation examples available on the web, as explained by the company in its article "13 Ways You Use Artificial Intelligence in Your Daily Life," published on its blog.

Moreover, the Google Assistant allows conversations in more than a dozen languages.

According to Rus, these translation technologies are part of the field of natural language processing or large language models.

These systems require vast amounts of data, whether text or other types of information, to function effectively. To illustrate this process, Rus invites us to think about object recognition in images: for an AI system to automatically recognize objects such as a phone, a shelf, or a chair, it needs to be trained with many examples of these objects.