CSR

Personalising digital interfaces over time with continuous learning of usage habits

- There is such diversity between services, interfaces and the people using them that managing all of this poses a major challenge in the field of digital accessibility.
- Users are all different. Some have no particular constraints but have usage habits and preferences. Others, such as people with disabilities or seniors, may have, in addition to those habits, constraints when using a digital service.
- These constraints can be very diverse, of a perceptual nature (visual, auditory, tactile), of a motor nature (pointing, manipulation, speech) or cognitive (comprehension, reading). However, it is hardly conceivable to anticipate all of them when designing a service.
- What if any service, or any interface, could continually adjust to users’ usage habits and constraints? This is where a Machine Learning algorithm can prove highly relevant.
Read the article

Datacenters: how should they be cooled in the era of AI?

Read the article
A businesswoman stands on a balcony overlooking a large city. She wears a white shirt and a black blazer, looking intently at her smartphone screen.

Geolocate objects indoors without energy supply: ambient IoT

Read the article

The carbon impact of AI: Orange’s navigator for the net-zero carbon transition

Read the article

Boosting women’s involvement in solar energy in Senegal: a key factor for society

Read the article
An individual is working on the inside of a phone, using a tool to manipulate electronic components. A wooden table is visible, with spare parts next to it.

Say goodbye to disposables; hello to circular electronics

Read the article
Various electronic devices, such as phones and tablets, along with internal components, are arranged in bins.

Electronic waste: innovation to kickstart the circular economy

Read the article