Disaitek is building cutting edge technologies on natural language processing to help enterprises leverage their conversational flows and make their transformation faster.
Regarding AI, Disaitek area of expertise is the use of deep learning methods for NLP tasks. More specifically, we use neural networks that have been trained in an unsupervised way on a huge corpus of documents and transfer their knowledge to other problems. In order to do this we use state of the art semi-supervised learning algorithms and create proxy tasks to get the most value possible out of our data.
Disaitek has been contributing to implementation in PyTorch of GPT and BERT, large pre trained model that capture deep information about syntax and grammar of languages.
Disaitek has been labelled as a Young Innovative Entreprise (Jeune Entreprise Innovante) by the French administration. It’s a recognition of our R&D program and of the innovation that we want to bring to market.
Transformation is a nightmare for most C-Level. Budgets that are allocated to IT and other services do not drive to the expected performance. Huge amount of money is wasted which can lead to dramatic outcomes for enterprises. Among the long list of root causes, we are tackling two majors ones.
Part of the problem is that we still rely on human on most non cognitive processes. At Disaitek we are building a solution to help people focus on their cognitive tasks. And we do it along a fundamental objective: reduce the amount of workflow changes needed to use our application. We do not want to add more transformation on transformation.
AI is about to be a cog in most IT environments and it is still considered as a black-box system. How can we trust what is not understood? It is why we are building expertise to understand AI in action, explain their decision, analyze their biases and test their robustness in an adversarial setup.
2nd largest European legal publisher
Disaitek has signed a strong partnership with Lefebvre Sarrut
This partnership allowed us to develop and train our deep learning models on a huge volume of real data produced in 5 different languages (English, French, Dutch, Spanish and Italian). Beyond that, ELS hosted Disaitek prototype in order to collect valuable feedback from end users.
Associated member Paris Saclay
Disaitek announced the signing of a major research partnership with @ENSIEE, an engineer school associated to Paris Saclay. This agreement, one of the very first of this kind in France, will focus on research of vulnerabilities of machine learning systems to malicious attacks.
Master of Civil Engineering
20 years of experience in consulting and project management.
Previously founded a Fintech which was merged with an ETI as for exit.
Concerned about compliance and regulation, he was also chairman of the supervisory board of a financial institution under FCA regulation.
Passionate about artificial intelligence and computational neuroscience. Anthony passed five certifications with Stanford university and university of Washington.
He’s in charge of the product roadmap and business development.
PhD Comp. Science
Passionate about artificial intelligence, he wrote several blog posts to explain how deep learning works and build awareness around security issues. He is a member of Intel Innovator program and was asked to talk in 3 meetups in Europe to present privacy and security concerns on machine learning. He is also specialized in NLP and is an active contributor to multiple open-source projects such as popular deep learning libraries and implementation of research articles.
He is in charge of research & development on Deep Learning stack.
PhD Computer Sciences, Mathematics or Physics:
Doing research on unsolved NLP tasks for now. Especially around abstractive summarization
We want to leverage continuous learning from users to optimize our deep learning stask and to personalize the way the systems act regarding the user habits
We want to build great experiences for our users and let them feel comfortable with our solutions. Great user experience for great people (technology .js)
Disaitek has developed strong expertise while driving R&D works….We propose to share it!
Meet UP has become a nice way to gather people and expert pleased to explain and share insights on lots of discipline.
Traditionally this meeting takes place in a remote place, gathering people from different horizons (employees, independent, founders, VC, academics…). Usually these people act outside of their work hour and independently from their company or others.
We think company must leverage this kind of activity and bring it inside your company
Why: It creates condition to innovation: Giving new insights to employees, they can imagine applicable solution on their work and in the process they are involved in
It creates conditions to remove silos inside the company. The time of the event, people can meet people from other services, create new internal links, and find new way to collaborate towards customer,
It’s also an opportunity to identify specific talents, and imagine new opportunities for internal mobility,
Finally, it can help building an innovative and positive image of the company to the employees, which in the current period of talent shortage is valuable.
Disaitek offers to bring valuable meet up inside your company. Depending on the level of the attendants you program to invite, several agendas are possible.
If you are interested in bringing information to your employees on breakthrough technology, if you want to experiment new engagement forms with them, contact us. You just have to provide snacks and refreshment and we handle the presentation for free!
Meetups can be done either in English or French.
Introduction to fundamentals of Machine Learning
Ok, what’s really behind the scene?
All kind of employees curious about this phenomenon and who try to find new tools to increase productivity in their work.
Give better intuition about what covers Machine learning
Categories of machine learning
How to train a machine learning model
When it comes to evaluate the precision of your model
Relevant frameworks of machine learning and AutoML
Bias in machine learning
Machine learning for NLP
Recognize context in your day to day job where machine learning can apply
Help to come up with relevant use cases suitable for your company
Unlock the potential of your Data
Hard to have enough labelled data?
Data scientist, people involved in machine learning development and concerned by the low quantity of labeled data.
How to train deep learning models on language modeling helps capturing syntax and semantic of languages
How to use to transfer this knowledge to other tasks
Multi-task learning: principles
How multi-task learning help models generalize better
Principles of semi supervised learning
Example of Virtual Adversarial Training to reduce the need of labeled data
New ideas to tackle existing problems
Machine Learning privacy and security
How really secure and ensure your models respect customer privacy?
All people involved in machine learning development
Key dates for this discipline
Principles of security and privacy of machine learning
State of the art in machine learning security and privacy
Principles of prevention. security and privacy by design
First evaluation of the risks of currently deployed models or systems