Public

Technical and non-technical professionals interested in generative AI approaches that are compatible with digital sovereignty and data privacy.

Pertinence

At a rapid pace, generative AI is contributing to a concentration of knowledge, skills, and power in the hands of a few companies. For companies relying on their services, the dependency and lock-in risk is enormous, with potential financial implications. This is the context in which models with open weights are situated.

Objectifs

At the end of the course, you will be able to:

• Articulate the role of open-weight LLMs within the current AI landscape.
• Analyze the benefits and drawbacks of open-weight vs. closed models for specific use cases.
• Identify deployment options for open-weight LLMs in enterprise environments.
• Define your AI requirements and understand how open-weight LLMs can address them.

Contenu

1. Understanding open-weight models vs. LLM providers
2. Benchmarks: uses and limitations
3. Ethical considerations and data privacy implications
4. Geopolitical context
5. Deep-dive: Apertus, the Swiss Open Source LLM
6. Tooling, frameworks and deployment options
7. Preview: Economics and scalability
8. From use case to requirements for solutions based on open-weight LLMs

Méthodes

Theory and interactive workshop.

Formateurs

The trainer combines extensive experience in data science leadership and the implementation of open-weight LLMs for large-scale organizations.

Prérequis

• No technical knowledge is required.
• Experience in using generative AI is helpful.

Attestation

You will receive an attestation of attendance at the end of the course.

Prix

CHF 600

Date et inscription

2 sessions à 2 heures 45 minutes

Sur demande

Lieu

Genève

Mode

Formation en présentiel

Langue

Anglais

Informations supplémentaire