When worlds collide: How will generative AI change the way we design and build software
What if you could verify every claim an AI makes? Discover how explainable, sovereign AI is building trust in the systems that matter most.
#1about 2 minutes
Introducing Aleph Alpha and its European AI vision
The founder of Aleph Alpha discusses the company's journey and its positioning as a European player in the generative AI space.
#2about 1 minute
Focusing AI on high-stakes enterprise use cases
Aleph Alpha targets critical B2B sectors like government and finance where data sovereignty and reliability are more important than consumer applications.
#3about 2 minutes
Tracing information flow for true AI explainability
A proprietary manipulation of the attention mechanism allows tracing factual claims back to specific sources, including identifying contradictory information.
#4about 4 minutes
Offering a full-stack AI solution for on-premise deployment
The platform is a complete, end-to-end stack that can be deployed in isolated, on-premise environments to ensure customers have full control and data privacy.
#5about 2 minutes
Building an AI talent hub outside major tech capitals
Locating in Heidelberg provides access to strong engineering talent from nearby universities and a unique company mission that attracts inbound tech applicants.
#6about 2 minutes
Arguing against heavy EU regulation on AI
Heavy regulation could divert critical resources from innovation to compliance, slowing Europe's ability to compete and secure its digital sovereignty.
#7about 2 minutes
Balancing open source contributions with commercial IP
Contributing to the community through open source is vital for reproducible research, but it must be balanced with protecting the IP needed for monetization.
#8about 3 minutes
Partnering on hardware for next-generation AI models
The partnership with Graphcore aims to overcome the limitations of GPUs for inefficient dense transformers by developing hardware for more modular, brain-like architectures.
#9about 2 minutes
Bridging the gap between language models and software
The next frontier in software development is creating a robust interface between stochastic large language models and structured, symbolic software systems.
#10about 12 minutes
Prioritizing societal challenges over AI doomsday scenarios
The more pressing danger from AI is not existential risk but the rapid disruption to knowledge work and the challenge of adapting our societal values and institutions.
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