Phoenix RETx

For researchers and for undergraduate and postgraduate students who already use artificial intelligence in their academic work without an explicit criterion for where it helps, where it contaminates and what must be disclosed.

Who it is for and what problem

What it is

What it includes

• Where artificial intelligence contributes to research and where it introduces a bias that cannot be traced afterwards.
• Traceability of evidence: how a claim produced with a model's help holds up, and what to do when it does not.
• The three pillars of DAL OS — Creative Destruction, Antifragility and AI Literacy — applied to research work, not to running a company.
• Disclosure criteria, so the work is defensible before a committee, a board of examiners or an editor.

How we work

• No lock-in: nothing we build ties you to us or to a vendor.
• You choose the stack, and if you already have one, we work with the one you have.
• Every phase passes through an approval gate of yours before the next one starts.
• And the capability stays inside your company: if you still depend on us when we finish, the work is not done.

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Next step

If you want to talk after reading it, write to us.