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devbas

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I believe there is a big opportunity for LLM guardrails due to the non- deterministic nature of the Transformer architecture.

However, the just announced Claude Cowork still warns humans to stay in control: https:// claude.com/blog/cowork-research-preview I assume this is because their non-human guardrails are not good enough yet to fully validate the output of an LLM.

What non-human guardrails does Axonflow employ to enforce a policy rule with X% confidence on a prompt / LLM output?

I usually consider programming books as a reference and don't "read" them. My way of getting value out of these books is remembering the high-level contents and diving deeper when there is the need (e.g, a coding problem that I need to take care of)

Great idea! Did you deploy a speech-to-text pipeline to achieve this? I always thought it would be relatively expensive to do podcast-to-text translation at scale (compared to the gains) but maybe I just didn't optimize it well enough :)

Writer here. As someone who spends a lot of time in public transport I am always disappointed in current public transport planners, since they are ‘static’ and can’t handle well disruptions.

I created the public transport assistant concept to explore the possible advantages of live location data within public transport and to investigate the possibility of creating a more dynamic route planner. For example, once we know in which train a passenger is, we can check when this train will arrive at a certain station and act upon it.

My next step will be to create a minimum viable product that encapsulates a basic route planning system (e.g. OpenTripplanner) and the described vehicle classification system.

Let me know what you think, feedback is always welcome!

JSON Schema 8 years ago

Shameless self plug here, few months back I created a project https://www.contenttagger.com that gives you hints for Schema tags based on a parent Schema attribute. You can also validate it with Google devtools + Facebook graph.

ContentTagger automatically shows you the 'child' attributes from a chosen domain or range attribute so it becomes more easy to select something. On top of that I'm able to pass a link with the code to Google Structured Data Developer console and Facebook Graph, so easy testing!

In the future I want to add more schemas (currently only schema.org) and create a library which you can use to query linked data yourself with SparQL.

Stack: Node, MongoDB, React

If you have any questions or feedback let me know so I can make the product even better, thank you!