devbas

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?

The introduction seems to have AI sprinkled all over it: ..we embarked on a significant journey, ..in this monumental upgrade.

Archive link: https://archive.li/OmQIU

Beginners question but what is its purpose?

Personally I really enjoy doing analog photography. As the feedback loop is very long, technique is important. Also, since the number of pictures is limited, I always have to ask myself the question: is there actually a picture here?

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)

So sorry to hear about your losses. Sending you a virtual hug through cyberspace.

Because the syntax is relatively complex and it is difficult to judge which endpoints and definitions to use.

Location: Amsterdam

Remote: Open to it

Willing to relocate: Yes (preferably not USA)

Technologies: Python, MLlib, Scala, JavaScript, PostgreSQL, Cassandra, Spark, RabbitMQ

Résumé/CV: https://www.linkedin.com/in/bastiangeneugelijk/

Website: https://bastiangeneugelijk.com

GitHub: https://github.com/devbas/

Email: bastiangeneugelijk [at] me [dot] com

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Machine Learning engineer looking for a new adventure in real-time streaming analytics.

Did we hug it to death? Got an error:

> Could not reach Cloud Firestore backend. Backend didn't respond within 10 seconds.

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 :)

It is very likely to be victim of survivorship bias here. It's not that there were no bad houses back in the day, they are just not here anymore. So it is easy to believe people built better houses in the past.

Sounds like anecdotal evidence to me so I rather put my faith in the statistics.

It doesn't work for me in Safari on Mac

Cant read this article, Medium shows me to signup for an account.

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!

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.