doppenhe

very cool , i wish it had multi screen mode

Very cool, does `npx hyperparam dataset.parquet` phone home?

Could HyParquet's approach be extended to other data formats beyond Parquet?

nice thanks for sharing

The rapid advancement of large language models (LLMs) like ChatGPT has captured headlines and imaginations. AI systems can now generate amazingly human-like text on any topic with just a few prompts.These behemoths, with their unparalleled capabilities, have necessitated a reevaluation of governance models. As organizations explore integrating LLMs into business operations, it’s crucial to implement governance measures enabling innovation while managing risks. As executives, understanding the transition from traditional machine learning governance to LLM-centric AI governance is crucial.

this makes me happy , I was the PM for that feature :)

This is great, thanks for sharing. Key component in evolving FM based applications is making them feel as deterministic as possible vs probabilistic. Framework like this would enable generating trust in the outputs of these FMs.. exciting.

Author here would love to discuss with the community

hi all creator here. We built this version of our product focused on dynamic data science teams that just wanted to be able to deploy, scale and run their models without worrying about ops. Some more details:

https://algorithmia.com/developers/teams

Deployment, inference and management can participate in this as well!

Here is the missing part for a total e2e solution: https://github.com/marketplace/actions/algorithmia-ci-cd

{disclaimer, we built this Github action}

It's not used for private models. Its meant to make sure if someone builds an application based on your models you won't yank that version from under them. If you never expose your model (for profit) you can delete at will and we have no rights.

Algorithmia here . What are you concerned about license wise? You own all ip always. There is some restrictions if you choose to commercialize on our service (mostly guarantee you won't take it down on users). System was built for this. Happy to answer questions

curious what kind of infrastructure have you built for deployment, serving and managing models?

Algorithmia | Sr. Software Engineer - Platform | REMOTE + ONSITE | Fulltime

Algorithmia is "DevOps for AI". The Algorithmia engineering team is responsible for building the Algorithmia platform, a highly-available distributed platform that runs the public algorithm marketplace on Algorithmia.com as well as large AI/ML workloads for our enterprise customers. Platform engineers build features and work with cloud providers to ensure our system is the most stable, highly-available, and feature-rich platform for AI/ML. Our stack includes Kubernetes, Docker, and various Java (Scala) microservices and backing stores.

https://algorithmia.bamboohr.com/jobs/view.php?id=34

please do!

stop by any time, we always like talking to developers.

live demo: https://algorithmia.com/algorithms/zeryx/openimagesDemo

colorization applied to video: http://demos.algorithmia.com/video-toolbox/

there is nothing that requires you to use GCP, Google ML services or anything along those lines. This was a surprise but true.

source: i am part of the Algorithmia team.

this doesn't solve the biggest problem with multi-cloud which is data egress though. Even if latency is acceptable you would get killed on data transfer for any significant amount of data.

am I missing something?

Mashape folks are fantastic. Remember augusto pitching in 2011. Cant help but be happy for the guy. Part i dont understand is how A16z funded Rapidapis.com and now Mashape. Is it not a clear conflict?

Have you tried using Algorithmia for this? We get around a lot of these limitations that Lambda has (you can also call us from lambda and we can host most of your DL models https://algorithmia.com/developers/algorithm-development/mod...).

Disclaimer: work @ algorithmia

So did we. Rasberry pi, spotify, facial recognition (using cmu open face) and a couple of other components...http://blog.algorithmia.com/hey-zuck-we-built-your-facial-re...

month

~20k

If I have to take a wild guess. It's associating IBM/Third Reich with how Facebook and Twitter have enabled Trump to become president through distribution of false news and uniting the alternative right.

Enterprise sales are hard.

They announced this a couple of weeks ago... im confused: https://cloud.google.com/endpoints/

ex Excel PM. There is a project that was between the Excel team and the high performance computing team at Microsoft for exactly this purpose. Not surprisingly mostly used by investment banks and insurance companies. (https://msdn.microsoft.com/en-us/library/ff877825(v=ws.10).a...)

Congrats to the reflect team, great to see the journey from TechStars to seed round.