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LexSiga

474 karma · joined March 18, 2020

I came here to talk ML and chew bubble gum. And I am all out of bubble gums.
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LexSiga··on Agent-Manager: A Tmux TUI for Running Claude Code, Codex and OpenCode
also - not everything needs to be unique. I think that is a leftover of some VC mind washing "you need a moat!". Many things can be great, and do somewhat similar things.
LexSiga··on AI content is everywhere on social media, especially LinkedIn
A social media without penalising mechanism will always favour spam.
LexSiga··on Agents Are the New Product's Interface
Damn them vibe commentators :s
LexSiga··on Agents Are the New Product's Interface
All of the above, I believe.
LexSiga··on I've sold out
Indeed. Also what a very annoying website.
LexSiga··on Claude Code LSP
since its flagged - gotta comment; I am not the author of the post. I was reading it in passing and thought it was interesting enough to submit. Indeeed did not paid enough attention as to how much "ai written" it was.
LexSiga··on European Cloud, Global Reach
works for me in the baltics.
LexSiga··on Migrating from AWS to a European Cloud – How We Cut Costs by 62%
The actual migration, a day or less. Now there was a 2-week sprint for testing and validating backup and restore before doing the actual migration. At the non-engineering level (management and such) of course there was a review and consideration time as well.
LexSiga··on Migrating from AWS to a European Cloud – How We Cut Costs by 62%
We are already available in Europe; it is just our infrastructure that is currently more us-centric in that sense.

Eventually as the demand grows we will of course deploy in EU region to improve the availability.

If it is more of a sovereign aspect; we are deployable on kubernetes;one can already use our installer on OVHCloud and deploy on a European region.

LexSiga··on Migrating from AWS to a European Cloud – How We Cut Costs by 62%
Part of the team here - Happy to discuss this further if you have any question about the move.
LexSiga··on The Big Dictionary of MLOps
So I guess this opens the question of which part really covers MLOps; I would love to see those but some strike me heavily as being part of the model development and training. I somewhat, in my simple mind always got stuck on the Ops in a “how to keep the system rolling” kind of way.
LexSiga··on Show HN: PizzaGPT – ChatGPT clone accessible from Italy
Life finds a way
LexSiga··on MLOps Without Infrastructure – Serverless ML
In a nutshell; no infra means infra but not managed by yourself; so you would focus on all the different ML pipeline in the journey (feature, training, inference) to create a real operationalised ML system.
LexSiga··on “DevOps is a culture, not a role”
Set of general principles and practices in an organisation.
LexSiga··on Don't build ML infra, build ML services in mins w Serverless ML – a course
I’ve participated in the first two lectures: it’s perhaps the most straight forward approach that I had to get an end to end ML service running.
LexSiga··on Testing feature logic, transformations, and feature pipelines with pytest
While this article is on offline testing with pytest we are also preparing a second one on continuous integration tests.
LexSiga··on Europe’s Digital Decade: digital targets for 2030
Well, all good and nice, but we are so far behind on data infrastructure, development, and investment that I do not know how realistic it is to set those targets when the basics are not here.
LexSiga··on [dead]
ok.
LexSiga··on The Ad-Based Internet Is About to Collapse
I am absolutely convinced by the argument around the needs and such, much less about the imminent collapse, Fraud and unreliability of the digital ads is not new, it is not even a bug, it is a feature of the people who work in advertising; they oversell the capabilities because there is a lag between old and new guard in that field. Simply put, it is only but a decade old, and the people who taught and got taught did not know how to handle this new tool resulting in a big divide between expectations and reality that has hurt (justifiably) the whole industry and will continue to hurt. But this is it not enough in my opinion to call it over.
LexSiga··on Open Source Design – community of designers and devs for open design processes
That is arguable, at best it is functional enough so that people can use it, at worst it is not functional for squat and it is mostly dominant because of the incubator attached to it.

In fact I wonder the rate of drop vs new user retention as it is hard to follow a thread, there is no clarity in the headline differentiations... it is really a tough argument to say that it lacks nothing and / or is a good example of function over design...

LexSiga··on Open Source Design – community of designers and devs for open design processes
I did not realized that aesthetic was not correlated with function. Probably a clear visual understanding to the actual value of something is meaningless, I suppose.
LexSiga··on Open Source Design – community of designers and devs for open design processes
I love that this gets some love. I found it odd that the website is in itself not very pretty (like... that kind of goes against the main selling point of the community).
LexSiga··on Google Drive is a sad joke, don't use it for business
That is a bit disingenuous; it maybe has issues in syncing with folders or such, but honestly when you work directly in the drive for your document creation and sharing and co-authoring, its a breeze.

It is good for certain use cases, and bad for others, what a big surprise, now lets not generalize.

LexSiga··on Machine Learning Engineer Guide: Feature Store vs. Data Warehouse
You are not wrong on the buzzword, but you are not absolutely right if you suggest that it is merely that; this is a recurring question and interrogation in that specific area.

The fact that it happens to be kinda buzz worthy is a collateral aspect: everything that answers what some people wonder and that is not yet answered plainly, is.

(and I mean, the first on the front page at this very second has : "We hacked apple" in the title.)

LexSiga··on How to build your own feature store for ML
Some sad soul just lost their job. Also thanks; I fixed it.
LexSiga··on How to build your own feature store for ML
As this topic will inevitably become more trendy find some some additional interesting resources on the subject as well:

- https://www.quora.com/What-are-the-implementation-challenges...

- http://featurestore.org/ (a list of -some of- the available feature stores)