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LexSiga

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I came here to talk ML and chew bubble gum. And I am all out of bubble gums.

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www.hopsworks.ai 24d ago

Agents Are the New Product's Interface

LexSiga
3pts0
www.hopsworks.ai 28d ago

Rolling Aggregations for Real-Time AI

LexSiga
2pts0
www.hopsworks.ai 28d ago

Agents Are the New Product's Interface

LexSiga
3pts3
sakana.ai 29d ago

Sakana.ai releases a model competiting with Fable

LexSiga
2pts0
www.onehouse.ai 1mo ago

Databricks Iceberg Support Has a Catch. It's Called Unity Catalog

LexSiga
2pts0
github.com 3mo ago

Ducklake Demo

LexSiga
1pts0
www.hopsworks.ai 4mo ago

Shift-left or shift-right? Fresh rolling aggregations for real-time AI

LexSiga
1pts0
www.hopsworks.ai 4mo ago

Product Needs to Be a Runtime for Agents – Be a Container, Not a Wrapper

LexSiga
1pts0
www.hopsworks.ai 4mo ago

Don't Be a Wrapper, Be a Container

LexSiga
1pts0
karanbansal.in 4mo ago

Claude Code LSP

LexSiga
77pts39
www.hopsworks.ai 5mo ago

Vibe migrating 1k pages and losing 80 percent of our traffic

LexSiga
1pts0
www.hopsworks.ai 5mo ago

Vibe Migrating over 1000 Pages and Losing 80% of Our Traffic

LexSiga
2pts0
github.com 9mo ago

MinIO stops distributing free Docker images

LexSiga
733pts555
www.rondb.com 10mo ago

4221 Python Clients, 100M Ops/SEC, 3ms P99: Make REST APIs Work for Real-Time ML

LexSiga
1pts0
grugbrain.dev 1y ago

Grugbrain.dev - A layman's guide to thinking like the self-aware smol brained

LexSiga
3pts0
www.cnbc.com 1y ago

Snowflake to buy database startup Crunchy Data for about $250M

LexSiga
1pts0
www.hopsworks.ai 1y ago

The 10 Fallacies of MLOps

LexSiga
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www.hopsworks.ai 1y ago

Migrating from AWS to a European Cloud – How We Cut Costs by 62%

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143pts66
www.hopsworks.ai 1y ago

What Is vLLM – Dictionary Entry (Hopsworks)

LexSiga
1pts0
www.hopsworks.ai 1y ago

Fallacies of MLOps

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1pts1
www.hopsworks.ai 1y ago

Migrating Hopsworks to Kubernetes

LexSiga
2pts0
practicaldataengineering.substack.com 1y ago

The History and Evolution of Open Table Formats

LexSiga
2pts0
github.com 1y ago

Query Snowflake tables locally without any need for a running warehouse

LexSiga
1pts0
www.dbtsai.com 1y ago

Petabyte-Scale Row-Level Operations in Data Lakehouses [pdf]

LexSiga
2pts0
9to5mac.com 1y ago

TMobile fined $60M for unauthorized access to data: the largest fine of its type

LexSiga
60pts18
voltrondata.com 2y ago

Performance Benchmarking on GPUs with Theseus – GPU Query Engine for Petabytes

LexSiga
1pts0
neo4j.com 2y ago

ISO GQL: A Defining Moment in the History of Database Innovation

LexSiga
3pts0
arxiv.org 2y ago

We have no idea how models will behave in production until production

LexSiga
38pts3
www.hopsworks.ai 2y ago

Doubling Down on Open Source: How RonDB Upholds the Principles Redis Left Behind

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2pts0
www.hopsworks.ai 2y ago

Function Calling in LLMs

LexSiga
2pts0
Claude Code LSP 5 months ago

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.

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.

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.

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.

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.

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...

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.

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.)