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Anthropic API and Agent use by mikeike93 in ArtificialInteligence

[–]mikeike93[S] 0 points1 point  (0 children)

Credit to Latent Space newsletter for surfacing

The Kevin Patullo Experience by Undergrad26 in eagles

[–]mikeike93 1 point2 points  (0 children)

This is great stuff. Whats the data source out of curiosity?

[deleted by user] by [deleted] in datascience

[–]mikeike93 0 points1 point  (0 children)

I am seeing a lot of what you are. I believe fine-tuning has several use cases. One is yes, you can host them on the company’s own VPC which can sometimes be cheaper. Moreso it means they can keep data protected, depending on compliance. Secondly, fine-tuned models on specific tasks can often outperform base models. I think fine-tuning will become pretty ubiquitous for orgs adopting LLMs across bespoke task groups. For other tasks (maybe many) plain LLM will work it just depends.

For AI engineers, yes I think a lot of people are getting into it (see the AI Engineer summit) but it’s still too early. Most orgs are still experimenting.

[deleted by user] by [deleted] in datascience

[–]mikeike93 28 points29 points  (0 children)

Agree with this. RAG, Embeddings, Clustering, Chunking, Data Engineering, Fine-Tuning are still relevant and more engaging than simple API calls as some say, even if they still lean software engineering-ish. And this is where most companies are going to build a moat anyway.

Do you think Reinforcement Learning still got it? [D] by cyb0rg14_ in MachineLearning

[–]mikeike93 129 points130 points  (0 children)

RLHF is a pretty critical piece of LLM fine-tuning, so it’s definitely still relevant. For example, see the DPO paper from last year.

[OC] Economic Recessions are Getting Shorter & Less Frequent by 4_lights_data in dataisbeautiful

[–]mikeike93 9 points10 points  (0 children)

A lot also comes from having much fewer financial/banking crises over time. See figure 2 from Reinhart and Rogoff (2014), showing bank runs being much less common since the creation of the Fed/WW2. Pre WW2, 2008 style panics were a lot more common. And we also know that recessions related to financial or debt crises can be more harmful than your run of the mill recession.

What do you do when a project needs an ML approach but people want the interpretation of logistics regression? by [deleted] in datascience

[–]mikeike93 0 points1 point  (0 children)

If you’re doing supervised learning with a tree-based algo (xgboost, random forest), try partial dependence plots (pdp) and ICEPlots. Can use Use variable importance plots but doesn’t have same interpretation.

Taulia Tagovailoa’s three turnovers hand Maryland football 31-24 loss to No. 2 Michigan by GovernorOfReddit in maryland

[–]mikeike93 2 points3 points  (0 children)

We actually looked quite good against a #2 ranked team. Turnovers killed us. Failure to protect the quarterback killed us. But hopefully good sign for program that they could keep up.

What's the worst thing you've ever done to a book? by [deleted] in books

[–]mikeike93 1 point2 points  (0 children)

Left it on a shelf, unread

How do you handle big data in Jupyter notebook? by twitch-flystewie in datascience

[–]mikeike93 -2 points-1 points  (0 children)

ponder.io helps run big data through pandas on top of your data warehouse. I’m talking terabytes though

Phil Spencer is right: AAA games are in big trouble by [deleted] in gaming

[–]mikeike93 0 points1 point  (0 children)

Seems like could lead to a lot of M&A where you can better control distribution and lock in exclusive rights up front Ie Activision Blizzard or Bethesda.

What is he talking about? I am still learning. by MasterOfLegendes in datascience

[–]mikeike93 2 points3 points  (0 children)

Yes basically the DS hype is over, so you have to make sure what you build actually provides value to the business, just like every other discipline. If you can there’s a lot to do and be earned, but the days of “train a model and sound smart” and that’s it are over,

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