josh-sematic

15 ms·

211.
SafeCoder (On-Prem Copiliot by HF)(huggingface.co)
1 points by josh-sematic 3y ago|0 comments
212.
Apple and Amazon are quieter about AI ambitions(emergingtechbrew.com)
1 points by josh-sematic 3y ago|0 comments
213.
Robotaxis can now operate 24/7 in San Francisco(axios.com)
2 points by josh-sematic 3y ago|0 comments
214.
OpenAI Launches GPTBot with Details on How to Restrict Access(searchenginejournal.com)
2 points by josh-sematic 3y ago|0 comments
215.
OpenAI launches webcrawler GPTBot, and instructions on how to block it(mashable.com)
1 points by josh-sematic 3y ago|0 comments
216.
Burn – A Flexible and Comprehensive Deep Learning Framework in Rust(github.com)
2 points by josh-sematic 3y ago|0 comments
217.
Understanding and Evaluating Vector Databases in Production(mlops.community)
2 points by josh-sematic 3y ago|0 comments
218.
Understanding Embeddings(huggingface.co)
2 points by josh-sematic 3y ago|0 comments
219.
by josh-sematic 3y ago
Only 2 hard problems in computer science: (1) cache invalidation (2) naming things (3) off-by-one errors :-D
220.
by josh-sematic 3y ago
Yes, I'm a huge fan of Huggingface. There's a tendency to always distrust anybody that is a company that is trying to make money. But "makes some money with some of their product offerings" != "is incapable of produ
221.
by josh-sematic 3y ago
FWIW, this is not proprietary, it's all FOSS. And hopefully there's something interesting in there even if you don't use any of the tools mentioned.
222.
by josh-sematic 3y ago
I think it depends a lot on the scale of what you're trying to do, whether it's worth it or not to invest in OSS/DIY. If you're one person looking to do a "one off" task like organizing some of your own music,
223.
Tuning and Testing Llama 2, Flan-T5, and GPT-J with LoRA, Sematic, and Gradio(sematic.dev)
98 points by josh-sematic 3y ago|22 comments
224.
Sematic/Ray as an ML platform combo(sematic.dev)
6 points by josh-sematic 4y ago|0 comments
225.
by josh-sematic 4y ago
The way packaging is designed to work in Sematic is for us to hook into your existing dependency management solution to determine what your dependencies are, then build a docker image for you based on those. As you point out, right now we o
226.
by josh-sematic 4y ago
There are several differences, but I'd say these are some of the main ones: UI: whereas Metaflow provides the ability to build your own result visualizations explicitly in your workflow (via their "cards" feature), Sematic ma
227.
by josh-sematic 4y ago
Glad it looks interesting to you! Regarding running a Kubernetes cluster, that's only required if you want the steps in your pipeline to all execute in their own containers. If your workflow is such that everything can run on a single
228.
by josh-sematic 4y ago
I'll confess I haven't used Tecton myself, but reading through their documentation it seems that they are much more focused on ETL style data pipelines with the final output being to a feature store. Whereas Sematic is looking at
229.
by josh-sematic 4y ago
MLFlow in general focuses more exclusively on the "lineage tracking" pieces alone. I.e. registering your models and such. They do have an experimental pipeline product as you mention, but it's different in a number of ways. I
230.
by josh-sematic 4y ago
Yup, most of these tools fall into the definition of "orchestration" in one way shape or form, though not all of them are targeted at Machine Learning pipelines, and not all of them focus as much on the low barrier to entry space