antti909

7 ms·

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Show HN: MaxAI answers questions about how PostHog works(github.com)
1 points by antti909 3y ago|0 comments
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by antti909 3y ago
Thanks for mentioning Haystack :)
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by antti909 3y ago
Heh, you seem to keep asking :) You could also ask in our community Discord, tbh, there are people who have been trying both.. There's definitely a ton of great things about langchain, so I'd be curious myself!
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Show HN: Semantic Search on AWS Docs(github.com)
38 points by antti909 3y ago|14 comments
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An LLM-powered GitHub end-of-day bot(github.com)
3 points by antti909 3y ago|0 comments
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A full-featured SQL client for Jupyter(github.com)
2 points by antti909 3y ago|0 comments
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by antti909 4y ago
To be precise - I don't think I'm saying 'local LLMs' above :) But technically possible, I guess, just hasn't been part of what's officially available. (There are also licensing issues still.) To answer your qu
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by antti909 4y ago
Thanks :) Answered a similar one somewhere else here - looks like you've found it already. Feel free to ask more in Discord https://haystack.deepset.ai/community
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by antti909 4y ago
Thanks :) Working on it. Re local models - indeed, all started with using the Transformer models for extractive QA and semantic search. With the Promptnode, and/or the Agents it's also now possible to combine local models/pip
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by antti909 4y ago
For the Agents? Yes, indeed. Referred in the article.
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by antti909 4y ago
Thanks for the emphasis :) Accurate!
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by antti909 4y ago
Very accurate observation :) So basically, a bit more freedom in picking the right tools for the job, connecting an LLM to proprietary data in a safe way, using multiple models simultaneously, and leveraging custom extractive/generativ
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by antti909 4y ago
See above - Haystack started a few years ago as a result of us working with some large enterprise clients on implementing extractive QA at scale. Now evolving to also allow the backend builders to mimic what's available from, e.g. Open
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by antti909 4y ago
LangChain is very cool tho :))
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by antti909 4y ago
Haystack has been around for a while now, and we've been mostly specializing in the extractive QA. The focus has been indeed on making the use of local Transformer models most easy and convenient for a backend application builder. You
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by antti909 4y ago
With a real-life application it's often about making the LLM work on top of your actual (private) data most reliably. By definition a proprietary hosted LLM can't know about it unless you bridge it somehow in a reliable manner.
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by antti909 4y ago
That's also one of the ideas behind using so-called retrieval-based augmentation. You can 'plug' an LLM like OpenAI's one (of Cohere, or a combo) to your data and make it provide accurate answers, but still leveraging al
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by antti909 4y ago
With Haystack you can also combine the use of [hosted] LLMs and smaller, local models, and different pipelines under the Agent too.
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by antti909 4y ago
Thanks for the spotlight :) We've spent quite a lot of time working on the Agents lately, and it's definitely a big focus. Couple of extra points to reflect on some of the comments here. It's quite straightforward to build a
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Semantic Search on AWS Docs(github.com)
4 points by antti909 4y ago|0 comments
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Deepset announces SaaS platform for NLP and $14mn from GV(techcrunch.com)
17 points by antti909 4y ago|1 comments
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by antti909 5y ago
Depends! When using 'DPR' (dense passage retrieval, potentially for more accurate results), a re-indexing is required.
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by antti909 5y ago
Whoa, this is cool :) I could think of a ton of marketing (or maybe even 'devrel') applications for it.
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by antti909 5y ago
Happy to help too - feel free to ask in the community channels as well :)
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by antti909 5y ago
Re structured data - in theory, yes :) We have to work a bit more in that direction. Here's the first step - querying table data, which could be really helpful for reports, financial data, etc. In regards to the storage backend - it&#x
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by antti909 5y ago
Glad it worked for you - thanks for sharing!
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by antti909 5y ago
Happy to help! - we've got Slack and everything :)
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by antti909 5y ago
Re "Kingston" - interesting! :) Probably, because of "Cambridgeshire"?
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by antti909 5y ago
Yep, that's definitely this challenge with commonly available models. In a real-life product development there's most often an important step of evaluating the model(s) and fine-tuning if necessary.
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by antti909 5y ago
Noted, we've been discussing dependencies internally indeed :) Thanks for the highlight above!!

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