akisej

7 ms·

1.
Databricks vs. Snowflake: The Battle to Power Enterprise AI(ashugarg.substack.com)
2 points by akisej 3y ago|0 comments
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by akisej 3y ago
Let me ask you something I always ask my reports: if you were your manager, what would you do?
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by akisej 3y ago
Pretty interface, although I remain unconvinced of how I'd actually use it. If I'm just prototyping for myself, LLM providers offer a decent history, and I rarely need to share notebook-style explorations of LLMs with my team. For
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Florence Nightingale, datajournalist: information has always been beautiful(theguardian.com)
2 points by akisej 3y ago|0 comments
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by akisej 3y ago
Appreciate the effort you put into this. In terms of user flow, I typically need one or two of these use cases at a time. In that case, I just type my conversion into a search engine like Google, and often use their default box. Can you sha
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by akisej 3y ago
Yup, that's part of it but I mean it bidirectionally - users can accidentally leak data to models too, which is concerning to SecOps teams without a way to monitor / auto-redact.
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by akisej 3y ago
These common issues tend to prevent LLMs from being used in the wild: * Data Leakage * Hallucination * Prompt Injection * Toxicity So yes it does include prompt injection, but is a bit broader. Data Leakage is one that several customers hav
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by akisej 3y ago
Great starting point! These diagrams notably miss a LLM firewall layer, which is critical in practice to safe LLM adoption. Source: We work with thousands of users for logicloop.com/ai
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by akisej 3y ago
How about Amplitude or Heap? For an open source alternative you could consider PostHog.
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Data Distribution Shifts and Monitoring(huyenchip.com)
1 points by akisej 3y ago|0 comments
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by akisej 3y ago
Very cool, but curious if you see people actually directly interacting with LLMs vs in a script as part of a larger application? I see myself needing debugging, visualizing output etc. so much that an IDE makes more sense to me as an interf
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by akisej 3y ago
Aw man, sorry to hear this about your friend. Inanimate objects are directly subject to the laws of physics, but living beings that have intention and will are able to circumvent those. For example, I can jump despite gravity existing. Yes,
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by akisej 3y ago
As long it's clear that this is fiction, how would something like this be more damaging than a series like The Man in the High Castle, or other sci-fi that imagines an alternate universe? I think it's a nifty technique that allows
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by akisej 3y ago
Yeah, in general the more data you're able to use (assuming the context window supports it), the better results tend to be. We arrived at the data schema being a good enough compromise at which the benefits outweigh the risks for sever
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by akisej 3y ago
This seems overall well-written and well-explained, but curious for that piece on fine-tuning. This article only recommends it as a last resort. That makes sense for a casual user, but if you're a company seriously using LLMs to provid
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by akisej 3y ago
Thanks for sharing how you keep the discussion quality high here. We responded to some thought-provoking questions on this thread about differentiation vs ChatGPT, other SQL Copilots, edge cases like more complicated queries etc. that we be
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by akisej 3y ago
On simpler multi-table joins we've been able to product good results, and we've done a lot of prompt engineering to make sure it takes the schema very seriously so that prevents hallucinations too. We're always finding new ed
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by akisej 3y ago
Thanks for sharing your experience. By organizing and storing queries, we hope to be able to improve these suggestions as well behind the scenes.
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by akisej 3y ago
Yup, our bet is that people are going to want better integration into data sources and actions resulting from their queries, and that a lot of business value will come from that.
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by akisej 3y ago
Yes, we can actually connect to third-party apps via APIs https://docs.logicloop.com/data-sources/supported-data-sourc...
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by akisej 3y ago
That's a great idea for future improvements, thank you for trying it out!
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by akisej 3y ago
Appreciate the vouch, @chatmasta! I actually did write those comments myself, and think that the 3-point explanation makes for a clear explanation. My cofounder and I both started our careers as software engineers, and I've been in the
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by akisej 3y ago
We use a combination of APIs from existing LLM providers, and do some serious prompt engineering to get the best from them. We're starting to train models on more SQL-specific prompts now.
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by akisej 3y ago
This feels like classic Hype Cycle content: the higher we peak on Inflated Expectations the lower we'll find ourselves on the Trough of Disillusionment.
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by akisej 3y ago
I understand your skepticism, here's how we think about things - * We only send data schema to underlying models: No data is actually sent there, but yes when you connect your database, we run the generated SQL on your database and sto
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by akisej 3y ago
Right, here's some ways we're different - * On your data schema: A lot of the ones we've seen recently don't actually generate these queries on your schema, so you still have to do a lot of manipulation or calculation to
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by akisej 3y ago
It varies. Theoretically, someone who doesn't know SQL should be able to generate it from this, but you'd still have to get someone to connect your datasource, and have a general sense for what you want to do. I'd say it&#x27
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by akisej 3y ago
Good question. A few different ways: * Model Selection: We pre-select the best models for SQL generation, so you don't have to A/B test and figure it out. As the number of models available increases, this can take a lot of time if
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by akisej 3y ago
Thank you, let us know what you think when you try it out.
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by akisej 3y ago
Agreed, that's always a risk with making data too easy to access, its context doesn't always come with it. While we initially thought it'd be most valuable for new SQL users, a lot of existing SQL experts actually find that i

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