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Now we know why OpenAI told its investors to avoid Glean[1]

[1]: https://www.reuters.com/technology/openai-tells-investor-not...


Off topic but does anyone know what exactly Sutskever's SSI (mentioned in the article and with a valuation of $32B...) is up to? They have released... well... absolutely nothing in the year+ of existence.


This article is getting a lot of hate but honestly it does have good amount of useful content learned through practical experience, although at an abstract level. For example, this section:

``` The teams that succeed don’t just throw SQL schemas at the model. They build:

Business glossaries and term mappings

Query templates with constraints

Validation layers that catch semantic errors before execution ```

Unfortunately, the mixing of fluffy tone and high level ideas is bound to be detested by hands on practitioners.


A simple way is perhaps implement a text-to-metrics system where metrics could be defined as SQL functions.


Exactly! Midnights Children and Moors Last Sigh are so non-linear that one cannot expect to get the hang of it till they are atleast 50 pages through. It's usually on the second reading that the amazingness of those initial pages is felt.


Big Rushdie fan here. I used to think it could be because of a lack of cultural context especially for books like Midnights Children and Moors Last Sigh but now I also think that it could also be a matter of taste. Rushdie himself quotes Milan Kundera who said: "...that the novel descended from two parents, Samuel Richardson’s Clarissa and Laurence Sterne’s Tristram Shandy". The latter is a style of writing where all conventional rules of literature are broken, it's just wildly creative so to speak. Rushdie's Midnights Children and James Joyce's Ulysses fall into this category.

If you want to see the other style of writing in Rushdie, I can suggest Shalimar The Clown or The Ground Beneath Her Feet. But these are nowhere near as grand as Midnights Children.

In either category, a fair amount of interest in history helps to enjoy his books.


Hi HN

PromptQL is a programmatic approach to LLM tool composition which has shown remarkable improvement in accuracy (~2x) and repeatability (~4x) when compared to traditional tool calling and chaining approaches.

Fundamentally, PromptQL separates the creation of a query plan from the execution of the query plan. PromptQL uses the LLM to first create a program to compose the different tool calls hence avoiding the challenges with in-context tool chaining like accuracy, repeatability and context limits.


It was published in New Yorker https://www.newyorker.com/magazine/1946/08/31/hiroshima

Fun fact the cover image if this edition was kind of a decoy (perhaps to accentuate the shock): https://www.newyorker.com/magazine/1946/08/31


Wow, brutal!

As an aside I would never had guessed this artstyle was a 40s cover.


> RAG doesn't have to involve vector search.

This. Not sure why RAG triggers vector search for everyone. Retrieval Augmented Generation is as generic as it can get.


Most likely for the same reason that so many people seem to think they need a vector-specific database and a framework like langchain to build any type of GenAI-enabled application... the content marketing is working.


Why do you think that's more reasonable :)

To me it seems a more risky use-case since you don't have control/observability over what an untrusted user is asking for?


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Hasura is looking for a Senior/Staff Software Engineer with proficiency in Rust to become part of the core engineering team. In this position, you will work on developing innovative features on the core product. We are writing the core components of the product in Rust to accelerate feature velocity hence Rust expertise is required. This is an exciting time to join this effort in the early stages.

If you are interested, please apply at: https://hasura.io/careers/?jobId=FjqRMQHVXKnW


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