It basically already has since they started developing dbt Fusion, so in that respect this probably doesn’t change much.
I expect they’ll keep developing Fusion but possibly as even more of a commercial-only offering than it already was.
1,361 karma · joined June 21, 2014
https://delphihq.com
I expect they’ll keep developing Fusion but possibly as even more of a commercial-only offering than it already was.
Not sure about multimodal as it’s not what I work on.
your comps are with “working in San Francisco”, not with your peers
*I found a pub called the Ranelagh, but it’s not in Pimlico, so I assume it’s a different one. It was the one he described as “really terrible,” so no big loss, I suppose.
Addendum: the other interesting thing I noticed was the ones he derided as having been “modernized” in the 1960s were also newly renovated today, with airy, Scandinavian, 2020s aesthetics. Presumably because unlike the traditional pubs, the 60s style became dated pretty quickly.
Unless I'm mistaken there's no native way in Hashquery right now to materialize the results back to your warehouse like you would with dbt.
The €80k is the start of the Mistral salary range. €100k is the top, which would put you in the top 1% of earners in France.
It’s nice to see some data on this. A lot of people talk about a 4-day workweek, but personally I think a 6-hour work day would be better.
At least in white-collar jobs, I think most people could fit the same amount of productivity into fewer (focused) hours.
Plus a day that’s roughly 9-3 instead of 9-5 would have the benefit of being aligned with school schedules (at least here in the US) and make things easier for working parents.
“Microsoft has assured us that there are positions for all OpenAl employees at this new subsidiary should we choose to join.”
What’s your quick pitch for why someone should use Revert vs competitors like Merge.dev and Nango?
Most of these use cases seem more “pull all data for a specific user/post/company” and less “do analytical queries on millions+ of column values.”
We’re all typescript under the hood so I’ll give this a look and see if we can use it.
Symphony wouldn’t support other LLMs currently, right? Only GPT-4?
Others include AtScale[0], dbt's MetricFlow[1], Google's Looker[2] (also a BI tool but powered by a semantic layer), and Propel[3].
[1] https://www.getdbt.com/product/semantic-layer
[2] https://cloud.google.com/blog/products/data-analytics/introd...
[3] https://www.propeldata.com
They're kind of an updated version of OLAP cubes if you're familiar with those.
Typically semantic layers sit on top of a data warehouse, let you define metrics using code or a UI, and provide APIs or SQL connectors so that you can query them.
One thing you really need with LLMs is consistency. Text-to-SQL kind of lets the LLM do whatever it wants - join tables that shouldn't be joined, define aggregates one way in one query and another way in the next.
Because semantic layers define how tables should join, measure definitions, etc., they mean people get consistent results from one query to the next, which builds trust in the LLM.
Cube (which was mentioned in another comment and has a great open-source semantic layer) has a good article about that here: https://cube.dev/blog/semantic-layer-the-backbone-of-ai-powe....
The average human cannot summarize (for example) Anna Karenina from memory.
Oftentimes data teams have those data sources in the warehouse already (or a process for ETLing new ones in).
Copying data only once means lower costs (maybe) and fewer inconsistencies.
Plus if they’ve done work to join/clean/transform the data in the warehouse they can take advantage of that for product analytics without having to reinvent the wheel in ChartBrew or Mixpanel.
Maybe re-submit it as a Show HN?
Also, it would be interesting if the answer linked to the relevant episode.