lmeyerov

28 ms·

331.
by lmeyerov 2y ago
I've been curious about this use case, so cool to see, and more so, to know it worked! This is essentially a realization of how graph RAG flavor systems work under the hood. Basically you create hierarchical summary indexes, such as to
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by lmeyerov 2y ago
Our scenario would be more like using Clickhouse / a dwh for session cohort/workflow filtering and then populating otel tools for viz goodies. Interestingly, to your point, the otel python exporter libs are pretty simple, so SQL r
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by lmeyerov 2y ago
Clickhouse has text + vector indexes, so that may be native, though we have never used them and I find vector indexes tricky to scale w other DBs. Text... Or neither... may be enough in practice tho as we mostly only care about searching on
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by lmeyerov 2y ago
As users of otel, we are looking at reusing otel for our LLM stack, and as it is easy to instrument, don't need a new framework for that part. However, the more interesting part is the storage: Imagine ingesting 100pg PDFs or 1M tweets
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by lmeyerov 2y ago
Yeah I think, after this snippet was written, cuda added __all_sync as an intrinsic. The divergent code before this was plain-ish cuda, and this snippet ensures they wait on the comparison vote before recurring. So in the AMD version, the c
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by lmeyerov 2y ago
It's supposed to be waiting for all threads to vote I'm not familiar with AMD enough to know if additional synchronization is needed. ChatGPT recommended adding barriers beyond what that gave, but again, I'm not familiar wit
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by lmeyerov 2y ago
Ah I was reading the 'deeper dive' section on my phone and missed it was a comparison, not a warning, thank you I'm curious how something like this example would translate: === Mapping lower-level ptx patterns to higher-level
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by lmeyerov 2y ago
Looks like the PTX translation is via another project ZLUDA, though how they bridge the differences in memory/consistency/etc models safely remains unclear to me...
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by lmeyerov 2y ago
Oh that will be interesting to understand, as PTX gets to more about trickier hw-arch-specific phenomena that diff brands disagree on, like memory models. Neat!
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by lmeyerov 2y ago
Sort of A lot of our hw-aware bits are parameterized where we fill in constants based on the available hw . Doable to port, same as we do whenever new Nvidia architectures come out. But yeah, we have tricky bits that inline PTX, and.. that
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by lmeyerov 2y ago
Tracking monthly/annual bookings (or whatever the MRR/ARR number is) for investors seperately from monthly/annual recognized recognized revenue for conservative operations seems simpler and achieves the same? And yeah, the bl
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by lmeyerov 2y ago
We use both so feel comfortable here -- We picked perspective over datashader and others for most basic charts & cross-filtering in louie.ai. It checks a LOT of boxes for intense tools. We do GPU server-accelerated things for bigger viz
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by lmeyerov 2y ago
I'm happy to see third-party comparisons, most of the marketing here indeed just assumes KGs are better with zero proof: marketers to be wary of. Unfortunately, I suspect a few key steps need to happen for this post to fairly reflect w
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by lmeyerov 2y ago
My intuition is: 1. For small individual queries, sqllite: think oltp. Naive graph databases are basically KV stores, and native ones, more optimized here. DuckDB may also be ok here but afaict it is columnar-oriented, and I'm unclear
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by lmeyerov 2y ago
Edit: I'd be curious which other papers/authors folks would add who are doing interesting work here. One starting point is to look at great synthesis, mechanized proofs, and PL folks who have been exploring neural synthesis, and t
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by lmeyerov 2y ago
Most of the papers in the syllabus are about the SAT/SMT-based solver era of program synthesis, and neural synthesis is popularly - with open benchmarks - succeeding on problems those failed to gain traction on. The research question i
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by lmeyerov 2y ago
If you think about classical synthesis as fancy tricks around optimizing SAT encodings & search, neural synthesis becomes about how to solve np-hard problems there instantly. There are other perspectives as well, but that's already
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by lmeyerov 2y ago
This is a very classic view, and while interesting, IMO the modern take doesn't start till lecture 22. I would expect a reformulation of the lecture series by now. As is, it reads as if an AI course does 21 lectures on Bayesian methods
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by lmeyerov 2y ago
Neat, afaict, if someone fine-tunes for their own data, the gliner stack is OSS so they may be able to just fork & rerun/continue
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by lmeyerov 2y ago
How does that even work, copying in and relicensing someone's bsd3 code as your own AGPLv3?
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by lmeyerov 2y ago
Where is the fine-tuning source code + data and with what license? Afaict that's the proprietary part which is why it isn't in their github and hf doesn't link to it. Hence my comment that I don't see how to do further f
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by lmeyerov 2y ago
I've been mixed on this, it seems great for throwaway projects but a dead end for ones that survive: * Out-of-the-box fine-tuned model for extraction makes for an easier start, so happy to see this out there * ... But presumably one of
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by lmeyerov 2y ago
It makes his grifting look and be less bad. It matters legally, as precedent is a big part of US law, and in PR, as he can claim it is not bribery because he has now defined it to not be.
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by lmeyerov 2y ago
Columnar analytics are slow in non-columnar engines
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by lmeyerov 2y ago
Right - so not a database, but a columnar analytics compute engine. Half of why we wrote arrow js was for pumping server arrow data to webgl, and the other half for powering arrow columnar compute libraries & packages like this. For sub
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by lmeyerov 2y ago
What is the formal logical system? Eg, KGs (RDF, PGs, ...) are logical, but in automated construction, are not semantic in the sense of the ground domain of NLP, and in manual construction, tiny ontology. Conversely, fancy powerful logics l
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by lmeyerov 2y ago
.. sounds like ZIRP
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by lmeyerov 2y ago
is this zero-interest rate phenomena in action?
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by lmeyerov 2y ago
Generally you do both and rank the combined results This is also why generally you don't get a vectordb and instead just add a vector index to the DB you are already using Re:semantic vs synonym, that's really domain dependent. As
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by lmeyerov 2y ago
And much more importantly for ooencl's success, poor compatibility of OpenCL implementations on Nvidia hardware by Nvidia + Microsoft platform-level software Eg, opencl on Nvidia GPUs for windows is/was missing (I have a many-year

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