lmeyerov

13 ms·

1.
by lmeyerov 4d ago
For us it's ~easy: we do security investigation CTFs against log dumps / DBs like Splunk. We run the AI CTF as usual.. except without the DB nor internet access. If they still get some right, that's a problem. (And most publi
2.
by lmeyerov 4d ago
My intuition is that many of the better & bigger 'private' code bases, at least in terms of claude code and codex... are not in fact private at this point. One lesson of running botsbench.com, in a slightly different domain, i
3.
by lmeyerov 6d ago
Much earlier, I tried to set up some static analysis tools so that the coding agent would have access to dataflow analysis etc. tools instead of just grep for typed python. If there were benefits, they weren't easily apparent :(
4.
by lmeyerov 6d ago
OpenAI says deidentified data from the private sessions go into training. (Well, explicitly said they will not rule that out.) That changes a lot of the conversation.
5.
by lmeyerov 7d ago
Very much agreed in the former I'm not so sure on the latter -- that introduces a bunch of tool calls, while the text patches are much closer to the semantic space imo and easy for harnesses If we rephrase this as instruction following
6.
by lmeyerov 7d ago
I wonder if the graph part is a distraction (data representation / syntax), and once you step back, if/how this relates to the wider concept of 'durable task lists' used in this kind of structured dynamic planning. Ex: D
7.
by lmeyerov 8d ago
Wonderful data point! It's been interesting investing into different classic verification & testing methods for gfql (CPU/GPU graph queries on dataframes) and Louie (agentic investigation harness) over the last couple of years
8.
by lmeyerov 9d ago
Picking rust also felt problematic as also somewhat out of distribution historically
9.
by lmeyerov 13d ago
... And it looks like everyone keeps using the same security startup to run the higher risk tasks, where individual staffers may be great yet, yet as an organization, the biggest labs got hosed in different ways That indemnity card excuse i
10.
by lmeyerov 14d ago
Moving towards streaming and generally out-of-core is great We recently added a Polars backend to GFQL (cypher graph queries on dataframes, no DB needed), both CPU and GPU mode, and super impressive. Noticeable improvements vs pandas/c
11.
by lmeyerov 21d ago
Yep!
12.
by lmeyerov 22d ago
Congrats! For those into the `pip install ...` flow and kuzu, is gfql: we started around the same time in a non-VC-funded oss manner with overlap in key architectural ideas: - cpu columnar vectorized engine + optionally the only open source
13.
by lmeyerov 29d ago
Interestingly, while we don't fine-tune generative models for Louie.ai, we found fine-tuning embedding models to be a major $ saver. Instead of 1K-2K wide frontier embedding vector lens... Just 64. Huge savings on vector DB $$$. I&#x27
14.
by lmeyerov 1mo ago
It's been fascinating doing a custom variant for GFQL, the first OSS embeddable Cypher property graph query engine for CPU+GPU - - accelerated launch of our new backends like polars, including a new lazy mode & planner, which are f
15.
by lmeyerov 1mo ago
A graph is a fancy way of saying a few async await calls, which a REPL can do (We added the same to louie.ai, not complicated)
16.
by lmeyerov 2mo ago
Fwiw, without naming names, I helped someone at a hackathon make their first app on something he was passionate about, later found out he had been recently homeless living on an abandoned boat, and now years later, afaict he turned that int
17.
by lmeyerov 2mo ago
agreed. gfql already gives this best-of-both for oss cpu+gpu cypher as we've been steadily working through benchmarks like ldbc, pokec, etc. The HPC lessons for graph algorithms is less obvious as the substrate the OP is working throug
18.
by lmeyerov 2mo ago
see graph500 we use igraph cpu / cugraph gpu in pygraphistry/gfql projects, and our experience is cugraph is ~10X+ on tiny cheap GPUs over igraph. looking at that table, where all seem same magnitude as igraph, I'd therefore
19.
by lmeyerov 2mo ago
cudf+cugraph are the table+graph algorithms that started around that same time to align with it, that's what helped get arrow funded from the nvidia side can't reply on the below, but re:networkx, it was more of the reverse, they
20.
by lmeyerov 2mo ago
cudf/cugraph is open source and helped fund the arrow ecosystem , I think it's good to give teams credit when they do work they didn't have to do and not misrepresent them. And yes, it works great, graph500 leaderboard leve
21.
by lmeyerov 2mo ago
We shared with the author how databricks multi-node and single-node graphframes were wildly inefficient for this kind of thing: we were measuring doing billion-edge graph traversals & scans in single node in-memory in seconds with regul
22.
by lmeyerov 2mo ago
Not really ;-) ~10 years ago, we helped create apache arrow, helped create GPU data frames, and been running for the last decade the open source pygraphistry and now gfql cpu+gpu property graph engine for this. Likewise, Nvidia has been doi
23.
by lmeyerov 2mo ago
Related, we recently release the polars version of GFQL, the only oss cypher property graph query engine for CPU+GPU, and even better, no database nor outside process needed. We started doing LDBC benchmarks vs neo4j, memgraph, kuzu, etc, a
24.
GFQL: Run Cypher on Polars, CPU and GPU, no database required(graphistry.com)
7 points by lmeyerov 2mo ago|0 comments
25.
by lmeyerov 2mo ago
I strongly disagree ;-) The paper's line of reasoning seems to continue the endless subjective loop of assuming your viz framework has the right abstractions & defaults , which the next person will rightfully disagree with for thei
26.
by lmeyerov 2mo ago
This feels like a bit of a semantic debate, but maybe a few useful perspectives, as interpret current bespoke work as not so rosy wrt collapse: - Synthetic datasets are typically human-steered today, which points to model collapse wrt learn
27.
by lmeyerov 2mo ago
I've been calling this Software Collapse It's the same problem that AI faces of Model Collapse: AIs that train on the internet ultimately just end up training on one another, stop moving forward, and end up as identical polished v
28.
by lmeyerov 2mo ago
I have to wonder: What's the open protocol - some sort of LTAP read/write path - for compute engines to target LTAP / lakebases? Sort of like how iceberg > deltalake, except now one layer up (OLTP+OLAP). LTAP / lakeba
29.
by lmeyerov 3mo ago
Fable adds guard rails like cyber refusals to mythos. Mythos is the starting point for fable. Same model family.
30.
by lmeyerov 3mo ago
AOP is a big influence for how we are designing hooks, including custom ones, for louie.ai's agent harness. More principled structure to what is already expected. I'm unclear on AOP in general, esp as proposed here. That's a

More ›