rdli

7 ms·

1.
by rdli 1mo ago
I couldn't find a client of any sort for WeatherNext, so I had Claude write a simple one: https://github.com/richarddli/weatherodds .
2.
by rdli 3mo ago
One thing that wasn't obvious in the post: it's usage (token) based pricing, not including in your existing Claude subscriptions.
3.
by rdli 8mo ago
Cybersecurity/AI seed startup | Founding AI Engineer | Bay Area | Full-time We're seed-staged, 3 people, building an AI for cybersecurity, looking for a founding AI engineer who wants to learn/apply SOTA techniques for AI. Id
4.
by rdli 8mo ago
I get that but just not entirely obvious how you do that for the Notion AI.
5.
by rdli 8mo ago
Securing LLMs is just structurally different. The attack space is "the entirety of the human written language" which is effectively infinite. Wrapping your head around this is something we're only now starting to appreciate.
6.
by rdli 9mo ago
Nothing super-fancy. We have a common GitHub repo in our org for skills, and everyone checks out the repo into their preferred setup locally. (To clarify, I meant that some engineers mostly use CC while others mostly use Codex, as opposed t
7.
by rdli 9mo ago
This is great. At my startup, we have a mix of Codex/CC users so having a common set of skills we can all use for building is exciting. It’s also interesting to see how instead of a plan mode like CC, Codex is implementing planning as
8.
Security Flaws in DeepSeek-Generated Code Linked to Political Triggers(crowdstrike.com)
3 points by rdli 10mo ago|0 comments
9.
by rdli 11mo ago
Polar Sky | Bay Area | Full-time | Founding AI Engineer Generative AI is rewriting how organizations use data, and breaking traditional security models in the process. We’re a team of cybersecurity, AI, and systems experts building the foun
10.
by rdli 1y ago
Polar Sky | Founding AI Lead | Bay Area/Seattle | Hybrid/Onsite | Full-time We're a well-funded, pre-seed cybersecurity startup focused on data security. I'm looking for a founding AI lead with experience in fine-tuning
11.
Secret Service dismantles telecom threat capable of crippling cell service in NY(politico.com)
2 points by rdli 1y ago|4 comments
12.
by rdli 1y ago
Polar Sky | Founding AI Lead | Bay Area/Seattle | Hybrid/Onsite | Full-time We're a well-funded, pre-seed cybersecurity startup focused on data security. I'm looking for a founding AI lead with experience in fine-tuning
13.
by rdli 1y ago
Seems that OpenAI is acquiring Io for $6.4B in an all-equity deal.
14.
by rdli 1y ago
I would think that that the NVidia Dynamo SDK (pipelines) is a big difference as well ( https://github.com/ai-dynamo/dynamo/tree/main/deploy/sdk/doc... ), or am I missing something?
15.
by rdli 1y ago
In this analogy, Dynamo is most definitely not like Django. It includes inference aware routing, KV caching, etc. -- all the stuff you would need to run a modern SOTA inference stack.
16.
by rdli 1y ago
This is really interesting. For SOTA inference systems, I've seen two general approaches: * The "stack-centric" approach such as vLLM production stack, AIBrix, etc. These set up an entire inference stack for you including KV
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The Agentic AI Runtime Stack(wing.vc)
1 points by rdli 1y ago|0 comments
18.
Outperforming DeepSeekR1-32B with OpenThinker2(open-thoughts.ai)
2 points by rdli 1y ago|0 comments
19.
Engineering Reasoning LLMs: Notes and Observations(thelis.org)
6 points by rdli 2y ago|0 comments
20.
by rdli 2y ago
The blog post was a little unclear, so my summary was: - They used QwQ to generate training data (with some cleanup using GPT-4o-mini) - The training data was then used to FT Qwen2.5-32B-Instruct (non-reasoning model) - Result was that Sky-
21.
Anthropic at $60B – How much might employee stock options be worth?(thelis.org)
1 points by rdli 2y ago|0 comments
22.
AI developer frameworks and the evolving AI infrastructure ecosystem(thelis.org)
1 points by rdli 2y ago|0 comments
23.
by rdli 2y ago
I took a brief look (~5 minutes). My $0.02 is that it's not clear what problem you're trying to solve. I get what some of the features do (e.g., templated prompts) but it would be v helpful to have an example of how you actually u
24.
by rdli 2y ago
(author here) I didn't put this in my post, but one of my favorite moments was when I read some of the LlamaIndex source code which pointed to the GitHub commit where they copied the code verbatim from LangChain. (LangChain is MIT-lice
25.
Lessons from building a small-scale AI application(thelis.org)
8 points by rdli 2y ago|6 comments
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by rdli 2y ago
Not a bad move by Red Hat. Red Hat lost the battle of the cloud to Azure, AWS, and Google, but AI is still a nascent space. vLLM's deployment model fits neatly into Red Hat's traditional on-premise / support-centric business
27.
by rdli 2y ago
I'm running ollama, but it's still slow (it's actually quite fast on my M2). My working theory is that with standard cloud VMs, memory <-> CPU bandwidth is an issue. I'm looking into vLLM. And as to sidestepping in
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by rdli 2y ago
Thanks! I should have been clearer -- embeddings are pretty fast (relatively) -- it's inference that's slow (I'm at 5 tokens/second on AKS).
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by rdli 2y ago
I'm working on something like this! It's simple in concept, but there are lots of fiddly bits. A big one is performance (at least, without spending $$$$$ on GPUs.) I haven't found that much in terms of how to tune/deploy
30.
by rdli 2y ago
This is cool! I've been trying out bits & pieces of the RAG ecosystem, too, exploring this space. Here's a question for this crowd: Do we see domain/personalized RAG as the future of search? In other words, instead of Goo

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