The Codex agent is only given tools to edit the single HTML file that displays on the homepage. The page is on a separate domain, so there's no cookie sharing, and the iFrame is in a sandbox. That said, the biggest risk is social engineering attacks.
Hi all - this is a small research prototype I built to explore cross-GPU reuse of transformer attention states.
When inference engines like vLLM implement prefix/KV caching, it's local to each replica. LMCache recently generalized this idea to multi-tier storage.
KV Marketplace focuses narrowly on the GPU-to-GPU fast path: peer-to-peer prefix reuse over RDMA or NVLink. Each process exports completed prefix KV tensors (key/value attention states) into a registry keyed by a hash of the input tokens and model version. Other processes with the same prefix can import those tensors directly from a peer GPU, bypassing host memory and avoiding redundant prefill compute.
Under optimistic conditions (perfect prefix importing), the prototype shows about a 15% reduction in latency and throughput gains without heavy tuning. The code is intentionally minimal (no distributed registry, eviction, or CPU/disk tiers yet) but it's a prototype of "memcached for attention."
I thought others exploring distributed LLM inference, caching, or RDMA transports might find the repo useful or interesting.
Oh really? I can't find anything about the memory model online. I'm not sure what's the best way to do this, but if there's a way for us to get in contact, I'd be interested in adjusting the project so it's developed in the most ergonomic way possible. I'm chatting with a couple of universities and I might issue a research grant for this project to be further fleshed out, so would be keen to hear your insights prior to kicking this off. My email is neel[at]berkeley.edu.
Hi all, this is a small research prototype I built that connects Rust's MIR (Mid-level IR) to Coq, the proof assistant used for formal verification.
cuq takes the MIR dump of a Rust CUDA kernel and translates it into a minimal Coq semantics that emits memory events, which are then lined up with the PTX memory model formalized by Lustig et al., ASPLOS 2019.
Right now it supports:
* a simple saxpy kernel (no atomics)
* an atomic flag kernel using acquire/release semantics
* a "negative" kernel that fails type/order checking
The goal isn't a full verified compiler yet. It's a first step toward formally checking the safety of GPU kernels written in Rust (e.g. correct use of atomics, barriers, and memory scopes).
Happy to hear thoughts from folks working in Rust verification, GPU compilers, or Coq tooling.
I agree with you. I agree with OP in the following sentences:
>We have now landed on our final strategy: start by figuring out the number of possible secret codes n. For each guess, calculate the number n_i' of codes that will still be viable if the Code Master gives response i in return. Do this for all possible responses.
But then I don't agree with:
>Finally, calculate the entropy of each guess; pick the one with the highest.
Why wouldn't we just pick argmin_{guess} sum{i in possible responses}{Pr[i] * n'_i} = sum{i in possible responses}{n'_i/n * n'_i} = sum{i in possible responses}{n'_i^2}? This is the guess that minimizes the expected size of the resulting solution space.
I open-sourced this repo to (1) identify all of the clickable components in a web app using `computer-use-preview`, (2) traverse the tree of actions using Browserbase/Stagehand, then (3) generate a reasonable MCP interface using GPT-5: https://github.com/neelsomani/web2mcp
You just need to set your login credentials in the .env file as specified in the README. Let me know if you have any questions - happy to share reasoning on the design!
Imo that might work for nursing or fields where some human element is desirable, but most physicians could reasonably be replaced even in the short-term. A lot of the work of a e.g. radiologist is just reading MRIs or providing diagnoses based on the data provided.
Yes, but it's also about turning a profit, because you have to incentivize power producers to build pumped storage / batteries / etc. The ISO markets are unregulated in that respect, since the government doesn't build or control the power plants.
Yeah it's actually very common, it's called pumped storage. Many power pricing models will treat them identically to batteries given they also bid into what's called the "ancillary services market," which exists for reliability purposes to balance the grid when supply and demand don't perfectly match up. You can read about other types of storage on the PJM ISO website: https://learn.pjm.com/energy-innovations/energy-storage
I think it's been tried too many times before. IMO too much friction to make a video when I already have tons of photos from the last year. It reduces to who can do the best videography which is a less level playing field than photos. I also swipe when I'm in public which isn't possible if there's an audio component
Yeah I'm curious to see what percent of users have been actively on Hinge for more than a year. They should be optimizing to minimize that if it's actually meant to be deleted
What exactly qualifies as a rejection (is it a swipe left or a match + date + unmatch)? Thinking match + date + unmatch is the more reasonable application but difficult to enforce
Second I just don't agree that it's the right optimization function, IMO you should max E[quality of partner] rather than max Pr[ending up with best quality partner]