did short consulting w/ openai about these and really worked out amazing use cases a few mo. ago, but looks like they have all but hidden group chats. https://chatgpt.com/gg/v/6a1775bdd970819388dc73fd7da45e36?token=XSm_dIpMSh3d3H-dM47F8A amazing feature. game changing. who has tried and if so, what use cases do you see? try and i'll make crazy pics of pizza for you.. submitted by /u/jdawgindahouse1974 [link] [留言]

submitted by /u/ExtensionEcho3 [link] [留言]

Article URL: https://www.ycombinator.com/companies/pelica/jobs/MDeC49o-machine-learning-engineer Comments URL: https://news.ycombinator.com/item?id=48301851 Points: 0 # Comments: 0

I am a software developer who has been using LLMs extensively at work. I wanted to develop a foundational understanding of LLMs, but have no background in machine learning or statistics. So, I started to read and take notes with the goal to eventually write up a developer's guide to the foundations of LLMs. The article kept growing, so I have split it into four parts. This is the first in the series. Hope this helps! submitted by /u/Normal-Tangelo-7120 [link] [留言]

Federal prosecutors charged a Google employee with fraud after he allegedly made $1.2 million on Polymarket bets related to Search-related trends in 2025, as reported earlier by ABC News. In their now-unsealed complaint, prosecutors allege that Michele Spagnuolo "knew the outcome of these wagers before the trading public did because he had accessed Google's confidential, […]

According to federal prosecutors, Michele Spagnuolo made more than $1 million on the prediction market platform using confidential information about Google Search traffic.

Your AI BDR that runs outbound sales autonomously Discussion | Link

I used to believe that the thing that we had to worry about with AI becoming more and more prevalent was like sentient robots that would take over like in the science fiction story I robot. But I don't think that's the case anymore because I think there is something far more sinister behind all the push for AI to become mainstream technology in the reason all these deep pockets are willing to pour so much of the cash into it. Because it spells control. If you control AI you can control the people because you can control the data they consume you can control how they consume it and what they will believe. Because as AI becomes more and more mainstream it leaves the door open for big corporations to feed us information they want us to have as well as the government. submitted by /u/crazyhomlesswerido [link] [留言]

[R] BEAM 100K memory benchmark: CSM vs Hindsight local artifact comparison I’m looking for feedback on a local agent-memory benchmark comparison, especially from people who care about evaluation methodology. I built an open-source R&D memory system called Context Swarm Memory (CSM). It uses bounded read-only memory shards, query routing, probe/recall/synthesis, cited packets, and explicit Committer-gated writes. The current comparison is against the accepted local Hindsight artifact on BEAM 100K: CSM: 0.757573 AMB score, 342 / 400 correct Hindsight: 0.733658 AMB score, 326 / 400 correct CSM uses 38.2% fewer answer-visible context tokens CSM is slower: 29.23s average retrieval vs 6.38s I want to be precise about the claim: This is not an official leaderboard claim. It is not a BEAM 10M claim. It is a committed local accepted-artifact comparison at 100K, and the next step should be independent replication or official chart acceptance. Repo: https://github.com/muhamadjawdatsalemalakoum/context-swarm-memory Evidence and reproducibility notes: https://muhamadjawdatsalemalakoum.github.io/context-swarm-memory/ The main question: what would make this comparison scientifically stronger before it is presented as a serious agent-memory result? submitted by /u/keonakoum [link] [留言]

Hey all, I want to setup a feed to stay on top of whats going on in specifically the software/web sector. Currently for this industry, I've only followed Cybernews, which is nice for what's going on with cyber security. However, I would also like to follow tech sources that generally have good writers and report on existing languages such as React, Vue, Django, Ruby, PostgreSQL, etc; as well as upcoming languages. Yes, I could search around and find whatever pops to the top of my search, but I would like to know what is actually reliable vs what might just look good. Also a plus if you can recommend any apps or sites that can create an organized feed or dashboard for news outlets. Things change quickly in this industry, so I'm trying to be a little more proactive to stay somewhat on top of things. Thanks! submitted by /u/Snowdevil042 [link] [留言]

submitted by /u/henk53 [link] [留言]

New preprint. A Mixture-of-Experts inference kernel (TritonMoE) written entirely in OpenAI Triton, targeting portability across NVIDIA and AMD without vendor-specific code. Highlights: A fused gate+up GEMM computes both SwiGLU projections from shared tile loads, eliminating 35% of global memory traffic. 89-131% of Megablocks throughput at inference batch sizes (up to 512 tokens) on A100; the same kernel runs on MI300X unchanged. Limitations: falls behind at 2048+ tokens, and degrades with 64+ experts under extreme routing skew. Paper: https://arxiv.org/abs/2605.23911 Code: https://github.com/bassrehab/triton-kernels Writeup with benchmarks: https://subhadipmitra.com/blog/2026/fused-moe-dispatch-triton/ submitted by /u/bassrehab [link] [留言]