Knowledge catalogue
arXiv:2609.16625v1 Announce Type: cross Abstract: How and why does a recommender system fail the users it serves? Oftentimes, practitioners are left to improve their algorithms based on a combination
GPT-6 Astra is an obviously broken product that needs to be taken off the market until it’s fixed. AXIOS: “.. It's increasingly clear that the Hugging Face breach wasn't a one-off incident.” @inafried
arXiv:2609.12609v1 Announce Type: new Abstract: Differences in vehicle kinematic characteristics between production autonomous vehicles (PAVs) and human-driven vehicles (HVs) have been limitedly inves
A brilliant suggestion by @GaryMarcus because, in the end, companies are offering AI as a product. It can be recalled or its deployment paused; its manufacturers can be held to account for its failure
Parmy Olson / Bloomberg: Only 4% of the startups in YC's 2026 spring batch had a native mobile app as their main product, down from 15% in 2013, as startups focus on AI and agents — Artificial intelli
arXiv:2609.08368v1 Announce Type: new Abstract: We present Miles v0.1, a full-stack, production-ready system for frontier post-training. Building upon the clean design of slime, Miles designs each sta
Q2D-Web uses agent citations, production web rankings, and a combined set expanded with LLM judgments. These three relevance sets reduce false negatives and reliance on a single labeling pipeline, whi
Our open-weight models, products and infrastructure give organisations a real choice over how and where they run AI, not just access to a model. That's frontier performance without the lock-in. Full s
Our partners at @CosineAI train their own coding model on real production code, for languages like Fortran and Verilog that generic models fumble. On cost per successful task, their Lumen Outpost mode
arXiv:2609.02107v1 Announce Type: cross Abstract: Discrete visual tokenization, predominantly driven by vector, scalar, and product quantization, lacks a unified conceptual framework for understanding
arXiv:2609.02730v1 Announce Type: new Abstract: Production recommender systems shape what billions of people see, and sustaining their performance requires continual optimization: as content, user beh
arXiv:2608.28875v1 Announce Type: cross Abstract: Supplying context at inference time to a large multimodal model is an inexpensive lever for adapting speech transcription to a domain, and earlier res
Amazon Quick proof-of-concept projects often stall when security teams review the production plan. This post walks through designing dashboards, Spaces, knowledge bases, agents, and Flows with securit
You made the product. Now build the business. We teamed up with some of the best GTM platforms so Replit Agent can fuel growth for you. Agentic intelligence that helps you find customers. Launch campa
I've always thought american robotics products took themselves too seriously. Glad to see huggingface take a page out of China's playbook here. No one actually needs something like this but it's so cu
⚡Meet Qwen3.8-Flash, a multimodal MoE and an early preview of the Qwen4 architecture, now open-weight! The production version Qwen3.8-Flash will be available soon via QwenCloud API at just 0.16/1M inp
This is one of the most useful writeups I have seen on keeping an LLM judge effective in production. (bookmark it) Netflix runs judges over hundreds of thousands of show-level recommendation explanati
Grok Bot is hands down one of the best products I have ever used. Maybe the best ever. I have had it less than a week. I am not a developer. I talk to one chat and it already knows my business better
‘Open Models, Production Agents’ is underway! Tonight means another event hosted at FriendliAI's San Francisco HQ. A very lively turn out, and a stellar lineup of panelists exploring how open models a
arXiv:2608.18733v1 Announce Type: cross Abstract: We present Flama, an open-source Python framework for developing and deploying production-ready web APIs, machine learning services, and large-languag
arXiv:2607.16230v2 Announce Type: replace-cross Abstract: Accurate pre-order shipping cost estimation is important in e-commerce because it affects price presentation, margin planning, and conversion.
'Agents = model + harness + context' is a much better mental model than treating the LLM as the entire product. The model provides capability, but the harness determines tools, permissions and behavio
arXiv:2608.14122v1 Announce Type: new Abstract: Production scheduling in complex manufacturing environments is challenging when sequence-dependent setup times, stochastic disturbances, and due-date co
Some say dogs look like their owners. Generative AI CEOs have come to sound like their product: frequently wrong, never in doubt, often full of BS. Dario is full of sh@t. Birds of a feather. JUST SAY
Maxwell Zeff / Wired: Current and former OpenAI employees say pressure to quickly ship products left less time for safety, contributing to incidents like the rogue agent hack — OpenAI's rogue agent ha
arXiv:2601.12178v2 Announce Type: replace Abstract: We propose a federated learning framework for the calibration of parametric insurance indices under heterogeneous renewable energy production losses
Powered by @Cerebras, Ultrafast generates up to 750 tokens per second, bringing our most intelligent model to products and workflows where every second counts. Ultrafast is designed for businesses whe
We’re launching DeepSeek-V4-Pro today! 🚀 🔷 Major Agent upgrades with strong production gains! 🔷 Flexible reasoning effort for V4-Pro & V4-Flash: low for simple tasks, high for daily Agent workflows, m
You don't stand up an agent. You upload a folder. Claude Code is a harness for your laptop. Managed Deep Agents is a harness for production. Want Slack? Add a file. Want a daily run? Add a file. Want
arXiv:2608.10845v1 Announce Type: cross Abstract: Spectral clustering methods for network data are commonly based on a few matrix representations, such as the adjacency matrix and the symmetric Laplac
arXiv:2511.22130v2 Announce Type: replace Abstract: To navigate ever-shifting real-world environments, agents must grapple with incomplete knowledge and adapt their strategies through experience. Howe
arXiv:2608.08237v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems in production operate under strict service level objectives (SLOs) on tail latency and infrastructure cos
Anthropic: Anthropic updates Claude Fable 5's biology safeguards to reduce false positives, cutting biology-related “fallbacks” by ~85% in testing across product surfaces — We're making updates to Cla
Megan Morrone / Axios: Filing: OpenAI says “Apple should not be permitted to use a baseless and pretextual lawsuit to make up for its failures to integrate AI into its products” — If the case survives
Fully onboard with productizing hillclimbing as an automated service for any agentic task. I've had the fortune of knowing @silennai since the AutoGPT days, and I know that him and Kion are going to d
After rigorous testing, our joint AI project with Daiwa Securities is entering the full-scale production phase. We're bringing our agentic AI systems to @Daiwa_JP’s wealth management teams to accelera
ChatGPT Work is OpenAI's fighter in the highest stake product category in history: bringing the power of coding agents to the masses. It's also how a billion users will soon use ChatGPT by default. I
arXiv:2608.03311v1 Announce Type: cross Abstract: Enterprise compliance management requires rapid adaptation to evolving regulatory frameworks (e.g., DORA, AI RMF, FedRAMP) and tight remediation SLAs.
arXiv:2603.20381v2 Announce Type: replace-cross Abstract: Understanding the fundamental mechanisms governing the production of meaning in the processing of natural language is critical for designing s
arXiv:2608.01544v1 Announce Type: cross Abstract: The CLIP Q-score is a novel, safe, fully reproducible, and computationally efficient method for extracting objective product quality metrics from visu
one thing i appreciate about silico is that it's a deeply humanist product. we designed silico to keep you in the experimental loop -- more observable, easier to steer, easier to understand we want to
Together AI gives developers a high-throughput production path for running DeepSeek V4 Flash across coding, tool-use, and agentic workloads. Start building: https://www.together.ai/models/deepseek-v4-
Finally a good paper testing whether agent memory needs an LLM at all. Production memory stacks spend extra model calls on summarizing interactions, writing records, and reranking retrievals. Every on
Together AI gives developers a high-throughput production path for running Inkling-Small on @NVIDIAAI Accelerated Infrastructure across multimodal, coding, and agentic workloads. Start building: https
Together AI gives developers a high-throughput production path for running Inkling-Small on NVIDIA Accelerated Infrastructure across multimodal, coding, and agentic workloads. Start building: https://
arXiv:2607.26780v1 Announce Type: new Abstract: The ability of large language models (LLMs) to process and generate text has introduced potential for applications in information extraction (IE). While
Simon Willison notes that both Anthropic and OpenAI build products that rely heavily on searching data but keep the underlying search index they use hidden from public view. He finds it surprising how
arXiv:2607.24819v1 Announce Type: cross Abstract: Wafer fabrication exhibits unique characteristics, including reentrant process flows, variable bottlenecks, and highly variable process conditions. In
arXiv:2607.22889v1 Announce Type: new Abstract: Learning the natural parameters z in R^n of discrete distributions mu_z from independent samples constrained to a subset S subseteq {0,1}^n is a foundat
New research from Meta and CMU. This one is on agentic context management for long horizon tasks. (bookmark it) Production agents accumulate context every turn. The usual fix compresses on a token thr
Our users have been really excited to try Kimi K3 and we're excited to bring it to Augment's product family. It is the most capable open-source model that we have tested to date. Try it today in Cosmo
We recently joined NVIDIA, Microsoft, and others in supporting open-weight AI. Today, we’re putting that belief into the product with model choice on Replit, starting with Kimi K3. The future is the r
Last week, we made ChatGPT Work available to enterprises. It's an awesome product. So for ChatGPT Enterprise customers, enroll by August 21, and each teammate who tries Work for the first time within
Together gives developers an efficient, high-throughput production path for K3’s long, tool-heavy agent workloads, hosted on Together AI’s US-based infrastructure with zero data retention. Start build
Kimi K3 will be here on Monday, but how do you know you’re ready to scale it in production? With our latest inference platform updates you can: 1/ Run shadow traffic to see how a new model performs on
Learn the architecture and design decisions behind an explainable next-best-product recommendation system for banking, built with Amazon SageMaker AI and PyTorch. A multi-tower neural network with lea
Introducing Agnost AI (YC S26): Product Analytics for AI Agents. Analytics was never built for chat & voice. And that is the new interface. Your users' hidden feature requests, bugs & churn hide in co
Great paper on self-improving agent harnesses. (bookmark it) If you maintain a production agent harness, finding every file behind one behavior is often harder than writing the edit. Harness Handbook
Are structured outputs in agents always good? This paper suggests that you might have to take a closer look. Your product's structured output surface is measurably more homogeneous than the chat surfa
Can’t tell if the PR reads more like a security incident or a product release… We suspected last week's cyberattack might have come from a frontier lab, given the sophistication of the agent. Turns ou