Knowledge catalogue
arXiv:2608.02576v1 Announce Type: new Abstract: We consider optimization problems defined on product spaces of simplices. Examples of this class of problems include learning low-rank discrete multivar
As your AI agents move from prototype to production, the challenge shifts from getting them to work to keeping them fast and efficient. Learn how to use Amazon Bedrock AgentCore Observability and Amaz
Enterprises are discovering that a scalable intelligence layer built on knowledge graphs delivers the institutional context that turns generic AI models into reliable production systems. As companies
A local coding agent, an in-app customer assistant, and an AI SRE triaging production logs may all use the same model class—but not the same harness, eval plan, or rollout risk. Mastra CEO Sam Bhagwat
arXiv:2607.01258v1 Announce Type: cross Abstract: The rapid advancement of Artificial Intelligence (AI) has been accompanied by significant increases in computational and environmental costs, driven b
Interrupt 2026 is coming to New York City and London this fall. → Hear from engineers + teams shipping agents in production → Keynotes from @hwchase17 + industry leaders on what's next for agents → Ha
arXiv:2507.07445v3 Announce Type: replace Abstract: Autonomous agents navigating human society must master both production activities and social interactions, yet existing benchmarks rarely evaluate t
In 2017, Elon Musk was photographed at the Tesla Model 3 production line on his birthday, with the accompanying message 'Never give up' emphasizing persistence and determination. The image captured a
I spend 10 minutes a day trying a new app. http://matrix.build is my favorite app today. You can tell from a product whether the team's thinking is clear. The thing I love about matrix is it helps you
Tesla has announced that it will increase production output at its Giga Berlin factory by another 20% to 7,500 vehicles per week starting in October of this year. This is in addition to the 20% produc
arXiv:2606.24655v1 Announce Type: cross Abstract: The explosive growth and complexity of product data within the dynamic Brazilian e-commerce landscape demand robust and specialized methods for struct
We’ve designed and built our first AI chip: Jalapeño. Designed from the ground up by OpenAI and brought to production with @Broadcom, Jalapeño is purpose-built for the LLM workloads powering ChatGPT,
Chevrolet's Corvette ZR1X, powered by a hybrid all-wheel drive system with 1,250 horsepower, set a new Pikes Peak production car record at the 104th running of the hill climb. Driven by IndyCar vetera
arXiv:2606.10699v1 Announce Type: cross Abstract: In the production process of network cables, ensuring the correct color sequence of wire pairs inside the standard connector plays a critical role in
arXiv:2606.01472v1 Announce Type: cross Abstract: High-stakes production document-generation systems require language models to be adaptive, evidence-grounded, and auditable. We present HOPM, a hierar
arXiv:2605.25665v1 Announce Type: cross Abstract: AI-native software development is often evaluated at the level of individual models, prompts, or generated artifacts. This framing is insufficient for
Many development teams are familiar with the hesitation that comes right before pushing a new feature live. As AI helps developers write code faster, the gap between rapid code generation and safe pro
arXiv:2605.20173v1 Announce Type: new Abstract: Production LLM agents combine stochastic model outputs with deterministic software systems, yet the boundary between the two is rarely treated as a firs
Network verification company Forward Inc. today launched Forward Predict, a new capability that lets network teams test proposed changes against a digital twin of their production network before deplo
Claude Code's product lead addresses how Anthropic tunes the 'harness' (the structural layer around the model) for each new model release to optimize performance and reduce verbosity. The company comm
arXiv:2605.03439v1 Announce Type: new Abstract: The exponential growth of e-commerce platforms in Indonesia has generated a massive volume of user-generated product reviews. Analyzing the sentiment of
arXiv:2007.02392v3 Announce Type: replace Abstract: We study the problem of estimating the parameters of a Boolean product distribution in d dimensions, when the samples are truncated by a set S subse
everyone would have a deeper appreciation for Agent Products that rock because of great Context/Harness Engineering if they… talked to: - LLM Base models - Post-Trained models with no harness (no tool
arXiv:2605.00506v1 Announce Type: new Abstract: We model utterance production as probabilistic cost-sensitive choice over contextual alternatives, using information-theoretic notions of cost. We disti
arXiv:2604.26983v1 Announce Type: cross Abstract: This paper presents a novel value-aware approach to product recommendation that simultaneously addresses the high dimensionality and sparsity of user-
arXiv:2604.25452v1 Announce Type: new Abstract: Sentiment analysis of product reviews on e-commerce platforms plays a critical role in automatically understanding customer satisfaction and providing a
LangGuard's agentic workflow governance engine represents one of the first production deployments of Lakebase, Databricks' platform for managing AI agents. The deployment demonstrates how organization
we have updated our partnership with microsoft. microsoft will remain our primary cloud partner, but we are now able to make our products and services available across all clouds. will continue to pro
Worth a read if you are building production-grade AI agents. // Stateless Decision Memory for Enterprise AI Agents // Most of the interesting AI agent papers right now are about capability. This one i
Going from local to production with agents can be tricky, especially when you go from a single user (you, the developer) to multi-tenant systems. Great blog from Sydney on best practices for doing thi
Production machine learning systems can experience performance degradation where predictions appear reasonable and metrics don't change immediately, yet decision quality decays over time in ways diffi
Emily Zemler / The Wrap: A look at Doug Liman's 70M Bitcoin: Killing Satoshi movie, which uses AI for sets, lighting, and more in post-production, cutting costs from an estimated 300M — “Bitcoin: Kill
Building agents locally does not mean they’re ready to deploy in production LangSmith deployments helps with that 🔐 One deployment, isolated data per user. Add custom auth so every user gets their own
arXiv:2604.09791v1 Announce Type: new Abstract: Small language models are attractive for production deployment due to their low cost, fast inference, and ease of specialization. However, adapting them
arXiv:2604.10885v1 Announce Type: cross Abstract: This paper proposes a method to review public acceptance of products based on their brand by analyzing the facial expression of the customer intending
arXiv:2604.09952v1 Announce Type: new Abstract: Many applications today use large language models for code generation; however, production systems have strict latency requirements that can be difficul
Reuters: Sources: Chinese chipmaker YMTC plans to build two more factories in addition to one that will be completed in 2026, more than doubling its production capacity — Chinese chipmaker Yangtze Mem
Electric pickup startup Slate Auto recently announced it raised $650 million in a funding round as it nears production of its Slate Truck. The vehicle, scheduled for late 2
Harrison Chase discusses the tradeoff between speed and focus when building a core product using a frontier model versus developing more customized solutions. Using a frontier model with a standard ha
This Reddit post from r/MachineLearning announces a build-from-scratch Python book focused on the engineering infrastructure surrounding AI systems — the components beyond the model call itself, such
Stability AI launched Brand Studio on April 8, 2026, a fully managed end-to-end creative production platform built specifically for professional marketing and advertising teams. Teams can embed t...
arXiv:2610.12957v1 Announce Type: cross Abstract: Embodied agents must translate multimodal observations and user requests into executable actions while adapting to product constraints, changing goals
arXiv:2610.12657v1 Announce Type: cross Abstract: Efficient autoregressive generation is increasingly limited by the memory footprint of the key-value (KV) cache, which grows linearly with sequence le
**Summary** TinyFish showcases a streamlined workflow for moving their web‑native machine‑learning model from post‑training into production using Databricks AI Runtime. The article details the deploym
arXiv:2610.08126v1 Announce Type: cross Abstract: Product Identification has sprung up to become one of the most challenging problems in the automation of the retail industry. With the new industry 5.
Vanity Fair: Q&A with Sam Altman on his kids, his rivalries, pronatalism, “prepping” for the apocalypse, new products, the IPO delay, Luca Guadagnino's Artificial, and more — In an exclusive video int
So much reporting on the Claude or OpenAI usage of the same handful of technology companies with competing products & huge cloud infrastructure of their own. There are many, many more firms out there
A thing to know about the AI business is labs that have frontier models can release half-built products and they work surprisingly well because the AI can just figure stuff out and improvise. Its like
Agents built and deployed on MongoDB’s Atlas Agent Engine can export OpenTelemetry traces to Arize AX, where teams can inspect each run, evaluate both the outcome and execution path, and test fixes be
arXiv:2609.30471v1 Announce Type: cross Abstract: Reference-based LLM-as-a-judge evaluation assumes the reference answer is the target. In deployed agentic systems that operate over dynamic entities (
arXiv:2609.31498v1 Announce Type: cross Abstract: Search is one of the most important features in e-commerce, directly driving customer engagement and business growth. A good product search system mus
arXiv:2609.29952v1 Announce Type: new Abstract: Before a product or policy change ships, the question that matters is how people will react to it. Augur rehearses that reaction offline: it builds a ty
arXiv:2609.30137v1 Announce Type: new Abstract: Customer experience (CX) agents use tools and large language models to address customer requests and guide conversational interactions with an organizat
arXiv:2609.25433v1 Announce Type: new Abstract: Modern production-scale recommender systems rely on complex, multi-task ranking models. Introducing new prediction tasks into these massive systems ofte
arXiv:2609.26642v1 Announce Type: cross Abstract: Successful agent execution need not identify which future product improvement its user would value. We present a decision-specific audit that maps a d
arXiv:2609.24122v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is hard to monitor in production: exhaustive relevance labels do not exist for non-stationary multi-million-passage
Found a great production use case for Jev. I used Jev to organize ~2.3K AI research papers. The total cost was $0.14, and it took about 83 seconds. The process: The papers already had old tags, which
arXiv:2609.20449v1 Announce Type: new Abstract: The economic value of inference depends on how capacity and task information are distributed across stages of AI production. We study these organization
Developer security startup Arcjet Labs Inc. today launched agent runtime security, a new offering that tracks what artificial intelligence agents do once they are running in production systems. Securi
arXiv:2609.18729v1 Announce Type: cross Abstract: Consumers increasingly use AI chatbots for advice on what to buy. With companies like OpenAI and Google monetising their AI through advertising, this