Search: “productivity”

Leaders across industries around the world are asking: How do we harness all of this powerful technology effectively and at scale, to solve real problems, and drive value and impact, right now?Google

arXiv:2604.08525v1 Announce Type: cross Abstract: Today's large language models (LLMs) are trained to align with user preferences through methods such as reinforcement learning. Yet models are beginni

Agent skills are great. I wanted to share some of my favorites from Jesse Vincent's 'Superpowers' skill pack 𝚠𝚛𝚒𝚝𝚒𝚗𝚐-𝚙𝚕𝚊𝚗𝚜 skill produces much better plans than any harness' built in plan mode that I'

arXiv:2604.07120v1 Announce Type: cross Abstract: Current operational Earth Observation (EO) services, including the Copernicus Emergency Management Service (CEMS), the European Forest Fire Informatio

arXiv:2604.06336v1 Announce Type: cross Abstract: Graph Transformers have recently attracted attention for molecular property prediction by combining the inductive biases of graph neural networks (GNN

arXiv:2604.06718v2 Announce Type: cross Abstract: Repurchase behavior is a primary signal in large-scale retail recommendation, particularly in categories with frequent replenishment: many items in a

Completely agreed. Everyone in SF knows how good these models are at coding / work automation. When it comes to writing, there’s still a insane amount of model-generated AI slop because there’s no eas

arXiv:2601.16074v2 Announce Type: replace Abstract: Industrial Cyber-Physical Systems (CPS) are sensitive infrastructure from both safety and economics perspectives, making their reliability criticall

arXiv:2410.08334v2 Announce Type: replace-cross Abstract: In this paper, we build a reinforcement learning framework to study how children compose numbers using base-ten blocks. Studying numerical cog

great question! knowledge (system prompt, skills) and tools (apis, clis, whatnot) will always be needed, even as the best way to build agents changes i would focus on those and processes around those

Migrating your existing application load balancer infrastructure from an on-premises hardware solution to Cloud Load Balancing offers substantial advantages in scalability, cost-efficiency, and tight

My X bookmarks have an 'intellectual shape' Apparently mine is: Technique-heavy, Tool-obsessed, Light on Opinion I didn't know until I ran the numbers OSS I've been building w/@LangChain to explore Ge

arXiv:2604.04868v2 Announce Type: replace-cross Abstract: Tabular foundation models (TFMs) such as TabPFN (Tabular Prior-Data Fitted Network) are designed to generalize across heterogeneous tabular da

Now your business analyst in HR, Finance, or Sales team can build a live app or dashboard, a slide deck that updates in real time, or anything for that matter for your CEO. Combine the speed and power

arXiv:2602.16005v2 Announce Type: replace-cross Abstract: We introduce ODYN, a novel all-shifted primal-dual non-interior-point quadratic programming (QP) solver designed to efficiently handle challen

Open swe uses deepagents under the hood Deepagents is general purpose, openswe is focused on coding @hwchase17 @LangChain This is a very interesting comparison. Now my question is: how to compare Deep

Since our initial announcement, we have started onboarding beta design partners. - Connect your Lakebase data - Build an application - Deploy to your Databricks account Reach out to your Replit/Databr

arXiv:2604.06265v1 Announce Type: new Abstract: Quantum-inspired tensor networks algorithms have shown to be effective and efficient models for machine learning tasks, including anomaly detection. Her

arXiv:2604.06391v1 Announce Type: cross Abstract: Graphs are a central representation in biomedical research, capturing molecular interaction networks, gene regulatory circuits, cell--cell communicati

arXiv:2511.19693v3 Announce Type: replace-cross Abstract: Payment networks form the backbone of modern commerce, generating high volumes of transaction records from daily activities. Properly modeling

what he said 🗣️ the very best agents today obsessively tailor the harness layer around the model I’m looking at you “5 things I learned from the Claude code leak” bros 👀 orchestration patterns, tool d

why not? what in the current harnesses are not bitter lesson-pilled? off top of head: will go away: - planning tools - compaction (or at least will matter less) not going away: - sub agents - skills -

Wrapped up the 3-day AI Engineer conference in London. Key takeaways: Planning & verification > implementation. Humans define what to build and validate it works. AI handles the coding. The harness ma

And that is what Thoth uses for its agents in the backend. Thanks for your contributions to oss @LangChain @hwchase17 https://github.com/siddsachar/Thoth AI that doesn't just work for you, it knows yo

Deep Agents or @LangChain? Just use the right tool for the right job great q! deepagents has more 'batteries included', which langchain v1 is a very minimalistic agent harness if you are doing more co

The referenced tweet (from @himanshustwts) is not publicly accessible without a login, so its exact content cannot be retrieved. However, based on contextual search results, this post appears to be...

I know it's self serving to say, but man I would've killed for a resource like Tinker and the tutorials, the cookbook, etc back when I was in undergrad. Following @karpathy blogs and training RNNs on

A user on X (formerly Twitter) expressed enthusiasm for an evaluation ('eval') track at an AI Engineer (@aiDotEngineer) event, noting its relevance to ClawBench — an open-source benchmarking and ev...

maybe some nuance 😄 I don’t think anyone is “lying” about how great Mythos will be —> but there’s expectation misalignment between the Test Harness set up for Mythos and a belief it was given this cra

most of the agents we see being built do this the main cases where we see people using 'agent in a sandbox' is when they are using claude agent sdk (which is poorly designed for 'harness outside sandb

The specific post at URL `https://x.com/sydneyrunkle/status/2042269358756397525` was not found in the search results, and the post ID does not match any retrieved content. The closest post found (s...

Vercel is positioning itself as a full-stack 'Agentic Infrastructure' platform, recognizing that weekly deployments have doubled in three months, with over 30% now initiated by coding agents — up ...

we got LangPod before GTA6 🙏 this series is gonna be sick - real stuff that breaks with agents, mental models, evals, tooling with some of the best builders across industry great to openly share all t

With closed agent platforms like Claude Managed Agents, your agent's memory belongs to them, not you. It's locked behind their API. Agent infra should be open: open harness, open memory, model agnosti

'Claude Code isn't magic. The harness layer is just software, and software is something any dev can shape to fit how they want to work.' Check out @Hacubu’s practical guide to building a custom agent

Highlights: 👉 28% coding improvement over GLM-5 with refined RL post-training 👉 Better long-horizon execution across hundreds of rounds and thousands of tool calls 👉 Thinking mode, tool calling, and s

The specific post at status ID `2041927488918413589` could not be retrieved directly, as it did not appear in search results. However, based on the surrounding context from the same account (@Vtriv...

If you're an AI/agent builder, it's so important that you don't overbuild and overcommit on a specific toolset and infrastructure. Frontier labs are shipping not just the models, but the harnesses and

Proud to power @NousResearch's Hermes Agent with MiniMax M2.7, and excited for what we're building together. Try MiniMax M2.7 in Hermes Agent today → https://portal.nousresearch.com #MiniMax #NousRese

> which is exactly why we believe memory should live outside of model providers open harness = open memory which everyone should want! The new Anthropic managed agents API is basically the Letta API t

arXiv:2606.17090v2 Announce Type: replace-cross Abstract: ANEForge is a Python package that programs the Apple Neural Engine (ANE), the fixed-function neural accelerator on every recent Apple device,

arXiv:2610.22230v1 Announce Type: cross Abstract: Meta deploys a heterogeneous fleet comprising NVIDIA GPUs, AMD GPUs, and proprietary MTIA accelerators to reduce costs and mitigate vendor lock-in. Ho

arXiv:2610.21325v1 Announce Type: new Abstract: Exact k-nearest-neighbor (kNN) search over image descriptors and embeddings underlies visual retrieval, near-duplicate detection, the evaluation of lear

arXiv:2610.22160v1 Announce Type: cross Abstract: Test-time context optimization adapts frozen language models through textual feedback, but ordinary conditional generation provides no separate contro

// FDE-Gym: Agents as Forward-Deployed Engineers // They found that the best agent configuration fully resolved 14 of 95 real customer-delivery tasks. FDE-Gym tests agents as forward-deployed engineer

arXiv:2610.22350v1 Announce Type: new Abstract: Existing agent benchmarks typically evaluate agents on well-specified tasks defined by issue reports, specifications, or task tickets. Real-world custom