Search: “agents”

Openness without compromises for your Apache Iceberg lakehouse

model-releasesgoogle-cloud-ai

Today, at the Apache Iceberg Summit in San Francisco, we are announcing the preview of read and write interoperability between BigQuery and Iceberg-compatible engines, including Trino, Spark, and othe

8 Apr 2026

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Model Releases

The feature I most want from AI labs right now is documentation on which underlying search engines they use when their chat tools run a sear…

DGX agent

The feature I most want from AI labs right now is documentation on which underlying search engines they use when their chat tools run a search OpenAI and Anthropic and Meta AI all have search and I ha

model-releasessimon-willison--x

8 Apr 2026

Tools

/autofix-pr now lets you kick off autofix straight from the command line. After finishing up a PR, just run /autofix-pr. It sends your sessi…

/autofix-pr now lets you kick off autofix straight from the command line. After finishing up a PR, just run /autofix-pr. It sends your session to the cloud so the PR autofixer has full context to addr

toolsboris-cherny--x

Check out the GLM-5.1 first impressions with Peter on our YouTube https://www.youtube.com/watch?v=f11tVBXWr2g

model-releaseszhipu-ai--x

Z.ai's GLM-5.1 is a 754-billion parameter open-weight Mixture-of-Experts model released on April 7, 2026 under an MIT license, designed as a post-training upgrade to GLM-5 with a focus on long-hori...

GLM-5.1 is now available in Go w/ Zero Data Retention

model-releaseszhipu-ai--x

GLM-5.1 is now available through OpenCode Go, a low-cost subscription service ($5 first month, then $10/month) that provides access to open-source coding models with a zero data retention policy, m...

INCREDIBLE GLM-5.1 weights are now opensource > i’ve had early access to the weights for the past few days > and yeah… this one matters a lo…

model-releaseszhipu-ai--x

INCREDIBLE GLM-5.1 weights are now opensource > i’ve had early access to the weights for the past few days > and yeah… this one matters a lot benchmarks? > SWE-Bench Pro: 58.4 > beats Opus 4.6 (57.3)

Join the ARC Prize team -- help us build ARC-AGI-4 and ARC-AGI-5

model-releasesfrancois-chollet--x

Join the ARC Prize team -- help us build ARC-AGI-4 and ARC-AGI-5 Platform Engineer - Benchmark Lead ARC Prize Foundation is hiring a senior engineer to build our benchmark platform * Expand ARC-AGI-3

enterprise-aibedrockcustomer-service

Applications

CyberArk deploys Bedrock automation for support-case resolution

Human

CyberArk deployed AI log-parsing automation for support teams. CyberArk reported up to 95% shorter case resolution time using AI in an AWS post co-written with CyberArk.

18 Feb 2026

Nine models, five coding tasks, one 16GB GPU

I ran five coding tasks against nine models on one RX 9060 XT (16 GB). Each run gets a single spec file in an empty directory and has to produce solution.py and test_solution.py, run its own tests, an

18 Oct 2026

DeepSeek releases V4.1-Flash-1017, an update it says offers 'stronger benchmark performance, faster task completion, and shorter outputs' than its predecessor (Saritha Rai/Bloomberg)

Saritha Rai / Bloomberg: DeepSeek releases V4.1-Flash-1017, an update it says offers “stronger benchmark performance, faster task completion, and shorter outputs” than its predecessor — DeepSeek relea

model-releasestechmeme

Local Ai

Ollama Cloud is always zero data retention, hosted in US and EU with no training.

**Ollama Cloud** provides a cloud-hosted model serving platform that *never retains user data* ('zero data retention') and does **not train on any incoming data**. The infrastructure is distributed ac

local-aiollama--x

Recap on Best Open Source AI Models so far

model-releasesr-stablediffusion

So after so many models have been released the past year, what are everyone's top models so far? And settings/loras? Since sometimes those can make the difference in results. I am sure most people are

we’re getting used to it by now but DeepSeek calling this a “minor update” while moving Terminal-Bench 4.0 from 31.2 to 42.3 is very funny. …

model-releasesclem-delangue--x

we’re getting used to it by now but DeepSeek calling this a “minor update” while moving Terminal-Bench 4.0 from 31.2 to 42.3 is very funny. also reports 77.0 on DeepSWE (vs 74.0 for Opus 5 and 73.0 fo

What do you guys use for chat interface?

I use Pi/OpenCode for coding tasks which still seems to be the most popular, but I'm wondering what you guys use for normal chat interface. It's been a few months since I've seen discussions about har

Why not run Qwen 3.8 Flash Next with the full n-gram-table?

Already posted here https://www.reddit.com/r/LocalLLaMA/comments/1x85hfj/strata_qwen_38_flash_next_fast_but_whats_it/phavui9/ , but I believe this topic deserves it's own post. The PLE, aka the n-gram

Xolotl (Strata based) - DeepSeek-V4.1-Flash (552B) on a single 4090 at ~27 tok/s, Uncensored 1017 quant coming in a couple of days

Hey all, been meaning to post this for a while. I've been building an inference engine based off Strata called Xolotl that runs DeepSeek-V4.1-Flash, all 552B of it, on one gaming PC. My setup is a sin

America’s next top model, Reflection’s Beam, is now live on Together AI. Trained on Together GPU Clusters, Beam is Reflection’s first open-w…

model-releasestogether-ai--x

America’s next top model, Reflection’s Beam, is now live on Together AI. Trained on Together GPU Clusters, Beam is Reflection’s first open-weight model. • ~501B-parameter MoE, 23B active • Built for c

Hardware

Architecting for Hardware Diversity: Meta's End-to-End Co-Design for High-Performance AI Training on AMD GPUs

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

hardwarearxiv-cs-lg

CAT-alyzing Honesty: Continuous Adversarial Training for Transferable LLM Honesty

arXiv:2610.22292v1 Announce Type: cross Abstract: Large language models (LLMs) are becoming prevalent in scenarios where honesty is critical. However, despite alignment training, these models still ex

Hardware

CertEx: Exact Visual Retrieval at Scale by Certified Exclusion

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

hardwarearxiv-cs-cv

Applications

Choosing the right AI model is an operating decision. Today, we’re sharing our first set of benchmarks drawn from work across the 75+ accoun…

Choosing the right AI model is an operating decision. Today, we’re sharing our first set of benchmarks drawn from work across the 75+ accounting and IT services firms that make up Thrive Holdings. We

applicationslinus-lee--x

Local Ai

Confidence-Calibrated Inference Expansion for Evaluator-Guided Test-Time Reasoning

arXiv:2610.20836v1 Announce Type: new Abstract: Evaluator-guided reasoning presents a local control problem at every step: trust the current answer, return a fallback, or spend more inference. We form

local-aiarxiv-cs-ai

congrats to the StepFun team on releasing Step 5 Preview open weights today we’re excited to be a launch partner and to support another Step…

model-releasestogether-ai--x

congrats to the StepFun team on releasing Step 5 Preview open weights today we’re excited to be a launch partner and to support another StepFun release as they bring Step 5 Preview to developers Step

DeepSeek V4.1 Flash on 4x DGX Spark: my numbers vs Patrick Moorhead's results via Wccftech.

A couple of weeks ago I read this Wccftech article about Patrick Moorhead's 4 Spark setup. I meant to post this a few days ago but ran some more tests first, and then my workstation had a problem afte

From Long Context to Selective Memory:A Survey of Memory-Centric Compression for Large Language Models

arXiv:2610.21165v1 Announce Type: new Abstract: Long-context capability has become essential for large language models (LLMs) to handle complex tasks, yet continuously expanding the context window doe

Local Ai

IKMo: Image-Keyframed Motion Generation with Trajectory-Pose Conditioned Motion Diffusion Model

arXiv:2505.21146v2 Announce Type: replace-cross Abstract: While text-to-motion generation is mainstream, integrating explicit spatial constraints has become a standard solution for precise animation.

local-aiarxiv-cs-cv

Kimi K3, three months after the hype: too big for almost anyone to run locally, and smaller models have already caught it

K3 came out in July hyped as the best open model you could download, and it scored 57 on Artificial Analysis, right up there with Opus 4.8 and GPT-5.5. I went back to see what running it actually look

Learning to Reason with Selective Internal Feedback

arXiv:2610.21392v1 Announce Type: new Abstract: Reinforcement learning from internal feedback can improve language models without ground-truth answers or external verifiers. However, confidence and co

safetyarxiv-cs-ai

Memory as Weights: Internalizing Long-Term History for Streaming Videos

arXiv:2610.22070v1 Announce Type: cross Abstract: Streaming vision-language models (VLMs) must continuously integrate information from the past while remaining responsive to current observations and u

Mine, Sample, Render: Test-Time Diversity Alignment Of Generative Models

arXiv:2610.21185v1 Announce Type: new Abstract: Modern generative models produce high-quality individual outputs but struggle to sample diversely, even when explicitly instructed to do so. We introduc

safetyarxiv-cs-ai

Research

Mixture of Multi-Sequence Feature Difference for Contrast-Enhanced MRI Synthesis

arXiv:2610.21703v1 Announce Type: new Abstract: Contrast-enhanced magnetic resonance imaging (CE-MRI) is crucial for accurately diagnosing and segmenting brain tumors. However, the acquisition of CE-M

researcharxiv-cs-cv

MoCaP: Mobile Code-as-Policies for Zero-Shot Mobile Manipulation from Passive Human Videos

arXiv:2610.20998v1 Announce Type: new Abstract: Passive human videos of everyday activity offer robots access to a massive amount of human experience without requiring a demonstration for each task. H

safetyarxiv-cs-ro

OmniVerifier-C1: Decomposed Graded Verifier for Rule-Governed Generative World Modeling

arXiv:2610.22355v1 Announce Type: new Abstract: Generative visual verifiers play a crucial role in advancing multimodal intelligence. To enhance the robustness of visual verifiers in complex multimoda

safetyarxiv-cs-cl

Research

OnBodyAI - Why the Next AI Needs a Body

arXiv:2610.21137v1 Announce Type: cross Abstract: The next AI will not win by knowing more about the world. It will win because it knows you: because it lives on your body, works for you and answers t

researcharxiv-cs-ai

PEDBench: Can Speech Models Detect Phonetic Errors?

arXiv:2610.20830v1 Announce Type: new Abstract: Phonetic error detection (PED) aims to identify phoneme-level substitutions, deletions, and insertions and is essential for educational and clinical spe

Prism-1: Position- and Rival-Independent Scoring for System One Models

arXiv:2610.22066v1 Announce Type: new Abstract: Given a state and a set of options, such as intents, tools or interface elements, System One decision models return a distribution over the options in o

Research

Recursive Reward Improvement via Adversarial Meta-Prompt Evolution

arXiv:2610.21040v1 Announce Type: new Abstract: Recursive Self-Improvement (RSI) has gained wide attention for its ability to work with limited data. In a proposer-solver loop, a proposer model writes

researcharxiv-cs-ai

The SAVE method: Learn the fundamentals to engineer trustworthy generative media

model-releasesgoogle-cloud-ai

Google Cloud Consulting works with organizations every day to build generative media that’s trustworthy, brand-aligned, and stands out. Instead of relying on clever or complicated prompting, we’ve ide

Training-Free On-Policy Distillation

arXiv:2610.22236v1 Announce Type: cross Abstract: On-policy distillation consolidates specialist models into one student at the price of rollouts, teacher passes and gradient steps for every teacher.

safetyarxiv-cs-ai

Training Reasoning Models to Generate Diverse Scientific Ideas

arXiv:2610.22324v1 Announce Type: new Abstract: One of the first steps of a research pipeline is generating ideas. Large Language Models (LLMs) are increasingly used to automate this step, but most of

Understanding How Neural Networks Learn (with interactive visualizations)

TL;DR -- Interpretability might be way more tractable than we thought, and the guy who helped convince everyone otherwise is now saying we can understand models by directly studying neurons and their

VALCON: Benchmarking and Enhancing Value Consistency in Large Language Models via Dual-Role Variation

arXiv:2610.21304v1 Announce Type: new Abstract: Current value alignment evaluations for large language models (LLMs) heavily rely on output compliance, overlooking whether LLMs maintain value consiste

VELD-QA: A Large-Scale Dataset for Visual Evidence Grounding and Question Answering in Long Documents

arXiv:2610.20964v1 Announce Type: cross Abstract: Existing long-document QA benchmarks rarely combine large-scale human-authored questions with detailed visual evidence annotations, limiting diagnosis

Verdict: Encode Once, Decide Many

arXiv:2610.20778v1 Announce Type: cross Abstract: Automating organizational work means answering many small typed questions about one piece of state (does this email need a reply, how urgent is it, wh

VisualTrust: Video Reasoning under On-Screen Claim Framing

model-releasesarxiv-cs-cv

arXiv:2610.21159v1 Announce Type: new Abstract: On-screen text can describe what a video shows, or it can frame what the video is supposed to mean. Current benchmarks treat both alike, testing whether

We’re excited to be day 0 partners for @reflection_ai’s first open-weight model! For a limited time, Beam is FREE on Ollama! In partnership …

We’re excited to be day 0 partners for @reflection_ai’s first open-weight model! For a limited time, Beam is FREE on Ollama! In partnership with @reflection_ai this model is hosted in the US with full

model-releasesollama--x

When Reality Outpaces Cognition: A New Scaling Principle for Reliable Intelligence

arXiv:2610.20764v1 Announce Type: new Abstract: This paper challenges the understanding capabilities of existing AI paradigms and emerging world models by asking a fundamental question: How quickly ca

4x R9700 builds with 127 used EPYCs: 10.7k all-in per machine. I built three (384GB VRAM)

I saw the 4x R9700 build for a 10-person startup here a few days ago and wanted to share my results, since I opted to spend most of the money on the cards. I went with a super cheap used EPYC instead