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Research1 мин

Microsoft acquired Maluuba a year before GPT-1 was released.

Microsoft acquired Maluuba a year before GPT-1 was released. The company's founder admits that he regrets the sale because Maluuba could have become the next OpenAI. Now the same deep learning team is back with a new project called Skyfall AI, and its first model is...

Telegram — Вайб-кодинг
General1 мин

Китайские учёные взяли робособаку в экспедицию по опасным лесам

🐕 Китайские учёные взяли робособаку в экспедицию по опасным лесам Биологи исследовали биоразнообразие в субтропических лесах гор Айлаошань, а помогал им Lynx M20S от DEEP Robotics. Робопёс перевозил снаряжение, разведывал маршруты и снимал дикую природу. Ему даже удалось…

Telegram — GPT Time | Нейросети | ИИ
Knowledge base1 мин

Work IQ: MCP Retrieve Tool

🚀 Meet the new retrieve MCP tool in Work IQ! The new retrieve tool enables agents to search a user’s workplace data across emails, files, meetings, Teams messages, people, and connected enterprise sources, bringing relevant organizational knowledge directly into agentic…

YouTube — Microsoft Developer
Startups1 мин

Datacenter at Home - GB300 GPU - w/ Asus DGX Station (ET900N G3)

What is going on everybody and welcome to a very exciting review of ASUS's take on the Nvidia DGX station. They're calling this the ET900N G3, but I'm going to keep calling it the DGX station or ASUS station for short. What we have here is 748 GB of coherent memory. That's kind…

YouTube — sentdex
Research1 мин

Where the Blocks Live: Tier-Aware KV-Cache Routing for vLLM at Scale

Привет, я Бон-хва Пак из Ware. На конференции Pite Wash в Северной Америке в 2026 году я представлю постер под названием «Где живет блок». Когда память GP заполняется, VLAD принудительно переместит кэш KB на CPU или в хранилище. VLAD будет отслеживать местоположение каждого…

YouTube — PyTorch Official
General1 мин

Google taught AI agents to independently improve their work

🤖 Google taught AI agents to independently improve their work The company opened access to Harness², a system that helps AI agents increase efficiency by up to 11% without retraining the model itself. Agents independently experiment with prompts, tools, memory and...

Telegram — GPT Time | Нейросети | ИИ
Knowledge base1 мин

My favorite new image editing tool

This is one of the coolest things I've seen this week. If you haven't played with Core 3 yet, you've got to try it. Now, this isn't sponsored. This is just an AI image editing tool that I've found to be really cool. So, check this out. I can upload like a YouTube thumbnail,…

YouTube — Matt Wolfe
Research1 мин

World of SWECraft: Agent Collaboration at Scale via Simulated Software Worlds

arXiv:2610.24061v1 Announce Type: new Abstract: As teams of AI agents take on larger projects and long-standing open problems, agent collaboration offers another dimension for scaling inference-time compute. To understand what makes such collaboration effective and scalable, we…

arXiv — cs.AI
Research1 мин

GardenBench: A lightweight, daily evaluation of LLM capabilities

arXiv:2610.23866v1 Announce Type: new Abstract: We introduce GardenBench, a benchmark with 11 test suites that evaluate the capabilities of Large Language Models (LLMs) across a range of tasks. By systematically prompting LLMs with various lightweight queries, we document…

arXiv — cs.AI
Research1 мин

What Social Media Teaches Us About Accumulative AI Risks

arXiv:2610.24006v1 Announce Type: new Abstract: Prominent AI safety discussions emphasize existential threats and catastrophic events, such as AI-enabled nuclear conflict or engineered biological outbreaks. This position paper argues that there is another type of AI risk that…

arXiv — cs.AI
Research1 мин

Unified Multiparadigm Fusion Intelligence for Rare Disease Diagnosis

arXiv:2610.24024v1 Announce Type: new Abstract: Rare diseases (RDs) affect an estimated 300 million people globally, leaving patients to navigate a protracted diagnostic odyssey constrained by clinical scarcity and fragmented medical knowledge. Artificial intelligence (AI) has…

arXiv — cs.AI
Research1 мин

Cache2LoRA: Understanding and Improving Context Internalization

arXiv:2610.24107v1 Announce Type: new Abstract: Context-to-LoRA methods encode documents as low-rank parameter updates, allowing language models to answer without retaining the source text in their decoding context. How reliably do these updates preserve facts and support their…

arXiv — cs.AI
Research1 мин

Joint, Decoupled, or Agent: When Each Multimodal Alignment Paradigm Wins

arXiv:2610.24108v1 Announce Type: new Abstract: Jointly pretrained multimodal encoders are a common way to combine modalities, while alternatives integrate their information during downstream training or inference. When does each approach win? We compare three paradigms,…

arXiv — cs.AI
Research1 мин

Self-Improving Video-to-Action Models

arXiv:2610.24177v1 Announce Type: new Abstract: Video generative models are an emerging tool for embodied agents: they can serve as scalable visual planners, generating videos that depict how to complete previously unseen tasks. However, executing these plans typically requires…

arXiv — cs.AI
Research1 мин

Distillation, Self-Training, and the Fragility of Learned Chemical Reasoning

arXiv:2610.24199v1 Announce Type: new Abstract: Automating synthesis planning for small-molecule drug design requires chemical reasoners that are accurate as well as open to inspection and adaptation, yet frontier language models remain unreliable at predicting reaction outcomes…

arXiv — cs.AI
Research1 мин

Cortex: A Fixed-Point Theory of Governed Coding Agents - Technical Report

arXiv:2610.24255v1 Announce Type: new Abstract: A coding agent combines a large language model (LLM) with a harness that plans, edits, and executes code. We study Cortex, a supervisory layer for pre-execution governance, requirement tracking, and iterative validation and repair.…

arXiv — cs.AI
Research1 мин

Probing Ambiguity: Adversarial Intent Resolution for Robust Text-to-SQL

arXiv:2610.24248v1 Announce Type: new Abstract: Text-to-SQL systems typically assume a one-to-one mapping between natural-language queries and correct SQL translations. In practice, however, many queries are inherently ambiguous, admitting multiple valid interpretations that…

arXiv — cs.AI
Research1 мин

AM-Bench: A Unified Taxonomy and Evaluation Suite for Agentic Misalignment

arXiv:2610.24264v1 Announce Type: new Abstract: As LLM-based agents are deployed with increasing autonomy in real-world environments, a critical failure mode emerges: agentic misalignment, where agents choose harmful actions over failure. However, existing safety benchmarks…

arXiv — cs.AI