Инфрақұрылым1 мин
Более 40 тыс. км автомобильных дорог Казахстана обеспечат мобильной связью
Определены дальнейшие шаги по реализации проекта и взаимодействию между АО «Транстелеком» и операторами сотовой связи.
Profit.kz — ИТ в Казахстане
Мақалалар каталогы
Барлық материалдар
Барлық жарияланған талдаулар, егеменді стек зерттеулері, экожүйе жаңалықтары және ЖИ модельдерінің шолулары.
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Материал
Зерттеулер1 мин
Главы Anthropic, OpenAI и xAI призвали замедлить разработку ИИ Из-за рисков для безопасности 👀 Глава Anthropic Дар...
Главы Anthropic, OpenAI и xAI призвали замедлить разработку ИИ Из-за рисков для безопасности 👀 Глава Anthropic Дар....
Telegram — BlueScreen.kz
Стартаптар1 мин
OpenAI ресурстарына $1 млн-ға дейінгі көлемде қол жеткізіп, өз AI-шешіміңізді жасағыңыз келе ме? 🚀23 қыркүйекте Аста...
OpenAI ресурстарына $1 млн-ға дейінгі көлемде қол жеткізіп, өз AI-шешіміңізді жасағыңыз келе ме? 🚀23 қыркүйекте Астанада OpenAI қатысуымен әлемдегі ең ірі AI-хакатон — HackAlem AI өтеді. Ол әзірлеушілерді, стартаперлерді, AI-энтузиастарды және болашақтың шешімдерін жасауға…
Astana Hub (KB mirror)
Саясат және реттеу1 мин
Мемлекеттік қызметтердің 90%-дан астамы онлайн қолжетімді, ЖИ ассистенттер 2 млн-нан астам сұранысты өңдеді
eGov GPT 51 мемлекеттік қызметті қамтып, азаматтардан түскен өтініштердің шамамен 30%-ын өңдейді.
Profit.kz — ИТ в Казахстане
Жалпы1 мин
В GPT-6 Astra обнаружили странную брешь между возможностями модели и проверками безопасности.
В GPT-6 Astra обнаружили странную брешь между возможностями модели и проверками безопасности. Astra понимает текст, набранный в неправильной раскладке, а защитные фильтры — нет. Сначала парень написал на украинском английскими буквами: "Привет. Ты меня понимаешь? Отвечай только…
Telegram — Вайб-кодинг
Жалпы1 мин
ИИ распознаёт блюда и считает калории: новую систему тестируют в Нацгвардии Казахстана - 24.kz
ИИ распознаёт блюда и считает калории: новую систему тестируют в Нацгвардии Казахстана - 24.kz.
24.kz
Жалпы1 мин
ИИ распознаёт блюда и считает калории: новую систему тестируют в Нацгвардии Казахстана - 24.kz
ИИ распознаёт блюда и считает калории: новую систему тестируют в Нацгвардии Казахстана - 24.kz.
24.kz
Стартаптар1 мин
Казахстанский стартап Fabs3D AI представил проект в Cambridge Innovation Center рядом с MIT - the-tech.kz
Казахстанский стартап Fabs3D AI представил проект в Cambridge Innovation Center рядом с MIT - the-tech.kz.
The Tech.kz — венчур и стартапы
Саясат және реттеу1 мин
Более 90% госуслуг доступно онлайн, ИИ-ассистенты использованы свыше 2 млн раз
Казахстан переводит госуслуги и экономику на рельсы искусственного интеллекта.
Profit.kz — тег «Искусственный интеллект»
Зерттеулер1 мин
Главы Anthropic, OpenAI и xAI призвали замедлить разработку ИИИз-за рисков для безопасности 👀Глава Anthropic Дарио...
❗️Главы Anthropic, OpenAI и xAI призвали замедлить разработку ИИИз-за рисков для безопасности 👀Глава Anthropic Дарио Амодей призвал крупнейшие ИИ-компании снизить темпы развития самых мощных моделей, чтобы технологии безопасности и контроля успевали за ростом возможностей ИИ.…
Telegram — BlueScreen.kz
Зерттеулер1 мин
Occamy-1.0: Open Pareto-frontier 35B Intelligence for Co-work
arXiv:2609.11977v1 Announce Type: new Abstract: Co-work agents execute complex workflows that combine information gathering, tool use, coding, and file manipulation across many model invocations. Because cost and latency accumulate over the full episode, their practical value…
arXiv — cs.AI
Зерттеулер1 мин
Language Is an Insufficient Substrate for Quantitative Reasoning, and Consequential Domains Need Large Quantitative Models
arXiv:2609.12105v1 Announce Type: new Abstract: The prevailing assumption in applied machine learning is that progress on consequential quantitative decisions such as pricing risk, allocating capital, triaging patients, or containing a network intrusion will follow from progress…
arXiv — cs.AI
Зерттеулер1 мин
Mined from Scientific Literature: Process Schemas for Atomic Layer Deposition and Etching in Materials Science
arXiv:2609.12139v1 Announce Type: new Abstract: Atomic layer deposition (ALD) and atomic layer etching (ALE) are reported heterogeneously across experimental and simulation literature in materials science, hindering comparison and machine-actionable reuse. We present four…
arXiv — cs.AI
Зерттеулер1 мин
Can LLMs in Draft-Verify-Revise Pipelines Resolve Deictic Ambiguity?
arXiv:2609.12162v1 Announce Type: new Abstract: Draft-verify-revise is a common LLM orchestration pattern for scaling inference-time compute. One LLM drafts, a second critiques the draft and provides feedback, and a third uses that feedback to revise the draft into the final…
arXiv — cs.AI
Зерттеулер1 мин
GTA: Graph Theory Agent and Benchmark for Algorithmic Graph Reasoning with LLMs
arXiv:2609.12265v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly asked to reason over structured data such as graphs, yet how reliably they can carry out multi-step graph algorithms in language remains unclear. Existing evaluations tend to use simple…
arXiv — cs.AI
Зерттеулер1 мин
Hybrid Physics-AI Framework of Body Center of Mass Dynamics from Wrist-Worn Sensors
arXiv:2609.12304v1 Announce Type: new Abstract: Wrist-worn IMU has been widely used for daily-life health monitoring. Yet, it does not fully represent whole-body dynamics, for which the body center of mass (COM) is considered the physiological reference standard. Therefore, this…
arXiv — cs.AI
Зерттеулер1 мин
Toward Robust Personalized Alignment for LLMs: Mitigating Persona Drift in Multi-Turn Dialogue
arXiv:2609.12373v1 Announce Type: new Abstract: Persona drift remains a central challenge for personalized language models, as user profiles evolve over long interactions rather than remain permanently fixed. Models must therefore revise persistent persona states when…
arXiv — cs.AI
Зерттеулер1 мин
Is Gaussian Splatting Becoming Neural Again? A Taxonomy and Controlled Study of Learned Parameterization
arXiv:2609.12395v1 Announce Type: new Abstract: Three-dimensional Gaussian Splatting (3DGS) combines explicit primitives with efficient rasterization, yet recent systems increasingly use neural networks to generate or share Gaussian parameters. We characterize this trend along…
arXiv — cs.AI
Зерттеулер1 мин
Harness or Model? Isolating the Harness Effect in Agentic Coding with a Contamination-Controlled Private Suite
arXiv:2609.11987v1 Announce Type: new Abstract: An agentic coding system couples a language model to a harness: the tools, prompts and control flow that turn a chat model into an autonomous software engineer. Vendors ship harnesses tuned to their own models, and practitioners…
arXiv — cs.AI
Зерттеулер1 мин
Reading the Whole Heart: Latent-Attention Masked Autoencoders for Multimodal Cardiac Representation Learning
arXiv:2609.12035v1 Announce Type: new Abstract: Cardiovascular diagnosis rests on integrating complementary modalities, like ECG, echocardiography, chest radiographs, and clinical variables, each capturing distinct but correlated aspects of cardiac physiology. Yet most medical…
arXiv — cs.AI
Зерттеулер1 мин
Competence-Gated Pooling of Language Models and Priors for Event Forecasting
arXiv:2609.12101v1 Announce Type: new Abstract: In hybrid forecasting, a language model is often one of several available signals. A system may already have a market, crowd, or statistical forecast and must decide whether the model adds useful information or should be ignored.…
arXiv — cs.AI
Зерттеулер1 мин
DU-NO: A Parameter-Efficient Double U-Shaped Neural Operator for Phase-Resolving Wave Modeling
arXiv:2609.12115v1 Announce Type: new Abstract: Phase-resolving wave models such as FUNWAVE-TVD are the accuracy standard for nearshore dynamics, resolving the shoaling, refraction, and breaking of individual waves, but their cost rules them out for the ensembles, uncertainty…
arXiv — cs.AI
Зерттеулер1 мин
When Successful Knowledge Graph Edits Displace Correct Answers: Rank-Level Locality beyond Parameter Support
arXiv:2609.12116v1 Announce Type: new Abstract: Editing a knowledge graph embedding (KGE) model to promote a desired answer can displace correct answers from the returned list. Locality tests based only on facts that reuse the edited parameter can miss this ranking effect. We…
arXiv — cs.AI
Зерттеулер1 мин
WinSyn: An Automated Pipeline for Realistic Enterprise Question-Answering Evaluation
arXiv:2609.12171v1 Announce Type: new Abstract: Enterprise settings provide a challenging environment for question-answering agents, which often rely on Retrieval-Augmented Generation, Deep Research (DR), and related techniques. Much of this challenge comes from the complexity…
arXiv — cs.AI
Зерттеулер1 мин
Soft Symbol Grounding for Prototypical Concepts
arXiv:2609.12247v1 Announce Type: new Abstract: Neuro-symbolic models are usually trained with supervision only on final labels, leaving the intermediate concepts unobserved. Since many concept assignments are consistent with a given label, training can predict labels correctly…
arXiv — cs.AI
Зерттеулер1 мин
Learning Symbolic Constraint Representations from Examples: A Neuro-Symbolic Approach
arXiv:2609.12267v1 Announce Type: new Abstract: Learning user-defined concepts as constraint networks has been extensively studied in the constraint acquisition (CA) literature. However, existing approaches typically rely on intensive interactions with a human oracle, making the…
arXiv — cs.AI
Зерттеулер1 мин
T-GADE: Thermodynamical Generative-AI-Driven Evolution of LLM Artifacts
arXiv:2609.12286v1 Announce Type: new Abstract: Integrating evolutionary computation and large language models (LLMs) requires control of population diversity as well as generative capability. Among LLM outputs, those with explicit structure, such as a description paired with…
arXiv — cs.AI
Зерттеулер1 мин
Robust Prototypical Networks for Few-Shot Sensor Fault Diagnosis
arXiv:2609.12287v1 Announce Type: new Abstract: Industrial fault diagnosis often operates with only a handful of labeled fault examples, making few-shot learning attractive for sensor monitoring. Standard prototypical networks are simple and effective; however, their class…
arXiv — cs.AI
Стартаптар1 мин
Do Influence-Derived Data Perturbations Enable Machine Unlearning? A Controlled Study of Three Plausible Roles
arXiv:2609.12313v1 Announce Type: new Abstract: We evaluate Deep Perturbation Learning (DPL), which perturbs training images and labels along influence-derived directions, in three roles in which prior work has positioned it for machine unlearning: a direct deletion signal (the…
arXiv — cs.AI
Зерттеулер1 мин
AIM: A Privacy-Aware Interoperable Memory Framework for Multi-Agent Multi-User LLM Systems
arXiv:2609.12320v1 Announce Type: new Abstract: Traditional large language models (LLMs) are scoped to individual user sessions, limiting their knowledge to a single conversation and preventing them from learning user preferences that evolve over time. Existing agentic memory…
arXiv — cs.AI