English translation is being prepared.
Matched fieldsSummary
Matched fieldsSummary
Matched fieldsSummary
Matched fieldsSummary
Matched fieldsSummary
Matched fieldsSummary
Matched fieldsSummary
Matched fieldsSummary
Matched fieldsSummary
Matched fieldsSummary
Matched fieldsSummary
Matched fieldsSummary
Matched fieldsSummary
In addition to its existing global and US-based inference options, Amazon Bedrock has added an in-India inference option: when calling in.moonshotai.kimi-k3, requests are processed only in the Mumbai and Hyderabad Regions, meeting strict data residency requirements. Ultrahuman already uses this model in production, leveraging prompt caching to reduce LLM costs by 80% and speed up multi-turn conversations by 85%. The article also provides sample OCR code that uses Kimi K3 to directly read scanned Hindi documents and ask follow-up questions in Hinglish.

In addition to its existing global and US-based inference options, Amazon Bedrock has added an in-India inference option: when calling in.moonshotai.kimi-k3, requests are processed only in the Mumbai and Hyderabad Regions, meeting strict data residency requirements. Ultrahuman already uses this model in production, leveraging prompt caching to reduce LLM costs by 80% and speed up multi-turn conversations by 85%. The article also provides sample OCR code that uses Kimi K3 to directly read scanned
Matched fieldsBody
AWS partner Cartesia provides voice models on AWS based on State Space Models (SSMs) with first-byte latency under 100ms: Sonic text-to-speech produces its first audio in about 90ms, supports more than 44 languages and voice cloning from 10-second audio samples, and Ink speech-to-text supports native turn detection and streaming transcription. SSMs achieve native streaming inference through fixed-size hidden states and token-by-token processing, avoiding the latency that comes from Transformers processing an entire sequence.

AWS partner Cartesia provides voice models on AWS based on State Space Models (SSMs) with first-byte latency under 100ms: Sonic text-to-speech produces its first audio in about 90ms, supports more than 44 languages and voice cloning from 10-second audio samples, and Ink speech-to-text supports native turn detection and streaming transcription. SSMs achieve native streaming inference through fixed-size hidden states and token-by-token processing, avoiding the latency that comes from Transformers
Matched fieldsBody
Kling 4.0 invited eight creators to share their hands-on creative experiences. Key capabilities include the physical performance of Dynamic Motions in highly difficult action sequences, more stable camera scheduling, and Native 30s Generation, which supports native 30-second generation. Omni Reference can fuse multiple visual references, and character consistency and lip-sync have both improved in long shots and Cantonese dialogue scenes.
Matched fieldsBody
In its ICML 2026 blog, LG AI Research points out that tabular foundation models such as TabPFN suffer from label shift: among 253 OpenML datasets, about 85% (214) are class-imbalanced, and in extreme cases 98.3% of test samples are predicted as the majority class, with minority-class recall nearly collapsing. The team proposes DistPFN, which at inference time multiplies predicted probabilities by a correction factor based on relative training class proportions, without changing the architecture, retraining, or estimating the test label distribution. ICML 2026 received a total of 23,918 submissions and accepted 6,352, for an acceptance rate of 26.6%.

In its ICML 2026 blog, LG AI Research points out that tabular foundation models such as TabPFN suffer from label shift: among 253 OpenML datasets, about 85% (214) are class-imbalanced, and in extreme cases 98.3% of test samples are predicted as the majority class, with minority-class recall nearly collapsing. The team proposes DistPFN, which at inference time multiplies predicted probabilities by a correction factor based on relative training class proportions, without changing the architecture,
Matched fieldsBody
NVIDIA has released the Cosmos Framework and Cosmos NIM for physical AI. The former provides modular tools and agent skills for training, reinforcement learning, optimization, and inference, while the latter provides accelerated inference services in container form. The Cosmos 3 Nano simulation recipe can generate synchronized camera video and LiDAR observations from released checkpoints, covering autonomous driving, robotics, and surgical scenarios. NIM uses quantization, speculative decoding, and KV-cache-aware routing to achieve a measured speedup of about 2–3x on H200, and Cosmos3-Nano generation tasks require 58 GiB of VRAM under BF16.

NVIDIA has released the Cosmos Framework and Cosmos NIM for physical AI. The former provides modular tools and agent skills for training, reinforcement learning, optimization, and inference, while the latter provides accelerated inference services in container form. The Cosmos 3 Nano simulation recipe can generate synchronized camera video and LiDAR observations from released checkpoints, covering autonomous driving, robotics, and surgical scenarios. NIM uses quantization, speculative decoding,
Matched fieldsBody
In October, Google launched its frontier reasoning model Gemini 4 Argon globally, covering Google AI Studio, the Gemini API, Google Cloud, Search, and the Gemini app. Two weeks later, it announced Gemini 4 Carbon, focused on long-horizon engineering and cybersecurity defense, which is currently undergoing pre-release testing with the U.S. government and select trusted cybersecurity parties through the Fairwind Program. In the same period, it released Genie 4, a real-time interactive world model that supports native audio and natural-language scene control; SynthID Detector opened globally in English and can identify AI content from partners such as OpenAI, NVIDIA, Kakao, and Apple.

In October, Google launched its frontier reasoning model Gemini 4 Argon globally, covering Google AI Studio, the Gemini API, Google Cloud, Search, and the Gemini app. Two weeks later, it announced Gemini 4 Carbon, focused on long-horizon engineering and cybersecurity defense, which is currently undergoing pre-release testing with the U.S. government and select trusted cybersecurity parties through the Fairwind Program. In the same period, it released Genie 4, a real-time interactive world model
Matched fieldsBody
Apple proposes an online reinforcement learning framework that directly trains a UI navigation agent on real iOS applications, splitting the agent into a Planning agent and a UI Grounding model, and uses an LLM-as-a-Judge to provide step-level dense rewards and task-completion terminal rewards, optimizing with PPO plus step-level advantage estimation. Its 8B agent achieves nearly a 7x improvement over the SFT baseline when generalizing out-of-distribution to the Android environment, and on real iOS applications surpasses Gemini-3.5-Flash and matches Gemini-3.1-Pro.

Apple proposes an online reinforcement learning framework that directly trains a UI navigation agent on real iOS applications, splitting the agent into a Planning agent and a UI Grounding model, and uses an LLM-as-a-Judge to provide step-level dense rewards and task-completion terminal rewards, optimizing with PPO plus step-level advantage estimation. Its 8B agent achieves nearly a 7x improvement over the SFT baseline when generalizing out-of-distribution to the Android environment, and on real
Matched fieldsBody