Kimi K3.1 Pro is an open-weight, natively multimodal agentic model, and our most capable 3T-class model to date. Post-trained from Kimi K3 with large-scale joint reinforcement learning across hundreds of downstream domains, it is the first model in the K3.1 series. With a…
Cognizant announced on November 6, 2026 that it had acquired Wizeline, a global services firm focused on AI-native engineering and digital product development for enterprises. Financial terms were not disclosed.
Hypersonica just landed a €100M round, the largest in European startup funding this year. See who else raised, deal sizes, top investors and sector trends for 2026.
Artificial intelligence (AI) stocks are plunging following the results of the midterm elections. One of the biggest talking points for Democrats on the campaign trail was heavier oversight over AI data centers. While more regulation could impact the hyperscalers, Apple is in a unique position to benefit no matter who controls Congress.
Stocks recovered some ground Friday after the U.S. market endured its worst day since the height of last year's tariff-fueled tailspin. The tech-heavy Nasdaq Composite and the benchmark S&P 500 gained 1.
Resonac is betting its advanced chip materials can make the multibillion-dollar merger that created the company pay off as AI demand surges. Managing Asia's Christine Tan speaks with CEO Hidehito Takahashi about growth plans,
Preference-based reward shaping can guide reinforcement learning, but adding preference signals to the reward may unintentionally change the task being optimized. We address this problem with IncentRL, a framework that introduces preference guidance while explicitly…
A state may need to be compressed before its exact downstream task is known. For a finite family of linear task operators $\{T_u\}_{u\in\U}$, we characterize exactly how much state must survive when only one of $K$ coarse task messages is available at compression time:…
Recent pre-trained foundation models provide rich multi-modal priors for downstream 3D vision tasks. However, the effectiveness of these representations in few-shot scenarios is limited by two fundamental challenges: High-dimensional features often contain substantial channel…
While Video Large Language Models (Video-LLMs) have recently demonstrated strong performance, reliably evaluating their fine-grained video understanding remains challenging. Existing benchmarks often rely on question answering or ground-truth caption matching, where models may…