Model quantization reduces the numerical precision used to store weights or perform calculations, such as converting 32-bit values to 8-bit or lower formats. Smaller representations can reduce memory, speed up inference, lower energy use, and enable models to run on phones, browsers, vehicles, or edge hardware. Quantization may be applied after training or included during training so the model learns to tolerate reduced precision. The efficiency gain can come with accuracy loss, especially for sensitive layers or unusual inputs. Hardware support, calibration data, activation ranges, and task requirements determine the best method. Every quantized version should be evaluated independently rather than assumed equivalent to its original model.
Nvidia CEO Jensen Huang will deliver the keynote at the GTC 2026 conference, where investors expect new AI product announcements and demand outlook updates.
Amazon and Cerebras have partnered to combine their AI chips in a new AWS service designed to accelerate inference for chatbots, coding tools, and other generative AI applications.
Palantir and Nvidia unveiled a sovereign AI OS reference architecture designed to deliver turnkey AI data centers. The platform integrates Nvidia Blackwell systems with Palantir’s enterprise AI software stack.
Meta introduced four new in-house MTIA chips designed for AI training and inference as the company accelerates data center expansion. The chips aim to improve performance and reduce reliance on external hardware suppliers.
Nvidia and Nebius have formed a strategic partnership to build hyperscale AI cloud infrastructure, with Nvidia investing $2 billion to support gigawatt-scale AI computing capacity.
Honor confirmed its Robot Phone will launch in the second half of the year, featuring a 200MP camera with a built-in three-axis mechanical gimbal system.
Burger King is testing an AI-powered headset system called Patty, designed to monitor operations, assist employees, and track service patterns in real time.
Nvidia reports record Q4 revenue of $68.1B and net income of $43B, driven by strong AI data center demand and continued hyperscale investment.
Meta plans to buy up to $100 billion in AMD GPUs and CPUs, issuing performance-based warrants as it ramps AI data centers and diversifies compute infrastructure.
A new platform called Rent a Human allows AI agents to outsource tasks to real people when automation falls short, highlighting an unusual hybrid model of human-in-the-loop labor.