In this Disrupt Roundtable session, Siddharth Mall, Ian McDiarmid, and Kaushik PS from TELUS Digital dove deep into the ...

How techniques like model pruning, quantization and knowledge distillation can optimize LLMs for faster, cheaper predictions.

Letting organizations and researchers add their own information during training and fine tuning may help them develop LLMs ...

LLM supply chains are vulnerable at many points, especially when companies use open-source, third-party components, poisoned or outdated pre-trained models, or corrupted training data sets.

With over 1 billion parameters trained using trillions of tokens on a cluster of AMD’s Instinct GPUs, OLMo aims to challenge ...

AMD develops its own 1B-parameters OLMo large language model for a wide variety of applications that was trained on Instinct ...

Presented in a recent paper, Spirit LM enables the creation of pipelines that mixes spoken and written text to integrate ...

We have 25x more efficiency than Hopper H100, 8K for LLM training with the highest performance ... FPS gaming since the pre-Quake days, where you were insulted if you used a mouse to aim, he ...

Waymo has long touted its ties to Google’s DeepMind and its decades of AI research as a strategic advantage over its rivals in the autonomous driving space. Now, the Alphabet-owned company is taking ...

Multimodal Large Language Models (MLLMs) have rapidly become a focal point in AI research. Closed-source models like GPT-4o, GPT-4V, Gemini-1.5, and Claude-3.5 exemplify the impressive capabilities of ...