Large-scale applications, such as generative AI, recommendation systems, big data, and HPC systems, require large-capacity ...

Quantum technologies like quantum computers are built from quantum materials. These types of materials exhibit quantum properties when exposed to the right conditions. Curiously, engineers can also ...

The memory chip market right now is governed by a triumvirate of companies, led by South Korean firm SK Hynix, followed by ...

Memory prices are plunging and stocks in memory companies are collapsing following news from Google Research of a breakthrough that will greatly reduce the amount of memory needed for AI processing.

Google developed a new compression algorithm that will reduce the memory needed for AI models. If this breakthrough performs as advertised, it could drastically reduce the amount of memory chips ...

Micron Technology (MU) shares fell to $339 Monday as fears over Alphabet’s (GOOGL) TurboQuant AI memory-compression algorithm raised concerns about long-term demand for high-bandwidth memory across ...

Investors were spooked by a new Google compression algorithm that makes AI models more efficient and requires less memory. Rising fears about a recession and higher inflation contributed to the ...

The compression algorithm works by shrinking the data stored by large language models, with Google’s research finding that it can reduce memory usage by at least six times “with zero accuracy loss.” ...

Running a 70-billion-parameter large language model for 512 concurrent users can consume 512 GB of cache memory alone, nearly four times the memory needed for the model weights themselves. Google on ...

Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for Apple Silicon and llama.cpp.

Google published a research blog post on Tuesday about a new compression algorithm for AI models. Within hours, memory stocks were falling. Micron dropped 3 per cent, Western Digital lost 4.7 per cent ...