Computing & AI stocks are heating up. 📈 Top 5 gainers on LBank: $CRWV +17.64% $KOPN +12.86% $BOT +12.36% $NBIS +11.41% $AEHR +9.63% Trade stock futures 24/7 with up to 50x leverage: #LBank# #StockFutures#

From computing to security, Alibaba Cloud offers ECS, Databases, Storage, Networking, and Cloud Native solutions designed to help business build, scale, and protect. Follow us to explore the future of cloud!

From computing to security, Alibaba Cloud offers ECS, Databases, Storage, Networking, and Cloud Native solutions designed to help business build, scale, and protect. Follow us to explore the future of cloud!

AI computing networks maker Ligent Technologies is set to debut on the Hong Kong stock exchange on Tuesday after raising $727 million in a IPO, adding to this year’s stampede of companies capitalizing on the global AI buildout

Re-computing the whole conversation every time you switch models? That might be wasted work. Title: Cross-Model KV Cache Transfer in LLM Families: A Closed-Form Linear Mapping for Prefill Reuse URL: ❓ What does this paper actually do? 💡 NVIDIA researchers show how to "translate" the KV cache computed by one model size and reuse it directly on a different-sized model from the same family, using a training-free, closed-form ridge regression mapping. ❓ Why bother transferring across model sizes? 💡 Production systems escalate from small to large models or swap models mid-conversation for cost/quality reasons. Recomputing the whole context from scratch every time (re-prefill) wastes a lot of compute. ❓ Does accuracy hold up? 💡 On good pairs it retains 73-98% of the target model's standalone accuracy. Weak pairs degrade badly, but adding a small MLP recovers up to 36.8 points of HellaSwag accuracy. ❓ How much faster is it? 💡 2.7-25x faster than re-prefill, with the biggest gains (25x) at 32K-token contexts, and accuracy stays nearly stable across 10-turn conversations. #LLM# #KVCache#

Quantum computing is advancing fast. But as Eclipse Partner @Sethwinterroth tells @FastCompany, the milestone that matters is practical quantum advantage: Solving a commercially useful problem classical computing can’t. When that happens, the race won’t just be between companies. Quantum will become a strategic capability shaping economics, security, and geopolitics. More from Seth on what to watch next: