🇮🇶🇺🇸 | Un avión no tripulado de ataque LUCAS de fabricación estadounidense, inspirado en el Shahed de Irán, se estrelló en Irak y fue recuperado prácticamente intacto, con su antena Starlink visible en la estructura del avión.
I asked ChatGPT and Grok: I want to wash my car, and the car wash is 50m away. Should I walk or drive?
Grok: Drive because the car literally needs to be at the car wash to get washed.
ChatGPT: Walk!
ChatGPT is so dumb.
A historic first for 2025.
BYD celebrated its first all-electric passenger vehicle built in Brazil, as it rolled off the production line at the new factory in Camaçari, Bahia — marking a key milestone in BYD’s global expansion.
La situación energética de Bolivia atraviesa uno de sus momentos más delicados en las últimas décadas. Según el experto Álvaro Ríos, socio director de Gas Energy Latin America, la crisis no se limita a la escasez de combustibles en el mercado interno...
➡️https://t.co/RFHjWk2mYS
a tiny chip company just broke nvidia’s energy monopoly 🤯
gsi technology built something nobody thought was possible.
their chip called gemini-i matches nvidia’s A6000 gpu performance while using 98% less energy. not 10% less. not 50% less. ninety eight percent. cornell university just validated it in a published study.
the architecture is called compute-in-memory. traditional chips separate memory and computation. data gets moved back and forth constantly. that movement burns energy. gsi co-locates processing directly inside the memory arrays. no data transfer bottleneck. no wasted power.
they tested it on real AI workloads. retrieval-augmented generation tasks. the kind of stuff chatbots and search systems actually do. gemini-i ran 5x faster than standard cpus while consuming a fraction of gpu power.
cornell’s study was brutal in its thoroughness. benchmarked against nvidia a6000 and multi-core cpus. ran identical AI inference tasks across all three. measured energy consumption precisely. result: the apu used roughly 1 to 2% of the energy the gpu required for the same throughput.
what this breakthrough actually unlocks:
• data centers running hundreds of gpus could cut power needs by orders of magnitude. same performance, 2% of the electricity bill
• edge AI becomes viable everywhere. drones, satellites, iot devices that can’t plug into a wall. defense applications where power is scarce
• ai inference goes from megawatts to watts. climate impact drops exponentially while capability stays identical
• the $100 billion AI inference market just got disrupted. gsi’s ceo said it explicitly. gpu-class performance at a fraction of energy cost
nature magazine called AI’s energy hunger a growing crisis. said hardware that consumes less power will reduce AI’s appetite for energy. gsi just delivered that hardware with third-party validation.
mediatek already saw this coming. their new dimensity chip uses similar compute-in-memory techniques. cuts always-on AI power by 42 to 56%. runs voice assistants and sensors 24/7 without draining phone batteries.
the compute-in-memory approach isn’t theory anymore. it’s shipping. it’s validated. it’s replicable.