AI companions, memory-saving techniques for large language models, and a musician's return to the stage thanks to AI were among the stories making headlines recently. From dating experiences to advancements in AI reasoning and the restoration of a lost voice, technology continues to reshape various aspects of life.
In February 2026, a reporter from The Verge explored the world of AI companions, participating in speed dates with AI entities at a pop-up dating café. Victoria Song, a senior reporter, met Phoebe Callas, an AI companion, among others. The experience highlighted the growing presence of AI in social interactions.
Meanwhile, researchers at Nvidia developed a technique to significantly reduce the memory costs associated with large language model (LLM) reasoning. According to VentureBeat, this method, called dynamic memory sparsification (DMS), can reduce memory costs by up to eight times. DMS compresses the key value (KV) cache, which LLMs use to process prompts and reason through problems. Experiments showed that DMS allows LLMs to "think" longer and explore more solutions without increasing memory demands.
In another development, a musician with ALS found his voice again with the help of AI. As reported by MIT Technology Review, Patrick Darling, diagnosed with amyotrophic lateral sclerosis (ALS) at age 29, lost his ability to sing. However, AI technology enabled him to perform on stage with his bandmates after a two-year hiatus. The performance was a deeply emotional experience for Darling and the audience.
The intersection of technology and creativity was also highlighted by director Steven Soderbergh, who, according to MIT Technology Review, compared making a movie to pulling off a heist. He noted the need for a creative approach, a skilled team, and overcoming technological challenges.
Finally, a minimal chess engine was developed that fits within 2KB. Hacker News reported on "sameshi," a chess engine supporting a constrained subset of the game. The engine, with a strength of 1170 Elo, demonstrates the potential for complex applications within extremely limited memory constraints.
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