[{"data":1,"prerenderedAt":35},["ShallowReactive",2],{"maker-volotat":3},[4],{"id":5,"name":6,"line":7,"ai":8,"cat":9,"year":10,"points":11,"comments":12,"rec":13,"s":14,"top":15,"kw":16,"maker":21,"domain":22,"tier":23,"attempts":24,"strip":25,"url":26,"mix":27,"praise":32,"objection":33,"sub":34},49783133,"Mini-AGI","Dynamic continual learning model trained on 8GB VRAM",false,"ai",2026,277,80,"debated",-0.03,4,[17,18,19,20],"continual learning","catastrophic forgetting","mixture of experts","batch-1 training","volotat","github.com","legend",0,"1301100315153355505111100113531155300000","https:\u002F\u002Fgithub.com\u002Fvolotat\u002Fmini-AGI\u002F",[28,29,30,31],11,10,1,18,"Continual learning approach on a single stream is interesting","Claims of AGI and learning are overstated; outputs are not coherent","continual learning model",1794036830708]