In this episode of Silicon Valley 101, @Valley101_Qian introduced @evermind
's memory system—not a crude and simplistic boost to retrieval-augmented generation, but a full lifecycle memory system architecture. This memory architecture achieved SOTA right from the start, with
RESEARCH
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Evermind Memory System SOTA Architecture for AI
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Benchmarks and accountability in AI lab evaluation
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assuming the benchmark is sufficiently general and the labs are sufficiently intellectually honest, the benchmark would not be maxxed. and if it was, you would see drift between the real user feedback from said company and the benchmark, thus holding labs accountable
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Company and Product Specific Benchmarks Prove Incredibly Helpful
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company / product specific benchmarks are incredibly helpful
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Internal Evals vs Public Benchmarks in AI Model Assessment
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many have evals internally, far fewer have released public benchmarks
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Companies Should Build Custom AI Benchmarks for Competitive Advantage
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Every company building on top of AI should be making their own benchmarks. This is the way if you want model progress to disproportionally benefit your company.
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Humanoid Robot Defeats Elite Table Tennis Players in Historic Match
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Table-tennis-playing robot makes history by beating elite human players https://
youtu.be/7UKiNNxPkAU?si
=gTKhUV2LOU2_FN7f
… via @YouTube #tabletennis #pingpong #humanoidtech #humanoid #robot #Robotics #AI #TechRevolution #TechInnovation #ArtificialInteligence #PhysicalAI @AlbertoEMachado @Eli_Krumova -
AI transforms financial services industry innovation
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Rethinking financial services in the age of AI
#AI #AIio #AIInnovation #ML #DataScience #Futureofwork @Scobleizer @AndrewYNg @drfeifei @KirkDBorne @fchollet @rowancheung @antgrasso -
60 Thought Leaders Answer 17 Questions about AI
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"60 Thought Leaders Answer 17 Questions about AI" Download 236-page PDF here: https://
linkedin.com/posts/gkrasada
kis_60-leaders-on-ai-17-questions-answered-activity-7453067953924694016-_Abt/
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AGI ALPHA: Gibbs-Game-Hamiltonian Framework for AGI Ascension
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Introducing “AGI ALPHA as a Far-From-Equilibrium Multi-Agent Work Engine”: Gibbs–Game–Hamiltonian framework for α-AGI Ascension. Author: Vincent Boucher, President of MONTREAL.AIand http://
QUEBEC.AI https://
github.com/MontrealAI/alp
ha-open-ended-rsi-system/blob/main/docs/gibbs_game_hamiltonian_framework/AGI_ALPHA_alpha_AGI_Ascension_Frontier_Synthesis_Publication.pdf
… #AGIALPHA #AIAgents
