company / product specific benchmarks are incredibly helpful
RESEARCH
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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 -
AGI ALPHA: Gibbs-Game-Hamiltonian Framework for Multi-Agent Systems
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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 http://
MONTREAL.AI and 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 -
Brute Force State Space Search Efficiency in AI Systems
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No, the top score if you didn't account for action efficiency would be 100%, achievable with 20 lines of Python. All you need is to brute-force the state space. Please stop spreading complete disinformation.
