The path forward in #AIImplementation isn't finding THE winner, but mapping the best fit model for the task. It's fair to expect from your #AIdevelopers to create a clear model-to-use-case mapping, driven by robust, comparative #LLMevaluations using industry-specific benchmarks. That's true optimization. πΊοΈ #Benchmarking #AIStrategy
Every LLM eventually reveals its specialty. Stop searching for the AI 'God Mode'! π βοΈ There's enough evidence to back up the #NoFreeLunch theorem out here! Let's quit chasing the perfect generalist and focus on the best tool for the job. #AIHacks π οΈ #AILeaderboards#AIEvals
Specialization over generalization = A better, more realistic way forward in #AI approach. #AIDevelopment#LLMInnovation Have a read of our Substack's writeup: https://t.co/WLh1dN2p8p
Core Philosophy # 3: Truth Should Be Accessible = Knowledge shouldn't be trapped. π We advocate for creating knowledge channels so real granular data on #LLMs model performance is accessible to every #engineer . Truth is power! βοΈ #DemocratizeAI#OpenEvaluation#AI#Leaderboards
The solution (time) is nigh! We're saying that truly comparative, publicly visible eval leaderboards for #AI should be the standard. Weβre making it happen. Give us a follow and strap in! π #PublicLeaderboards#AITransparency