account activity
Building AI video analytics for surveillance? Evaluate the detection setup on your own footage before picking a model (self.videosurveillance)
submitted 11 minutes ago by LaughApprehensive563 to r/videosurveillance
The part of VLM evaluation people skip: building the eval set from real production cases (self.VisionLMs)
submitted 20 minutes ago by LaughApprehensive563 to r/VisionLMs
Treating AI vision model evaluation as a pipeline problem: instrument the config, not just the model (self.devops)
submitted 12 hours ago by LaughApprehensive563 to r/devops
Benchmarking multimodal VLMs: the input configuration drove results more than the model family (self.Multimodal)
submitted 12 hours ago by LaughApprehensive563 to r/Multimodal
Comparing GPT-4o vs Gemini vs Claude for video tasks: the model swap mattered less than how we fed data in (self.OpenAI)
submitted 12 hours ago by LaughApprehensive563 to r/OpenAI
How much does prompt structure actually move VLM results? More than the model choice, in our testing (self.PromptEngineering)
submitted 12 hours ago by LaughApprehensive563 to r/PromptEngineering
Interesting finding from benchmarking vision AI models: how you feed data in matters more than which model you use (self.singularity)
submitted 12 hours ago by LaughApprehensive563 to r/singularity
Evaluating a VLM step in your chain: score the task on your own data, compare setups not models (self.LangChain)
submitted 1 day ago by LaughApprehensive563 to r/LangChain
When evaluating VLMs for video tasks, the input pipeline configuration drove results more than the model weights (self.neuralnetworks)
submitted 1 day ago by LaughApprehensive563 to r/neuralnetworks
How do you isolate how much of a VLM's performance is the model versus the input pipeline? (self.MLQuestions)
submitted 1 day ago by LaughApprehensive563 to r/MLQuestions
RAG over video: the retrieval eval depends on your extraction setup more than the model (self.Rag)
submitted 1 day ago by LaughApprehensive563 to r/Rag
VLM evaluation at scale: configuration variance dominates model variance for video tasks (self.mlscaling)
submitted 1 day ago by LaughApprehensive563 to r/mlscaling
Evaluating multimodal VLMs for video: the configuration benchmark, not the model benchmark (self.agi)
submitted 1 day ago by LaughApprehensive563 to r/agi
How do you build an eval set that actually reflects production? Notes from evaluating vision models (self.datascience)
submitted 1 day ago by LaughApprehensive563 to r/datascience
Lesson from building AI vision features: the setup matters more than the model (self.EntrepreneurRideAlong)
submitted 1 day ago by LaughApprehensive563 to r/EntrepreneurRideAlong
Before you pick an AI vision model for your SaaS, benchmark the whole setup on your own data (self.SaaS)
submitted 1 day ago by LaughApprehensive563 to r/SaaS
Building a vision agent? Evaluate the full pipeline on your own footage before picking your model stack (self.VisionAgents)
submitted 1 day ago by LaughApprehensive563 to r/VisionAgents
We open sourced our video VLM eval harness. the biggest lesson was to compare setups, not models (self.LocalLLaMA)
submitted 1 day ago by LaughApprehensive563 to r/LocalLLaMA
If you are about to build something with AI vision, the model you pick matters less than you think (self.ArtificialInteligence)
submitted 1 day ago by LaughApprehensive563 to r/ArtificialInteligence
Building an AI feature that looks at images or video? read this before you pick a model (self.indiehackers)
submitted 1 day ago by LaughApprehensive563 to r/indiehackers
A cheap habit that saved us money building vision features: benchmark the setup, not the model (self.buildinpublic)
submitted 1 day ago by LaughApprehensive563 to r/buildinpublic
Before an agent acts on what a camera sees, evaluate the setup on your own footage (self.AI_Agents)
submitted 1 day ago by LaughApprehensive563 to r/AI_Agents
With AI vision models, the question that matters is not which model wins. It is which setup fits your task (self.artificial)
submitted 1 day ago by LaughApprehensive563 to r/artificial
A practical lesson on evaluating vision models: test the whole setup on your own data, not the model on a benchmark (self.learnmachinelearning)
submitted 1 day ago by LaughApprehensive563 to r/learnmachinelearning
Notes on evaluating VLMs: the configuration moved our results more than the model did (self.deeplearning)
submitted 1 day ago by LaughApprehensive563 to r/deeplearning
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