In this episode, Philip Kiely and Ali Taha from Baseten discuss the complexities and innovations in inference engineering for large AI models. They cover topics including model deployment, speculative decoding, quantization, hardware optimi…
Firehose
Filtered to Podcasts, tagged “continual learning” · clear filters
Browse: People · Companies · Papers · Podcasts · Hacker News · Deep dives
Browse by tag
Inference engineeringSpeculative decodingQuantizationModel deploymentTool callingKV cacheTensor parallelismExpert parallelismGPU hardwareRubin GPUVideo diffusionAutoregressive modelsDiffusion modelsTraining-inference convergenceContinual learningOpen source modelsInference infrastructureModel optimizationLatency vs throughputMulti-modal models
Intelligence on the Edge: Liquid AI's Ramin Hasani on the Search for Device-Native Foundation Models
This episode features Ramin Hassani, CEO of Liquid AI, discussing the company's journey from biologically inspired neural networks at MIT to developing device-native foundation models. He makes a technically grounded case for efficient, har…
Device-native AIFoundation modelsNeural network architectureBiologically inspired AIOut-of-distribution generalizationComputational efficiencyNonlinear systemsHardware-aware AIAutomated model designGating mechanismsInput-dependent dynamicsEdge computingAI hardwareAgentic AIContinual learningEmergent intelligence
In this episode, Thomas Ahle discusses the development of thermodynamic computing chips and the challenges of chip design automation using AI agents. He explains how his team built an open-source Verilog simulator with AI collaboration to o…
thermodynamic computingchip design automationformal verificationVerilog simulationAI agentsopen source EDAcontinual learningprobabilistic machine learninghardware-software co-designauto formalizationsoftware complexityAI-generated codeBayesian inferencestochastic differential equationsMarkov chain Monte Carlodiffusion modelsneural network accelerationrecursive self-improvementAI safetyagentic coding