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1:42:17EN
Cognitive Revolution "How AI Changes Everything"· 20 abr 2024PódcastThe Cheapest Inference Provider Is the Most DangerousPresenta: Nathan LabenzFireworks AI cofounders Lin Qiao and Dmytro Ivchenko explain why subsidized GPU bills vanish, how LoRA serving can cut cost a hundredfold, and why OpenAI is the rival that actually matters.Infraestructura y despliegueInferenceAI cost & performance+3
8 diapositivas13:19EN
Matthew Berman· 18 ene 2024Running a Local Language Model as an Offline BackupMatthew Berman · Forward FutureMatthew Berman demonstrates a 2024 local-model setup, from selecting a quantized model and storing it on an external drive to planning backup power.Local inferenceFoundation ModelsInfraestructura y despliegue+1
1:19:52EN
Cognitive Revolution "How AI Changes Everything"· 18 oct 2023Pódcast1,000 H100s Take 115 Days; 22,000 Take FivePresenta: Nathan LabenzNathan Labenz and Trey Kollmer walk through cluster math that turns GPT-4-scale training into a weekly experiment, then four papers on search-augmented models, recursive code improvers, spatial maps inside Llama 2, and what networks do when they have no idea.Modelos y entrenamientoAI researchModel Interpretability+3
4 diapositivas7:02EN
Matthew Berman· 18 oct 2023Connecting AutoGen to a RunPod-Hosted Model with Text Generation WebUIMatthew Berman · Forward FutureIn a 2023 walkthrough, Matthew Berman connects AutoGen to Dolphin 2.1 Mistral 7B through an OpenAI-compatible API and tests a small coding task.Ingeniería de agentesOpen-weight modelsMulti-agent systems+2
3 diapositivas4:42EN
Matthew Berman· 17 oct 2023Connecting AutoGen to a Local Model With LM StudioMatthew Berman · Forward FutureMatthew Berman demonstrates an early local-model setup and explains where agent behavior still needs work.AgentesOpen-weight modelsInfraestructura y despliegue
1:01:26EN
Cognitive Revolution "How AI Changes Everything"· 25 jul 2023PódcastAlexNet Used Two GPUs. GPT-4 Took Twenty Thousand. The Shortage Will Be Back.Presenta: Nathan LabenzRun:ai CTO Ronen Dar on filling idle accelerators, why H100s can be cheaper per experiment, and why Llama 2 undercuts compute governance.Infraestructura y despliegueAI cost & performanceDistributed training & inference+3
3 diapositivas8:17EN
Matthew Berman· 22 jun 2023Using OpenLLM to Serve Open Models Through an APIMatthew Berman · Forward FutureMatthew Berman demonstrates a local model server, its interactive API and a Python client in a 2023 walkthrough.Open-weight modelsInferenceInfraestructura y despliegue+1
6 diapositivas11:49EN
Matthew Berman· 1 jun 2023Testing Wizard-Vicuna 30B: Responses, Reasoning, and CodeMatthew Berman · Forward FutureMatthew Berman examines a model marketed as uncensored, demonstrates a 2023 cloud setup, and runs an informal collection of tests.Modelos y entrenamientoEvaluacionesAI Safety+1
1:20:49EN
Cognitive Revolution "How AI Changes Everything"· 25 may 2023PódcastA Wafer-Scale Chip So AI Stops Waiting on AmdahlPresenta: Nathan LabenzAndrew Feldman, CEO of Cerebras, tells Nathan Labenz why one 2.5-trillion-transistor die, sparse linear algebra, and a 16-machine supercomputer are a better shape than a GPU cluster.Infraestructura y despliegueInferenceAI cost & performance+3
6:42EN
Jane Street· 23 may 2023Ezio on Linux Engineering and Collaboration at Jane StreetEzio · Jane StreetA London engineer explains his team’s infrastructure work, the Pride community group and why new hires should ask questions.Infraestructura y despliegueCompany CultureCareers+1
3:03EN
Jane Street· 10 may 2023Rajan on IT, Collaboration and Learning at Jane StreetRajan · Jane StreetRajan describes the IT team's role supporting critical systems and the problem-solving skills he brought from studying chemistry.CareersCompany CultureInfraestructura y despliegue
5 diapositivas8:05EN
Matthew Berman· 29 mar 2023A 2023 Guide to Running the Original GPT4All Model LocallyMatthew Berman · Forward FutureMatthew Berman demonstrates an early CPU-based GPT4All release, its terminal installation and the resources available for fine-tuning.Open-weight modelsModelos y entrenamientoInfraestructura y despliegue
26:02EN
Lex Fridman· 9 feb 2020PódcastMoore’s Law Is Not Dead—It Is a Cascade of S-CurvesPresenta: Lex FridmanJim Keller explains why transistor scaling keeps outrunning its obituary, and how exponential hardware changes the mathematics AI can attempt.Infraestructura y despliegueSemiconductorsScaling Laws+3
5 diapositivas57:57EN
Jane Street· 8 may 2019Sebastian Funk on a Fast, Safe and Maintainable Packet ProcessorSebastian Funk · Jane StreetA single-core market-data case study shows how latency targets, allocation control and generated code can coexist with high-level abstractions.Software engineeringBenchmarksInfraestructura y despliegue
6 diapositivas1:06:49EN
Jane Street· 30 ene 2018Bryan Cantrill on Finding the Butterfly Behind a Performance HurricaneBryan Cantrill · JoyentSmall defects can produce vast performance failures across layers of abstraction. Bryan Cantrill explains how to investigate them with questions, instrumentation and visualization.Observabilidad y fiabilidadInfraestructura y despliegueSoftware engineering
1:27:23EN
Lenny's PodcastPódcastGoing All In on AI at Cisco: Jeetu Patel on Platforms, Packet Loss and Telling People the TruthPresenta: Lenny RachitskyCisco's president and chief product officer explains how a 90,000-person company went AI-first, what Cisco does in the AI infrastructure stack, and the leadership and career lessons behind it.Empresa y estrategiaIA empresarialAI Strategy+3
1:19:25EN
Lenny's PodcastPódcastInside Mercado Libre: How 18,000 Engineers Ship 30,000 Changes a Day Without an Army of PMsPresenta: Lenny RachitskySebastian Barrios, formerly head of product and engineering at Mercado Libre and now SVP of Engineering at Roblox, explains how a Latin American giant runs engineering and product as one team.Empresa y estrategiaLeadershipCompany Building+3
30:30EN
Lex FridmanPódcastFrom Bitcoin Magazine to Ethereum 2.0: Vitalik Buterin on Building a World ComputerPresenta: Lex FridmanVitalik Buterin traces Ethereum's origin in the Bitcoin community, the governance fights that followed, and the proof-of-stake and sharding upgrades still to come.Infraestructura y despliegueCryptocurrency
1:18:48EN
Lex FridmanPódcastData Movement, Not Math: How to Make Deep Learning Fit on Robots and PhonesPresenta: Lex FridmanMIT professor Vivienne Sze explains why moving data dominates the energy cost of neural networks and how co-designing hardware and algorithms can cut it by orders of magnitude.Infraestructura y despliegueInferenceAI cost & performance+3
45:46EN
Unsupervised Learning: With Jacob EffronPódcastGiving AI a Nervous System: Voice, Touch, and the Post-Keyboard InterfacePresenta: Jacob EffronLiveKit's Russ explains how voice AI, multimodal chat, cloud browsers, and on-device models are reshaping how humans work with machines.Multimodal y mediosIA de vozMultimodal AI+3
51:55EN
Unsupervised Learning: With Jacob EffronPódcastThe Search Engine Under AI Apps: Why Bigger Context Windows Aren't EnoughPresenta: Jacob EffronTurbopuffer CEO Simon on object-storage databases, vector-search trade-offs, and the AI features that will become SaaS table stakes.Infraestructura y despliegueVector searchGeneración aumentada por recuperación+3
46:48EN
Unsupervised Learning: With Jacob EffronPódcastSnowflake's AI Stack: Small Models, the Text-to-SQL Iceberg, and Why Governance Comes FirstPresenta: Jacob EffronSnowflake head of AI Baris Gekken explains how Arctic and Cortex were built, where enterprise AI actually works today, and why precision, governance and evaluation matter more than raw model capability.Empresa y estrategiaInfraestructura y despliegueIA empresarial+3
1:30:18EN
Lex FridmanPódcastNight Markets and Chip Foundries: A Week in Taiwan with Jensen HuangPresenta: Lex FridmanLex Fridman follows NVIDIA's CEO through Computex, street food and long chats about Taiwan's tech history, export controls and how to choose business partners.Empresa y estrategiaInfraestructura y despliegueSemiconductors+3
1:02:06EN
Lex FridmanPódcastLearning TensorFlow Hands-On: From a Mystery Line to Handwritten DigitsPresenta: Lex FridmanGoogle Brain's Sherry Moore walks a Deep Learning School audience through how TensorFlow works and two core labs, linear regression and MNIST digit recognition.Modelos y entrenamientoInfraestructura y despliegueOpen-source ecosystems+3
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