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1:42:17EN
Cognitive Revolution "How AI Changes Everything"· 20 avr. 2024PodcastThe Cheapest Inference Provider Is the Most DangerousAnime : 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.Infrastructure et déploiementInferenceAI cost & performance+3
8 diapositives13:19EN
Matthew Berman· 18 janv. 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 ModelsInfrastructure et déploiement+1
1:19:52EN
Cognitive Revolution "How AI Changes Everything"· 18 oct. 2023Podcast1,000 H100s Take 115 Days; 22,000 Take FiveAnime : 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.Modèles et entraînementAI researchModel Interpretability+3
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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.Ingénierie d’agentsOpen-weight modelsMulti-agent systems+2
3 diapositives4:42EN
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.AgentsOpen-weight modelsInfrastructure et déploiement
1:01:26EN
Cognitive Revolution "How AI Changes Everything"· 25 juil. 2023PodcastAlexNet Used Two GPUs. GPT-4 Took Twenty Thousand. The Shortage Will Be Back.Anime : Nathan LabenzRun:ai CTO Ronen Dar on filling idle accelerators, why H100s can be cheaper per experiment, and why Llama 2 undercuts compute governance.Infrastructure et déploiementAI cost & performanceDistributed training & inference+3
3 diapositives8:17EN
Matthew Berman· 22 juin 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 modelsInferenceInfrastructure et déploiement+1
6 diapositives11:49EN
Matthew Berman· 1 juin 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.Modèles et entraînementÉvaluationsAI Safety+1
1:20:49EN
Cognitive Revolution "How AI Changes Everything"· 25 mai 2023PodcastA Wafer-Scale Chip So AI Stops Waiting on AmdahlAnime : 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.Infrastructure et déploiementInferenceAI cost & performance+3
6:42EN
Jane Street· 23 mai 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.Infrastructure et déploiementCompany CultureCareers+1
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Jane Street· 10 mai 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 CultureInfrastructure et déploiement
5 diapositives8:05EN
Matthew Berman· 29 mars 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 modelsModèles et entraînementInfrastructure et déploiement
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Lex Fridman· 9 févr. 2020PodcastMoore’s Law Is Not Dead—It Is a Cascade of S-CurvesAnime : Lex FridmanJim Keller explains why transistor scaling keeps outrunning its obituary, and how exponential hardware changes the mathematics AI can attempt.Infrastructure et déploiementSemiconductorsScaling Laws+3
5 diapositives57:57EN
Jane Street· 8 mai 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 engineeringBenchmarksInfrastructure et déploiement
6 diapositives1:06:49EN
Jane Street· 30 janv. 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.Observabilité et fiabilitéInfrastructure et déploiementSoftware engineering
1:27:23EN
Lenny's PodcastPodcastGoing All In on AI at Cisco: Jeetu Patel on Platforms, Packet Loss and Telling People the TruthAnime : 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.Entreprise et stratégieIA en entrepriseAI Strategy+3
1:19:25EN
Lenny's PodcastPodcastInside Mercado Libre: How 18,000 Engineers Ship 30,000 Changes a Day Without an Army of PMsAnime : 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.Entreprise et stratégieLeadershipCompany Building+3
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Lex FridmanPodcastFrom Bitcoin Magazine to Ethereum 2.0: Vitalik Buterin on Building a World ComputerAnime : 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.Infrastructure et déploiementCryptocurrency
1:18:48EN
Lex FridmanPodcastData Movement, Not Math: How to Make Deep Learning Fit on Robots and PhonesAnime : 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.Infrastructure et déploiementInferenceAI cost & performance+3
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Unsupervised Learning: With Jacob EffronPodcastGiving AI a Nervous System: Voice, Touch, and the Post-Keyboard InterfaceAnime : Jacob EffronLiveKit's Russ explains how voice AI, multimodal chat, cloud browsers, and on-device models are reshaping how humans work with machines.Multimodal et médiasIA vocaleMultimodal AI+3
51:55EN
Unsupervised Learning: With Jacob EffronPodcastThe Search Engine Under AI Apps: Why Bigger Context Windows Aren't EnoughAnime : Jacob EffronTurbopuffer CEO Simon on object-storage databases, vector-search trade-offs, and the AI features that will become SaaS table stakes.Infrastructure et déploiementVector searchGénération augmentée par récupération+3
46:48EN
Unsupervised Learning: With Jacob EffronPodcastSnowflake's AI Stack: Small Models, the Text-to-SQL Iceberg, and Why Governance Comes FirstAnime : 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.Entreprise et stratégieInfrastructure et déploiementIA en entreprise+3
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Lex FridmanPodcastNight Markets and Chip Foundries: A Week in Taiwan with Jensen HuangAnime : 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.Entreprise et stratégieInfrastructure et déploiementSemiconductors+3
1:02:06EN
Lex FridmanPodcastLearning TensorFlow Hands-On: From a Mystery Line to Handwritten DigitsAnime : 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.Modèles et entraînementInfrastructure et déploiementOpen-source ecosystems+3
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