絞り込み結果
69 件並び順
1:42:17EN
Cognitive Revolution "How AI Changes Everything"· 2024年4月20日ポッドキャストThe Cheapest Inference Provider Is the Most Dangerousホスト 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.
13:19EN
Matthew Berman· 2024年1月18日Running 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.
1:19:52ENCognitive Revolution "How AI Changes Everything"· 2023年10月18日ポッドキャスト1,000 H100s Take 115 Days; 22,000 Take Fiveホスト 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.
7:02ENMatthew Berman· 2023年10月18日Connecting 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.
4:42ENMatthew Berman· 2023年10月17日Connecting 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.
1:01:26ENCognitive Revolution "How AI Changes Everything"· 2023年7月25日ポッドキャストAlexNet Used Two GPUs. GPT-4 Took Twenty Thousand. The Shortage Will Be Back.ホスト Nathan LabenzRun:ai CTO Ronen Dar on filling idle accelerators, why H100s can be cheaper per experiment, and why Llama 2 undercuts compute governance.
8:17ENMatthew Berman· 2023年6月22日Using 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.
11:49ENMatthew Berman· 2023年6月1日Testing 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.
1:20:49ENCognitive Revolution "How AI Changes Everything"· 2023年5月25日ポッドキャストA Wafer-Scale Chip So AI Stops Waiting on Amdahlホスト 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.
6:42EN
Jane Street· 2023年5月23日Ezio 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.
3:03ENJane Street· 2023年5月10日Rajan 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.
8:05ENMatthew Berman· 2023年3月29日A 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.
26:02EN
Lex Fridman· 2020年2月9日ポッドキャストMoore’s Law Is Not Dead—It Is a Cascade of S-Curvesホスト Lex FridmanJim Keller explains why transistor scaling keeps outrunning its obituary, and how exponential hardware changes the mathematics AI can attempt.
57:57ENJane Street· 2019年5月8日Sebastian 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.
1:06:49ENJane Street· 2018年1月30日Bryan 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.
1:27:23EN
Lenny's PodcastポッドキャストGoing All In on AI at Cisco: Jeetu Patel on Platforms, Packet Loss and Telling People the Truthホスト 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.
1:19:25ENLenny's PodcastポッドキャストInside Mercado Libre: How 18,000 Engineers Ship 30,000 Changes a Day Without an Army of PMsホスト 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.
30:30ENLex FridmanポッドキャストFrom Bitcoin Magazine to Ethereum 2.0: Vitalik Buterin on Building a World Computerホスト 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.
1:18:48ENLex FridmanポッドキャストData Movement, Not Math: How to Make Deep Learning Fit on Robots and Phonesホスト 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.
45:46EN
Unsupervised Learning: With Jacob EffronポッドキャストGiving AI a Nervous System: Voice, Touch, and the Post-Keyboard Interfaceホスト Jacob EffronLiveKit's Russ explains how voice AI, multimodal chat, cloud browsers, and on-device models are reshaping how humans work with machines.
51:55ENUnsupervised Learning: With Jacob EffronポッドキャストThe Search Engine Under AI Apps: Why Bigger Context Windows Aren't Enoughホスト Jacob EffronTurbopuffer CEO Simon on object-storage databases, vector-search trade-offs, and the AI features that will become SaaS table stakes.
46:48ENUnsupervised Learning: With Jacob EffronポッドキャストSnowflake's AI Stack: Small Models, the Text-to-SQL Iceberg, and Why Governance Comes Firstホスト 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.
1:30:18ENLex FridmanポッドキャストNight Markets and Chip Foundries: A Week in Taiwan with Jensen Huangホスト 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.
1:02:06ENLex FridmanポッドキャストLearning TensorFlow Hands-On: From a Mystery Line to Handwritten Digitsホスト 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.もっと見る69 件中 24 件を表示