Chaînes mises à jour récemment

Choisissez-en une pour ne voir qu’elleToutes les chaînes →

Résultats

35 articles
Trier
Diapositives0:22EN
Matthew Berman· 18 oct. 2026DeepSeek's Memory Use: A Short Claim About KV CacheMatthew Berman · Forward FutureMatthew Berman links lower cache memory use to serving more tokens, but the excerpt does not state the comparison behind its figures.KV caching & prefix reuseInferenceInfrastructure et déploiement
0:50EN
Matthew Berman· 2 sept. 2026Matthew Berman on Using Idle Computers for AI InferenceMatthew Berman · Forward FutureBerman points to Darkbloom as a way to put spare computing capacity to work on AI models, while raising the question of how far distributed inference can go.Distributed training & inferenceInfrastructure et déploiementInference+2
0:41EN
Matthew Berman· 28 août 2026Could Faster AI Agents Shift More Work to the Cloud?Matthew Berman · Forward FutureMatthew Berman reflects on a conversation about faster inference and local-computer limits. Whether the CPU is a bottleneck depends on the particular agent workload and execution environment.InferenceInfrastructure et déploiementAI agents
Diapositives0:48EN
Matthew Berman· 25 août 2026Matthew Berman on Earning From Idle Mac Compute With DarkbloomMatthew Berman · Forward FutureA proposed network of Apple Silicon Macs could serve AI inference, but the earnings shown are projections that depend on hardware, availability and demand.Distributed training & inferenceInferenceLocal inference+1
9 diapositives13:09EN
Matthew Berman· 14 août 2026AI News: Ultrafast Inference, Claude Watermarks and New ModelsMatthew Berman · Forward FutureMatthew Berman reviews an ultrafast coding preview, text watermarking, Grok Bot, open-weight models and Computer History.InferenceOpen-weight modelsAgents de code+2
1:24EN
Matthew Berman· 22 juil. 2026Matthew Berman on Using Model Routing to Reduce AI CostsMatthew Berman · Forward FutureA short, sponsored explanation of splitting planning and coding between models of different cost, with a customer savings claim from DigitalOcean.AI cost & performanceInferenceAgents de code
0:24EN
Matthew Berman· 2 mars 2026A Surprise in AI Token Usage and CostsMatthew Berman · Forward FutureMatthew Berman reacts to a rising usage bill and notes why monitoring token consumption matters.AI cost & performanceInference
0:58EN
Matthew Berman· 13 févr. 2026Why Inference Speed Matters for AI AgentsMatthew Berman · Forward FutureMatthew Berman argues that faster model output can make agent workflows more useful, pointing to new Claude and Codex releases in February 2026.InferenceAI cost & performanceAI agents
0:52EN
Matthew Berman· 13 févr. 2026GPT-5.3-Codex-Spark Brings Faster Coding InferenceMatthew Berman · Forward FutureMatthew Berman highlights OpenAI's smaller coding model and its use of Cerebras hardware for low-latency responses.Agents de codeInferenceSemiconductors
2 diapositives0:24EN
Matthew Berman· 26 janv. 2026Matthew Berman Checks His Clawdbot Token CostsMatthew Berman · Forward FutureA short usage check reveals unexpectedly high model spending over two days.AI cost & performancePersonal agentsInference
3 diapositives12:13EN
Matthew Berman· 15 janv. 2026OpenAI’s Cerebras Deal and the Race for Faster AI InferenceMatthew Berman, Andrew Feldman, Greg Brockman · Forward FutureMatthew Berman explains why inference speed and computing capacity matter, while a closer look at the agreement and benchmark puts his 100-times-faster scenario in context.InferenceSemiconductorsOpenAI+2
Diapositives1:33EN
Matthew Berman· 15 janv. 2026OpenAI’s Cerebras Deal and the Limits of a 100× Speed ClaimMatthew Berman, Andrew Feldman · Forward FutureMatthew Berman discusses OpenAI’s 2026 agreement for Cerebras inference capacity and a speed chart. The contract and comparison require more context than the video’s headline provides.OpenAIInferenceSemiconductors+1
2 diapositives1:38EN
Matthew Berman· 29 déc. 2025NVIDIA’s Groq Licensing Deal and the Inference MarketMatthew Berman · Forward FutureMatthew Berman discusses why NVIDIA licensed Groq’s inference technology and hired members of its team.SemiconductorsInferenceAI cost & performance+1
2 diapositives11:34EN
Matthew Berman· 25 déc. 2025Nvidia’s Groq Licensing Deal: AI Inference, Talent and Competitive StrategyMatthew Berman, Jonathan Ross · Forward FutureGroq investor Matthew Berman examines a non-exclusive technology license and the move of senior Groq staff to Nvidia, and speculates about the future of AI chips.SemiconductorsInferenceAI Strategy+1
2 diapositives1:02EN
Matthew Berman· 31 oct. 2025Inside a Cerebras Data Center in Oklahoma CityMatthew Berman · Forward FutureMatthew Berman tours the facility and explains its wafer-scale chips, racks and cooling system.InferenceInfrastructure et déploiementAI cost & performance
3 diapositives14:07EN
Matthew Berman· 23 oct. 2025Inside Cerebras’s Oklahoma City AI Data CenterMatthew Berman, Andrew Feldman, Billy Wooten · Forward FutureMatthew Berman tours the facility with Cerebras CEO Andrew Feldman and Scale Data Centers COO Billy Wooten, exploring wafer-scale chips, liquid cooling and backup power. Their performance and expansion figures are presented as company claims from 2025.SemiconductorsInfrastructure et déploiementInference+2
4 diapositives8:47EN
Matthew Berman· 16 sept. 2025Why Identical LLM Prompts Can Produce Different Answers at Temperature ZeroMatthew Berman · Forward FutureMatthew Berman explains Thinking Machines Lab’s work on batch-invariant inference and what its reproducibility experiment actually showed.InferenceAI researchObservabilité et fiabilité+1
6 diapositives12:10EN
Matthew Berman· 6 mars 2025Mercury Coder and Diffusion Language Models: Speed, Demos and LimitsMatthew Berman · Forward FutureMatthew Berman explores Inception’s 2025 coding model, comparing iterative text refinement with autoregressive generation and examining speed claims.Modèles et entraînementInferenceAgents de code+2
5 diapositives10:01EN
Matthew Berman· 5 févr. 2025DeepSeek R1 Code Optimization and a $3 Visual Counting ExperimentMatthew Berman · Forward FutureMatthew Berman examines a human-guided coding improvement and a small reinforcement-learning experiment, then considers their implications for AI research.Reinforcement LearningGPU programming & kernelsAI research+2
6 diapositives10:39EN
Matthew Berman· 29 oct. 2024Zamba2-7B: A Hybrid Mamba–Transformer Model Tested on Coding and ReasoningMatthew Berman · Forward FutureMatthew Berman compares Zyphra’s efficiency claims with his own informal tests, including Python games, spatial puzzles and simple word tasks.Modèles et entraînementOpen-weight modelsBenchmarks+2
5 diapositives9:38EN
Matthew Berman· 15 oct. 2024Liquid Foundation Models: Company Benchmarks and a Hands-On TestMatthew Berman · Forward FutureMatthew Berman reviews Liquid AI’s 2024 model and memory claims, then tries the 40B preview on coding, logic, and instruction-following prompts.Foundation ModelsÉvaluationsBenchmarks+2
Diapositives0:54EN
Matthew Berman· 16 sept. 2024OpenAI’s o1 Preview: A First Look at Longer ReasoningMatthew Berman · Forward FutureMatthew Berman introduces the o1-preview and o1-mini models and tries a Python game prompt.Modèles et entraînementInference
Diapositives0:44EN
Matthew Berman· 29 août 2024NVIDIA Adds Multi-LoRA Serving to Its RTX AI ToolkitMatthew Berman · Forward FutureIn an NVIDIA-partnered video, Matthew Berman describes using multiple adapters with one base model and a vendor-reported throughput gain.Fine-tuningInferenceInfrastructure et déploiement
3 diapositives5:50EN
Matthew Berman· 27 juil. 2024A Mixture-of-Agents Demo Using Groq and StreamlitMatthew Berman · Forward FutureMatthew Berman walks through a 2024 Groq-powered multi-agent project, from setup to inspecting its layered responses.Multi-agent systemsAgent orchestrationInference+1
Charger plus24 sur 35 affichés