- 20VC: Why Robotics Will be 100x Bigger than Coding Agents | Inference Will Be a $10TRN Market: What No One Sees | Why Software Investors are F***** Today with Naveen Rao, UnconventionalThe Twenty Minute VC (20VC) · 2026-10-24普通模型能力和每 token 价格可能下降,但能显著提高能源转换效率的硬件仍有差异化空间。
- AI Cyber Panic, Ken Griffin's Bubble Warning, The Fall of France?All-In Podcast · 2026-10-23开放权重模型有利于修改、审计和解释,但要以合适价格获得全球稳定的推理算力并不容易。
- Why AI Compute Comes in Rectangles — Erik Bernhardsson, Modal CEOLatent Space · 2026-10-22再通过快速启动、快照和调度,把长期采购的容量切成细粒度服务。
- Why Real-World AI Is Harder Than the Benchmark | EliseAI’s Mario Martonea16z Show · 2026-10-18语音服务则必须同时协调识别、生成、延迟和整条系统链路。
- The Race to Recursive Self-Improving AIa16z Show · 2026-10-12MakerMaker.AI 选择推理效率作为切入口,理由兼具递归性和商业性:推理越高效,系统用于进一步试验与改进的资源也可能越充裕。
- Software That Never Breaks: OutSystems CEO Woodson Martin on Building Enterprise-Grade Apps at AI SpeedThe Cognitive Revolution · 2026-10-07大多数企业工作负载无需前沿模型,路由策略与专用工具链可显著降低成本。
- Beyond the God Model | Alex Atallah & Amjad Masada16z Show · 2026-10-03开发者持续比较能力、价格和实际任务表现
- Frontier Chips for Frontier AI Labs, with Walter Goodwin, Founder/CEO of FractileNo Priors · 2026-10-02对高速、低 batch 的大模型推理,反复读取权重和状态所需的内存带宽可能更关键。
- Why Dwarkesh is Wrong about Computer Use + How OpenAI shipped its Jev competitor in 1 WeekLatent Space · 2026-09-30异步调用与 WebSockets 试图减少模型等待工具的时间;
- OpenRouter: from Seed to Stripe — with OpenRouter’s Alex Atallah & AMP’s Anjney MidhaLatent Space · 2026-09-25OpenRouter 团队则看到另一面:即使模型能力持续提升,不同模型在成本、速度、安全策略和具体任务上的差异仍会迫使开发者不断切换。
- Jev: System One models for Prod, not God — with Diogo Almeida, CEO, TypeSafe AILatent Space · 2026-09-21核心指标不是人格感或长篇推理,而是结构化输出、低延迟、校准能力、稳定版本及“每美元智能”。
- Databricks CEO on AI Pacing, Cyber Risk, and the Enterprisea16z Show · 2026-09-18成本上用网关预算+智能路由+换 harness(同模型可差 ~2×)压住账单
- Why Diffusion Will Win AI Inference with Inception Co-Founder and CEO Stefano ErmonNo Priors · 2026-09-18下一轮 AI 竞争的主战场是**推理效率**而非训练规模
- The Next Frontier of AI Video Is Controla16z Show · 2026-09-17H3 Max = 开源权重帖训 + 系统/硬件优化,而不只是换基座。
- Aaron Levie on Why Open AI Winsa16z Show · 2026-09-05推理成本是真正战场
- The Inference Engineering Masterclass — Philip Kiely & Ali Taha, BasetenLatent Space · 2026-08-03真正的目标不是让模型勉强吐出 token,而是在接近原始模型质量的前提下,以更高速度、更低成本和更强可靠性服务真实流量。
- Why AI Infrastructure must evolve for Agent Experience — Akshat Bubna, Modal CTOLatent Space · 2026-07-08因此,真正的产品并非裸 GPU,而是冷启动、快照恢复、区域容量、可靠投递、尾延迟控制、持久化存储和网络隔离的组合。