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周五. 10 月 23rd, 2026
Chicago 12, Melborne City, USA

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周五. 10 月 23rd, 2026
Chicago 12, Melborne City, USA
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Category Investment

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AI Unit Economics by Workload: Why One Blended Cost per User Is Misleading
  • adminadmin
  • AI
  • business
  • 28 9 月, 2026
  • 2 Comments
AI Unit Economics by Workload: Why One Blended Cost per User Is Misleading

How to analyze AI unit economics by workload, model, customer and successful task instead of relying on one blended cost per user.

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GPU Inference Cold Starts: Why Model Loading Can Break Autoscaling
  • adminadmin
  • AI
  • business
  • 28 9 月, 2026
  • 0 Comments
GPU Inference Cold Starts: Why Model Loading Can Break Autoscaling

How model loading, container startup and cache warming affect GPU inference autoscaling and interactive AI latency.

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AI Cost Attribution: How to Measure Spend by Feature, Customer and Successful Task
  • adminadmin
  • Agent
  • AI
  • 26 9 月, 2026
  • 0 Comments
AI Cost Attribution: How to Measure Spend by Feature, Customer and Successful Task

A practical framework for attributing AI spend across models, features, customers, agents and successful business outcomes.

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GPU Memory Planning for AI Inference: KV Cache, Context Length and Concurrency Explained
  • adminadmin
  • AI
  • business
  • 26 9 月, 2026
  • 0 Comments
GPU Memory Planning for AI Inference: KV Cache, Context Length and Concurrency Explained

How to plan GPU memory for AI inference across model weights, KV cache, context length, batching and concurrent users.

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AI FinOps: How to Control Model, GPU and Agent Costs Without Slowing Product Teams
  • adminadmin
  • AI
  • business
  • 25 9 月, 2026
  • 2 Comments
AI FinOps: How to Control Model, GPU and Agent Costs Without Slowing Product Teams

A practical AI FinOps framework for allocating model, GPU and agent costs, setting budgets, detecting waste and optimizing cost per successful task.

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AI Inference Batching: The Hidden Trade-Off Between GPU Efficiency and User Latency
  • adminadmin
  • AI
  • business
  • 25 9 月, 2026
  • 0 Comments
AI Inference Batching: The Hidden Trade-Off Between GPU Efficiency and User Latency

How inference batching improves GPU utilization while creating latency trade-offs, and how teams can tune batch size for interactive and background AI workloads.

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AI Data Center Networking: Why GPUs Need More Than Fast Chips
  • adminadmin
  • AI
  • chip
  • 24 9 月, 2026
  • 0 Comments
AI Data Center Networking: Why GPUs Need More Than Fast Chips

Why AI data center performance depends on networking, topology, congestion, storage and collective communication—not GPUs alone.

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AI Vendor Lock-In: A Practical Exit Plan for Enterprise Teams
  • adminadmin
  • AI
  • AI models
  • 23 9 月, 2026
  • 1 Comments
AI Vendor Lock-In: A Practical Exit Plan for Enterprise Teams

A practical enterprise framework for reducing AI vendor lock-in across models, prompts, data, embeddings, tools, evaluation and infrastructure.

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GPU Utilization for AI: Why Expensive Hardware Can Still Sit Idle
  • adminadmin
  • AI
  • business
  • 23 9 月, 2026
  • 1 Comments
GPU Utilization for AI: Why Expensive Hardware Can Still Sit Idle

Why GPU utilization is a critical AI infrastructure metric, and how batching, memory pressure, scheduling and workload shape real economics.

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Humanoid Robot ROI: How to Build a Business Case Before a Pilot
  • adminadmin
  • AI
  • business
  • 22 9 月, 2026
  • 0 Comments
Humanoid Robot ROI: How to Build a Business Case Before a Pilot

A practical humanoid robot ROI framework covering task selection, labor substitution, utilization, teleoperation, safety, integration and pilot economics.

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HTTP 429 in Multimodal AI Agents: Retry Budgets Without Cascading Failures

  • admin
  • 21 10 月, 2026
HTTP 429 in Multimodal AI Agents: Retry Budgets Without Cascading Failures
Deep Tech Policy Impact

MCP OAuth Token Audience Checks: A Multi-Tenant AI Agent Security Runbook

  • admin
  • 20 10 月, 2026
MCP OAuth Token Audience Checks: A Multi-Tenant AI Agent Security Runbook
Deep Tech Policy Impact

TURN Relay Budgets for Real-Time AI Avatar Calls: An ICE Connectivity Runbook

  • admin
  • 18 10 月, 2026
TURN Relay Budgets for Real-Time AI Avatar Calls: An ICE Connectivity Runbook
Deep Tech Policy Impact

Audio-Video Sync in Real-Time AI Avatars: A WebRTC Instrumentation and Drift Playbook

  • admin
  • 18 10 月, 2026
Audio-Video Sync in Real-Time AI Avatars: A WebRTC Instrumentation and Drift Playbook
Deep Tech Policy Impact

When AI Evaluation Agents Browse Off-Scope: Engineering Lessons from Tencent and Amap

  • admin
  • 18 10 月, 2026
When AI Evaluation Agents Browse Off-Scope: Engineering Lessons from Tencent and Amap
Deep Tech

Why Real-Time Voice AI Stutters: Jitter Buffers, Barge-In and a Reliability Playbook

  • admin
  • 17 10 月, 2026
Why Real-Time Voice AI Stutters: Jitter Buffers, Barge-In and a Reliability Playbook

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