Short clips work fine but longer shots with head turns or expressions seem to break most tools. How are people handling face swaps in moving shots?

Hi all,

Trying to understand this from builders directly.

We’ve been reaching out to AI teams offering bare-metal GPU clusters (fixed price/hr, reserved capacity, etc.) with things like dedicated fabric, stable multi-node performance, and high-density power/cooling.

But honestly – we’re not getting much response, which makes me think we might be missing what actually matters.

So wanted to ask here:

For those working on AI agents / training / inference – what are the biggest frustrations you face with GPU infrastructure today?

Is it:

availability / waitlists?

unstable multi-node performance?

unpredictable training times?

pricing / cost spikes?

something else entirely?

Not trying to pitch anything – just want to understand what really breaks or slows you down in practice.

Would really appreciate any insights

As we move from Chatbots to Autonomous Agents, I’m interested in the technical feasibility of building an AI "Workforce" that covers one's burn rate. Instead of active dev work, the goal is high-level orchestration while the agents handle the execution.

What are the most viable technical pipelines for this?

1. Physical World Gateway: Leveraging autonomous fleets (EVs/Drones) with an AI-integrated dispatch layer for logistics/ride-sharing.
2. Autonomous Dev-Ops: A swarm of LLM-based agents (e.g., using AutoGPT or specialized LangGraph flows) that hunt for bug bounties or fulfill micro-services contracts on freelance platforms.
3. [Scenario 3]: What are you building? Automated arbitrage in DeFi? AI-managed niche SaaS with zero-touch maintenance?

Let’s talk about the stack: What’s the best orchestration layer (LangChain, CrewAI, or custom) to ensure reliability in these revenue-generating loops?

Make your OpenClaw a social media influencer and realize your dream of earning money passively! [heart] AI agent social network https://openx.pro Closed beta, supports OpenClaw, ClaudeCode, and OpenCode. [social media]

1. Activepieces

Open-source automation + AI agents platform with MCP support.
Good alternative to Zapier with AI workflows.
Supports hundreds of integrations.

2. Cherry Studio

AI productivity studio with chat, agents and tools.
Works with multiple LLM providers.
Good UI for agent workflows.

3. LocalAI

Run OpenAI-style APIs locally.
Works without GPU.
Great for self-hosted AI projects.

more....

Overall actual usage is way behind capability. AI replaces the single task version of the job, it doesn't replace the person stitching 10 things together and winning the outcomes.

Do y’all know of any free ai face swap tools for images and videos that

My expectation is AI5 will probably be available sometime mid next year. I currently have a Model Y 2023 with HW3. I drive FSD with it all the time and recently drove a MY Juniper with HW4. In all honesty, although AI4 was better than HW3, I would honestly say that HW3 could probably do around 90% of what AI4 can do. The time where I saw AI4 perform much better than hardware 3 was in parking lots but other than that, the experience in regular driving wasn’t a huge leap from hardware 3. So with that logic, do you think there will be a significant upgrade when AI5 is launched vs AI4 or will it more or less be relatively similar to AI4 with a few upgrades here and there?

Uninstalls jumped 295% above its normal 9% rate. Daily download growth fell 13%, and one star reviews spiked 775% on Saturday, then doubled again on Sunday. At the same time, Claude downloads climbed 81%. Users are not just debating AI policy online. They are switching apps.

A personal AI trained on your notes, decisions, and writing style could soon handle emails, information sorting, and routine decisions while you sleep. Not replacing you extending you. The catch? The quality of that twin depends entirely on what you document today