Towards AI Governance

Hacker News

Let's start an open-source, non-profit AI government. Create LLM agents to represent every politician, decision-maker, and policymaker. By simulating their decision-making processes, we can measure their performance against actual human decisions. This would involve considering both short-term and long-term consequences. Running this experiment for 5-10 years would generate valuable comparison data, allowing the public to interact with and contribute to the development of the project. A week ago, Balaji announced a challenge to create an open-source demo of a President Biden deepfake. This isn't new; we've seen such videos before. However, there hasn't been a project that combines all the open-source models and allows us to talk and interact with the deepfake. This is the initial release. Responses will stream live. To make this real-time on consumer GPUs and indistinguishable, a lot of work needs to be done, such as aligning LLMs, training text-to-speech, and optimizing the LipSync video generation model. The same post I submitted earlier was flagged by someone for being political in nature and is no longer visible. Please do not flag it; this is not a political post. Let's discuss the implications of such a project on our society.

Visit product View on Hacker NewsJul 20, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, model · Missing: mac, macos, cursor

93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: video · Missing: mobile apps, ios, personal

57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: lua, ide, io · Missing: https docs, excited, just released

31%31% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: profit, training · Missing: arr, mrr, revenue

21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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