this post was submitted on 24 Sep 2023
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The AI Community On Kbin

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Welcome to m/ArtificialIntelligence, the place to discuss all things related to artificial intelligence, machine learning, deep learning, natural language processing, computer vision, robotics, and more. Whether you are a researcher, a developer, a student, or just a curious person, you can find here the latest news, articles, projects, tutorials, and resources on AI and its applications. You can also ask questions, share your ideas, showcase your work, or join the debates and challenges. Please follow the rules and be respectful to each other. Enjoy your stay!

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Training AI models like GPT-3 on "A is B" statements fails to let them deduce "B is A" without further training, exhibiting a flaw in generalization. (https://arxiv.org/pdf/2309.12288v1.pdf)

Ongoing Scaling Trends

  • 10 years of remarkable increases in model scale and performance.

  • Expects next few years will make today's AI "pale in comparison."

  • Follows known patterns, not theoretical limits.

No Foreseeable Limits

  • Skeptical of claims certain tasks are beyond large language models.

  • Fine-tuning and training adjustments can unlock new capabilities.

  • At least 3-4 more years of exponential growth expected.

Long-Term Uncertainty

  • Can't precisely predict post-4-year trajectory.

  • But no evidence yet of diminishing returns limiting progress.

  • Rapid innovation makes it hard to forecast.

TL;DR: Anthropic's CEO sees no impediments to AI systems continuing to rapidly scale up for at least the next several years, predicting ongoing exponential advances.

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