YC

Y Combinator Cast

01/24/25

@ Y Combinator

The deadline to apply for the first Y Combinator spring batch is February 11th, and accepted applicants will receive $500,000 in investment along with access to a top startup community.

GT

Garry Tan

01/24/25

@ Y Combinator

Large language models are becoming significantly larger and smarter, with AI labs adopting a strategy of scaling more parameters, data, and compute to improve model performance.

GT

Garry Tan

01/24/25

@ Y Combinator

The performance of AI models has been doubling every six months, raising questions about whether we are nearing the end of the era of scaling or just at the beginning of a new paradigm that could revolutionize AI.

GT

Garry Tan

01/24/25

@ Y Combinator

OpenAI's release of GPT-2 in November 2019 marked a significant milestone with 1.5 billion parameters, followed by GPT-3, which was over 100 times larger and more capable than its predecessor.

GT

Garry Tan

01/24/25

@ Y Combinator

The influential paper on scaling laws for neural language models published in January 2020 established that increasing model size, data, and compute leads to consistent improvements in performance, emphasizing the importance of scale over algorithm.

GT

Garry Tan

01/24/25

@ Y Combinator

Training AI models can be likened to a recipe with three main ingredients: the model itself, the data it is trained on, and the compute power used for training.

GT

Garry Tan

01/24/25

@ Y Combinator

Larger models have more parameters, which are the internal values adjusted during training to enhance prediction accuracy, and they are trained on significantly more data, often measured in tokens.

GT

Garry Tan

01/24/25

@ Y Combinator

Training larger models requires substantial computing power, which translates to more GPUs running for extended periods and consuming increasing amounts of energy.

GT

Garry Tan

01/24/25

@ Y Combinator

The scaling laws paper revealed that increasing parameters, data, and compute leads to a smooth, consistent improvement in model performance, demonstrating that performance is more dependent on scale than on the algorithm used.

GT

Garry Tan

01/24/25

@ Y Combinator

Further research confirmed that scaling laws apply to various models, including those for text-to-image and image-to-text tasks, while in early 2020, these laws for large language models (LLMs) were largely unknown outside of OpenAI, except for one researcher who focused on the scaling hypothesis, suggesting that increasing the size of data and compute would lead to the emergence of intelligence.

GT

Garry Tan

01/24/25

@ Y Combinator

The scaling laws became a foundational principle for AI development after being popularized by researchers, including those at OpenAI and Google DeepMind, who emphasized that it's not just about making models larger, but also about training them on sufficient data.

GT

Garry Tan

01/24/25

@ Y Combinator

Research indicated that previous models like GPT-3 were undertrained; despite their size, they hadn't been trained on enough text to reach their full potential. For instance, Chinchilla, a model smaller than GPT-3, outperformed larger models by being trained on four times more data.

GT

Garry Tan

01/24/25

@ Y Combinator

Chinchilla's success demonstrated that optimal model training requires not only larger models but also adequate data, marking a significant milestone in the development of advanced AI models like GPT-4 and others.

GT

Garry Tan

01/24/25

@ Y Combinator

There is ongoing debate in the AI community about whether we have reached the limits of scaling laws, as the latest models have become larger and more expensive, yet their capabilities seem to be plateauing.

GT

Garry Tan

01/24/25

@ Y Combinator

Despite increasing GPU resources, the intelligence improvements from the current generation of LLMs are not meeting expectations, with reports of failed training runs and diminishing returns emerging from major labs. Additionally, the lack of high-quality data to train new models has become a major bottleneck for AI development.

YC

Y Combinator Cast

01/24/25

@ Y Combinator

We could run out of data for various reasons, but I think that's not going to happen.

YC

Y Combinator Cast

01/24/25

@ Y Combinator

If the old scaling laws are beginning to lose their edge, we need to consider what comes next for AI development.

YC

Y Combinator Cast

01/24/25

@ Y Combinator

OpenAI's new class of reasoning models hints at a potential new direction for scaling AI models.

YC

Y Combinator Cast

01/24/25

@ Y Combinator

The longer models like GPT-3 are able to think through complex problems, the better they perform.

YC

Y Combinator Cast

01/24/25

@ Y Combinator

With the release of GPT-3, it seems the sky is the limit for this new paradigm of scaling large language models.

YC

Y Combinator Cast

01/24/25

@ Y Combinator

GPT-3 made headlines by smashing benchmarks previously considered out of reach for AI, excelling in software engineering, math, and PhD-level science questions.

YC

Y Combinator Cast

01/24/25

@ Y Combinator

GPT-3 represents a huge leap forward, not just a small improvement over its predecessors, and researchers believe this trajectory will continue.

YC

Y Combinator Cast

01/24/25

@ Y Combinator

Instead of just scaling up model size during training, researchers are likely to focus on scaling the compute available for the model's Chain of Thought.

YC

Y Combinator Cast

01/24/25

@ Y Combinator

By allowing models to think longer, large language models can leverage more compute on the fly, enhancing their intelligence for complex problems.

YC

Y Combinator Cast

01/24/25

@ Y Combinator

While scaling pre-training may have plateaued, training test time compute could open up a new paradigm for scaling laws, unlocking previously unimaginable capabilities.

YC

Y Combinator Cast

01/24/25

@ Y Combinator

Large language models are crucial in the pursuit of artificial general intelligence, and the principles of scaling apply to other models as well, including image diffusion and robotics.

YC

Y Combinator Cast

01/24/25

@ Y Combinator

We are still in the early stages of scaling other modalities, indicating that significant advancements are yet to come.

How Scaling Laws Will Determine AI's Future | YC Decoded

Takeaways