I shan't! It's science from a scientist.
On Thursday, February 13, 2025 at 07:44:11 PM EST, Alan Grayson
<[email protected]> wrote:
This is wothless. Stop wasting our time. AG
On Thursday, February 13, 2025 at 5:32:52 PM UTC-7 [email protected] wrote:
Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach
https://arxiv.org/abs/2502.05171
https://twitter.com/akazlev/status/1890193777526292745
We study a novel language model architecture that is capable of scaling
test-time computation by implicitly reasoning in latent space. Our model works
by iterating a recurrent block, thereby unrolling to arbitrary depth at
test-time. This stands in contrast to mainstream reasoning models that scale up
compute by producing more tokens. Unlike approaches based on chain-of-thought,
our approach does not require any specialized training data, can work with
small context windows, and can capture types of reasoning that are not easily
represented in words. We scale a proof-of-concept model to 3.5 billion
parameters and 800 billion tokens. We show that the resulting model can improve
its performance on reasoning benchmarks, sometimes dramatically, up to a
computation load equivalent to 50 billion parameters.
New research paper shows how LLMs can "think" internally before outputting a
single token!Unlike Chain of Thought, this "latent reasoning" happens in the
model's hidden space.TONS of benefits from this approach.Let me break down this
fascinating paper...
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