Bengio, YoshuaLecun, Yann
This study analyzes various approaches for optimizing test-time compute scaling in LLMs, including search algorithms with process verifiers (PRMs) and refining the proposal distribution through revisions. Beam search outperforms best-of-N at lower generation budgets...
SmartScaling is a methodology that uses the advanced machine-learning algorithms to reduce the actual simulation runtime thus mitigating the above challenges in characterizing multiple PVT corners.
NVIDIA Triton is an open-source AI model serving platform that streamlines and accelerates the deployment of AI inference workloads in production. It helps developers reduce the complexity of model serving infrastructure, shorten the time needed to deploy new AI models, and...
We need to transform our value offerings towards optimization of customers processes. To enable this, we are increasingly investing in capabilities for machine learning, AI, and deep learning, and I think we are also quite far ahead in implementing these within our operations. The final component...
The surveyed papers found in the Model-free category use Q-learning and SARSA (see Appendix A.2), two reference algorithms for Temporal Difference learning. As we mentioned earlier, RL techniques are usually affected by large state spaces, which directly impacts the performance of the ...
To rigorously benchmark the proposed SVD method, we compare it against commonly used methods implemented in machine learning algorithms to re-scale images: cubic interpolation; linear interpolation; and, nearest neighbor interpolation. To demonstrate the effectiveness of the SVD method, we start by ben...
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The BlackAnt platform is a framework that provides a solution to the problem that users are faced with a number of resource-intensive computations (in particular artificial intelligence—deep learning—machine learning algorithms) that they need to provi
Reinforcement learning from human feedback (RLHF) has proven effective in aligning large language models (LLMs) with human preferences. However, gathering high-quality human preference labels can be a time-consuming and expensive endeavor. RL from AI Feedback (RLAIF), introduced by Bai et al....