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Cancer Drug Discovery Generative Artificial Intelligence Software Innovation

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R&D
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Talks
Talks
 
 
01 All Quantum Discussions.md
01 All Quantum Discussions.md
 
 
02 Quantum Technology Timeline.md
02 Quantum Technology Timeline.md
 
 
03 Emerging Quantum Advantages.md
03 Emerging Quantum Advantages.md
 
 
04 TensorFlow Quantum, Qiskit.md
04 TensorFlow Quantum, Qiskit.md
 
 
05 PQCs in Medical Analysis.md
05 PQCs in Medical Analysis.md
 
 
06 Medical Quantum Forecast.md
06 Medical Quantum Forecast.md
 
 
07 Embedding Medical Data, QML.md
07 Embedding Medical Data, QML.md
 
 
08 QML Algorithms History.md
08 QML Algorithms History.md
 
 
09 Qiskit or PennyLane PyTorch Ports.md
09 Qiskit or PennyLane PyTorch Ports.md
 
 
10 100 Resources for Medical.md
10 100 Resources for Medical.md
 
 
11 100 Coding Tips.md
11 100 Coding Tips.md
 
 
12 Potential Radiomics QML.md
12 Potential Radiomics QML.md
 
 
13 Specific QiML Algorithms.md
13 Specific QiML Algorithms.md
 
 
14 How to: QML Loss, Optimizer.md
14 How to: QML Loss, Optimizer.md
 
 
15 Healthy QiML Industry.md
15 Healthy QiML Industry.md
 
 
16 QiML Algorithm Architecture.md
16 QiML Algorithm Architecture.md
 
 
17 Deep Learning Quantum Parameters.md
17 Deep Learning Quantum Parameters.md
 
 
18 NIH Developer Seminar.md
18 NIH Developer Seminar.md
 
 
19 QML Algorithms, Medical School.md
19 QML Algorithms, Medical School.md
 
 
1st answer Open WebUI Stanford Medicine.pdf
1st answer Open WebUI Stanford Medicine.pdf
 
 
20 QML Algorithms, Medical R&D.md
20 QML Algorithms, Medical R&D.md
 
 
21 Quantum Algorithm Time Complexity.md
21 Quantum Algorithm Time Complexity.md
 
 
22 Medical QiML Software Migration.md
22 Medical QiML Software Migration.md
 
 
23 Better Quantum-inspired Processing.md
23 Better Quantum-inspired Processing.md
 
 
24 Surpassing Competition, 3 QiML.md
24 Surpassing Competition, 3 QiML.md
 
 
25 Practical QiML 2.0 for Healthcare.md
25 Practical QiML 2.0 for Healthcare.md
 
 
26 QiML 2.0 Speed-Ups, New Era.md
26 QiML 2.0 Speed-Ups, New Era.md
 
 
27 Tensor Network Revolution.md
27 Tensor Network Revolution.md
 
 
28 Tensor Network, Neural Network.md
28 Tensor Network, Neural Network.md
 
 
29 Tensor Networks vs. PCA and PLS.md
29 Tensor Networks vs. PCA and PLS.md
 
 
30 LLM Explainability, Tensor Networks.md
30 LLM Explainability, Tensor Networks.md
 
 
31 How to Code LLMs, Tensor Networks.md
31 How to Code LLMs, Tensor Networks.md
 
 
32 Drug Discovery Generative AI.md
32 Drug Discovery Generative AI.md
 
 
33 Drug Discovery GenAI, De Novo.md
33 Drug Discovery GenAI, De Novo.md
 
 
34 Meta Llama 3 Fine-tuning, RAG.md
34 Meta Llama 3 Fine-tuning, RAG.md
 
 
35 Meta Llama 3 Drug Discovery GenAI.md
35 Meta Llama 3 Drug Discovery GenAI.md
 
 
36 Cancer Drug Discovery AI.md
36 Cancer Drug Discovery AI.md
 
 
37 Cancer Drug Discovery Innovation.md
37 Cancer Drug Discovery Innovation.md
 
 
38 How to Develop APIs, GenAI.md
38 How to Develop APIs, GenAI.md
 
 
39 Local GenAI Model Frameworks.md
39 Local GenAI Model Frameworks.md
 
 
AgentExecutor_GPT4o_Python_Cloud_HRCPU.ipynb
AgentExecutor_GPT4o_Python_Cloud_HRCPU.ipynb
 
 
Blip_Gradio_Python_Cloud_HRCPU.ipynb
Blip_Gradio_Python_Cloud_HRCPU.ipynb
 
 
COVER.png
COVER.png
 
 
LICENSE.md
LICENSE.md
 
 
README.md
README.md
 
 

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Drug Discovery Generative AI

The Generative Artificial Intelligence Software Public Repository for Cancer Drug Discovery is on GitHub.

The research summary is a look ahead using effective tensor network machine learning approaches to accelerate GenAI.

The goal is to implement effective architectures and methodologies into Large Language Models (LLMs) for enhanced Drug Discovery Generative AI performance.

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Cancer Drug Discovery Generative Artificial Intelligence Software Innovation

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