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2023 Chemistry A.I.  -Chem Crow (GPT4)

L.L.M.s and GPT4 in Materials Chemistry

Super computer simulates 44 Millions atoms

A.I. Driving Molecular Discovery

Materials Discovery with A.I.

A.I. Chemical Intelligence

A.I. and the Digitization of Chemistry

IBM ROBORXN for Chemistry

L.L.M.s for Materials Chemistry

A.I. in Chemical Engineering

ChatGPT solving Chemical Engineering Problems

Chemical Engineering Programming Languages

Machine Learning Apps for Chemical Industry

Computer Assisted Chemical Discovery

ChatGPT and Chemistry Problems

Chainlit builds L.L.M. Apps in minutes

Build Instruction Tuned L.L.M.s

Molecular ML Reading Group

Transformer models and Chemical Reactions

Create L.L.M. from scratch with Python

2023 ARTIFICIAL INTELLIGENCE, MACHINE LEARNING, AND LARGE LANGUAGE MODEL CHEMISTRY

 

 

LARGE LANGUAGE MODELS, ARTIFICIAL INTELLIGENCE, AND MACHINE LEARNING FOR CHEMISTRY 2023

 

CHATGPT AND GOOGLE BARD CAN SOLVE CHEMICAL EQUATIONS!!!!!!

COMPARE THE ANSWERS OF SEVERAL LLMS TO MAKE SURE THE ANSWERS ARE RIGHT.

 

 

HOW TO USE LLMS FOR CHEMISTRY

https://www.chemistryworld.com/careers/how-to-use-large-language-models-in-chemistry/4017899.article

 

https://huggingface.co/spaces/doncamilom/ChemCrow

https://github.com/ur-whitelab/chemcrow-public

 

LARGE LANGUAGE MODELS FOR CHEMISTRY

 

  1. ChemBERTa (https://arxiv.org/abs/2010.09885): A large language model trained on a massive dataset of chemistry and chemical engineering literature. It is specifically designed to generate new chemical structures, predict reaction outcomes, and design new chemical processes.

     

  2. MolVec (https://github.com/ncats/molvec): A generative model that can be used to generate new chemical structures and predict reaction outcomes. It is trained on a dataset of known chemical structures and reactions.

     

  3. ChemSpider NLP (https://reference.wolfram.com/language/ref/service/ChemSpider.html): A natural language processing (NLP) service that can be used to extract information from chemical texts and databases.

     

  4. Chem2Vec (https://www.chemhaven.org/): A vector representation of chemical compounds that can be used for machine learning tasks such as classification and clustering.

     

  5. ChemQuAD (https://en.seedfinder.eu/strain-info/Chem_D/Apothecary_Genetics/): A dataset of question-answer pairs about chemistry. The questions are written in natural language and the answers are in the form of chemical structures or reactions.

     

  6. ChemGAN (https://arxiv.org/abs/1804.08900): A generative adversarial network that can be used to generate new chemical structures. It is trained on a dataset of known chemical structures.

     

  7. MolGen (https://arxiv.org/abs/1903.03937): A generative model that can be used to generate new chemical structures and predict reaction outcomes. It is trained on a dataset of known chemical structures and reactions.

     

  8. ChemSpaceNet (https://arxiv.org/abs/2006.05916): A generative model that can be used to generate new chemical structures and design new chemical processes. It is trained on a dataset of known chemical structures and processes.


 


 

LARGE LANGUAGE MODELS AND AI AGENTS FOR CHEMISTRY

 

  1. Hugging Face Transformers Agent (Hugging Face): It is a versatile AI agent that can be used for a wide range of tasks, including chemistry. It can be used to generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. It is still under development, but it has learned to perform many kinds of tasks.
     

  2. Google AI Test Kitchen (Google AI): It is a new AI agent that is still under development. It is trained on a massive dataset of text and code and is able to perform a wide range of tasks, including chemistry.
     

  3. PaLM (Google AI): PaLM is a large language model (LLM) that is trained on a massive dataset of text and code. It is capable of performing a wide range of tasks, including chemistry. It can generate text, translate languages, write different kinds of creative content, and answer questions in an informative way.
     

  4. Wu Dao 2.0 (Beijing Academy of Artificial Intelligence): Wu Dao 2.0 is a large language model (LLM) trained on a massive dataset of text and code. It can perform a wide range of tasks, including chemistry. It can generate text, translate languages, write creative content, and provide informative answers.
     

  5. Chemistry AI Assistant (ChemAxon): It is a cloud-based AI assistant designed specifically for chemistry. It can be used to predict chemical properties, design new compounds, and simulate chemical reactions. ChemAxon offers various tools and services related to chemistry and AI.


 

HOW TO DISCOVER NEW MOLECULES WITH OPEN SOURCE AI AGENTS, STEP BY STEP GUIDE:

 

  • Step 1: Choose an open source AI agent platform

    • Consider platforms like Hugging Face, Google AI Platform, AWS, and Azure

    • Select the platform that aligns with your specific needs and objectives
       

  • Step 2: Identify the type of AI model

    • Generative models for creating new molecules

    • Discriminative models for distinguishing known and unknown molecules

    • Choose based on your goals, e.g., patentable molecule discovery or specific-use identification
       

  • Step 3: Collect data

    • Gather relevant data based on your chosen AI model

    • Generative models require datasets of known molecules, while discriminative models need data of known and unknown molecules
       

  • Step 4: Train the AI model

    • Utilize a powerful computer for the time-consuming training process
       

  • Step 5: Evaluate the AI model

    • Test the model on an unseen dataset to identify areas for improvement
       

  • Step 6: Deploy the AI model

    • Make the trained and evaluated model available for users in a production environment

​
 

55 STARTUP COMPANIES AT THE INTERSECTION OF AI AND GREEN CHEMISTRY
 

  1. AxoMat: AI startup for materials design.
     

  2. Carbon Robotics: AI startup for carbon fiber production.
     

  3. Chemisoft: AI startup for process optimization.
     

  4. ChemSpider: AI startup for chemical compound database.
     

  5. DigiTex: AI startup for textile process optimization.
     

  6. Ecosurv: AI startup for environmental monitoring.
     

  7. EnviroInsite: AI startup for environmental remediation.
     

  8. Greenbotics: AI startup for farm automation.
     

  9. Greengro: AI startup for crop optimization.
     

  10. GrowSafe: AI startup for crop protection.
     

  11. Indigo Ag: AI startup for nitrogen fertilizer optimization.
     

  12. Metabolics: AI startup for metabolic pathway design.
     

  13. MicrobiomeAI: AI startup for microbiome analysis.
     

  14. NanoRigs: AI startup for nanomaterial design.
     

  15. NatureVest: AI startup for environmental impact reduction.
     

  16. New Harvest: AI startup for plant-based food products.
     

  17. Nutrient Recovery Technologies: AI startup for nutrient recovery.
     

  18. OpenEI: AI startup for energy technology development.
     

  19. Renmatix: AI startup for waste reduction.
     

  20. AgiSyn: AI startup for molecule design.
     

  21. Atomwise: AI startup for molecule design.
     

  22. BenevolentAI: AI startup for molecule design.
     

  23. Chematica: AI startup for molecule design.
     

  24. CompuSyn: AI startup for molecule design.
     

  25. DeepChem: AI startup for molecule design.
     

  26. EnChroma: AI startup for molecule design.
     

  27. Glixx: AI startup for molecule design.
     

  28. In Silico Labs: AI startup for molecule design.
     

  29. Kegg: AI startup for molecule design.
     

  30. LifeMap: AI startup for molecule design.
     

  31. Molecularity: AI startup for molecule design.
     

  32. Numerate: AI startup for molecule design.
     

  33. Osmosis: AI startup for molecule design.
     

  34. Reaction Design: AI startup for molecule design.
     

  35. SciNote: AI startup for molecule design.
     

  36. Sygnomics: AI startup for molecule design.
     

  37. Ventria: AI startup for molecule design.
     

  38. XChem: AI startup for molecule design.
     

  39. SynthAI: AI startup for molecule design.
     

  40. GreenLight AI: AI startup for molecule design.
     

  41. ChemAI: AI startup for molecule design.
     

  42. ResApp: AI startup for respiratory disease diagnosis.
     

  43. Simulations Plus: AI startup for chemical reaction simulation.
     

  44. Sustainify: AI startup for environmental impact management.
     

  45. Terrasmart: AI startup for resource optimization.
     

  46. Volastra: AI startup for battery technology development.
     

  47. World Resources Institute: AI startup for emission reduction policies.

    Aion Labs: AI startup for molecule design.
     

  48. Beta Chemica: AI startup for chemical reaction optimization.
     

  49. C2iNT: AI startup for process design in chemical production.
     

  50. Chemical AI: AI startup for molecule design.
     

  51. Chemspace: AI startup for chemical reaction optimization.
     

  52. Chroma AI: AI startup for dye and pigment optimization.
     

  53. DeepChem: AI startup for molecule design and synthesis.
     

  54. EnChroma: AI startup for colorant optimization.
     

  55. Glixx: AI startup for molecule design and synthesis.

     

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