"No one is harder on a talented person than the person themselves" - Linda Wilkinson ; "Trust your guts and don't follow the herd" ; "Validate direction not destination" ;
Showing posts with label LLMSeries. Show all posts
Showing posts with label LLMSeries. Show all posts

December 02, 2023

2024 Predictions - LLM Series - Domain-Specific GPT, Multimodal World, SpeedyPrototyping, ResponsibleAI

2024, More products / Innovation with Improved Benchmarks for Domain-Specific GPT, Multimodal World, SpeedyPrototyping, ResponsibleAI and Privacy assured personalized LLM recommendations for Mental Health, Healthcare Tips

1. Improved Benchmarks from Domain-Specific GPT - Go niche with a Domain-Specific GPT. Bring your data, and domain knowledge and Build your LLM. Why settle for generic when you can bring your data and craft a model that knows your field inside out? More benchmarks and newer models both custom / open source across domains #CustomizedAI #CustomGPT

2. #Personalized answers with privacy - Welcome Personal Data + LLM for mental health, healthcare, and suggestions. Your privacy remains intact while you enjoy tailor-made advice crafted just for you. #PersonalizedAdvice #PrivacyMatters.

3. Integrated Multimodal World - It's a #Multimodal World! Knowledge isn't just text; it's Images + Text + Data. Embrace the power of combined data forms to receive enriched, multimodal insights that tell the complete story for recommendations, personalization. #MultimodalKnowledge #HolisticAI

4. #SpeedyPrototyping - Supercharge your innovation engine with Ideas an ensemble of Models. Watch your prototyping speed take off as diverse AI models converge to refine your visions faster than ever! #SpeedyPrototyping #AIEnsemble

5. #ResponsibleAI Model building and solutioning - It's not just about building models; it's about building them right—robust, reliable, and fair. For all infrastructure providers, LLM training vendors, evaluators, and advocates for responsible AI, your insights are invaluable. #AIEthics #ResponsibleAI #GenAI #LLM #Domains #2024 #Predictions #perspectives

Domain Specific GPT

  • BloombergGPT
  • ClimateBERT
  • KAI-GPT
  • ChatLAW
  • FinGPT
  • BioMedLM

Ref - Link1, Link2

Custom Training Models

The future is Intelligence as a Service (Commodity)

  • LLM OS
  • LLM Super App
  • LLM based content creation tools

Keep Exploring!!!


November 26, 2023

LLM Notes

LLM Notes from Andre Karpathy Slides






Keep Exploring!!!

November 20, 2023

The New Stack and Ops for AI

Consistency, User Exp - LLMOps Best practices

  • Framework
  • Repeatable/precise ways
  • AI augments human capabilities
  • User Experience
  • Keep humans in loop
  • Iterate and improve
  • Communicate capabilities
  • Suggestive prompts








  • Consistency

  • Output from JSON grammar


  • Seed parameter


  • Ground Truth



  • Microservice and Keeping track
  • Function Calling

  • DB / Browse data

  • Evaluate performance







  • Semantic Cache
  • Lookup if already in the cache







Keep Exploring!!!


November 14, 2023

LLMOps, Guardails

LLMOps

LLM monitoring in real-time for factual / sentiments/hallucinations. Loved the visualization.


Giskard is an open-source framework for testing all ML models

A Survey on Bias and Fairness in Machine Learning

Evaluating LLM Response

  • Response Evaluation Criteria
  • Factual accuracy of Response
  • Coherence, Grammar
  • Efficiency
  • Safety
  • Emotion, Bias




Ref - Link

Keep Exploring!!!

June 11, 2023

How to train your own LLM - Copilot type LLMs

Notes

  • Scenarios to custom train
  • Privacy, IP, Customization
  • Smaller and Efficient Models
  • Restrict Information shared with LLM models

  • Code completion model by Replit

Stack

  • Databricks pipeline
  • Hugging Face for tokenizers / inference tools for code
  • MosaicML - GPU and model training

  • Training LLM Architecture

  • Extensive code base of Git / Stackoverflow

  • Data preprocessing 
  • All preprocessing in distributed fashion
  • Lot of work on notebooks
  • Removed auto generated code from training
  • Anonymize data remove PII info
  • Remove code that does not compile
  • Remove Python2 code and keep it for one version
  • Maximum line length set

  • Custom Vocabulary creation
  • Custom tokenizer for domain specific dataset

MosaicML for training




Future

  • Optimal / Smaller LLM
  • Customized LLMs
  • LLM with reasoning

Keep Exploring!!!