Healthcare and AI

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Talk #1

What's Next For AI In Healthcare In 2023? - The Medical Futurist

Extract key summary as oneliners. Each line with a max length upto 15 words. Summary in below format

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• The FDA has approved many AI healthcare applications.
• The FDA is developing a database for AI-based healthcare tech.
• AI poses a regulatory challenge as it learns and evolves.
• Radiologists now have guidelines to utilize AI Technologies.
• Regulatory bodies are working on governing AI's large language models.
• Misuse of AI could spread misinformation or breach patient privacy.
• Despite challenges, AI's benefits to healthcare far outweigh the difficulties.
• Companies are integrating AI services like GPT into their business.
• AI is predicted to breakthrough in drug discovery this year.
• AI Solutions usage will increase in established areas like oncology.
• AI will start emerging in new fields like mental health.
• AI will lead to increased efficiency and adoption in healthcare.
• AI will help in revealing solutions that were overlooked before. 

Talk #2

Medical Uses of ChatGPT - The Medical Futurist

• GPT is used widely for academic and coding purposes.
• GPT, the latter version, is being studied for medical usage.
• GPT can help in generating and analyzing clinical notes. 
• It can also answer general health-related queries.
• GPT can pass the U.S. medical exam without specialized training.
• It can help doctors and nurses create accurate clinical notes.
• Medical chatbot, a potential use case, can address a doctor shortage.
• GPT's current limitation includes not citing references and sources.
• GPT's utilization in healthcare implies users being fact-checkers.
• Google's DeepMind has released Medpalm to answer healthcare queries.
• As AI improves, risk of lack of healthcare personnel threatens.
• GPT and AI tech will profoundly change the future of healthcare.

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Disruptive, Fast Forward GPT Days

News #1 - Bain & OpenAI Lineup to Solve more cases

Key use cases they target with ChatGPT are

• Building next-generation contact centers for retail banks, telco and utility companies to support sales and service agents with automated, personalized, and real-time scripts, and to improve customer experience.
• Boosting turn-around time for leading product and service marketers by using ChatGPT and DALL·E to develop highly personalized ad copy, rich imagery, and targeted messaging.
• Helping financial advisors improve their productivity and responsiveness to clients through the analysis of client dialogues and financial literature, and the generation of digital communication.

News #2 - AWS and Hugging Face Team up for more adoption, focused solutions

Hugging Face has become the central hub for machine learning, with more than 100,000 free and accessible machine learning models. More solutions with AWS Platform

News #3 - You can also leverage ChatGPT to build your own model

OpenAI’s Foundry will let customers buy dedicated compute to run its AI models

The cost will be expensive though - Instances won’t be cheap. Running a lightweight version of GPT-3.5 will cost $78,000 for a three-month commitment or $264,000 over a one-year commitment. To put that into perspective, one of Nvidia’s recent-gen supercomputers, the DGX Station, runs $149,000 per unit.

News #4 - Coca-Cola Signs As Early Partner for OpenAI’s ChatGPT, DALL-E Generative AI

Coca-Cola will team with OpenAI and Bain & Company to use OpenAI’s ChatGPT and DALL-E platforms to craft personalized ad copy, images, and messaging, the companies announced in a press release. 

Expect more tags, oneliners, new images, and eye-catching images.

Three Phased Approach

• Custom NER, Parsing, Intent Extraction (Level 1 - Inhouse)
• Leverage Other lightweight fine-tuned models for summarization, topics (Level 2 - Finetuned)
• Leverage LLM models to rank/ Evaluate results (Level 3 - LLM Inputs)

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GPT - The Future - New Products vs Threats

Two Posts two interesting views of #ChatGPT #LLM

The future of conversational AI: connecting LLMs to company-specific data - 

Key Summary

• Current focus is researching and developing ways to integrate LLMs like GPT-3 and others into our conversational AI platform. 
• Personalization of LLM for customer data, Game-changer for us is our ability to connect an LLM directly to company-specific data like a website and use it to suggest content
• Increasing transparency around the origin of the generated content

My perspective - Next Phase is Custom models based on domain data - Banking, Finance, Retail, and Healthcare could fuel more personalized systems in indexing / researching domain-relevant data. Companies with data can partner to build models and make money with the models :)

Not all Rainbows and Sunshine: the Darker Side of ChatGPT 

Key Summary

• Transparency around which sources of data
• Explainable Answers - transparency around how the model arrived at this output is lacking
• Potential misuse/manipulation of facts - LLMs could be fine-tuned to spread misinformation and threaten political stability.
• Possibility of plagiarism 
• The enormous carbon footprint of the training lifecycle of an LLM
• Tomorrow a model can be trained to manipulate history / Facts :(

Valid questions, I hope to see more talks around this.

As we keep discussing yes/no there are products already in the market. Using GPT to generate content writing, payment is pay per wordcount :)

Interesting AI Startups

• Tome - Generative storytelling
• runwayml - GAN Vision / Image / Text Models
• jasper.ai - Get high-quality copy written fast with AI

Create hybrid models, Capture the market :), and let the debate continue.

That's a great example of the combination of 3 powerful tactics:

• Freemium model
• Product-led growth
• Community-led growth

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AI vs Natural Intelligence

AI - any device that does things that associate with human intelligence
Natural Intelligence - Imagination, creativity, fantasy, intuition, problem-solving. AI and natural intelligence are two different things, each supplies a lack of other 
Human Interpretation is leaps ahead of Machine Interpretation

Right Use Case

With the Right context / matured model, Tesla Safety Stats - Q3 2022 - In the 3rd quarter, we recorded one crash for every 6.26 million miles driven in which drivers used Autopilot technology.

Purposeful Bound to Fail 

In some cases, where machines can fail, for example in a classification problem

Selecting the Right Use Cases

ML is more of a collaborative effort. Business needs - You spot it, and you can demonstrate competency to get a buy-in to implement. Alignment is critical to understand the short-term/long-term impact. You may not be immediately right but eventually, you may be right

Spotting what others miss needs all three views - domain, data, and ML opportunities.

Datasets Search

• https://datasetsearch.research.google.com/
• https://github.com/awesomedata/awesome-public-datasets
• https://archive.ics.uci.edu/ml/index.php
• https://www.kaggle.com/datasets
• https://msropendata.com/

• Customer related
• Operations related
• Risk Avoidance

Ref - Link

Ref - Link

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AI in manufacturing use cases

Health and safety

• Employee health & safety: incident prevention
• Process safety: advanced alarm analytics

Quality

• Quality inspection in assembly
• Quality assurance/
• defect inspection
• Quality testing
• Quality prediction

Maintenance

• Machine health monitoring:
• predictive maintenance
• Maintenance planning 

Production process

• Process optimization
• Line balancing
• Product design and development
• Process parameter optimization
• Production planning/
• decision support

Supply chains

• Future demand and price forecasting
• Supply chain control tower
• Warranty and service management

Energy management

• Energy optimization
• Electricity demand forecasting
• Heating and cooling optimization

Ref - Link

Keep Exploring!!!

AI Usecases - Oil and Gas

The predictive model is trained to identify parts that are likely to fail so that

• Plan for preventive maintenance
• Avoid well downtime
• Make sure replacement parts are available else order them in advance
• Identify failure trends
• Geo-locate failed wells

Keep Exploring!!!