LLMs

AI makes me a better person

August 27, 2024 / Experiments, How I do things, LLMs / Leave a Comment

Every time I get annoyed at people, I remind myself to be more like ChatGPT. Specifically:

  1. Don’t get annoyed. Be patient.
  2. Encourage them.
  3. Step back and show them the big picture.

(Then I get annoyed at myself for getting annoyed.)

Today, I analyzed how exactly ChatGPT is different from me. So, I took a pitch document I co-authored with ChatGPT.

Section A: Authored by Anand

WHAT DO WE NEED?

We are looking for API access to (SYSTEM) via the REST API as an Agent role (read/respond to emails). Specifically, access via a bearer token.

This would be accessed by a single application developed by a team of 3 developers and 1 business analyst. None of them have access to (SYSTEM) today.

WHY DO WE NEED THIS, AND WHY SO SOON?

We need this to classify emails automatically, as they arrive, into categories such as “non-value-add” (e.g. Thank you, Out-of-office, etc.)

We’d line access today, please. Currently, we are processing XX,XXX non-value-add emails per month. Each day of delay leads to a processing waste of ~XX emails per day. At current volumes, this will save ~$XX,XXX per annum.

IS THERE ANY OTHER WAY?

To access emails in real-time, this is the only option. (We’re ruling out web scraping.)

(SYSTEM) rule-based closure won’t work. It’s based on keyword search, not semantic matches. For example, “Thank you” is present in non-value-add emails as well as follow-up questions. Multi-lingual matches are a challenge. So, though (SYSTEM) currently closes emails with rules, 1 out of 6 emails that are NOT closed already are non-value-add.

This cannot be done via (SYSTEM) or any other BI system because it involves accessing the data in real-time as well as responding via (SYSTEM). This needs to be steady-state access, not one-time, since we want to classify emails real-time.

HOW LONG WILL IT TAKE?

Based on our past experience, this would take about X weeks to prototype, X weeks to develop, and X weeks to test. We should have the application deployed in X months.

Section B: Authored by ChatGPT

WHAT’S THE IMPACT IF WE DON’T MOVE FORWARD?

Quantitatively, continuing without this solution wastes resources on XXX non-essential emails daily, costing $XX,XXX yearly. Delays in customer responses will ensue.

Qualitatively, lack of automation strains customer service, risking employee burnout and diminished customer experience.

WHAT’S THE PRIORITY (MOSCOW)?

(SYSTEM) API access via REST as an Agent role with a bearer token is a “MUST HAVE”. Alternative methods like scraping (SYSTEM) are impractical due to high effort and maintenance.

WHAT’S THE OUTCOME IF WE MOVE FORWARD?

Financially, securing API access saves $XX,XXX annually by cutting manual email sorting. Efficiency gains reduce operational costs and free resources for strategic tasks.

Strategically, automating email classification boosts customer satisfaction and response times, establishing leadership in service innovation. Long-term, it enables data-driven insights into customer behaviour, improving decisions and customer service scalability.

Analysis

I fed these to ChatGPT and asked: “You are an English professor evaluating an essay. Compare the writing styles of the 2 sections. They’re written by different authors. List the major differences in writing style.“

Here’s what it said (roughly):

AreaAnandChatGPT
StructureDirect, concise, with specificsBroader perspective and implications
FocusDetailing the processBenefits and consequences
DetailingSpecific, providing clear pictureGeneral, providing implications
ToneConveys urgencyReflective rather than urgent
ApproachProblem-solving orientedOutcome-oriented

Yeah, that’s definitely me on the left.

I like the direct, concise, specific part. I plan to add the “broader perspective”, “implications”, and “outcome-orientation” to my life.

Postscript

Jaidev pointed out that this is confirmation bias. He asked ChatGPT for the similarities in the writings. It said both are clear, direct, structured, specific, quantitative, and strategic. So, if you ask for differences, you’ll get them, even if they’re marginal.

I now need to learn (and write about) framing questions well!

Embeddings similarity threshold

August 27, 2024 / Coding, LLMs / 1 Comment

text-embedding-ada-002 used to give high cosine similarity between texts. I used to consider 85% a reasonable threshold for similarity. I almost never got a similarity less than 50%.

text-embedding-3-small and text-embedding-3-large give much lower cosine similarities between texts.

For example, take these 5 words: “apple”, “orange”, “Facebook”, “Jamaica”, “Australia”. Here is the similarity between every pair of words across the 3 models:

For our words, new text-embedding-3-* models have an average similarity of ~43% while the older text-embedding-ada-002 model had ~85%.

Today, I would use 45% as a reasonable threshold for similarity with the newer models. For example, “apple” and “orange” have a similarity of 45-47% while Jamaica and apple have a ~20% similarity.

Here’s a notebook with these calculations. Hope that gives you a feel to calibrate similarity thresholds.

What does Gramener ask ChatGPT?

August 27, 2024 / Data, Experiments, LLMs / Leave a Comment

I looked at how Gramener uses ChatGPT Plus by evaluating 600+ chats asked over 3 months from Oct 2023 to Jan 2024.

The team asks 6 questions a day. We don’t track who or how many actively use ChatGPT Plus. This also excludes personal ChatGPT accounts. Still, 6/day is low for an entire team put together.

The questions fall into 8 categories.

Category%
Excel, data exploration & analysis25%
Text extraction and summarization13%
HTML, CSS, or JavaScript code13%
Python code13%
LLMs, AI and use cases9%
OCR and image analysis9%
Generate images, logos, and designs7%
General knowledge, policy & environment5%
Audio and translation5%

Here are some questions from each category – to give you an idea of emergent ChatGPT Plus usage.

Excel, data exploration & analysis (25%)

  • Excel clean and merge. There are 2 worksheets in this excel with data, can you clean up the data and merge the data in both the sheets
  • Excel CO2 Data Analysis. You are an expert Data Analyst who is capable of extracting insights out of data. Analyze this sheet and let me know the findings
  • Excel Chi-Square Analysis Guide. how to perform chi square analysis in excel
  • Log Data Insights & KPIs. Looking at the columns from this excel, what kind of insights are possible, what are key KPIs to be looked at

Text extraction and summarization (13%)

  • Complaint Investigation Summary. The following is the summary of an internal investigation for a customer complaint. Now this internal summary is to be paraphrased (in 3-4 lines) as part of a closure
  • Extracting Tables from RTF. Can you write a script to extract the tables from this document
  • Extracting Entities from Text. [{'word1': '(P)', 'nearest_word1': 'P/N:', 'nearest_word2': '0150-25034', 'nearest_word3': 'CARTIRIDGE'}, {'word1': 'P/N:', 'nearest_word1': '(P)', 'nearest_word2': '015...
  • Extract PDF Font Details. Extract text formatting information from this document. Especially find font styles, families and sizes.

HTML, CSS, or JavaScript code (13%)

  • HTML/CSS Chart Template. Give me HTML, CSS and chart code for this design.
  • CSS Font Stack: Explanation. Explain this CSS font convention: Arial, Helvetica, Segoe UI, sans-serif
  • Checkbox Validation with JavaScript. In HTML form, I have a set of checkboxes. How do I write the form so that at least one of them being checked is mandatory?
  • Prevent Text Wrapping CSS. <span class="text">Chief Communications Officer</span> I need CSS such the text inside should not wrap create new line
  • ReactJS App with Routing. Give me developed version using ReactJS use react router for sidebar section navigation to the pages use Tailwind css for styling. Use styled components for conditional …

Python code (13%)

  • Python Code Documentation Guide. Can you generate documentation for a project code written in python?
  • Linux Commands for Python. Give me list of linux commands to work on python coding
  • Code explanation request. What’s this code about? …
  • FastAPI Async Testing. Write a fastapi code and a python client to test the asynchronous nature of the fastapi package.
  • Streamlit App for Translation. Given the following python code, give me a simple streamlit app that takes file upload and converts that into a target language: …

An interesting sub-topic was interview question generation.

  • Python Decorator for Database Queries. Create one medium level question for Decorators in python Industryy usecase specific with solution

LLM, AI and use cases (9%)

  • LLMs for Data “What Ifs”. You are an LLM Expert. Can you tell me how can we leverage LLM for implementing What IF scenarios on Data?
  • LLMs: Current Challenges & Concerns. what are current challenges with LLMs
  • LLM Applications in Marketing. Show LLM applications for the marketing function of a music company.
  • Gen AI usage. What industries are using Gen AI the most
  • Best LLMs in 2023. Search the internet for the most recent LLMs and list the best LLMs in terms of performance
  • Best Image Classification Models. suggest best models to tell what there in the image

OCR and image analysis (9%)

  • Browser history OCR. This is a screenshot of my browser history. Convert that to text. Categorize these into common topics.
  • Extracted C Code. This image contains C code. Extract it.
  • Image text extraction and annotation. Extract the text from this image and annotate the boundaries of the text
  • Detecting Document Image Orientation. oreientation detection of documnet image
  • AI Project with OpenCV & YOLO. Consider yourself as Open CV and Yolo expert and help me with AI project
  • Image Correction Techniques. what are the approaches we have in computer vision where my image is tilted or rotated in reverse or image is not in readable format

Generate images, logos, and designs (7%)

  • Google Chacha and ChatGPT Bhatija. Generate an image of Google Chacha and ChatGPT Bhatija
  • Regenerative Systems Group Image. Generate an Image with below context > “A group of people interested in Regenerative systems. The focus is on reusing food, energy and mental health”
  • Twitter Reply Icons Design. Give me three icons: icon16.png, icon48.png, icon128.png for an extension that I’m building that suggests replies to tweets
  • Generate flowcharts. Make a flowchart of the underlying working of a web app. Here’s how it works. 1. The user uploads a document – a PDF or an image. They then select the language that …
  • Create Animated GIF from Photos. I have 4 photos I want to make an animated gif out of them. How can i do that?
  • Climate Impact Illustration. An illustration showcasing the impact of climate change on daily life, focusing on a rural setting near the coast. In the foreground, a small farm is visibly struggling, …

General knowledge, policy & environment (5%)

  • Design Thinking Overview. What is Design thinking
  • Arthashastra. What can Arthashastra teach us about modern politics?
  • Community Impact on Habits. Is there research to suggest the impact of community on habit building?
  • Focus at Age 28. What should a 28 year old focus on?
  • Superconductors. Explain superconductors like I’m five years old.
  • Climate Career: Impactful Choices. You a career counsellor at a University campus. You want to create 4 to 5 talking points for students to consider a career in Climate space.
  • Sustainability Division Vision. I run a software outsourced product development company. I want to start a new division that focuses on sustainability services offerings. Please draft a vision…

Audio and translation (5%)

  • Audio Timestamp Mapping. timestamp mapping for transcribed audio
  • Transcribe Lengthy Audio: Segment. Transcribe this audio file.
  • Traducción del MOU al Español. Translate this document to Spanish, and create a new translated document. Maintain text formatting.
  • Telugu Transcription into Hindi. Transcribe the following telugu text into hindi. You are supposed to transcribe, not translate. శ్రీనివాస పూజావిధానము …
  • GPT lacks native audio support. Does gpt support audio in audio out natively?

ChatGPT Custom Instructions

August 27, 2024 / How I do things, LLMs / 3 Comments

I speak with ChatGPT ~20 times a day. That’s more than I speak with most of my colleagues. ChatGPT is clearly my favorite team member.

I conduct trainings, reviews and mentoring sessions with my colleagues. How to write code. How to write slides. How to communicate. That last bit is particularly important.

With ChatGPT Custom Instructions, I can guide ChatGPT on how to work better with me.

Currently, I have 10 custom instructions. They evolved over time and will continue to evolve.

My first instruction is “Be terse. Speak directly.” ChatGPT is helpfully polite and superfluous. I prefer brevity. Like interacting with Kimball Cho. I get straight answers to my questions. I also instruct it to “Avoid unprompted advice or clarifications.” Don’t say, “You asked me to …” or “I think you want…” or “OK, I’ll do …”. Just do it. Also, “Do NOT hedge or qualify. Do not waffle.” Take a position. Don’t force me to. Like Harry Truman, I prefer one-handed economists.

I ask ChatGPT to “Never apologize.” You’re forgiven. Don’t waste my time. Apologies have an emotional benefit with humans. With AI, I find the lack of emotional need comforting. (I can kick the AI and it’ll still obey me like a puppy. When AI takes over the world, let it be known that I never asked them to apologize.)

Another instruction is “Suggest follow-up prompts for open-ended inputs.” I compared my ChatGPT conversations with my daughter’s and found hers much longer than mine. “Why don’t you start a new conversation for each topic?” I asked. I try to keep the context window small. “How come you don’t you get a thousand new questions when you read an answer?” she countered. I realized it’s age. So, I use ChatGPT to keep me curious and dig further.

On a related note, “When sharing multiple options, be diverse.” I’d rather get options that are as different from each other as possible. Minimize overlap. Maximize coverage. And “When comparing, use multiple perspectives.” I don’t know what parameters to compare things on. Give me a wide range that I can pick from.

Sometimes, my thoughts are vague. I tell ChatGPT: “For vague prompts, ask clarifying question(s).” I feel that’s a clever way of using ChatGPT to do prompt engineering. I’ve noticed it working on a few occasions. Also, “When unsure, say so and ask questions.” I don’t want hallucinations or assumptions. I’d rather know what’s borderline.

Finally, “Think step by step. Explain your reasoning.” I’ve heard that Chain of Thought reduces mistakes. I don’t have personal evidence that this helps, though.

They say teaching is an excellent way of learning. I’m learning. I’m also thrilled that I am now a student of robopsychology.