Tag Archives: ai

mutation testing from a five year old (according to chatgpt)

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I asked ChatGPT to explain mutation testing to a five year old to see what it would say. I got this back:

Alright, imagine you have a big puzzle made of Lego blocks. Each block represents a piece of code that makes up a computer program. Now, let’s say we want to make sure that our puzzle is put together correctly so that our program works properly.

Mutation testing is like having a mischievous Lego wizard who comes and changes some of the pieces in our puzzle to see if we notice. He might swap a blue block for a red one, or turn a block upside down. After he’s done, we carefully check our puzzle again to see if it still looks right and if our program still works.

If we can still solve the puzzle and our program still works even with the changes the wizard made, then we know our puzzle – or our program – is really strong. But if we can’t solve the puzzle or our program stops working, then we know there’s a problem and we need to fix it. So, mutation testing helps us make sure our programs are really robust and can handle unexpected changes.

It’s a good example of how ChatGPT is an aide and not a solver. First paragraph is good. In the second part, I love the mischievous Lego wizard who comes and changes some of the pieces to see if we notice. It’s a good premise. We see if our program still works with the changes.

The third paragraph leads us astray. If we notice the change, that is good. If the program stops working it is also good, means we noticed the change. Mutation testing is about having good tests that can detect change. Not a robust program with unnecessary code that behaves the same way when changed.

[uberconf 2023] Practical AI Tools for Java Developers

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Speaker: Ken Kousen

@kenkousen

For more, see the table of contents

Prompt Engineering

  • Tools are improving fast, might not be needed as job
  • Suggest context (ex: “pretend you are”)
  • Give example of what you want

Chat GPT

  • Free version is GPT 3.5 Turbo (improved performance over original 3.5)
  • $20/month for GPT 4. Can make 25 requests in a three hour block.
  • Have not noticed quality control over plugins.
  • Plugins change rapidly.
  • Apologizes when you correct it.
  • Warning about pasting your company’s code in
  • Trained thru summer 2021
  • Can’t read files on local file system (Bard can). Can read link but doesn’t know it can
  • Often wrong if you ask it about whether can do something. Like talking to toddler; says want thinks want to know.
  • Temperature – tweaks creativity vs precision
  • REST API docs
  • REST API: cookbook has examples
  • Must give credit card to call REST APIs. Pennies are for 1000 tokens (about 750 words). Charged for both input and output words. Also limits on context (amount GPT remembers). Not expensive if don’t use it much. Ken’s bill has been pennies and too low to be sent a bill.
  • REST API JSON response says how many tokens used. Can also see graph when log into account
  • Had it make multiple choice questions on a topic

Chat GPT Code Interpreter

  • Code Interpreter beta feature.
  • Need to explicitly enable under settings.
  • From OpenAI, not third party
  • ex: can convert Groovy to Kotlin DSL for Gradle

DALL-E

  • First popular text to image generation tool
  • A generation behind text/GPT.
  • Stable Diffusion free, but behind on quality
  • Prefers MidJourney, more realistic

Whisper

  • Audio to text
  • Takes audio or video and writes transcription.
  • Free (unless use REST API)
  • Mac Whisper – $20 on time fee for larger models. Good for transcribing videos of talks. Slow first time. After that (including other videos, fast. [caching?]
  • Creates .srt file (Subtitles)

Claude.AI

  • Free beta
  • Only available in US and UK
  • Can hold 100K tokens. ex: can summarize a novel
  • Quality comparable to ChatGPT 3.5, but not as good as 4.0
  • Can upload many file types
  • Harder to get back to previous conversations than ChatGPT. Need to click on “A” icon on top to see them
  • Doesn’t do image

Bard

  • Can upload answers to Google docs on Ken’s personal account, but not business account
  • Used to be able to answer who Venkat is but can’t anymore.

Llama 2

  • Meta announced today
  • Pretrained language model
  • Free unless large company (aka: competitors)

Descript

  • Transcribes and edits video
  • Can give instructions – ex: shorten gaps in video, remove filler words
  • If don’t move around much, will make it look like you are looking at camera
  • Can give text and select a voice. With 30 minute sample, can train on your voice

Canva

  • Can describe presentation want and Canva makes a draft
  • Can choose theme from list of choices
  • Magic eraser – brush over part of image don’t want and replaces with background nearby
  • Beats Sync – line of slide transition to beats of music
  • Magic Write – like GPT 3.5
  • Magic Design – give own image and make presentation around that

GitHub Copilot

  • Virtual pair programmer
  • Plugins for VSCode and IntelliJ
  • If hesitate, suggests code
  • Can’t agree to part of suggestion. Need to accept it all or delete
  • Guesses right a lot because knows what have done before in a training class
  • Always looks plausible because trained on own code. Need to look carefully
  • Next generation is GitHub CopilotX. Only available via wait list. VS Code only at this point, can use for pull requests.
  • GitHub Next – tools in a variety of states – https://githubnext.com. “Visualizing a Codebase” runs as github action to see packages

IntelliJ AI Assistant

  • Not much documentation on how it works. Only one blog post
  • In Ultimate, not Community
  • In beta edition
  • Can highlight code and ask to explain it
  • If don’t like suggestion, can request it suggests something else and get more choices
  • Can write commit message for you
  • Find issues with code when know language well
  • Helps in language know less well because it knows the API/syntax
  • Good for nuisance tasks that would take a lot of time

YouTube Summary

  • Get summary or transcript of video
  • Free
  • Up to 20 minute video

My take

I was doing my interview with the Build Propulsion Lab so was a few minutes late. It was a full room so my seat was on the floor. Luckily, the room had a large aisle so I could sit near the front instead of in the very back! And the carpet was comfy.

As far as Ken’s actual talk, it was great. I liked the overview of a bunch of tools and seeing the REST APIs for calling OpenAI. Great breath of topics and fun examples! I learned a lot including some tools I hadn’t heard of. And some very cool functionality!

[2023 kcdc] With Great Power Comes Great Responsibility: The Ethics of AI

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Speaker: Matthew Renze

Twitter: @matthewrenze

For more, see the table of contents.

History

Tech has a tendency to be abused

  • land – slaves
  • mechanized war fare – expand influence
  • cyberware – mass surveillance

Alice and Bob

  • Need to decide if want to get cat or dog for kids.
  • One researches cats and one dogts.
  • Get into info bubble thinking cat lovers hate dogs and vice versa and mad at each other
  • Then talk to real people, learn people like both and get a cat and a dog.
  • A generation later they lose their jobs due to robots/AI. Their kids see lots of jobs because tech savvy.
  • Kids convince parents to upskill and get new job
  • Another generation later grandkids want biological augmentation and to marry an AI.
  • Feel lost in world no longer recognize
  • Learn about technology and see it is an evolution. Learn from grandchildren.

Today

  • When search for something, get more of it.
  • Then info bubble/echo chambers
  • Goal is to maximize engagement. This results in more extreme content so people click
  • Lose privacy – ex: shopping data predict pregenancy
  • Can deanonymomize data with data of birth, sez and zip code
  • Little privacy now and soon a lot less
  • Algorithmic bias – ex: racially bias criminal risk score, males preferred in resumes

AI

  • Uncanny valley – distrust things that almost like us
  • Hallucination – making up believeable, but false info
  • Misinformation at scale
  • Lack of AI literacy

What can we do

  • Delete cookies
  • Incognito mode
  • Throwaway emails
  • Stop using “click holes” to get pulled down rabbit holes
  • Opt out
  • Privacy regulations
  • Limit/stop using social media
  • Talk to other people

AI Developers

  • Eliminate bias in data – diverse datasets, exclude protected attributes, retrain algorithm over time
  • Be able to explain how AI made decision. Use decision tree vs neural network where can.
  • Let users choose how much error they allow
  • Don’t allow full autonomous

Fight misinformation

  • Who is the author/publisher?
  • What are their sources?
  • How strong is the evidence?

Near Future

  • Significant unemployment – simple/repetitive/costly jobs. Expect 20%+ jobs to go away by 20230 and be replaced by other higher tech jobs
  • Labor market unprepared for rapid change
  • Society is unprepared for change.
  • Many people left behind in poverty.
  • Synthetic media – indistinguishable from human data. Propaganda/misinformation at scale. Deep fakes. Deep nude (remove clothes without permission), etc
  • With 10 likes, AI knows you well as colleague.
  • Surveillance capitalism – can’t detect being manipulated
  • Greater social stratification – income gap
  • Safety issues – does self driving car protect driver or pedestrian
  • Autonomous weapons – currently a human is in the loop

Solutions

  • Educate everyone/AI literacy, Basics of ML, DL (deep learning), RL (reinforcement learning)
  • Job retraining
  • Retirement options for those too old to reskill
  • Mandatory higher ed – mandatory high school was controversial
  • Universal basic income/negative income task
  • Deep fake detection – arms race
  • Digital alibi – so can prove what doing at all times and therefore not in fake ideo
  • Blockchain for everything so have complete audit trail
  • Default mode of skepticism

Further Future – Speculative

  • AGI (artificial general intelligence) – at least as smart as average person
  • Improve health
  • Solve biggest problem – climate change, politics, government
  • Humans could become obsolete – ex: horses became obsolete to farms. “Peak horse” was in 1915
  • Collapse of modern institutions – could break capitialism.
  • Changes already faster than society can adapt. What happens when new discoveries every day?
  • Dystopian future – authoritarianism, communism, fascism, AI religion, AI super bureaucracy
  • Or a better AI based government
  • ASI (artificial super intelligence) – if create AGI, intelligence exposion can happen fast. AGI can rewrite its own code.
  • Alignment problem – how do we align human and AI values. Reward hacking – find loopholes
  • AI run amok – what happens if robot mine astroids. When does it stop
  • Conflicts – are we pets, ants, raw materials, competition, a threat?

Positives

  • We evolved for short bursts of stress.
  • Modern society is chronic stress
  • Be mindful with tech
  • Respect AI
  • Don’t fear/fight change
  • Use tech when beneficial and skip when not
  • Reward AI goal states
  • Keep ability to intervene if decision doesn’t align

Long run

  • Peacefully coexist with AI
  • AI wins
  • AI and humanity merge – most likely option
  • Humanity ends itself

Merge

  • No “us vs them” problem.
  • Phones an extension of us
  • Younger generation willing to merge with mind
  • VR/AR glasses
  • Gene editing
  • Brain/computer interfaces
  • Next version of people likely to be vary different

My take

The Alice and Bob stories are fun. There was a ton of information. It went very fast and definitely need time to process. I expected more discussion of ethics rather than covering “everything” but I’m happy with how it turned out.