PixelProf @ PixelProf @lemmy.ca

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3

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144

Joined

2 yr. ago

+1 to safety razors in general. The disposables always used to make my neck and chin look like a horror film, not for lack of research on using. Switching to safety razors, I only shave around my beard so I use the same blades for a long while and shave infrequently, and I've been using the same pack of blades that I bought 5+ years ago. A little cardboard and metal, way less waste, I have a huge supply of razors so I haven't thought about buying in ages, and I get a way better shave after just a little practice.

And the waste reduction can't be understated.

This isn't a informed statement just a hot take, but maybe capitalism wouldn't be so evil if everyone tipped into the growth end of Maslow's before turning insulin into high-end consumer goods.

I researched creative AI and how AI can help people be creative, people thought it was a ridiculous and pointless topic. I'm biased.

Firstly, I think it's important to see the non-chat applications. Goblin Tools is a great example of code we just couldn't have written before. Purely from an NLP perspective, these tools are outstanding, if imperfect.

I'm excited to see new paradigms of applications come up when talented new developers are able to locally run LLMs and integrate them into their everyday programming, and too see what they can cook up in a world where that's normal.

I'm interested in LLMs not to generate data on the fly, but to pre-generate and validate massive amounts of content or data than we'd otherwise be able to for things like games.

From a chat perspective, I like that it can support fleshing out ideas, parsing lots of data in a usable way.

And finally I'm excited for how lightweight LLMs could affect user interface design. I could imagine a future where OSs have swappable LLMs like they have shells that can allow for natural language interfacing with programs.

I don't know, it's just really accessible NLP, and that's great.

Every time. Try to get ahead of your work? Well, good for you, that first 20% went really well, now let's spend the next two weeks on "work" that interferes with your other needs and needs to get thrown out because there's no way it's integrating with the other 80% that needs to happen within the next hour and also everything that you did for the other 20% is useless and needs to be redone now that you broke it with that tangent.

It's been a painful summer "preparing" to teach my fall courses.

I sit somewhere tangential on this - I think Bret Victor's thoughts are valid here, or my interpretation of them - that we need to start revisiting our tooling. Our IDEs should be doing a lot more heavy lifting to suit our needs and reduce the amount of cognitive load that's better suited for the computer anyways. I get it's not as valid here as other use cases, but there's some room for improvements.

Having it in separate functions is more testable and maintainable and more readable when we're thinking about control flow. Sometimes we want to look at a function and understand the nuts and bolts and sometimes we just want to know the overall flow. Why can't we swap between views and inline the functions in our IDE when we want to see the full flow? In fact, why can't we see the function inline but with the parameter variables replaced by passed values to get a feel for how the function will flow and compute what can be easily computed (assuming no global state)?

I could be completely off base, but more and more recently - especially after years of teaching introductory programming - I'm leaning more toward the idea that our IDEs should be doubling down on taking advantage of language features, live computation, and co-operating with our coding style... and not just OOP. I'd love to hear some places that I might be overlooking. Maybe this is all a moot point, but I think code design and tooling should go hand in hand.

Yeah, Barkley's talks have helped a lot so far. Previous psychiatrists largely wrote off diagnoses because I was successful in work, but overlooked the challenges at home. Some trauma therapy combined with Barkley's unique focus of adult symptoms of ADHD really opened my eyes to it.

Still doubts, still confusion, but clearing up.

The beatings will continue until morale productivity improves.

Edit: Sorry, morale is irrelevant.

I'm really torn on this, because on one hand the over generalization of ADHD prevented me - and is still preventing me - from taking my own diagnosis too seriously, but that same information got me to at least think about it and get a consult with a psychiatrist on it in the first place.

It helped the diagnosis but not the feelings of being an imposter post-diagnosis.

It's also tough to reconcile that I may thrive in high pressure situations, but they're still exhausting and I don't like them, and definitely not being dependent on them to do anything. Medication helped the minute to minute, but the week to week is still a total blur.

I appreciate the comment, and it's a point I'll be making this year in my courses. More than ever, students have been struggling to motivate themselves to do the work. The world's on fire and it's hard to intrinsically motivate to do hard things for the sake of learning, I get it. Get a degree to get a job to survive, learning is secondary. But this survival mindset means that the easiest way is the best way, and it's going to crumble long-term.

It's like jumping into an MMORPG and using a bot to play the whole game. Sure you have a cap level character, but you have no idea how to play, how to build a character, and you don't get any of the references anyone else is making.

This is a very output-driven perspective. Another comment put it well, but essentially when we set up our curriculum we aren't just trying to get you to produce the one or two assignments that the AI could generate - we want you to go through the motions and internalize secondary skills. We've set up a four year curriculum for you, and the kinds of skills you need to practice evolve over that curriculum.

This is exactly the perspective I'm trying to get at work my comment - if you go to school to get a certification to get a job and don't care at all about the learning, of course it's nonsense to "waste your time" on an assignment that ChatGPT can generate for you. But if you're there to learn and develop a mastery, the additional skills you would have picked up by doing the hard thing - and maybe having a Chat AI support you in a productive way - is really where the learning is.

If 5 year olds can generate a university level essay on the implications of thermodynamics on quantum processing using AI, that's fun, but does the 5 year old even know if that's a coherent thesis? Does it imply anything about their understanding of these fields? Are they able to connect this information to other places?

Learning is an intrinsic task that's been turned into a commodity. Get a degree to show you can generate that thing your future boss wants you to generate. Knowing and understanding is secondary. This is the fear of generative AI - further losing sight that we learn though friction and the final output isn't everything. Note that this is coming from a professor that wants to mostly do away with grades, but recognizes larger systemic changes need to happen.

100%, and this is really my main point. Because it should be hard and tedious, a student who doesn't really want to learn - or doesn't have trust in their education - will bypass those tedious bits with the AI rather than going through those tedious, auxiliary skills that you're expected to pick up, and use the AI was a personal tutor - not a replacement for those skills.

So often students are concerned about getting a final grade, a final result, and think that was the point, thus, "If ChatGPT can just give me the answer what was the point", but no, there were a bunch of skills along the way that are part of the scaffolding and you've bypassed them through improper use of available tools. For example, in some of our programming classes we intentionally make you use worse tools early to provide a fundamental understanding of the evolution of the language ergonomics or to understand the underlying processes that power the more advanced, but easier to use, concepts. It helps you generalize later, so that you don't just learn how to solve this problem in this programming language, but you learn how to solve the problem in a messy way that translates to many languages before you learn the powerful tools of this language. As a student, you may get upset you're using something tedious or out of date, but as a mentor I know it's a beneficial step in your learning career.

Maybe it would help to teach students about learning early, and how learning works.

Yeah, I knew freelance folks who provided long term support with such complicated setups. The base daily rate plus hourly with a monthly retainer and weekly on call fees. Wild.

Or, hourly = extremely high paid contract work.

Education has a fundamental incentive problem. I want to embrace AI in my classroom. I've been studying ways of using AI for personalized education since I was in grade school. I wanted personalized education, the ability to learn off of any tangent I wanted, to have tools to help me discover what I don't know so I could go learn it.

The problem is, I'm the minority. Many of my students don't want to be there. They want a job in the field, but don't want to do the work. Your required course isn't important to them, because they aren't instructional designers who recognize that this mandatory tangent is scaffolding the next four years of their degree. They have a scholarship, and can't afford to fail your assignment to get feedback. They have too many courses, and have to budget which courses to ignore. The university holds a duty to validate that those passing the courses met a level of standards and can reproduce their knowledge outside of a classroom environment. They have a strict timeline - every year they don't certify their knowledge to satisfaction is a year of tuition and random other fees to pay.

If students were going to university to learn, or going to highschool to learn, instead of being forced there by societal pressures - if they were allowed to learn at their own pace without fear of financial ruin - if they were allowed to explore the topics they love instead of the topics that are financially sound - then there would be no issue with any of these tools. But the truth is much bleaker.

Great students are using these tools in astounding ways to learn, to grow, to explore. Other students - not bad necessarily, but ones with pressures that make education motivated purely by extrinsic factors than intrinsic - have a perfect crutch available to accidentally bypass the necessary steps of learning. Because learning can be hard, and tedious, and expensive, and if you don't love it, you'll take the path of least resistance.

In game design, we talk about not giving the player the tools to optimize their fun away. I love the new wave of AI, I've been waiting for this level of natural language processing and generation capability for a very long time, but these are the tools for students to optimize the learning away. We need to reframe learning and education. We need to bring learning front and center instead of certification. Employers need to recognize this, universities need to recognize this, highschools and students and parents need to recognize this.

This should be interesting to play with. Does anyone know of any Copilot-like VS Code extensions that provide similar UX but hook into a custom local/remote server? I would love to write my own pipeline and context builder for it, but I haven't written a VS Code extension before and a starting point would be good.

I haven't worked with any of the current code-based open models so I don't really know how it compares, excited to hear thoughts from others on this.

When I teach story points (not in an official Agile Scrum capacity, just as part of a larger course) I emphasize that the points are for conversation and consensus more than actual estimates.

Saying this story is bigger than that one, and why, and seeing people in something like planning poker give drastically differing estimates is a great way to signal that people don't really get the story or some major area wasn't considered. It's a great discussion tool. Then it also gives a really rough ballpark to help the PO reprioritize the next two sprints before planning, but I don't think they should ever be taken too seriously (or else you probably wasted a ton of time trying to be accurate on something you're not going to be accurate on).

Students usually start by using task-hours as their metric, and naturally get pretty granular with tasks. This is for smaller projects - in larger ones, amortizing to just number of tasks is effectively the same as long as it's not chewing away way more time in planning.

You check the clock. You check again, because you didn't actually read the time because you were too absorbed in the process of checking the clock that you forgot to check the clock.

You check the clock again. You have a new email. You consider checking the clock again, but give up and accept your fate because checking the clock a (second? Third? Tenth? First?) time is just too much right now, you're already running late anyways so it was kind of all procrastinating in the first place. You don't even know what you were supposed to be checking it for. Just wait and see, it's probably not that important. Maybe you'll check the clock and see if it sparks your memory.

You check the clock. You finally see the time. The bus drives past you.

The ways we cope and overcome, and the ways we don't.