I really want to see if worker owned cooperatives plus AI could do help democratize running companies (where appropriate). Not just LLMs, but a mix of techniques for different purposes (e.g., hierarchial task networks to help with operations and pipelining, LLM for assembling/disseminating information to workers).
It is real, you just have to have sufficient funds already to be able to pay someone else to do the active part of the income and make sure they are earning less than their worth so that you can pick up the excess. Most effective if there are many layers in between, so that the income becomes increasingly passive as you move up the chain, so that those under you have something to strive for, because you don’t want to be in charge of hiring all of those people, so you hire people to hire those people, each taking a cut of the value along the way.
But don’t worry, the American Dream™ is that, as long as you keep working about 10 layers deep in value cuts, eventually you might be able to get into layer 3 or 4 and get your kid into the job early so that they can get to layer 5 or 6, and maybe they’ll have enough money to get their kid to 6 or 7.
C could just be a blank and you have to bit blit the arrow on yourself.
I don’t know why, but I still can’t open a core file without going I’m in. I don’t do QA, though, and so tinkering with final breath of my program frozen in time maintains some novelty.
My two cents, after years of Markdown (and md to PDF solutions) and LaTeX and a full two years of trying to commit to bashing my head against Word for work purposes, I’m really enjoying Typst. It didn’t take long to convert my themes, having docs I can import which are basically just variables to share across documents in a folder has been really helpful. Haven’t gone too deep into it but I’m excited to give it a deeper test run over the next little bit.
I get both sides of the argument here. I think we need to have this big reaction because companies have held so much power over employees for so long - I’ll avoid ranting about worker-owned cooperatives here - but the past few years I’ve surprised myself by moving into a bit of a “slippery slope” camp with these things. Not to say it shouldn’t happen, but that we need to be prepared for the follow-up.
Hopefully related example, in education: There were some really big push backs recently where I am over bad treatment of the students in highschool, all legit. The school board ignored it for a long time, it got bad, they finally took it seriously. Then they overcorrected and stopped believing teachers at all and started jumping straight to firing at almost any complaint. Then students started weaponizing complaints, and now teachers are getting fired for trying to enforce deadlines and for giving low marks because students are complaining about how deadlines, grades, and meeting grading requirements are detrimental to mental health and well-being, and now there are a bunch of these students from this board in my university classes failing hard and filing complaints about courses being too difficult and other things despite them having glowing reviews just a few years prior.
I guess what I’m getting at: I think it’s fair for someone to choose not to hire people like this because it’s possible that the people willing to stand up and make an important fuss over these things might not know where the line stands between a worthwhile complaint and a non-worthwhile one, and might make a company look badexternally even though it’s doing good internally, just not to someone new to the workforce’s expectations.
I also think it’s fair to go the opposite direction, because ultimately we need major change in the way companies/everything are structured that lead to these nasty layoffs and poor conditions and if someone does raise issues where there aren’t, hopefully we are prepared enough and in the right enough to take it seriously, but weather it and act in everyone’s best interests.
That too, and I can really efficiently manage the items going into bags given I backpack my groceries and want pretty specific configurations…
Totally agree. I forgot about those, as I’ve only encountered the weighing ones once in the past very long time and it was a mess, I can totally get hate if weighing ones are the only experience with them.
I almost exclusivity self-checkout for groceries, and it had drastically sped up my checkout time as most people in my area opt to use traditional checkout and the stores are still keeping lots of lanes open (just closing the express lanes). The last 3 times I’ve used a non-self checkout, each time I was double charged for items or didn’t have reduced prices applied and didn’t notice because I was bagging.
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.
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.
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.
Hmm… Nothing off the top of my head right now. I checked out the Wikipedia page for Deep Learning and it’s not bad, but quite a bit of technical info and jumping around the timeline, though it does go all the way back to the 1920’s with it’s history as jumping off points. Most of what I know came from grad school and having researched creative AI around 2015-2019, and being a bit obsessed with it growing up before and during my undergrad.
If I were to pitch some key notes, the page details lots of the cool networks that dominated in the 60’s-2000’s, but it’s worth noting that there were lots of competing models besides neural nets at the time. Then 2011, two things happened at right about the same time: The ReLU (a simple way to help preserve data through many layers, increasing complexity) which, while established in the 60’s, only swept everything for deep learning in 2011, and majorly, Nvidia’s cheap graphics cards with parallel processing and CUDA that were found to majorly boost efficiency of running networks.
I found a few links with some cool perspectives: Nvidia post with some technical details
Solid and simplified timeline with lots of great details
It does exclude a few of the big popular culture events, like Watson on Jeopardy in 2011. To me it’s fascinating because Watson’s architecture was an absolute mess by today’s standards, over 100 different algorithms working in conjunction, mixing tons of techniques together to get a pretty specifically tuned question and answer machine. It took 2880 CPU cores to run, and it could win about 70% of the time at Jeopardy. Compare that to today’s GPT, which while ChatGPT requires way more massive amounts of processing power to run, have an otherwise elegant structure and I can run awfully competent ones on a $400 graphics card. I was actually in a gap year waiting to go to my undergrad to study AI and robotics during the Watson craze, so seeing it and then seeing the 2012 big bang was wild.
Yeah I probably should have added the /s to that one.
My guess was that they knew gaming was niche and were willing to invest less in this headset and more in spreading the widespread idea that “Spatial Computing” is the next paradigm for work.
I VR a decent amount, and I really do like it a lot for watching TV and YouTube, and am toying with using it a bit for work-from-home where the shift in environment is surprisingly helpful.
It’s just limited. Streaming apps aren’t very good, there’s no great source for 3D movies (which are great, when Bigscreen had them anyways), they’re still a bit too hot and heavy for long-term use, the game library isn’t very broad and there haven’t been many killer app games/products that distinct it from other modalities, and it’s going to need a critical amount of adoption to get used in remote meetings.
I really do think it’s huge for given a sense of remote presence, and I’d love to research how VR presence affects remote collaboration, but there are so many factors keeping it tough to buy into.
They did try, though, and I think they’re on the right track. Facial capture for remote presence and hybrid meetings, extending the monitors to give more privacy and flexibility to laptops, strong AR to reduce the need to take the headset off - but they’re first selling the idea, and then maybe there will be a break. I’ll admit the industry is moving much slower than I’d anticipated back in 2012 when I was starting VR research.