Yes, I do think people posting their “artwork” in ai subs are dumb. And I use AI all day where it excels at solving business problems, pattern recognition and outlier detection. But using gen AI to mask lack of creativity or talent is a scourge on humanity.
And subbed.
Personally, if I see AI content I block the user that posted it. If a community is all about AI, I block the community. I want to see content from people that have actual talent or something intelligent to contribute.
Also, managers generally don’t like their people going to HR about things without already knowing the situation ahead of time.
Yep. This part. Even if you convince HR, your manager will be able to come over the top and say no. And if they feel like you are an HR risk, that’s exactly what will happen.
Yep. “What’s the most interesting project you’ve been a part of” is my favorite. Same vane, opened the door to so many follow ups.
So often it’s “how do you translate temporal data for a random forest model” and then see run headlights as I have to explain the word temporal and then how feature selection for machine learning actually works.
They are literally only taught the Python code now, with no explanation of why, how, or when certain tools are appropriate. Real “Bang on a nail with a screwdriver long enough” level education.
As an employer who hires folks in the data science field, I’ve become more disappointed in recent college graduate job-readiness every year for the last decade. At this point I’d prefer a resume to say “watched 100 hours of YouTube videos about data science” over a masters in the field.
And these poor people have 100k in student loan debt with no marketable job skills and are competing against 10s of thousands of other recent grads with no marketable job skills and college has created a lose-lose environment.
No wonder enrollment is dropping, the cost of the education is absolutely not worth it and people are starting to see it.
You can never have too many clamps, screwdrivers, or tape measures.
Ryobi cordless tools are great consumer level battery powered tools. They aren’t as high of quality as Milwaukee or DeWalt, but for the average homeowner, they are more than good enough. That said, I do prefer my DeWalt drill and impact because they are more compact, but for all the rest, Ryobi is fine.
Also a good tool box and tool bag. Having a place for everything makes finding and using your tools so much easier, and having the bag to fill with tools for whatever job you’re tackling has proven to be a game changer.
Sure, self-hosting is a great option for very large projects, but a random python library to help with an analytics workflow isn’t going to self-host. Those projects, along with 27,999,990 others have chosen GitHub, often times explicitly to reduce the barrier to contribution.
Also, all of those examples are built on thousands of other FOSS projects, 99% of which aren’t self-hosting. This is the same as arguing only Amazon is a bookseller and ignoring the thousands of independent book publishers creating the books Amazon is selling.
GitHub has 28 million public repos
Gitlab is has less than an order of magnitude as many Under a million in 2020, and nearly 80% without FOSS license.
Is it everyone’s favorite, or best, or most feature rich. Nah. Is it where the FOSS projects are. Yes.
This is what republicans have always done well. They organize locally, take over school boards and city councils, drive the change they want to see in local communities and drive support locally to drive voter turn out nationally.
We don’t see democrats crashing school board and city council meetings, participating in local politics en mass to drive local change with near the same effectiveness as republicans, and it leads to underwhelming participation in national elections, as the left sits around wondering “what has the DNC done for me”.
Lots of boring applications that are beneficial in focused use cases.
Computer vision is great for optical character recognition, think scanning documents to digitize them, depositing checks from your phone, etc. Also some good computer vision use cases for scanning plants to see what they are, facial recognition for labeling the photos in your phone etc…
Also some decent opportunities in medical research with protein analysis for development of medicine, and (again) computer vision to detect cancerous cells, read X-rays and MRIs.
Today all the hype is about generative AI with content creation which is enabled with Transformer technology, but it’s basically just version 2 (or maybe more) of Recurrent Neural Networks, or RNNs. Back in 2015 I remember this essay, The Unreasonable Effectiveness of RNNs being just as novel and exciting as ChatGPT.
We’re still burdened with this comment from the first paragraph, though.
Within a few dozen minutes of training my first baby model (with rather arbitrarily-chosen hyperparameters) started to generate very nice looking descriptions of images that were on the edge of making sense.
This will likely be a very difficult chasm to cross, because there is a lot more to human knowledge than thinking of the next letter in a word or the next word in a sentence. We have knowledge domains where, as an individual we may be brilliant, and others where we may be ignorant. Generative AI is trying to become a genius in all areas at once, and finds itself borrowing “knowledge” from Shakespearean literature to answer questions about modern philosophy because the order of the words in the sentences is roughly similar given a noun it used 200 words ago.
Enter Tiny Language Models. Using the technology from large language models, but hyper focused to write children’s stories appears to have progress with specialization, and could allow generative AI to stay focused and stop sounding incoherent when the details matter.
This is relatively full circle in my opinion, RNNs were designed to solve one problem well, then they unexpectedly generalized well, and the hunt was on for the premier generalized model. That hunt advanced the technology by enormous amounts, and now that technology is being used in Tiny Models, which is again looking to solve specific use cases extraordinarily well.
Still very TBD to see what use cases can be identified that add value, but recent advancements to seem ripe to transition gen AI from a novelty to something truly game changing.
As I’ve heard this explained, enterprise admins have scripts, and to a less important extent muscle memory, tied to Control Panel layout and command lines, and that’s not a group you want to irritate.
The study forbes referenced appears to be essentially “how to design offices for gen z”, presuming they really want to use an office.
The tips to drive virtual engagement are pretty standard management material at this point.
Would have liked to see some real evidence to “boomerang” being philosophical, that felt like a cheap misuse of the term to seem more relevant than “what kind of games should be in the break room”
For those not in North Texas, the three school districts listed are all neighboring districts 15 miles or so north of Fort Worth. They are all high income, predominantly white areas doing everything they can to keep it that way.
Racism in Southlake Highschool unified the city against diversity, with some of the earliest school board meeting takeovers to protect white people saying the N word way back in 2021.
Keller ISD is going big on the book banning, but to deflec, the superintendent was certain to point out it’s not the district, but the parents banning the books. And the board of trustees voted 5-0 to prohibit pronouns in school despite listening to parents in favor of use of pronouns.
Oh and Colleyville, you bastion of religious and racial and gay rights acceptance.
We also have a chronic disposition toward optimism. You know “the American dream” and all that.
So a disease with a 10% mortality rate has a 90% survival rate. And 90% is bigger than 50%, so when you factor in chronic optimism it’s basically a 100% survival rate in our brains.