Lack of versioning in workspaces. Multiple times I've been "vibe coding" my way happily through adding feature after feature until ... the chatbot goes off the rails and breaks stuff. No amount of additional prompting will fix the issue no matter how many time Claude/CoPilot says "I see the problem. Let me fix that..." and it only gets worse.
Claude provides a * SINGLE STEP * of undo. Gee, thanks.
So, now I'm forced to snapshot code myself. I just wish that was built in.
The death of entry-level math and CS jobs is greatly exaggerated, I believe.
First, costs and ROI of AI are on a collision course and companies are finding they can't simply lay off smart people and replace them with "vibe-working" employees. Secondly, not only will more junior workers adapt to new hybrid human/AI workflows better than more senior workers, they're likelier to apply them to parts of the job that are low-value, routine. Third, the next frontier for agents and models is within very narrow domains where more junior AI-savvy workers are in a great position to collect, capture and refine the data models from subject matter experts. Who better to ask "What about X ...?" and "How do you know Y...?" from experts?
1. AI/ML is not an oracle. It is neither wise nor omniscient. Never rely on AI for advice (I tell them the pizza glue story). Never rely on AI for opinion (because if you ask for a different opinion it will deliver it, happily).
2. AI/ML is not a source. It can helpfully summarize things and tell you things that may be true but then you need to seek out the sources both to smoke out the errors and hallucinations but also to be exposed to gritty details that get sandpapered away by the "smoothing" of the ML models. AI output tends to be like those posts that show the average face for every country. The resulting faces are interesting and pleasant but should never be confused with real people.
3. Generative AI (text, images, videos, code) is an amazing and fun way to turn an idea into something concrete. But ... beware the pitfalls. A) Beware the delight of novelty. Even if the image/text is kind of coherent and novel, scrutinize the details. Did the result express your original intent?
B) Sweat the details. If the result doesn't show/say 100% of what you wanted then it isn't 100% yours. If you stopped there, you would be letting the AI/ML dictate the limits and "flavor" of your creation. It would be better to use the generated output as inspiration or a guide to what you ultimately create.
I like your argument, not because it is a good analogy for AI but because it is a good contrast. Copyright isn't a guarantee or magic force field blocking fair competition. It is a permeable buffer against lazy knockoffs and time-boxed so that buffer doesn't choke all future creativity.
People on this thread need to focus on what "derivative" and "fair use" mean and understand both are measured on a somewhat fuzzy spectrum, subject to interpretation.
In a perfectly fair world AIs/MLs could vacuum up all human knowledge, fair and square. (In an ideal world, they would do that adhering to polite opt-in/opt-out agreements with copyright holders. We can dream). Input isn't theft.
On output, two magic genies would stand at the gate, the Derivative Genie and Fair Use Genie and review anything spat out by the AI/ML. If it crossed agreed upon thresholds the Genies would bar the gates and issue a stern warning to prompt again (or maybe the AL/ML would auto-adjust the prompt and try again).
So, if your prompt asked for a 300-word poem about thrash metal mosh pit dancing and it spat out a poem where 85% of it match one of the handful of available mosh pit poems in its database, the Derivative Demon would block the output and raise an alarm.
On the other hand, if you asked for a line by line analysis of a famous mosh pit dancing poem (by name) or maybe asked for a satirical spoof of said poem, the Fair Use Demon would overrule the Derivative Demon and give the output a pass.
That's as fair as this could get, especially if you add one more thing: An Appeals Court (maybe corporate, maybe 3rd party, maybe state run) with a Settlement Pool. If a copyright holder could prove the Genies let pass something they shouldn't, the AL/ML would fix that. If real damage is done, the creator would get a settlement from the pool.
The point is that the Input Genie is out of the bottle. Creators just look foolish trying to squeeze it back in. Better, they should focus on making the output Genies and the Appeals process as effective and fair as possible for everyone.
Does he WANT worldwide eternal Jihad against the US/West?
If there's a better use for "Some people just want to watch the world burn" in the history of the world, I can't think of one. He's always been a toddler brain clueless to consequences and, in this case, he likes the idea that HE would get to be the Big Boy to push the Big Red Button. Fun toy.
- I'd like to see this as a hosted app versus something that has to be "installed" in a chatbot.
- It needs a text search feature for both the outline and full text. That would allow searching for text containing "government", highlight instances and seeing their context. And same for searching the outline for "government" and seeing supporting text.
This could be an equally useful paradigm for fiction and for source code. For fiction, it would be really useful if this could be trained to identify character introductions and locations and their mentions. Imagine how convenient it would be for the outline to mention a plot point about "Mary Sullivan" where the paragraph in chapter 22 only says "his mother" when talking about "John Sullivan."
At minimum, you have to provide a snapshot/example of what you're building.
I'm most intrigued by your comment pile digestor. I've often wanted something like that while cruising the Internet but I'm not sure how'd you monetize it. In the commercial world, software for analyzing customer-submitted questions and comments has been a valuable service for a long time, even before AI/ML engines came along. So, that's useful but it's a hard problem, very domain-specific.
Anyway, as others have said the main things you have to do to attract interest/business are: 1) Explain specifically what pain you are solving for what specific user/customer, 2) Offer specifics (examples, features) of how you solve that pain better than anyone else.
I agree with you this would be valuable, mostly for persuading the general public.
The skepticism you're getting amounts to "biased people/government won't care no matter what" and "fancy tech makes the evidence look more doctored, not less." They're not wrong but there are some disputes this could settle. Some people have argued that the moment where an ICE agent appears to withdraw Pretti's gun might just be him retrieving his own fumbled gun. Maybe a synthesized view could clear that up.
Personally, I think it will come down to the moment where one goon said "He's got a gun" and another one took that as license to shoot him three times. The other 6 or so gunshots were a kneejerk pile-on to that cowardly act.
So much for the 2nd Amendment, right?
Right, the analogy would be "What does being a builder mean if carpenters are swinging the hammers?" We'll have to be software "Foremen" who develop plans and know enough algorithms, data structures and architecture to tell the AI how to frame the house and what kind of pipe to lay even if we're not doing that ourselves.
I'm intrigued and might need something like this but...
Your splash page doesn't give much of an idea of what this app does (far less than what you said in the comment above).
IMO, I shouldn't have to create an account to see what an app has to offer. A few screenshots and a feature list might help me decide if creating an account is worth the trouble.
In general, how is this better than a spreadsheet of contacts or the contacts app on my phone?
Your only operative complaint is "confused." What are you confused about? The high-level goals and requirements? Your own approach and criteria for success? Structuring your time/effort?
Without knowing what you are asking exactly, there are a ton of ways to structure a large project.
One of my favorites is: Pick some challenging (but not too challenging) use-case that intersects an interesting subset of the core requirements. Decide on ONE design principle you want to follow (highly testable, clear separation of concerns, pluggable sources/endpoints, whatever) and then build the crappiest/minimal version that does those two things (handles the main use-case and strictly adheres to your design principle) while being totally crappy in every other way (i.e. bad UI, brute-force algorithms, whatever).
As you design/build this "slice"/MVP of functionality, keep notes about out-of-scope parts you can't/won't touch according to the rules above. Those will become seeds for the rest later.
This method yields a lot of advantages: 1) It provides a way to get started without analysis-paralysis, 2) it results in proof-of-concept, perhaps a demo for what you are going to eventually build, 2) You think through a lot but don't build so much or get lost in details you won't build, 3) If you hate the MVP, you can throw it away and build it again the right way (which will be better, as a result).
For a really big project, just iterate on the above by picking more slices/use-cases. You might have to refactor/redesign as you go but pretty quickly you'll have built up enough scaffolding that the rest of the project will flow easily or be delegated easily.
The rule that stops this cold for me is:
"Note that the distinct numbers being sorted would be hidden. That is, all the nodes in the partial order would look the same."
So, you point to two random nodes and watch them sort? Do you see the "hidden" numbers after they are sorted?
As is, that sounds boring and "random" in the way my sons use that term, without purpose or reason.
If you had more in mind, please describe exactly what the player sees before and after they select two nodes.
This could also be a way for social discovery that studios could promote:
Imagine a rack of album cards at Target where each costs a $1 and lets you play samples of all the tracks on the album (read lyrics and liner notes, etc) and puts $1 in your online wallet. So, kids (or anyone) could sample different albums and then save up to buy whole albums they like. Also, already redeemed ("used") cards would still play samples so kids could share/trade them as a way to say "check this music out!"
Can you imagine Billboard charts of Top Album Cards (Sampled and Bought) which would be so much more impactful than a lame count of streams or whatever. The charts would represent music kids are actually trading and talking about.
Even if your observations/findings are brilliant, you can't be taken seriously unless you're published in an academic journal and you can't do that "cold."
Basically, the prerequisites are: 1) You have to speak the language and 2) You have to know some people.
#1 Know the Language - Let's say you believe you have a new mathematical proof. Even if it was perfectly valid, you'd get instantly rejected for publishing if it wasn't formatted correctly, used accepted language and definitions of things, was sufficiently rigorous and referenced relevant prior work.
That's tough for an amateur to pull off by themselves. So, one solution is to take your best attempt at a rigorous amateur proof to a mathematician at a local college or university. Even a curious grad student in the field who is willing to indulge you can help clean up the work.
As a bonus, that can help with problem #2 - knowing some people. If your proof, now translated to proper mathematician-speak, holds water maybe you can leverage your proof-reader to "level-up" and get your proof seen by an actual professor in the field who can lend you some credibility and get you introduced to other mathematicians.
Even then, your chances of getting published are near zero. However, the recent example of two high-school students who came up with a novel proof of the Pythagorean theorem shows how it can be done. They first were able to present a "poster" of their proof at a conference where it was seen by mathematicians and where they could be quizzed about it on the spot. Surviving that gauntlet PLUS the exposure allowed them to catch the eye of a publisher willing to take a chance on them.
Claude provides a * SINGLE STEP * of undo. Gee, thanks.
So, now I'm forced to snapshot code myself. I just wish that was built in.