At this moment, I agree. Your average person (which doesn't really exist) has already been exposed and trained on ChatGPT. Arguing moving to another "chat" experience has not gone well, for example Bing, etc. Pretty sure Google had the "box" figured out first and won. I think people overthink how much effort people are willing to put into "change". There is nothing wrong with staying put if it works, after all, there is an unlimited number of other things happening in this world besides AI.
Ohh that is a great idea! And since we already have the political field in SQL!. I will start working on some of this and update the website this week. Thank you for the awesome suggestions!
Not the author. Just my thoughts on supplying context during tests like these. When I do tests, I am focused on "out of the box" experiences. I suspect the vast majority of actors (good and bad, junior and senior) will use out of the box more then they will try to affect the outcome based on context engineering. We do expect tweaking prompts to provide better outcomes, but that also requires work (for now). Maybe another way to think is reducing system complexity by starting at the bottom (no configuration) before moving to top (more configuration). We can't even replicate out of the box today much less any level of configuration (randomness is going to random).
Agree it is a good test to try, but there are huge benefits beings able to understand (better recreate) 0-conf tests.
My .02$. Show you can tackle harder problems. That includes knowing which problems matter. That happens with learning a "domain", versus just learning a tool (e.g. web development) in a domain.
Change is scary, but thats because most aren't willing to change. Part of the "scare" is the fear of lost investment (e.g. pick wrong major or career). I can appreciate that, but with a little flexibility, that investment can be repurposed quicker today that in pre-2022 thanks to AI.
AI is just another tool, treat it like a partner not a replacement. That can also include learning a domain. Ask AI how a given process works, its history, regulations, etc. Go confirm what it says. Have it break it down. We now can learn faster than ever before. Trust but verify.
You are using Cursor, that shows a willingness to try new things. Now try to move faster than before, go deeper into the challenges. That is always going to be valued.
Not saying these are perfect, but consider reviewing the work of groups like the Internet Society or even IEEE sectors. Boots on the ground to some extent such as providing gear and training. Other efforts like One Laptop Per Child also leaned into this kind of thinking.
What could it could mean for a "tech" town to be born, especially with what we have today regarding techniques and tools. While the dream has not really bore out yet (especially at a village level), I would argue we could do even better in middle America with this thinking; small college towns. While its a bit of existing gravity well, you could do a focused effort to get a flywheel going (redo mini Bell labs around the USA solving regional problems could be a start).
Yes it takes decades. My only thought on that is, many (dare say most) people don't even have short term plans much less long term plans. It takes visionaries with nerves and will of steel to stay on paths to make things happen.
Pick a university, and given them $1B to never use Windows, MacOS, Android, Linux, or anything other than homebrew?
To kick-start, given them machines with Plan9, ITS, or an OS based on LISP / Smalltalk / similar? Or just microcontrollers? Or replicate 1970-era university computing infrastructure (where everything was homebrew?)
Build out coursework to bootstrap from there? Perhaps scholarships for kids from the developing world?
Can someone share a youtube showing DeepSeek vs others? I glanced through comments and seeing lots of opinions, but no (easy) evidence. I would like to see a level of thoroughness that I could not do myself. Not naysaying one model over another, just good ole fashion elbow grease and scientific method for the layperson. I appreciate the help.
Here [1] is the leaderboard from chabot arena, where users vote on the output of two anonymous models. Deepseek R1 needs more data points- but it already climbed to No 1 with Style control ranking, which is pretty impressive.
Link [2] to the result on more standard LLM benchmarks. They conveniently placed the results on the first page of the paper.
The local chapters in San Francisco of the Internet Society and Association for Computing Machinery are co-hosting AI Day SF. This one day fundraising (tax deductible) strives to provide a wide view of AI from learning how to integrate AI into systems (training) to several presentations across public and private sectors (thought leadership). This in-person event hopes to provide a one stop shop to get caught up on AI of today! We appreciate your support.
I would like to see (better) solutions not only for source code, but general web-pages and applications. For example, bookmarks in a browser are ok, but it would be a lot better if you could easily annotate and later reference / rank / prioritize. A browser is a pretty good proxy to the world's knowledge including source code. It be nice if they would level up in these regards.
There are tools for aspects of all these areas, but still feel unsolved (easy, feature-full).
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