I'm no academic, but I have read that harnesses dictate the output more than the models themselves. I'm not educated enough on the topic so I will defer to those smarter than me to chime in.
100%, r/science 15 years ago was very strict on keeping the conversation serious and no low effort posts or jokes. That subreddit is now littered with stupid comments, jokes, and you have to dig to find serious commentary. Reddit is dying and I love it.
The capabilities of local LLM text-to-image is honestly pretty damn impressive. IMO, I think local image generation is currently ahead of local code generation. I can get an image in seconds locally with the quality being way higher than what I'd expect from a local model. However with coding it's much slower and much less impressive. I'm sure there's a reason for this and I'm not an AI expert so I'll let the smarter folks tell me why, but that's just been my observation thus far.
I think there's a lot of setup and context required for an AI agent to consistently write good code. Once the agent has these guard rails in place I usually get great quality- far better than what I would write in most cases.
I think where things get dicey is being able to write in any language. I write and review code in many languages and frameworks I'm not fluent in, so it's hard for me to distinguish between working code and great code. I can spot when the fundamental logic is wrong, but when it comes to "best fit" choices I'm clueless.
It's worrying to say the least. Today it's "get this working", tomorrow it's "can it also do XYZ?", next week it's "we have a 40% spike in crashes, you MUST resolve this IMMEDIATELY!"
Meanwhile the devs are furiously asking AI how to fix it, every flavor of every model will give you a different diagnosis, GH Copilot will throw a million high/critical at you, and you still have no idea if it's fixed or not.
It's the exact reason why you still need to know the languages you're using despite what leadership/product teams demand.
I still have serious questions about the validity of the ChatGpt hugging face debacle. How is it that OpenAI being the tech giant they are, didn't have a completely air gapped environment for this to run in?
Agreed. Skills are hardly transferrable unless you are just focusing on globally applicable things like syntax, structure, etc. The most useful skills are things that are not well known and project/ organization specific. The "tribal knowledge" aspect of coding.
Excellent advice. A compromised phone number is an absolute nightmare, most MFAs default to SMS as a last resort. I lost my Okta verify login at work since I transferred phones, thought I'd need a ticket with our ID team but turns out my phone number is sufficient. Wasn't thrilled about that.
So an online identity verification service had millions of IDs exfiltrated, many of which were linked to marijuana dispensaries? Oh man, my ID is definitely out there, shit.
Been reading "Sapiens: A Brief History of Humankind", this piece is mentioned as the earliest proof of the Cognitive Revolution that we know of. It displays how humans were able to envisions things that do not exist, crafting fiction from reality. How early man was able to share stories and how religions probably came to be.
Despite the stigma surrounding semaglutide, its impact across various health conditions has been remarkable. Bringing that same level of innovation to cognitive disorders could be truly transformative for society
Exactly. Forget the AI aspect, this is entirely to identify users for any purposes they deem necessary. People are ignoring the surveillance state aspect of this. Reminds me of the device id debacle they have attached to their outbounds Windows network calls
Making life easier for yourself and your team is a big one for me, so I totally agree with you. Some times people don't complain about things they should be complaining about, because they don't know they can change them. I find that most big ticket items that unblock devs aren't code related but organizational which can in effect turn to coding issues.
Makes sense given the ubiquity of agentic coding. I made a joke to my coworker today that all we do is make sure AI agents can communicate with other AI agents.
I assume it's because Go is so opinionated? I experimented with it and found it almost boring to write, but I strangely loved it. Now in the AI era I crave the forced uniformity.