I fire off the ide switch the model and think oh great this is better. I switch to something that worked before and man, this sucks now.
Context switching llm, Model Release Fatigue
I fire off the ide switch the model and think oh great this is better. I switch to something that worked before and man, this sucks now.
Context switching llm, Model Release Fatigue
What we call code, and what we call data, is just a question of convenience. For example, when editing or copying WMF files, it's convenient to think of them as data (mix of raster and vector graphics) - however, at least in the original implementation, what those files were was a list of API calls to Windows GDI module.
Or, more straightforwardly, a file with code for an interpreted language is data when you're writing it, but is code when you feed it to eval(). SQL injections and buffer overruns are a classic examples of what we thought was data being suddenly executed as code. And so on[0].
Most of the time, we roughly agree on the separation of what we treat as "data" and what we treat as "code"; we then end up building systems constrained in a way as to enforce the separation[1]. But it's always the case that this separation is artificial; it's an arbitrary set of constraints that make a system less general-purpose, and it only exists within domain of that system. Go one level of abstraction up, the distinction disappears.
There is no separation of code and data on the wire - everything is a stream of bytes. There isn't one in electronics either - everything is signals going down the wires.
Humans don't have this separation either. And systems designed to mimic human generality - such as LLMs - by their very nature also cannot have it. You can introduce such distinction (or "separate channels", which is the same thing), but that is a constraint that reduces generality.
Even worse, what people really want with LLMs isn't "separation of code vs. data" - what they want is for LLM to be able to divine which part of the input the user would have wanted - retroactively - to be treated as trusted. It's unsolvable in general, and in terms of humans, a solution would require superhuman intelligence.
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[0] - One of these days I'll compile a list of go-to examples, so I don't have to think of them each time I write a comment like this. One example I still need to pick will be one that shows how "data" gradually becomes "code" with no obvious switch-over point. I'm sure everyone here can think of some.
[1] - The field of "langsec" can be described as a systematized approach of designing in a code/data separation, in a way that prevents accidental or malicious misinterpretation of one as the other.
But everyone needs to have an MCP server now. So Supabase implements one, without that proper authorization layer which knows the business logic, and voila. It's exposed.
Code _is_ the security layer that sits between database and different systems.
But it doesn't have support Helm charts.
Cloud computing architecture > Delivery links to SaaS, DaaS, DaaS, PaaS, IaaS: https://en.wikipedia.org/wiki/Cloud_computing_architecture
Cloud-computing comparison: https://en.wikipedia.org/wiki/Cloud-computing_comparison
Category:Cloud_platforms: https://en.wikipedia.org/wiki/Category:Cloud_platforms
awesome-selfhosted has a serverless / FaaS category that just links to awesome-sysadmin > PaaS: https://github.com/awesome-selfhosted/awesome-selfhosted#sof...
This is a more featureful version.
Also, why would Waymo, in the long term, use Uber for this?
They have the car, the driver, the app/software. They are not gonna share a big chunk of the profit with Uber in long term. The current partnership is probably just a tactical thing for both, not a strategic one.
I use Waymo's all the time. There are still some quirks they need to figure out and polish the experience, but it really is happening and it appears that Uber's head is in the sands or I'm missing something here.
They do, however, have a major lead in terms of consumer adoption. To normal people who use llm's, ChatGPT is _the_ model.
This gives them a lot of opportunities. I don't know what's taking them so long to launch their own _real_ app store, but that's the game they are ahead of everyone else because of the consumer adoption.