Readit NewsIf no one is marketing a product, then nobody knows about it.
I can answer any questions people have about the experience (within code of conduct guidelines so I don't get in trouble...)
I've been curious how much these AI models look for more niche coding language expertise, and what other knowledge frontiers they're focusing on (like law, medical, finance, etc.)
- Organize notes in org-mode is much quicker - The best support for lists (and I do list most of the times) - Tags and properties - Perfect integration with agenda - Great TODOs support - Code blocks with highlights, execution and results
It has some Obsidian-like features inside Org Mode.
So, if you're looking for an easier-to-use UI, it's not it, but if you're looking for Obsidian-like linking and backlinking, it has that.
1. Agent can create its own tools and save them to memory
2. You create a SQL (and web app?) workbench per agent run
3. Grok fell off a cliff in the last month. Was this consistent over multiple runs?
4. Agents have a difficult time backtracking. Would unwinding system state and agent context make backtracking better? (Harder to implement this, though)
5. Since each new month only uses final state from previous month, agent has no way to understand why error occurred in previous month
We're all pretty cross-stack - there are some hardware people and some software people, but the product is quite integrated. Personally, my time has been mostly focused on the RL stack recently, and after there are more robots in the wild, I suspect my time will transition to working on building this data feedback loop.
I try to answer questions pretty actively on our Discord so happy to chat there about whatever you like
I'm super interested in learning more about the training process of world and robotics model and the data challenges there.
Is anybody tracking the IP ranges of bots or anything similar that's reliable?
It seems like they're taking the "what are you gonna do about it" approach to this.
Edit: Yes [1]
[1] https://github.com/FabrizioCafolla/openai-crawlers-ip-ranges
Unfortunately, no mainstream OS actually implements the capability model, despite some prominent research attempts [2], some half-hearted attempts at commercializing the concept that have largely failed in the marketplace [3], and some attempts to bolt capability-based security on top of other OSes that have also largely failed in the marketplace [4]. So the closest thing to capability-based security that is actually widely available in the computing world is a virtual machine, where you place only the tools that provide the specific capabilities you want to offer in the VM. This is quite imperfect - many of these tools are a lot more general than true capabilities should be - but again, modern software is not built on the principle of least privilege because software that is tends to fail in the marketplace.
[1] https://en.wikipedia.org/wiki/Capability-based_security
[2] https://en.wikipedia.org/wiki/EROS_(microkernel)
[3] https://fuchsia.dev/
[4] https://sandstorm.io/
And totally agree that instead of reinventing the wheel here, we should just lift from how operating systems work, for two reasons:
1. there's a bunch of work and proven systems there already
2. it uses tools that exist in training data, instead of net new tools