I'm surprised there's not more discussion about potential inflection points here. When technology gets faster, it opens up whole new classes of UX that were hard to predict
For example, faster internet didn't mean being able to view 100x as many HTML4 web pages. It brought SaaS, streaming media and interactivity.
I'm not good at predicting, but some ideas:
1. All information gets augmented in real time with personalised context.
2. AI interaction seems more like find-as-you-type than a back and forth.
3. AI produces many outputs to pick from. Either the human, AI, or another system can do the deciding.
Even if it's last year's model, speeding up LLM inference could open up all sorts of opportunities.
4. Pervasive , distributed dragnet surveillance under the misrepresentation that it's not a search until a human pulls the data. But a small on-device "E2E preserving" "safety" model that runs on your phone and snitches when illegal communication content is suspected.
Edit: also consider centralized Room-641A-type surveillance when models summarize and/or flag all calls processed by public telephony
Right, instead of just having more LLM conversations as they get faster and cheaper we'll find products having AI that never had it before.
How about an actually smart thermostat that checks the weather and possibly makes decisions more like a human would i.e. tool calling, judgement, preference, history, personal plans.
Sure we have thermostats and you can configure rules and data sources, hook up Google calendar, etc but it has to be all predetermined and breaks as soon as anything stops working. AI could make this less brittle. AI agents are more flexible.
I think the most important direction will be: you spawn hundreds of agents at the same time, and let them work in a breadth-first search style. So you will not necessarily get your answers much faster, but they will be much more thoroughly researched. And if you do want faster responses, you can do that at the expense of quality.
Yes, this is a great point and it’s even one that the Cerebras CEO spruiks for his own chips. Talaas has gone furthest on the spectrum here, so seems to have the most potential to evolve the use cases.
Wardley's original post on this [0] is worth a read. OP adds cowboys and city folk, and makes it a bit more personal.
5 interesting things that are worth making explicit:
1. These teams/roles are as much about appetite and attitude, as they are about someone's skills and capabilities. Some people just aren't comfortable or happy when operating in these environments.
2. Innovation isn't just at the early "0 to 1" stages. Townspeople need to innovate to scale from a million users to a billion.
3. Successful orgs have teams at all stages, working together. Each team evolves what the previous stage built. And cowboys / pioneers are only successful if they can build on industrialised components.
5. As a product evolves, it moves through the stages. Teams either need to let go, or change their way of working.
In other words, gradient descent isn't good at combinatorial optimisation. I'm sure the research is better but the hype in the blog post leaves a bad taste.
There must be a version of Rich Sutton’s Bitter Lesson that applies to alternative computing like this, along with all the other exciting specialised hardware we've seen come and go over the years, like expert systems, optical computing, neuromorphic computing, etc.
Something like:
General purpose commodity silicon with rapidly evolving software generally beats specialised hardware.
Software is just so much faster to iterate and improve than hardware. AI is also improving it too (eg AlphaEvolve).
Specialized hardware may give a single, significant improvement that grabs headlines but in the long term, compounding small improvements win.
> General purpose commodity silicon with rapidly evolving software generally beats specialised hardware.
All of the Amiga people are sighing right now, as they recall how their beautiful, elegant system synergistically designed with custom chips was outpaced by CPU/memory brute force in the early 90s.
Likewise, the lesson Seymour Cray had to learn a couple of times because it didn't quite sink in the first time: "Never go up against CMOS when your company is on the line."
It requires O(N^4) evaluations to compute Fisher Information Matrix for N-dimensional parameterization of the problem in original formulation. But there are closed form solutions and more economical representations of covariance matrix (LoRA, hehe).
I don't think they are even referring to gradient descent here. I think they are referring to systems like AlphaEvolve where they use LLMs to give an informed/heuristical guess to try to tackle an otherwise insurmountable search space.
In hardware Prolog/Kanren/expert systems? That would be possible with libre microcode for Intel, and not this spyware corporate shithole we are living it.
We would be able to switch microcode at boot and set one for security, another one for C performance, others for Lisp performance and so on.
isn't it still an odd choice for a nonprofit? it's hard to imagine a world without OpenAI and ChatGPT now, but at some point they decided being the best is most important. and presumably most profitable, since why just need a little more money?
Maybe, but somehow I doubt the American Heart Association is planning to open a chain of pork barbecue restaurants to support its mission against heart disease.
It looks a lot like a CvRDT (i.e. a state-based CRDT).
They describe it as a commutative monoid, which means it has associativity and commutativity. CvRDTs also need idempotence, so they can handle duplicate data. Either they are idempotent too (which would make it semilattice-like), or the network protocol handles the deduplication outside of the data itself.
Letting the payload/application define the merge operation is clever. I assume it would mean contracts could opt in to idempotency if it doesn't already exist.
The other bit Freenet has added is doing all this with DHT routing and subscriptions, rather than a more basic peer mesh. This is very different to a blockchain and means it probably isn't suited for anything transactional.
> CvRDTs also need idempotence, so they can handle duplicate data. Either they are idempotent too (which would make it semilattice-like), or the network protocol handles the deduplication outside of the data itself.
Freenet's summary/delta synchronization mechanism implicitly disregards duplicate updates. The idea is that a peer A creates a "summary" of a contract's state which is sent to the other peer B which then creates a "delta", which contains anything in B's state that isn't in A's state. The delta is then sent from B to A bringing A's state up-to-date. Thus the contract defines a custom synchronization mechanism for its state which can be very efficient.
These summaries and deltas are just arbitrary bytes as far as the framework is concerned, their meaning is entirely up to the contract.
> The other bit Freenet has added is doing all this with DHT routing and subscriptions, rather than a more basic peer mesh. This is very different to a blockchain and means it probably isn't suited for anything transactional.
That's correct, Freenet doesn't guarantee a global consensus although in practice contract states will converge within a few seconds. This is good enough for applications like group chat and social networks but for a cryptocurrency you still need to solve the double-spend and global ordering problems.
> Heck, there's others who were wealthy in scripture, even kings are they all doomed?
This is a great question. In the next verses, the disciples ask pretty much the same thing: "Who then can be saved?" and then Jesus explains to them:
With men this is impossible, but with God all things are possible.
Whether it's a camel or a rope (and whether it's a literal needle or a small city gate, as some people argue), I think is less important (though still interesting). Either way, after the rich young ruler walks away, Jesus turns to his disciples and paints a picture something that's completely impossible without God, no matter how hard we might try by ourselves.
Genesis is a theological narrative, which is very different to most things we read these days, especially as a software engineer.
1. The general consensus is that there were more people. This is assumed in Genesis and it (annoyingly!) doesn't bother to explain it, as the audience at the time already assumed it. Also, the authors weren't interested in all the logistics and technicalities that we are today.
2. Cities referenced in Genesis were likely fortified settlements, rather than like modern cities.
The idea that people in Africa could only build simple huts is a myth that came from the colonial era. Africa had large cities, architecture and metallurgy while parts of Europe were still tribal.
If you're keen to learn more, there are some good books that explain this much better than a comment can, such as "How to Read the Bible for All Its Worth" by Fee & Stuart and "Genesis for Normal People" by Pete Enns. I haven't read it but "African Civilizations" by Graham Connah is probably the go-to book on how African cities and technologies were so much further ahead than traditional European/US narratives place them.
The best resource for these kinds of questions is probably "The Bible Project". They have a load of YouTube videos and podcasts that cover these kinds of questions.
thanks.
if there were more people, then how can we all get the sin from adam and eve:
The biblical data consistently understands Adam and Eve to have been real individual human beings from whom all humanity’s descent may be traced. This representation begins as early as Genesis 4, where Adam and Eve have sexual relations and produce children, one of whom kills another. In Genesis 5, there is a lengthy genealogy of Adam’s descendants, whose offspring eventually form all the nations of the world listed in Genesis 10. The contents of these stories are reproduced in similar genealogies in the books of Chronicles and Luke, which trace Adam’s descendants down to those who returned from the exile (1 Chronicles 1–9) and to Jesus Christ (Luke 3:23–38).
From the docs, `add-skill` auto detects from 16 different potential paths to copy skills to in a repository (.claude/, .codex/, .Gemini/, etc).
`add-skill` also let's you install skills globally (~/). From the code, `skills` looks like it doesn't support global installs but under the hood it passes all args to add-skill, so you should be able to install skills globally or install multiple skills (even if the wrapper doesn't expect it).
Aside: although lots of agents have adopted SKILLS.md conventions, they're currently all using their own paths. There doesn't seem to be a consensus yet, like there is with AGENTS.md. There are even 3 generic paths: .agent/skills/, .agents/skills/ and just skills/
The best thing I can come up with right now for multi-agent installation is symlinks.¹ This tool doesn’t seem to even try to solve the updating or versioning requirements.
Although it's not clear how to upgrade them (I doubt there is any version management built-in), the installer does specify where it will be installed (And lets you choose global/project level.
What's interesting is that it doesn't seem to meet the normal requirements of an urgent action.
Previous alerts, for context: https://www.gov.uk/alerts/past-alerts
Does anyone know where this came from and what the procedure is for sending? Presumably Cabinet Office / COBR, or NFCC.