mikmoila
mikmoila on Hacker News
Yes "at any substancial level" . But still, its all about deterministic processes and still it obeys the law that the same input gives the same output. Or do you mean that the fluctuations like computing environment might ruin the determinism?
I think you're referring to the fact that the sheer amount of computations is something too time consuming for us to follow? But still it is not "magical" - in theory we could follow all the steps, there's no hidden information.
"you could never have accomplished"; I am not able to follow the logic here - there is no "magic" in LLMs, they're built by humans and we know what they do.
Humans built the tool which enabled the result. AI used the tooling for eliminating the dead ends. Yes, I can appreciate the practical value of all this, but IMHO it is not a kind of breakthrough result the article gives impression of.
"The effort succeeded when we switched to using Prove2Me, an open collaborative platform for formalizing mathematics designed by Tianyi Peng and his collaborators at Columbia University."
So in the end, it required tooling crafted by humans.
https://openjdk.org/legal/aiShitposting, the reasons are very clear and explicit: The risks of having legal problems are very clear.
Google for example GEMA vs. OpenAI.
Posted by
mikmoila on Monday July 27, 2026 @03:47PM
from the jameskoppel.com dept.
Code contains deviations from assumed behaviour, and some behaviours might manifest themselves as failures. Some failures might be exploitable by attackers.
Yes, imagine a breakthrough moneymaker product containing generative AI parts; It'll be under legal attacks from day zero...
OpenJDK project (interim) AI-policy faq (
https://openjdk.org/legal/ai):
"What are the intellectual-property risks of using generative AI tools?
The Oracle Contributor Agreement (OCA) requires that a contributor own the intellectual property rights in each contribution and be able to grant those rights to Oracle, without restriction. Most generative AI tools, however, are trained on copyrighted and licensed content, and their output can include content that infringes those copyrights and licenses, so contributing such content would violate the OCA. Whether a user of a generative AI tool has IP rights in content generated by the tool is the subject of active litigation."
How about intellectual-property risks?
I don't I use Java for small scripts/tools.
Are they really? I've been under impression that agentic LLMs are just instances of the LLMs, no "specialized training" involved
Very interesting tool; I've done something quite similar by implementing a CLI-mode interpreter to VS Code Rest-client (
https://marketplace.visualstudio.com/items?itemName=humao.re...) files, with a support of executing a test-code (Javascript) against the result of http operations.
The idea was to have a tool which could run .http files in batch mode, and also to execute the selected set of http operations concurrently.
There is nothing special in getters and setters, the runtime sees them as methods and may optimize them as it'd do for any other methods.
Posted by
mikmoila on Tuesday March 05, 2024 @05:13PM
from the openjdk.org dept.
Good point, isn't this the partial compilation?
Posted by
mikmoila on Tuesday September 12, 2023 @02:55PM
from the github.com dept.
Also there are some traceability issues involved in using asynchronous APIs: "In the asynchronous style, each stage of a request might execute on a different thread, and every thread runs stages belonging to different requests in an interleaved fashion. This has deep implications for understanding program behavior: Stack traces provide no usable context, debuggers cannot step through request-handling logic, and profilers cannot associate an operation's cost with its caller. "
https://openjdk.org/jeps/444
In addition, this implementation detail might help in gaining some insight: "The synchronous networking Java APIs, when run in a virtual thread, switch the underlying native socket into non-blocking mode. When an I/O operation invoked from Java code does not complete immediately (the native socket returns EAGAIN - “not ready” / “would block”), the underlying native socket is registered with a JVM-wide event notification mechanism (a Poller), and the virtual thread is parked. When the underlying I/O operation is ready (an event arrives at the Poller), the virtual thread is unparked and the underlying socket operation is retried."
https://inside.java/2021/05/10/networking-io-with-virtual-th...
Nima uses virtual threads where blocking call blocks only the current virtual thread but not the underlying carrier-thread, which can run another virtual thread while waiting i/o to complete.
One at a time, not concurrently.
"callRemote" simulates a blocking outbound http-call.
Right to the spot, thanks for sharing this! I've always thought that having a decision log of justifying design/implementation choices which are somehow surprising would be healthy thing to do.
Fascinating info, thanks for sharing this with all the details! Didn't watch your youtube video but do you use any formal systems like TLA+ internally for validating your designs?