arkmm

6 ms·

31.
by arkmm 1y ago
How are you guys reaching users with such a technical value proposition? Cold emailing engineers first and then expanding the conversation from there?
32.
by arkmm 1y ago
This is a really great explanation.
33.
by arkmm 1y ago
IMO if you think you can sell to users within the niche, you can publish a blog post of benchmarks and that'll serve as strong technical marketing for your niche. It also keeps open the option to sell to an incumbent (possibly helps ma
34.
by arkmm 1y ago
Missing the California high-speed rail on their list of examples.
35.
by arkmm 1y ago
When do you think fine tuning is worth it over prompt engineering a base model? I imagine with the finetunes you have to worry about self-hosting, model utilization, and then also retraining the model as new base models come out. I'm c
36.
by arkmm 1y ago
Automating applying to jobs makes sense to me, but what sorts of things were you hoping to use Operator on Amazon for?
37.
by arkmm 1y ago
A bit of a minor detail, but this piqued my interest "DOM-aware browser integration" - could you say a little more?
38.
by arkmm 1y ago
Not affiliated, but someone's already working on that for you: https://www.realavatar.ai/
39.
by arkmm 1y ago
This is cool! Also have found the Playwright MCP implementation to be overkill and think of it more as a reference to an opinionated subset of the Playwright API. LinkedIn has this reputation of being notorious about making it hard to build
40.
by arkmm 1y ago
This is an interesting take, thanks for sharing. I wonder how someone should adjust their blogging if they believe their primary audience will be LLMs.
41.
by arkmm 1y ago
What are some examples where you've provided the LLM enough context that it ought to figure out the problem but it's still failing?
42.
Tesla FSD (Supervised) in Manhattan [video](youtube.com)
9 points by arkmm 1y ago|0 comments
43.
by arkmm 1y ago
Did you try recalibrating your cameras? After a windshield replacement my HW3 FSD camera calibration was off and it was similarly terrible like you were describing (going way too close to curbs), but then I recalibrated on a straight highwa
44.
by arkmm 1y ago
Congrats! You never forget your first.
45.
by arkmm 1y ago
Very cool to see an early stage company doing this! I always hear that healthcare has a lot of red tape to handle so it's hard for startups to operate without tons of VC funding. How'd you guys find your initial users and figure o
46.
by arkmm 1y ago
I think most code these days is boilerplate, though the composition of boilerplate snippets can become something unique and differentiated.
47.
by arkmm 1y ago
Neat - didn't realize there were affordances for scraping in Excel (but in hindsight I shouldn't be surprised). I didn't follow the connection between modern looming and scraping though?
48.
Ask HN: Web scraping in production?
4 points by arkmm 1y ago|5 comments
49.
by arkmm 1y ago
Anecdotal, but in the last few months my wife went from not wanting me to turn on AP/FSD to now using it for all her drives. The v13 models feel like a massive improvement.
50.
by arkmm 1y ago
Going to have to update the tokenizer for DolphinGemma https://blog.google/technology/ai/dolphingemma/
51.
by arkmm 2y ago
How did you fit 550MB of bytecode into the context window? Was this using 2.5 in an agentic framework? (i.e. repeated model calls and tool usage)
52.
by arkmm 2y ago
There are some options out there, depending on what type of task you're trying to fine tune. I think RL finetuning for DeepSeek e.g. isn't well developed yet, but you can finetune a small LLama model (~3B params) for classificatio
53.
by arkmm 2y ago
same
54.
Ask HN: What are you using o1 / DeepSeek for?
10 points by arkmm 2y ago|3 comments
55.
by arkmm 2y ago
Obtaining a detailed map doesn't seem difficult. This is the same company that created Street View. E.g. SF has ~1000 miles of streets [1], that would only take 50 hours of paying for manual driving to map all of SF at 20mph. 1. https
56.
by arkmm 2y ago
I've been running off a Raspberry Pi for years and it's been very stable. The main things for me were to use a good SD card, to use Ethernet instead of Wifi, and to also reboot the Pi daily via an automation.
57.
by arkmm 3y ago
I might be missing something but it seems like most of the speed up is from quantization which is commonly used already, and the CPU instance used here isn't that much cheaper (~10-15%?) than a GPU instance that could run the model. Fo
58.
Ask HN: Are people still labeling NLP datasets manually?
3 points by arkmm 3y ago|0 comments
59.
Ask HN: Hype aside, what practical issues come up when building LLM-based apps?
3 points by arkmm 3y ago|1 comments
60.
by arkmm 5y ago
Any resources you'd recommend for someone trying to get back into the scene after a long hiatus? Looking for nuanced/informative discussions without too much hype.

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