Areibman

7 ms·

61.
by Areibman 2y ago
Nice to finally see one of the labs throwing weight behind a much needed simple abstraction. It's clear they learned from the incumbents (langchain et al)-- don't sell complexity. Also very nice of them to include extensible traci
62.
Nix and Containers: Why Not Both?(flox.dev)
13 points by Areibman 2y ago|4 comments
63.
Natural Language to Animation(gauss.qemlabs.com)
1 points by Areibman 2y ago|0 comments
64.
by Areibman 2y ago
Congrats on the launch! Given the size of the niche (developers building voice agents), do you find there's a lot of demand for testing and observability? From my anecdata, many of the voice AI agent builders are using SDKs and builder
65.
Show HN: AI spelling and grammar checker for docs(github.com)
3 points by Areibman 2y ago|0 comments
66.
by Areibman 2y ago
Yes, here's a directory of many of them https://staf.ai
67.
by Areibman 2y ago
This is unnecessarily harsh. Not every model has a publicly available tokenizer, and using a fallback like cl100k is usually a decent enough estimator from my experience. Besides, there's a warning message for when you specify a model
68.
by Areibman 2y ago
Best one I've found out there. If there's another, very open to replacing
69.
by Areibman 2y ago
Perhaps at some point! Right now, we haven't been seeing most demand on the language side of things as multi-modal image really hasn't popped off yet
70.
by Areibman 2y ago
Anthropic actually has a Claude 3 tokenizer tucked away in one of their repos: https://github.com/anthropics/anthropic-tokenizer-typescript At this moment, Tokencost uses the OpenAI tokenizer as a default tokenizer, bu
71.
Show HN: Token price calculator for 400+ LLMs(github.com)
268 points by Areibman 2y ago|76 comments
72.
by Areibman 2y ago
No— you have to explicitly checkmark it for the change to happen. We saw the famous OpenInterpreter tweet where the agent deleted every file on someone’s computer. We wanted to avoid that
73.
by Areibman 2y ago
Alex here—- one of the team members behind the project. We built this for the Llama3 Cerebral Valley Hackathon. The idea was this: My ~/Downloads folder is extremely messy, and I wanted an agent to fix it for me. So we built one. Llama
74.
by Areibman 2y ago
Some others have mentioned before, but there are actually several projects working on exactly this: https://github.com/Arize-ai/openinference https://github.com/traceloop/openllmetry https:/
75.
by Areibman 2y ago
It was a question more for us than general public. I think YC is probably the best first check you can get since they invest in companies with nothing more than an idea.
76.
by Areibman 2y ago
We got rejected (2nd time applying) and ended up raising a substantial seed/pre-seed round at excellent terms a month later. Is there a compelling reason to still apply?
77.
Show HN: Write JSON processor queries (jq) in natural language(github.com)
38 points by Areibman 3y ago|0 comments
78.
by Areibman 3y ago
To what degree do lawyers actually want to track their time accurately? I used to work a timesheet intensive job (consulting). The quiet rule was log the minimum 45h/w if you like your engagement; log your actual hours if you hate it.
79.
by Areibman 3y ago
We knew the time would come, but we built ChatOCR in a week. If we overthought the time horizon problem, we'd have 0 users and $0. But also, GPT-4-Vision is multi-modal but does not specifically use OCR. Our tool is used mostly to extr
80.
by Areibman 3y ago
We use a third party plugins manager called pluginlab.ai. It manages auth and subscriptions for plugins users by prompting them to sign in when they hit a paywall.
81.
by Areibman 3y ago
As a (former) ChatGPT plugins developer, our business has absolutely tanked due to GPTs. Discoverability is nonexistent because search is just buried by spam. At least with plugins, there were only a few hundred to sort through, and most ha
82.
by Areibman 3y ago
Makes sense. Coframe ( https://coframe.ai ) comes top of mind
83.
by Areibman 3y ago
Very slick, straightforward demo. Question on my mind: The AI A/B testing space seems to be getting crowded. In what way do you see Just Words standing out?
84.
Cake Eating Problem(python.quantecon.org)
2 points by Areibman 3y ago|0 comments
85.
by Areibman 3y ago
I'm not sure I'd classify most of these as AI agents, it's mostly web crawlers. (Though the definition of agent is fuzzy enough that I suppose you could lump them in). I'm also curious, will adding "Common Crawl&quo
86.
Show HN: Easy token counting and price calculation for LLMs(github.com)
3 points by Areibman 3y ago|1 comments
87.
by Areibman 3y ago
I just came back from Puerto Vallarta, and it's shocking how pharmacies advertise their drugs to tourists. I'm talking massive signs with every prescription med under the sun-- Adderall, Xanax, Retinol, you name it. All next to th
88.
Show HN: BestGPTs(github.com)
1 points by Areibman 3y ago|0 comments
89.
by Areibman 3y ago
LLM observability strikes me as an extremely, extremely crowded space. And YC has funded an enormous number of them. What do you think is the key differentiator between you and everyone else? Is vendor lock-in really that huge of an issue?
90.
by Areibman 3y ago
Maybe I'm missing something here, isn't this largely achieved by ONNX already? [0] https://onnx.ai

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