Jack Fratto
43 posts

Jack Fratto
@JackFratto
https://t.co/iUgJYct2Qf https://t.co/2MwOecRmcl
เข้าร่วม Mart 2020
94 กำลังติดตาม16 ผู้ติดตาม

@daniellevine How do you get a legal product in front of lawyers?
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If you are on X a lot, it might seem every lawyer is operating a fleet of agents.
I've presented to more than 1000 legal professionals in the last 90 days.
Very few are using AI. Even fewer are using it in any meaningful way.
There's still so much alpha.
Matt Margolis@ItsMattsLaw
I think that boat has left the dock
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@nick_mahar Building crosshairintelligence.com to help builders determine the best LLM for their domain by weighing performance/cost/speed
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Day 2 #buildinpublic
- Added 3D Pareto frontier for the following dimensions:
1. Performance
2. Cost
3. Speed
- Added a filter for speed.
- Added support for viewing on mobile.
What should I work on next?
crosshairintelligence.com
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@annieqyang Working on crosshairintelligence.com (OSS) to assist builders with choosing the correct model based on their domain/needs.
This is my side-quest currently :)
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Day 11 of #buildinpublic
so excited to have connected with 228 people 🥳
am looking to connect with more #builders, especially:
> AI startups & SaaS
> eCommerce & local businesses
> AI content creators
happy to swap tips on acquiring users, iterating on ideas, and indie hacking in general 🫡🎉
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Anyone seen any cool projects using World Models recently? I'm looking to list models on crosshairintelligence.com.
#ai #worldmodel
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@silvn00 @DanielSmidstrup Ain't that just a fancy way to say 'straight'?
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@peepayan10 @Tancrededib Why not just sell the data to prosthetics companies? I don't think humanoid robots are the future of industrial automation
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@Tancrededib looking for a technical cofounder
building the new gen way of training robots for industrial automation using brain-muscle signals from humans to acquire pre-contact muscle intent closing in the sim2real gap more than ever!
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Day 1 #buildinpublic
Open Source LLM benchmarking leaderboard.
gh: github.com/JackFratto/cro…
Future plans
-------------
1. Add benchmarks for domains affected by world models
2. Capture agentic performance
3. Create custom evaluator
4. Add section for relevant research
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@MindTheToken I started crosshairintelligence.com recently. Its OSS for benchmarking LLMs. Currently it captures how much of each domain (Finance/Legal/etc.) each model covers. Eventually the goal is to have it cover World Models and their domain coverage as well.
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