Prashanth Rao @tech_optimist
AI engineer working with graphs & LLMs @kuzudb. Blogging about AI @ https://t.co/gLektr01zQ and https://t.co/QT8Lnl6WPB Toronto 🇨🇦 Joined October 2013-
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💯 % agree, but it's not that the docs are "bad" or anything. It's actually quite hard to communicate the benefits of DSPy. Most people who understand it have gotten there only when they built something and saw the value of its programming model for themselves. Such a strange…
💯 % agree, but it's not that the docs are "bad" or anything. It's actually quite hard to communicate the benefits of DSPy. Most people who understand it have gotten there only when they built something and saw the value of its programming model for themselves. Such a strange…
@HamelHusain Writing prompts is dead -> I define structured inputs
For those interested, ephemeral graphs in production are thing. @Bauplan_labs were one of the early adopters of @kuzudb and are running 50K+ ephemeral graphs in Kuzu daily for their query planner! 🤯
For those interested, ephemeral graphs in production are thing. @Bauplan_labs were one of the early adopters of @kuzudb and are running 50K+ ephemeral graphs in Kuzu daily for their query planner! 🤯
As someone who works in open source, and engages with other open source devs (maintainers, contributors, users) every day, I think a lot about network effects. In the end, long term usage and adoption of an open source tool totally depends on network effects. The quality of the…
Recently, @YourTechBud and I have been deep diving into the code base of DSPy, and we're finding different ways to demonstrate the power of signatures, modules and optimizers. The "DSPy way" is a little alien at first (because you give up "control" over what prompts you write).…
@tech_optimist @ThePeshwa @DSPyOSS GEPA works in iterations, where it uses the training set to perform the reflection, and the validation set to choose the next candidate to improve (the pareto frontier tracking) as well as to choose the overall best performing candidate at the end. Given this, my experience has…
I really like the explanation I just got from @rjurney about how overfitting can occur. "At the limit, it could just write instructions to categorize every instance separately. That would be overfitting". Looking at the verbosity of prompt #3 in this example, it does seem like…
I really like the explanation I just got from @rjurney about how overfitting can occur. "At the limit, it could just write instructions to categorize every instance separately. That would be overfitting". Looking at the verbosity of prompt #3 in this example, it does seem like…
The right question is not to ask if DSPy is production ready, but rather: >> why would you want to go to prod without a declarative, eval-driven, composable framework? << the nightmare isnt a fast evolving framework ... its a repo full of brittle prompt engineered programs
The right question is not to ask if DSPy is production ready, but rather: >> why would you want to go to prod without a declarative, eval-driven, composable framework? << the nightmare isnt a fast evolving framework ... its a repo full of brittle prompt engineered programs
Try out the new graph algorithm tutorial on the Nobel laureate mentorship graph in @kuzudb! In writing this tutorial, I learned the name of a new laureate, Adam Wiess, who won the 2011 Nobel prize in Physics for his work in cosmology. Adam Wiess is the Physics laureate in this…
Try out the new graph algorithm tutorial on the Nobel laureate mentorship graph in @kuzudb! In writing this tutorial, I learned the name of a new laureate, Adam Wiess, who won the 2011 Nobel prize in Physics for his work in cosmology. Adam Wiess is the Physics laureate in this…
Machine & LM cost << human labour cost. In the vast ocean of prompt space, why be a human floating around like a mariner without a compass? Be like @DSPyOSS 🛥️⚓️
Machine & LM cost << human labour cost. In the vast ocean of prompt space, why be a human floating around like a mariner without a compass? Be like @DSPyOSS 🛥️⚓️
This post dramatically undersells what they did here. Used a couple prompt optimization algorithms to end up with 1️⃣ a prompt that works on a smaller/cheaper/faster model, 2️⃣ successfully processes all problematic inputs, 3️⃣ and the prompt is significantly _shorter_
This post dramatically undersells what they did here. Used a couple prompt optimization algorithms to end up with 1️⃣ a prompt that works on a smaller/cheaper/faster model, 2️⃣ successfully processes all problematic inputs, 3️⃣ and the prompt is significantly _shorter_
The Rust 🦀 community is getting some really cool DSPy-like features next week - looking forward to trying it out!!!
The Rust 🦀 community is getting some really cool DSPy-like features next week - looking forward to trying it out!!!
Joel Grus 🤠 @joelgrus
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Vincent D. Warmerdam @fishnets88
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Jeremy Howard @jeremyphoward
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pedram.md @pdrmnvd
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vincenzo @alargemike
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William Callahan @WilliamCallahan
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dsaccon @dsaccon
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Arun @arun31415
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vicki @vboykis
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Sarah Drasner @sarah_edo
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fernandoperez.org @fperez_org
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Shreya Shankar @sh_reya
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