Ankur Gupta @getpy
Tweets on Python, Technology, Software Development, Programming. Joined January 2012-
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Submitted a talk on @MLflow for @__bangpypers__ next meet-up 🤞 github.com/bangpypers/mee…
For $10/hour, you can self-host Kimi and generate stories (or anything else) at 440 tokens/sec on 8 H200 GPUs with Prime Intellect. The key is not to worry about latency. For example, if you want 26,400 tokens from 24 questions, you can self-host Kimi and get that in about a…
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).…
Reading the instructions created from GEPA on my datasets has been my delight lately. The amount of insights gathered through reflection is incredible.
Reading the instructions created from GEPA on my datasets has been my delight lately. The amount of insights gathered through reflection is incredible.
Both DSPy and (especially) GEPA are currently severely under hyped in the AI context engineering world
🤢 as a 🐕 due to bad outside 🥘 Landed at my mom place now to be taken care of and revive. No 🥰 like 🧓 ❤️
After 14years in Germany, I’m back in my beloved Bangalore with bigger dreams than I initially left with 🤩 If you’re building something in automotive or anything tech really, I have a decade of R&D experience & expertise at Mercedes, let’s talk! DMs open.
I am working on TemplateAdapter for a future PR to dspy. If you know/care about dspy's Adapters please let me know what you think of that syntax. With TemplateAdapter, you can define easily (re)create the XMLAdapter. Or, you don't like dspy default [[ ##, no problem, you can…
The Zen of DSPy Information flow beats incantation. Signatures over spells. Context is key. Composition over concatenation. Downstream alignment beats upstream vibes. Keep the spec, the strategy, and the learning separate.
The Zen of DSPy Information flow beats incantation. Signatures over spells. Context is key. Composition over concatenation. Downstream alignment beats upstream vibes. Keep the spec, the strategy, and the learning separate.
Debugging old school style with breakpoints in a c++ application coz no LLM access here.
It’s delightful to build on the shoulders of DSPy. Until now, I had been looking at it through the eyes of a user (and I loved it, though I could see some friction here and there). But now, seeing it through the eyes of a library developer, it feels completely 100% delightful.…
🚀 At HOTTECHSTACK, I’ve been experimenting with something new: running a private LLM on GPUs in cheap cloud alongside OpenAI and Claude. The tricky part? Figuring out how to manage traffic between all these models. That’s where a proxy comes in. A proxy sits between the client…
#personal My wife’s grandmother 👵 passed today at the age of 87. Had her only kid at 18 and raised him as a single parent, she went on become a head of a primary school. What a life of overcoming struggle, challenges and succeeding 🙌 Om Shanti 🙏
For all DSPy peeps, this is probably a must watch. Lots of the history behind why DSPy looks the way it does, and the right ways to actually use DSPy in practice.
For all DSPy peeps, this is probably a must watch. Lots of the history behind why DSPy looks the way it does, and the right ways to actually use DSPy in practice. https://t.co/iPPeukD0FM
Multi-agent AI: 'Let's vote on the truth!' Formal verification: 'Or we could just prove it?' New framework resolves AI disagreements with theorem proving. No more believing the confident liar. Open source: github.com/evalops/cognit…
And this is how you write a hook 🪝… brilliant 🤩
And this is how you write a hook 🪝… brilliant 🤩
This new paper from Stanford shows that the impact of GenAI on early career hiring is significant. People are finding it hard to get jobs. The impact is in areas where GenAI adoption is strongest - software and customer service. Physical jobs like healthcare remain unimpaired.
MAST identifies 14 failure modes for multi-agent systems across 200 tasks. Small interventions can mitigate these failure modes! Sorry to sound like a broken record, but DSPy integration into these MAS can really mitigate these failure modes. I am currently wrapping DSPy in AG.
Really cool -- looks like system design and prompts can have more impact than foundation model weight training past some point.
Really cool -- looks like system design and prompts can have more impact than foundation model weight training past some point.
Is there a CLI framework for building agents that take care of basic tooling?.
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