Antaripa Saha

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Antaripa Saha

Antaripa Saha

@doesdatmaksense

consulting companies in applied ai | doing maths in my free time

Katılım Kasım 2018
466 Takip Edilen15.2K Takipçiler
Antaripa Saha
Antaripa Saha@doesdatmaksense·
@wh0sumit i sometimes wonder if i am missing out on something given i have been doing wfh from my hometown for the past 5 years of my career. then i self-reflect and say whatever and move on
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sumit 🏴
sumit 🏴@wh0sumit·
i’ve been living in blr for over 1.5 years now, and i’ve realized i’ve only been to a handful of events. personally, i’ve always felt the information exchange at most events is pretty low. on the other hand, the people i’ve met 1:1 have been far more valuable for me. those conversations have taught me a lot. just my personal opinion.
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Aakash Kumar Nain
Aakash Kumar Nain@A_K_Nain·
If the algo is truly fixed, I expect an up tick in my reach as my mutuals are great!
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Hamel Husain
Hamel Husain@HamelHusain·
New Blog Post: Do Automated Evals Work? There has been a rise of tools that look through your traces with AI and identifies issues. We tested these tools with real production data to see how good they are. Where they shine - They often spot issues human miss - Integrate into your workflow: viewing traces, creating LLM judges etc. Where they fall short - They miss problems that require domain expertise and taste - Don't have great mechanisms to learn from human feedback - You can get similar results from using your coding agent So you should use them? Yes, BUT do so iteratively with you in the loop. We describe how in the post: parlance-labs.com/blog/posts/aut… It's also a good idea to try using your coding agent with you in the loop, which we discuss in the post. This was written with @doesdatmaksense , who led the research and collated the results.
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Antaripa Saha
Antaripa Saha@doesdatmaksense·
@neural_avb congratulations. one of the best high quality channel on ml out there. keep going!
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AVB
AVB@neural_avb·
Channel reached 33,000 subs today pizza is on me
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Antaripa Saha
Antaripa Saha@doesdatmaksense·
@anmolbuildz @HamelHusain assuming you are talking about programmtic way of checking, this can be done if you have fixed heuristics to check on, what about cases where there's reasoning involved?
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Antaripa Saha
Antaripa Saha@doesdatmaksense·
Do automated evals actually work? I and @HamelHusain spent last few weeks testing the auto-evals efficacy of different evals platforms. We took 100 real production traces from an apartment-leasing voice agent, manually reviewed the failures, masked the labels, and asked different systems to do the same error-analysis task and discover failure modes. We tested dedicated eval platforms like Braintrust, Arize, and LangSmith, along with ChatGPT, Codex, Claude Code, and Factory Droid. Full post here: parlance-labs.com/blog/posts/aut…
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Neeraj
Neeraj@ThePeshwa·
@doesdatmaksense @gridinoc @HamelHusain By failures do you mean tool call failures or final outputs being wrong? If your labels were on final output correctness, did you have access to a sme for the final labels? Very relevant to my usecase and I struggle with access to SMEs.
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Joe Barrow
Joe Barrow@barrowjoseph·
Writing a *long* post about speculative decoding, how it works and the major techniques developed through to dSpark. If you want to be a beta reader please let me know! 🙏 This goes for anyone who does or does not understand it yet!
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Antaripa Saha
Antaripa Saha@doesdatmaksense·
@_Suresh2 @HamelHusain do you mean the tool outputs too? we have provided the full traces bec many times the end outputs were correct but internal tool calls were wrong, so we wanted to check those failures too
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Antaripa Saha
Antaripa Saha@doesdatmaksense·
presenting the home office built with adult money
Antaripa Saha tweet mediaAntaripa Saha tweet mediaAntaripa Saha tweet mediaAntaripa Saha tweet media
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Antaripa Saha
Antaripa Saha@doesdatmaksense·
@A_K_Nain thank you bhaiya. aayiye ap kabhi north east humare ghar
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Antaripa Saha retweetledi
Antoine Chaffin
Antoine Chaffin@antoine_chaffin·
Whether you are GPU poor or GPU rich, today's release of PyLate has something for you! GPU maxxers: MaxSim kernels greatly speed up training while lowering the memory requirements CPU enjoyers: TACHIOM enables lightning fast multi-vector indexing and search directly on CPU
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