Пікірлер

• 
  @MoadKISSAI9 сағат бұрын

  Omg, didn't know about that. Definitely going to the pipeline. Thanks for sharing! About the newsletters, there was theneurondaily, rundown ai, and what was the third one please? Something Valley when you all nodded so it must be an important one 😄 BTW, The Batch from Andrew NG is also a great one.

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  @andresrubio2015Күн бұрын

  Always inspiration

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  @lucindalinde4198Күн бұрын

  Excellent session! Your explanations are so helpful and very much appreciated

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  @mohammedshuaibiqbal5469Күн бұрын

  How can we track testing and benchmarking agents using AgentOps

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  @AI-MakerspaceКүн бұрын

  AIMS-AgentOps-CrewAI-Demo: github.com/chris-alexiuk/AIMS-AgentOps-CrewAI-Demo/tree/main Event Slides: www.canva.com/design/DAGJ55plCbY/PDASCroDOh-Upiu_lICWkw/view?DAGJ55plCbY&

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  @givanildogramacho441Күн бұрын

  Greg I 'd like to talk about llama3 great lectuce. 😊

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  @parinaztabari23322 күн бұрын

  How can I access this Colab (llama_index_tracing tutorial.ipynb)? Can you share the link?

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  @AI-Makerspace2 күн бұрын

  We've shared your comment with the presenter! We expect he'll get back with you shortly!

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  @leonardjin9103 күн бұрын

  On a scale from 1 to John Wick how much do you love your dog? 😆🤣🤣😆

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  @AI-Makerspace3 күн бұрын

  Watch the full video! kzread.info/dash/bejne/aqiHwZptXZiundI.html

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  @enceladus964 күн бұрын

  Thank you thank you thank you thank you thank you

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  @csmac3144a5 күн бұрын

  KZread quality still 720p. Really hard on the brain to follow the code examples.

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  @AI-Makerspace3 күн бұрын

  Stay tuned! Thanks for the ping and the reminder!

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  @lucindalinde41987 күн бұрын

  Thank you thank you thank you for this fantastic explanation of DSPy. I didn't understand it before this great webinar.❤

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  @AI-Makerspace7 күн бұрын

  You're welcome! 🫶

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  @givanildogramacho4417 күн бұрын

  Great point about agents, but I have a question. Whats != Agentic between other ?

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  @AI-Makerspace6 күн бұрын

  Thanks for your question Givanildo! We do need to clarify this idea that we're playing with on distinguishing between "multi-agent" and "multiple agent," even internally. There is, admittedly, ambiguity here, and we will seek to clarify it more fully in our next multi-agent event. But we created it because we have found it to be a useful mental model. The point of making this distinction was to recognize that the complexity and dynamism of multi-agent systems varies, sometimes quite widely. For instance, multi-agent systems presented today often feel constrained, linear, and prescriptive. It many cases multi-agent systems could just as well be single agent systems created with one prompt (albeit a quite long one). Conversely, a truly complex "multi-agent" system would, in our estimation, *require* the use of multiple agents, even to the point that each LLM was fine-tuned to a specific task. Something like that - what do you think!?

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  @janroggisch23108 күн бұрын

  Thank you very much for providing historical context, to me this is one of the most important aspects of learning about new tech, and understanding where, how, and why it fits in.

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  @AI-Makerspace8 күн бұрын

  💯we couldn't agree more!

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  @MannyBernabe8 күн бұрын

  good stuff. Thx!

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  @AI-Makerspace8 күн бұрын

  AIMS-CrewAI-Demo: github.com/AI-Maker-Space/AIMS-CrewAI-Demo Event Slides: www.canva.com/design/DAGJPj_tw-c/hSR7mYwEiRqCoK_L4RRcEg/view?DAGJPj_tw-c&

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  @andresrubio20158 күн бұрын

  Nice

• 
  @supergaulig9 күн бұрын

  Good video but one question: Why did you choose to create the testset step-by-step yourself and not use the provided TestSetGenerator from Ragas? Was is not available back then?

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  @AI-Makerspace8 күн бұрын

  That's right! They had just rolled it out it when we had them on for this more recent event: kzread.infoAnr1br0lLz8?si=_wIYqsL4vcVM5QDq

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  @mattfarmerai9 күн бұрын

  Wow great video. I just found your channel, already a fan. 🦾🤖

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  @AI-Makerspace9 күн бұрын

  Let's goooooo!

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  @smklearn-hy9me9 күн бұрын

  Does ragas work only on openai model, which model i can use for testset genrator as critic and generative model please help me out

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  @AI-Makerspace9 күн бұрын

  You can use any LLM that has OpenAI API compatibility. This means most closed source models, as well as open source options through certain hosting strategies (NIMs, vLLM, etc)

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  @smklearn-hy9me9 күн бұрын

  @@AI-Makerspace i dont have openai api key Can i use models from hugging face

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  @smklearn-hy9me9 күн бұрын

  Please help me out I want to genarate the test set data using models other than hugging face Like generate model and critic model

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  @sillystuff624712 күн бұрын

  best video i found on learning word2vec concepts by building up from simple examples. very helpful for people who learn by doing.

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  @AI-Makerspace12 күн бұрын

  You're speaking our language @sillystuff - we're all about learning, building, shipping, and sharing! Thanks for the comment and we're glad you found it useful!

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  @CoCoandMay13 күн бұрын

  amazing talk~~

• 
  @andres.yodars14 күн бұрын

  top

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  @MarinaQian14 күн бұрын

  Has there been any update yet?

• 
  @micbab-vg2mu15 күн бұрын

  great talk - thank you:)

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  @truliapro711215 күн бұрын

  Very useful 👌

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  @therobotocracy15 күн бұрын

  More more more DSPy please!

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  @user-zh6zn4hk1k15 күн бұрын

  absolutely

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  @AI-Makerspace14 күн бұрын

  Loud and clear guys! We'll see what we can do 🤓

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  @freakstiches15 күн бұрын

  Nice intro dudes lol music hooked me

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  @rakeshkumarrout262915 күн бұрын

  This is the most awaited and most useful and trendy thing in the market.

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  @AI-Makerspace15 күн бұрын

  DSPy - Advanced Prompt Engineering?: colab.research.google.com/drive/1Il47YSattSnWV5cfSzSD7b2rWuyv7n6O?usp=sharing Event Slides: www.canva.com/design/DAGIl1M_SYI/1nhzSuhN8YQ0uxN_wqP99g/view?DAGIl1M_SYI&

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  @seanbergman892715 күн бұрын

  Stoked that you are diving into DSPy! Would be cool if you could do a RAG demo and show how to generate an evaluation metric from free form text responses.

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  @AI-Makerspace14 күн бұрын

  @@seanbergman8927 we think RAG is definitely the next step here for sure! Stay tuned!

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  @MrTulufan19 күн бұрын

  RAGAS starts at time 20:15, before which is just an overview of langchain and the RAG QA pipeline

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  @AI-Makerspace16 күн бұрын

  Thanks for the timestamp here MrTulufan!

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  @rakeshkumarrout262922 күн бұрын

  this is quite useful,its really commendable how you come up with trendy topics with codes.

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  @AI-Makerspace21 күн бұрын

  Thanks Rakesh! We agree - Allan really crushed it with this one!

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  @RaviPrakash-dz9fm22 күн бұрын

  Can anyone tell me how ragas actually calculates these numbers. Like manually I get it, but what do the algorithms or functions look like? Like how does it measure faithfulness?

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  @AI-Makerspace21 күн бұрын

  Hey Ravi great question! We go a bit deeper into this in our more recent event with the creators! kzread.infoAnr1br0lLz8?si=UG6vRnSY9oVtAuAT We'd recommend reading through the docs and digging into the source to go EVEN deeper! e.g., docs.ragas.io/en/stable/concepts/metrics/faithfulness.html

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  @AI-Makerspace22 күн бұрын

  The Loss Function in LLMs - Cross Entropy: colab.research.google.com/drive/1VEk0mdGYKfPezWDJ4ErajNNlr4pq2Duk?usp=sharing Event Slides: www.canva.com/design/DAGH7_m5E48/HlpvFnc2VbCsjNiiFGdYnQ/view?DAGH7_m5E48&

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  @user-wf4mo5kc1y24 күн бұрын

  This is really great explanation. I have one query, lets say I want to improve the performance by focusing on Faithfulness or Answer Relevance, so which RAG optimization techniques I should follow to increase Faithfulness or which techniques can improve Relevance or Precision etc.

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  @AI-Makerspace24 күн бұрын

  The answer is, unfortunately, it depends! The whole system needs to work together (from data quality, to retrieval quality, to model performance, to prompting), and it needs to work for your use case. What is the best metric to use for your use case? That also depends. It all comes down to metrics-driven development: docs.ragas.io/en/stable/concepts/metrics_driven.html , but you need to decide which direction to drive! There are some simple things to do after you set up RAG like reranking, but for any given use case the details really matter with regards to what steps you should take.

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  @Amruth-lv6nk24 күн бұрын

  Can I use vertex model as the policy model?

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  @AI-Makerspace27 күн бұрын

  Multi-Agent Systems - LangGraph Pilot Demo: colab.research.google.com/drive/1YDQs2RySVelF9BjCYgSq2qC_xiIVdYpN?usp=sharing Slides: www.canva.com/design/DAGHLLEXvXQ/7tm3VDBZw3YKZJHsG-C8Vw/edit?DAGHLLEXvXQ&

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  @BHARTIDEVI.-8828 күн бұрын

  Needed more content for this and code with more complex architectures .

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  @AI-Makerspace27 күн бұрын

  This was completed in a 30min. Lightning Lesson - so we didn't dive too deep - but we do have a separate video where we dive in a bit deeper! Check it out here: kzread.infoulTvNAXI_1E?si=-Pvd5A4KS1GKXWnG

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  @rakeshkumarrout262928 күн бұрын

  this is quite ueful, can you help me with how to assign a name to my rag app?? can you make a video on DSPY with custom data RAG.

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  @AI-Makerspace27 күн бұрын

  DSPy is on the horizon!

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  @out_and_about0828 күн бұрын

  Thanks ! Where can I find the colab notebook?

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  @AI-Makerspace27 күн бұрын

  Thanks for the reminder! colab.research.google.com/drive/1YDQs2RySVelF9BjCYgSq2qC_xiIVdYpN?usp=sharing

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  @sitedev28 күн бұрын

  I just built a multi-agent article researching and writing team using Flowise. They’ve just added a UI for creating chatflows powered by LangGraph. No code needed - just clever prompt engineering.

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  @lionhuang920928 күн бұрын

  Where can we download ppt file?

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  @AI-Makerspace28 күн бұрын

  Thanks for the reminder! www.canva.com/design/DAGHLLEXvXQ/7tm3VDBZw3YKZJHsG-C8Vw/edit?DAGHLLEXvXQ&

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  @jdavidnorena28 күн бұрын

  @@AI-Makerspace put it in the description please, in case in future this comment gets lost, btw amazing video thanks a lot for sharing !

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  @AI-Makerspace27 күн бұрын

  @@jdavidnorena got it going in a comment!

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  @AI-Makerspace29 күн бұрын

  Mistral Fine-Tune: colab.research.google.com/drive/1RLl-n_pIAQKldWpc-UD8MhAhHO4wzYAl?usp=sharing Event Slides: www.canva.com/design/DAGHR69OPB4/Xy3m9rj3eWTfF9uFsEDDgQ/view?DAGHR69OPB4&

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  @prasad_ytАй бұрын

  I like the way you simplify and explain- starting with the big picture and then breaking down in to the details.❤

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  @koescoin810Ай бұрын

  This model solved many problems to users who doesn't want to send private documents to cloud just for fine tuning or RAG. Thank's to Gradient for this great milestone.

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  @thomashsu5252Ай бұрын

  Great context. I really rllearnd something

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  @AI-MakerspaceАй бұрын

  Nice!

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  @AI-MakerspaceАй бұрын

  How LLMs Choose the Next Token: colab.research.google.com/drive/1dGdMVkwlHDIitsMDWOhPTS1jwxM_5qmD?usp=sharing Event Slides: www.canva.com/design/DAGGnrrq5zg/Wij3fvn2jmXVMRjx6LrnvA/view?DAGGnrrq5zg&

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  @MegaClockworkDocАй бұрын

  Great Work. Please consider using data which is not part of the training data as the haystack for the long context search to create a more real-world example.

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  @AI-MakerspaceАй бұрын

  There doesn't seem to be evidence to suggest that the data being known makes this task easier - but we can definitely make that modification!

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  @damiangilgonzalez8011Ай бұрын

  Good job!! I would like to have the code :(

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  @AI-MakerspaceАй бұрын

  You got it Damian! github.com/bytewax/real-time-rag-workshop/tree/main/workshops/aimakerspace-2024