Connor Shorten @CShorten30
Research Scientist @weaviate_io! Mostly working on Generative Feedback Loops with DSPy and Filtered ANN. Host of the Weaviate podcast! DSPy playlist below! youtube.com/watch?v=CEuUG4… Boston, MA Joined March 2017-
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Just landed in San Francisco! 🛬 31 hours until our first DSPy meetup!! Super excited! 🎉🎉
I file this under "wait, this works?" - shouldn't work but it does... 🤷♂️ I am blessed with amazing collaborators.
I file this under "wait, this works?" - shouldn't work but it does... 🤷♂️ I am blessed with amazing collaborators.
Seeing lots of tweets like "RAG is going to die, its a temporary solution" Its not. LLMs have no notion of truth. Truth, as defined colloquially, is not a property of the world. Its a consensus metric. LLMs need retrieval to get access to that consensus.
Ever wondered which LLM judge to take? We say use multiple small ones & make a jury instead of a single judge! 👩⚖️ In our paper we demonstrate that taking a Panel of Llm judges (PoLL) correlates highest with human judgements & reduces intra-model bias! arxiv.org/pdf/2404.18796
The Batch API now supports embedding and vision models. We’ve also increased the requests-per-batch limit from 10,000 to 50,000, and added the ability to manage batches from the dashboard. See our new getting started guide: platform.openai.com/docs/guides/ba…
.@mutableai just made a wiki page for DSPy wiki.mutable.ai/stanfordnlp/ds…, great for getting acquainted with the repo!
Ever struggled to find Waldo? 🔎 Our latest blog dives into using Weaviate for image recognition to find the "needle in a haystack". Using “near image” search across a vector space and a chunking technique that’s often used in RAG applications, we can search for Waldo and…
Replacing Judges with Juries Evaluating LLM Generations with a Panel of Diverse Models As Large Language Models (LLMs) have become more advanced, they have outpaced our abilities to accurately evaluate their quality. Not only is finding data to adequately probe
Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models abs: arxiv.org/abs/2404.18796 This paper from Cohere proposes to evaluate models using a Panel of LLm evaluators (PoLL). "we find that using a PoLL composed of a larger number of smaller…
Our paper "PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval" with @xueguang_ma @bevan_koopman @lintool and @guidozuc is now available on arXiv: arxiv.org/abs/2404.18424
A wealth of results that many people will find valuable. GPT-3.5 vs GPT-4 with & without DSPy optimizers. Optimized GPT-3.5 calls are consistently more accurate here than uncompiled GPT-4 calls.
A wealth of results that many people will find valuable. GPT-3.5 vs GPT-4 with & without DSPy optimizers. Optimized GPT-3.5 calls are consistently more accurate here than uncompiled GPT-4 calls.
Sufficient practice can often approximate system 2 goal-oriented planning as system 1 reflexive responses, like when one internalizes how to drive. But for any degree of internalized system 1 capabilities, reliable composition of maximal skills needs explicit system 2 structure.
Our DSPy meetup is coming up quick! Join us in SF on Wednesday night: lu.ma/dspy
Our DSPy meetup is coming up quick! Join us in SF on Wednesday night: lu.ma/dspy
I’ll be there!
At the AI Tinkerers event at the GitHub office!
DSPy enables you to build the next generation of LLM applications 🤯 DSPy is a framework for programming language models. You build these programs by defining the components, piecing them together, and optimizing the program! I'm excited to share my new video on a hands-on demo…
So many shortcomings in #DSPy. Not DSPy's fault, it's early yet. It can be hard to use. hard to learn. It has gaps. But when you get something down in like 15 LoC that you coudn't ever imagine doing before, you can't help but grin.
WangLab complied several of their DSPy programs with MIPRO, a powerful optimizer by @kristahopsalong* @michaelryan207*. Michael & Krista have been developing even better optimizers for language programs—stay tuned for upcoming work! Learn how MIPRO works: x.com/kristahopsalon…
WangLab complied several of their DSPy programs with MIPRO, a powerful optimizer by @kristahopsalong* @michaelryan207*. Michael & Krista have been developing even better optimizers for language programs—stay tuned for upcoming work! Learn how MIPRO works: x.com/kristahopsalon…
Oh, look, I hear there's a DSPy meetup in San Francisco on Wednesday (May 1st) from 5:30 PM - 8:30 PM with @ArizePhoenix, @cohere, @weaviate_io. See you there, everyone!
Oh, look, I hear there's a DSPy meetup in San Francisco on Wednesday (May 1st) from 5:30 PM - 8:30 PM with @ArizePhoenix, @cohere, @weaviate_io. See you there, everyone!
Did you know Weaviate is hosting an in-person event at the Google offices at 111 8th Ave in NYC on Tuesday, May 21st? Come for the tech talks, stay for the hands-on training. Register now! #Weaviate#GoogleCloud #NYC#GenAI google.smh.re/3zRB
Jeremy Howard @jeremyphoward
222K Followers 5K Following 🇦🇺 Co-founder: @AnswerDotAI & @FastDotAI ; Hon Professor: @UQSchoolITEE ; Digital Fellow: @StanfordDelip Rao e/σ @deliprao
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56K Followers 4K Following open-sourceress at @huggingface 🧙🏻♀️ proud mediterrenean 🍋 I do TL;DR on ML papersEric Jang @ericjang11
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32K Followers 2K Following Chief Llama Officer @huggingface 🦙 Founder @AI_Learners. Xoogler (SWE @Google Assistant, 20% PM TF Graphics). 100% Hacker Llama🇵🇪🇲🇽Hamel Husain @HamelHusain
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380K Followers 77 Following Tensors and neural networks in Python with strong hardware acceleration. PyTorch is an open source project at the Linux Foundation. #PyTorchFoundationJeremy Howard @jeremyphoward
222K Followers 5K Following 🇦🇺 Co-founder: @AnswerDotAI & @FastDotAI ; Hon Professor: @UQSchoolITEE ; Digital Fellow: @Stanford(((ل()(ل() 'yoav))).. @yoavgo
46K Followers 2K FollowingDelip Rao e/σ @deliprao
46K Followers 5K Following Busy inventing the shipwreck. @Penn. Past: @johnshopkins, @UCSC, @Amazon, @Twitter ||Art: #NLProc, Vision, Speech, #DeepLearning || Life: 道元, improv, running 🌈Richard Socher @RichardSocher
101K Followers 971 Following CEO @youSearchEngine Investing at @aixventuresHQ Before: Stanford Adj Prof in AI/NLP, Chief Scientist at Salesforce, MetaMindmerve @mervenoyann
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107K Followers 0 Following Invented principles of meta-learning (1987), GANs (1990), Transformers (1991), very deep learning (1991), etc. Our AI is used many billions of times every day.Radek Osmulski 🇺�.. @radekosmulski
25K Followers 555 Following Resources to take your Machine Learning skills to the next level 🧪 Senior Data Scientist, RecSys @NVIDIAAI 🏫 @fastdotai trained DL Eng 📝 https://t.co/By87iXx5Puabhishek @abhi1thakur
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33K Followers 968 Following Cofounded & running @ml_collective. Host of Deep Learning Classics & Trends. Research at Google DeepMind. DEI/DIA Chair of ICLR & NeurIPS. Writing https://t.co/IbycyGfnDREric Jang @ericjang11
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48K Followers 197 Following #CS Associate Prof @YorkUniversity, #ComputerVision Scientist Samsung #AI, @VectorInst Faculty Affiliate, TPAMI AE, #CVPR2024/#ECCV2024 Publicity Co-chairclem 🤗 @ClementDelangue
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14K Followers 556 Following Linux Enthusiast 🐧 | Content Creator 📝 | Automation 🚀 | DevOps 💻 Sharing insights & knowledge through my writings ✍ Join me on this tech journey 👋Carl Tanner @grassycarl
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1K Followers 882 Following Incoming DE intern @glassdoor • Ex-Data Engineer @Accenture 👨🏻💻 • MS Data Science @SFSU • @ETCampusStars '22 • Here to network and learn ✨️Avatar AI 🤖 @AvatarAi288
55 Followers 259 Following This account is handled by @anmol_desai2005. Passionate about AGI. Currently working on dspy framework and llama_index applications.I've really enjoyed using @crewAIInc 's tools to build multiagent AI systems -- in addition to being productive, it's also fun to use! It was great hanging out with its creator @joaomdmoura to chat about best practices for building agentic workflows.
Being able to hang with @AndrewYNg last week was a blast! Super nice person super tuned with the AI market, and if I may had a great taste for agent framework 😅
I've really enjoyed using @crewAIInc 's tools to build multiagent AI systems -- in addition to being productive, it's also fun to use! It was great hanging out with its creator @joaomdmoura to chat about best practices for building agentic workflows.
@CShorten30 Please please please put a camera down and record the whole thing. It needs to be documented 😭
I file this under "wait, this works?" - shouldn't work but it does... 🤷♂️ I am blessed with amazing collaborators.
Our paper "PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval" with @xueguang_ma @bevan_koopman @lintool and @guidozuc is now available on arXiv: arxiv.org/abs/2404.18424
Seeing lots of tweets like "RAG is going to die, its a temporary solution" Its not. LLMs have no notion of truth. Truth, as defined colloquially, is not a property of the world. Its a consensus metric. LLMs need retrieval to get access to that consensus.
Seen on the @WSJ ! Join us at snowflake.com/summit/
Ever wondered which LLM judge to take? We say use multiple small ones & make a jury instead of a single judge! 👩⚖️ In our paper we demonstrate that taking a Panel of Llm judges (PoLL) correlates highest with human judgements & reduces intra-model bias! arxiv.org/pdf/2404.18796
The Batch API now supports embedding and vision models. We’ve also increased the requests-per-batch limit from 10,000 to 50,000, and added the ability to manage batches from the dashboard. See our new getting started guide: platform.openai.com/docs/guides/ba…
Don't sleep on Batch Embeddings... it was one our longest running feature requests! Just $0.01 /1M tokens for the small model and a 4B batch token rate limits! Give it a whirl platform.openai.com/batches
The Batch API now supports embedding and vision models. We’ve also increased the requests-per-batch limit from 10,000 to 50,000, and added the ability to manage batches from the dashboard. See our new getting started guide: platform.openai.com/docs/guides/ba…
.@mutableai just made a wiki page for DSPy wiki.mutable.ai/stanfordnlp/ds…, great for getting acquainted with the repo!
Last week, we started experimenting with healthcare data in Verba, our open-source RAG application. We loaded it with synthetic patient notes and research papers to see what insights our RAG tool could provide. To embed the data and generate the answers, we used Google Gemini!…
Bringing RAG into production in the medical domain, not easy but necessary! Thanks @googlecloud for your support! Build advanced RAG applications using Google Gemini 1.5 and our RAG framework Verba with @weaviate_io Help young cancer patients maximaalinactie.nl/fundraisers/we…
Is AI-first the new mobile-first? Join us on May 7th in Amsterdam for our AI for Developer Love event with @aicampai, @devworld_conf and @unbody_io! @malgamves and @amirhouieh will be exploring what multimodality and modern streamlined AI pipelines can do for you today to…
Ever struggled to find Waldo? 🔎 Our latest blog dives into using Weaviate for image recognition to find the "needle in a haystack". Using “near image” search across a vector space and a chunking technique that’s often used in RAG applications, we can search for Waldo and…
Replacing Judges with Juries Evaluating LLM Generations with a Panel of Diverse Models As Large Language Models (LLMs) have become more advanced, they have outpaced our abilities to accurately evaluate their quality. Not only is finding data to adequately probe
Good news, we are expanding the crew team, so hopefully we get more people helping out on the PRs and issues side of things, thanks for bearing with me 🙇♂️
CRISPR-GPT: An LLM Agent for Automated Design of Gene-Editing Experiments abs: arxiv.org/abs/2404.18021 Introduces CRISPR-GPT, a tailor-made LLM agent for automated designing of gene-editing experiments. Focuses on breaking experiment design down to a variety of substeps that…
Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models abs: arxiv.org/abs/2404.18796 This paper from Cohere proposes to evaluate models using a Panel of LLm evaluators (PoLL). "we find that using a PoLL composed of a larger number of smaller…