Official Account of Gradient Flow (https://xitter.cf/t.co/DqotXS1cam) and The Data Exchange podcast (https://xitter.cf/t.co/YWlNNZ9Stl)
San Francisco
Joined January 2023
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Gradient Flow retweeted
Our CPO @Aurimas_Gr recently joined @GradFlowTech to discuss the challenges and innovations in training and scaling #LLMs. You'll hear about things like:
→ Going from MLOps to LLMOps
→ Scale and complexity of LLM clusters and training
→ Frontier models and training cycles
→ LLMOps enterprise lessons
→ Experimentation in agentic systems
→ What lies ahead
Listen here: thedataexchange.media/neptun…
Gradient Flow retweeted
Check out this awesome article by Ben Lorica at @GradFlowTech. "Taming the Unstructured Beast: Data Tools for Unleashing Generative AI" explores the complexities of integrating custom data for GenAI and LLM applications through fine-tuning or building Retrieval Augmented Generation (RAG) systems.
Ben's article navigates the challenges and landscape of tools designed to handle unstructured data. Among these tools is @UnstructuredIO. Our tools empower you with solutions for data ingestion and cleaning, chunking, and embedding enterprise data in unstructured formats like PDF, HTML, Excel, and images.
You can read the article here: gradientflow.substack.com/p/…. In case you missed it, tune in to the Aug 2023 podcast where Ben Lorica chatted with Unstructured CEO @_Brian_Raymond on this Youtube video: youtu.be/Umdi0gtndOc.
Gradient Flow retweeted
“Open Philanthropy’s expanding web of AI influence stems from its long-running effort to steer Washington toward rules that address long-term catastrophic risks … Its apocalyptic focus is reinforced by the group’s alignment with #effectivealtruism”
#eacc
politico.com/news/2023/10/13…
Gradient Flow retweeted
That's a wrap 🙏 to all @AIconference attendees, speakers, sponsors, volunteers, and staff #aiconf2023 ☑ See you next year
Gradient Flow retweeted
The current prevailing approach for developers is to use proprietary LLMs through APIs. Hagay Lupesko @MosaicML explains why it is critical for organizations to build their own custom and domain-specific Generative AI models
Gradient Flow retweeted
The current prevailing approach for developers is to use proprietary LLMs through APIs. Hagay Lupesko @MosaicML on why factors such as domain specificity, security, privacy, regulations, IP protection & control, will prompt organizations to opt to invest in their own custom LLMs
Gradient Flow retweeted
🚀 Join Jakub Zavrel, Founder & CEO @ZetaVector, as he explores the top AI trends of 2022. Dive into the 100 most cited AI papers and learn about the future of Language Models, Multimodal AI, Reasoning, #SyntheticData and more.
#MachineLearning #DataScience #DeepLearning #NLproc
Gradient Flow retweeted
Chris Wiggins [professor @columbia | cofounder @hackNY | Chief #DataScientist @nytimes] describes their fascinating new book that explores the ways in which data, machine learning, and AI have shaped society. Unlock the past, shape the future!
#DataScience #MachineLearning
Gradient Flow retweeted
A detailed overview of Skyplane, an open source project that accelerates wide-area transfers in the cloud via overlay routing and parallelism. Skyplane moves terabytes of data reliably and efficiently (>20Gbps) at up to 4x lower costs (between different clouds or regions)
Gradient Flow retweeted
Discover challenges in scaling machine learning data sets with researcher Pablo Villalobos Sánchez of Epoch AI . Explore #scalinglaws & other trends in #NLProc, computer vision, and more.
#MachineLearning #AI #deeplearning #datascience #MLdata #DataCentricAI
Gradient Flow retweeted
Putting Synthetic Data to work! On #TheDataExchangePod: Jinsung Yoon and Sercan Arik @Google @GoogleAI, on a new, state-of-the-art neural architecture for generating high-fidelity and privacy-preserving synthetic data of diverse data modalities.
Gradient Flow retweeted
Brandon Jenkins, COO @Fundrise, on their recent foray into technology investing, specifically startup companies in the data infrastructure space. Learn how they're giving their users access to a diversified set of very promising startups in the data infrastructure space.
Gradient Flow retweeted
Want to run #MachineLearning in the cloud? Zongheng Yang of @ucbrise Sky Computing Lab, gives a detailed overview of SkyPilot, a groundbreaking intercloud broker that lets you efficiently run ML jobs on any cloud (whether you use a single cloud or multiple cloud providers).
Gradient Flow retweeted
Trends and Opportunities in #DataEngineering and Data Infrastructure with Jesse Anderson and Evan Chan 🙌 topics include unstructured data management tools; streaming; data discovery; DataOps & more
Gradient Flow retweeted
Don't be caught off guard! Experts Gabriela Zanfir-Fortuna @futureofprivacy and Andrew Burt @bnh_ai provide concrete tips & guidance to #Data, #MachineLearning, & #AI teams who are wrestling with AI regulations.
Gradient Flow retweeted
Don't be caught off guard! Experts Gabriela Zanfir-Fortuna @futureofprivacy and Andrew Burt @bnh_ai provide concrete tips & guidance to #Data, #MacchineLearning, & #AI teams who are wrestling with AI regulations.
Gradient Flow retweeted
@GradFlowTech published an overview of specialized hardware for AI and mentioned: "[Cerebras' Andromeda], an AI supercomputer boasting 13.5 million cores and the ability to deliver over 1 exaflop of AI compute power."
Read their full article here: hubs.li/Q01B5XSY0
Gradient Flow retweeted
Dylan Patel on the state of specialized hardware for #AI, RISC V, usage of @PyTorch / @TensorFlow / JAX, and the Biden administration’s export controls.
#MachineLearning #AI #deeplearning #datascience
Gradient Flow retweeted
A conversation with Peter Norvig & Alfred Spector, part of the team of authors behind the highly-acclaimed book, Data Science in Context, a must-read guide on what you need to know to use #DataScience more effectively and ethically.
#NLproc #SyntheticData #MachineLearning #AI